-Authors: Terry J Lee, Erica Suh, Kimball Hill, Stephen
-R Piccolo
+Authors: Terry J Lee, Erica Suh, Kimball Hill, Stephen R Piccolo
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract
-BackgroundClassification algorithms
-assign observations to groups based on patterns in data. The
-machine-learning community have developed myriad classification
-algorithms, which are used in diverse life science research domains.
-Algorithm choice can affect classification accuracy dramatically, so it
-is crucial that researchers optimize the choice of which algorithm(s) to
-apply in a given research domain on the basis of empirical evidence. In
-benchmark studies, multiple algorithms are applied to multiple datasets,
-and the researcher examines overall trends. In addition, the researcher
-may evaluate multiple hyperparameter combinations for each algorithm and
-use feature selection to reduce data dimensionality. Although software
-implementations of classification algorithms are widely available,
-robust benchmark comparisons are difficult to perform when researchers
-wish to compare algorithms that span multiple software packages.
-Programming interfaces, data formats, and evaluation procedures differ
-across software packages; and dependency conflicts may arise during
-installation.
-FindingsTo address these challenges,
-we created ShinyLearner, an open-source project for integrating
-machine-learning packages into software containers. ShinyLearner
-provides a uniform interface for performing classification, irrespective
-of the library that implements each algorithm, thus facilitating
-benchmark comparisons. In addition, ShinyLearner enables researchers to
-optimize hyperparameters and select features via nested
-cross-validation; it tracks all nested operations and generates output
-files that make these steps transparent. ShinyLearner includes a Web
-interface to help users more easily construct the commands necessary to
-perform benchmark comparisons. ShinyLearner is freely available at https://github.com/srp33/ShinyLearner.
-ConclusionsThis
-software is a resource to researchers who wish to benchmark multiple
-classification or feature-selection algorithms on a given dataset. We
-hope it will serve as example of combining the benefits of software
-containerization with a user-friendly approach.
+AbstractBackgroundClassification algorithms assign observations to groups based on patterns in data. The machine-learning community have developed myriad classification algorithms, which are used in diverse life science research domains. Algorithm choice can affect classification accuracy dramatically, so it is crucial that researchers optimize the choice of which algorithm(s) to apply in a given research domain on the basis of empirical evidence. In benchmark studies, multiple algorithms are applied to multiple datasets, and the researcher examines overall trends. In addition, the researcher may evaluate multiple hyperparameter combinations for each algorithm and use feature selection to reduce data dimensionality. Although software implementations of classification algorithms are widely available, robust benchmark comparisons are difficult to perform when researchers wish to compare algorithms that span multiple software packages. Programming interfaces, data formats, and evaluation procedures differ across software packages; and dependency conflicts may arise during installation.FindingsTo address these challenges, we created ShinyLearner, an open-source project for integrating machine-learning packages into software containers. ShinyLearner provides a uniform interface for performing classification, irrespective of the library that implements each algorithm, thus facilitating benchmark comparisons. In addition, ShinyLearner enables researchers to optimize hyperparameters and select features via nested cross-validation; it tracks all nested operations and generates output files that make these steps transparent. ShinyLearner includes a Web interface to help users more easily construct the commands necessary to perform benchmark comparisons. ShinyLearner is freely available at https://github.com/srp33/ShinyLearner.ConclusionsThis software is a resource to researchers who wish to benchmark multiple classification or feature-selection algorithms on a given dataset. We hope it will serve as example of combining the benefits of software containerization with a user-friendly approach.
-Only visualiation steps performed, rather than machine learning (which
-could take several hours/days). The created figures match those in the
-article. The content of other output files was not checked.
+Only visualiation steps performed, rather than machine learning (which could take several hours/days). The created figures match those in the article. The content of other output files was not checked.
-Authors: Peter J. B. Hancock, Roland J. Baddeley,
-Leslie S. Smith
+Authors: Peter J. B. Hancock, Roland J. Baddeley, Leslie S. Smith
-Abstract: Obtained from OpenAlex
+Abstract: Obtained from OpenAlex
-AbstractA neural net was used to analyse samples of natural images and
-text. For the natural images, components resemble derivatives of
-Gaussian operators, similar to those found in visual cortex and inferred
-from psychophysics. While the results from natural images do not depend
-on scale, those from text images are highly scale dependent. Convolution
-of one of the text components with an original image shows that it is
-sensitive to inter-word gaps.
+AbstractA neural net was used to analyse samples of natural images and text. For the natural images, components resemble derivatives of Gaussian operators, similar to those found in visual cortex and inferred from psychophysics. While the results from natural images do not depend on scale, those from text images are highly scale dependent. Convolution of one of the text components with an original image shows that it is sensitive to inter-word gaps.
-Matlab code written by Iain Davies to reproduce original paper; natural
-images provided by Peter Hancock.
+Matlab code written by Iain Davies to reproduce original paper; natural images provided by Peter Hancock.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Computational properties of use of biological organisms or to
-the construction of computers can emerge as collective properties of
-systems having a large number of simple equivalent components (or
-neurons). The physical meaning of content-addressable memory is
-described by an appropriate phase space flow of the state of a system. A
-model of such a system is given, based on aspects of neurobiology but
-readily adapted to integrated circuits. The collective properties of
-this model produce a content-addressable memory which correctly yields
-an entire memory from any subpart of sufficient size. The algorithm for
-the time evolution of the state of the system is based on asynchronous
-parallel processing. Additional emergent collective properties include
-some capacity for generalization, familiarity recognition,
-categorization, error correction, and time sequence retention. The
-collective properties are only weakly sensitive to details of the
-modeling or the failure of individual devices.
+Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.
-Authors: Andrew G. Barto, Richard S. Sutton, C. W.
-Anderson
+Authors: Andrew G. Barto, Richard S. Sutton, C. W. Anderson
-Abstract: Obtained from OpenAlex
+Abstract: Obtained from OpenAlex
-It is shown how a system consisting of two neuronlike adaptive elements
-can solve a difficult learning control problem. The task is to balance a
-pole that is hinged to a movable cart by applying forces to the cart’s
-base. It is argued that the learning problems faced by adaptive elements
-that are components of adaptive networks are at least as difficult as
-this version of the pole-balancing problem. The learning system consists
-of a single associative search element (ASE) and a single adaptive
-critic element (ACE). In the course of learning to balance the pole, the
-ASE constructs associations between input and output by searching under
-the influence of reinforcement feedback, and the ACE constructs a more
-informative evaluation function than reinforcement feedback alone can
-provide. The differences between this approach and other attempts to
-solve problems using neurolike elements are discussed, as is the
-relation of this work to classical and instrumental conditioning in
-animal learning studies and its possible implications for research in
-the neurosciences.
+It is shown how a system consisting of two neuronlike adaptive elements can solve a difficult learning control problem. The task is to balance a pole that is hinged to a movable cart by applying forces to the cart’s base. It is argued that the learning problems faced by adaptive elements that are components of adaptive networks are at least as difficult as this version of the pole-balancing problem. The learning system consists of a single associative search element (ASE) and a single adaptive critic element (ACE). In the course of learning to balance the pole, the ASE constructs associations between input and output by searching under the influence of reinforcement feedback, and the ACE constructs a more informative evaluation function than reinforcement feedback alone can provide. The differences between this approach and other attempts to solve problems using neurolike elements are discussed, as is the relation of this work to classical and instrumental conditioning in animal learning studies and its possible implications for research in the neurosciences.
-The check was relatively easy to do because the Python code was simple,
-but the documentation was not good. Computations took about 6 minutes to
-run.
+The check was relatively easy to do because the Python code was simple, but the documentation was not good. Computations took about 6 minutes to run.
-This code had some difficulties involving the Python package ANNarchy.
-All scripts were eventually able to be run, and most figures were
-reproduced as in the ReScience paper. However two figures were very
-different from the originals. Some figures also varied considerably when
-changing the seed.
+This code had some difficulties involving the Python package ANNarchy. All scripts were eventually able to be run, and most figures were reproduced as in the ReScience paper. However two figures were very different from the originals. Some figures also varied considerably when changing the seed.
-The three figures from the ReScience article “[Re] A Generalized Linear
-Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviours”
-were reproduced using the code provided by the article authors. The code
-was straightforward to run and took minimal computation time.
+The three figures from the ReScience article “[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviours” were reproduced using the code provided by the article authors. The code was straightforward to run and took minimal computation time.
-Authors: Nicholas G. Davies, Adam J. Kucharski,
-Rosalind M. Eggo, Amy Gimma, CMMID COVID-19 working group, W. John
-Edmunds
+Authors: Nicholas G. Davies, Adam J. Kucharski, Rosalind M. Eggo, Amy Gimma, CMMID COVID-19 working group, W. John Edmunds
-Abstract: Obtained from abstractsource
+Abstract: Obtained from abstractsource
-R code and packages worked well; simple edits needed to working
-directory.
+R code and packages worked well; simple edits needed to working directory.
-Abstract: Obtained from OpenAlex
+Abstract: Obtained from OpenAlex
-The global impact of COVID-19 has been profound, and the public health
-threat it represents is the most serious seen in a respiratory virus
-since the 1918 H1N1 influenza pandemic. Here we present the results of
-epidemiological modelling which has informed policymaking in the UK and
-other countries in recent weeks. In the absence of a COVID-19 vaccine,
-we assess the potential role of a number of public health measures –
-so-called non-pharmaceutical interventions (NPIs) – aimed at reducing
-contact rates in the population and thereby reducing transmission of the
-virus. In the results presented here, we apply a previously published
-microsimulation model to two countries: the UK (Great Britain
-specifically) and the US. We conclude that the effectiveness of any one
-intervention in isolation is likely to be limited, requiring multiple
-interventions to be combined to have a substantial impact on
-transmission. Two fundamental strategies are possible: (a) mitigation,
-which focuses on slowing but not necessarily stopping epidemic spread –
-reducing peak healthcare demand while protecting those most at risk of
-severe disease from infection, and (b) suppression, which aims to
-reverse epidemic growth, reducing case numbers to low levels and
-maintaining that situation indefinitely. Each policy has major
-challenges. We find that that optimal mitigation policies (combining
-home isolation of suspect cases, home quarantine of those living in the
-same household as suspect cases, and social distancing of the elderly
-and others at most risk of severe disease) might reduce peak healthcare
-demand by 2/3 and deaths by half. However, the resulting mitigated
-epidemic would still likely result in hundreds of thousands of deaths
-and health systems (most notably intensive care units) being overwhelmed
-many times over. For countries able to achieve it, this leaves
-suppression as the preferred policy option. We show that in the UK and
-US context, suppression will minimally require a combination of social
-distancing of the entire population, home isolation of cases and
-household quarantine of their family members. This may need to be
-supplemented by school and university closures, though it should be
-recognised that such closures may have negative impacts on health
-systems due to increased absenteeism. The major challenge of suppression
-is that this type of intensive intervention package – or something
-equivalently effective at reducing transmission – will need to be
-maintained until a vaccine becomes available (potentially 18 months or
-more) – given that we predict that transmission will quickly rebound if
-interventions are relaxed. We show that intermittent social distancing –
-triggered by trends in disease surveillance – may allow interventions to
-be relaxed temporarily in relative short time windows, but measures will
-need to be reintroduced if or when case numbers rebound. Last, while
-experience in China and now South Korea show that suppression is
-possible in the short term, it remains to be seen whether it is possible
-long-term, and whether the social and economic costs of the
-interventions adopted thus far can be reduced.
+The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.
-Replication of key findings from Report 9 using CovidSim
-reimplementation.
+Replication of key findings from Report 9 using CovidSim reimplementation.
-Authors: Seth Flaxman, Imperial College COVID-19
-Response Team, Samir
-Bhatt
+Authors: Seth Flaxman, Imperial College COVID-19 Response Team, Samir Bhatt
-Abstract: Obtained from OpenAlex
+Abstract: Obtained from OpenAlex
-Following the detection of the new coronavirus1 severe acute respiratory
-syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China,
-Europe has experienced large epidemics of coronavirus disease 2019
-(COVID-19). In response, many European countries have implemented
-non-pharmaceutical interventions, such as the closure of schools and
-national lockdowns. Here we study the effect of major interventions
-across 11 European countries for the period from the start of the
-COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns
-started to be lifted. Our model calculates backwards from observed
-deaths to estimate transmission that occurred several weeks previously,
-allowing for the time lag between infection and death. We use partial
-pooling of information between countries, with both individual and
-shared effects on the time-varying reproduction number (Rt). Pooling
-allows for more information to be used, helps to overcome idiosyncrasies
-in the data and enables more-timely estimates. Our model relies on fixed
-estimates of some epidemiological parameters (such as the infection
-fatality rate), does not include importation or subnational variation
-and assumes that changes in Rt are an immediate response to
-interventions rather than gradual changes in behaviour. Amidst the
-ongoing pandemic, we rely on death data that are incomplete, show
-systematic biases in reporting and are subject to future consolidation.
-We estimate that—for all of the countries we consider here—current
-interventions have been sufficient to drive Rt below 1 (probability Rt
-< 1.0 is greater than 99%) and achieve control of the epidemic. We
-estimate that across all 11 countries combined, between 12 and 15
-million individuals were infected with SARS-CoV-2 up to 4 May 2020,
-representing between 3.2% and 4.0% of the population. Our results show
-that major non-pharmaceutical interventions—and lockdowns in
-particular—have had a large effect on reducing transmission. Continued
-intervention should be considered to keep transmission of SARS-CoV-2
-under control. Modelling based on pooled data from 11 European countries
-indicates that non-pharmaceutical interventions—particularly
-lockdowns—have had a marked effect on SARS-CoV-2 transmission, driving
-the reproduction number of the infection below 1.
+Following the detection of the new coronavirus1 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (Rt). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that—for all of the countries we consider here—current interventions have been sufficient to drive Rt below 1 (probability Rt < 1.0 is greater than 99%) and achieve control of the epidemic. We estimate that across all 11 countries combined, between 12 and 15 million individuals were infected with SARS-CoV-2 up to 4 May 2020, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions—and lockdowns in particular—have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control. Modelling based on pooled data from 11 European countries indicates that non-pharmaceutical interventions—particularly lockdowns—have had a marked effect on SARS-CoV-2 transmission, driving the reproduction number of the infection below 1.
-This reproduction required several hours of compute time, but the
-reproduction itself was straightforward. All the R code was provided,
-along with a working Dockerfile.
+This reproduction required several hours of compute time, but the reproduction itself was straightforward. All the R code was provided, along with a working Dockerfile.
-R code for this paper shared with an earlier codecheck certifice
-(2020-011) from the same codebase.
+R code for this paper shared with an earlier codecheck certifice (2020-011) from the same codebase.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-AbstractBackgroundLight
-exposure entrains the circadian clock through the intrinsically
-photosensitive retinal ganglion cells, which sense light in addition to
-the cones and rods. In congenital achromatopsia (ACHM; prevalence
-1:30-50,000), the cone system is non-functional, resulting in severe
-light avoidance and photophobia at daytime light levels. How this
-condition affects circadian and neuroendocrine responses to light is not
-known.MethodsIn
-genetically confirmed ACHM patients (n=7; age 30-72 years; 6 women, 1
-male), we examined survey-assessed sleep/circadian phenotype (PSQI, ESS,
-MEQ, MCTQ), self-reported visual function (NEI-VFQ-25), sensitivity to
-light (VLSQ-8) and use of spectral filters that modify chronic light
-exposure. In all but one patient, we measured rest-activity cycles using
-actigraphy over 3 weeks and measured the melatonin phase angle of
-entrainment using the dim-light melatonin onset
-(DLMO).ResultsACHM
-patients experience a severely attenuated light-dark cycle due to severe
-light sensitivity and habitual use of filters to reduce retinal
-illumination. In aggregate, both MEQ and MCTQ indicated a tendency to
-late chronotype. We found regular rest-activity patterns in all patients
-and normal phase angles of entrainment in participants with a measurable
-DLMO.ConclusionsOur
-results reveal that a functional cone system and exposure to daytime
-light intensities are not necessary for regular behavioural and hormonal
-entrainment, even when survey-assessed sleep and circadian phenotype
-indicated a tendency for a late chronotype and sleep problems in our
-ACHM cohort. Our results can be explained by an adaptation mechanism in
-circadian photoreception which adjusts to the range of habitual light
-exposures.
+AbstractBackgroundLight exposure entrains the circadian clock through the intrinsically photosensitive retinal ganglion cells, which sense light in addition to the cones and rods. In congenital achromatopsia (ACHM; prevalence 1:30-50,000), the cone system is non-functional, resulting in severe light avoidance and photophobia at daytime light levels. How this condition affects circadian and neuroendocrine responses to light is not known.MethodsIn genetically confirmed ACHM patients (n=7; age 30-72 years; 6 women, 1 male), we examined survey-assessed sleep/circadian phenotype (PSQI, ESS, MEQ, MCTQ), self-reported visual function (NEI-VFQ-25), sensitivity to light (VLSQ-8) and use of spectral filters that modify chronic light exposure. In all but one patient, we measured rest-activity cycles using actigraphy over 3 weeks and measured the melatonin phase angle of entrainment using the dim-light melatonin onset (DLMO).ResultsACHM patients experience a severely attenuated light-dark cycle due to severe light sensitivity and habitual use of filters to reduce retinal illumination. In aggregate, both MEQ and MCTQ indicated a tendency to late chronotype. We found regular rest-activity patterns in all patients and normal phase angles of entrainment in participants with a measurable DLMO.ConclusionsOur results reveal that a functional cone system and exposure to daytime light intensities are not necessary for regular behavioural and hormonal entrainment, even when survey-assessed sleep and circadian phenotype indicated a tendency for a late chronotype and sleep problems in our ACHM cohort. Our results can be explained by an adaptation mechanism in circadian photoreception which adjusts to the range of habitual light exposures.
-This reproduction successfully reproduced all figures output by the
-original code. All original MATLAB code was provided and the
-reproduction had a small compute time.
+This reproduction successfully reproduced all figures output by the original code. All original MATLAB code was provided and the reproduction had a small compute time.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Perturbation of neuronal activity is key to understanding the
-brain’s functional properties, however, intervention studies typically
-perturb neurons in a nonspecific manner. Recent optogenetics techniques
-have enabled patterned perturbations, in which specific patterns of
-activity can be invoked in identified target neurons to reveal more
-specific cortical function. Here, we argue that patterned perturbation
-of neurons is in fact necessary to reveal the specific dynamics of
-inhibitory stabilization, emerging in cortical networks with strong
-excitatory and inhibitory functional subnetworks, as recently reported
-in mouse visual cortex. We propose a specific perturbative signature of
-these networks and investigate how this can be measured under different
-experimental conditions. Functionally, rapid spontaneous transitions
-between selective ensembles of neurons emerge in such networks,
-consistent with experimental results. Our study outlines the dynamical
-and functional properties of feature-specific inhibitory-stabilized
-networks, and suggests experimental protocols that can be used to detect
-them in the intact cortex.
+Perturbation of neuronal activity is key to understanding the brain’s functional properties, however, intervention studies typically perturb neurons in a nonspecific manner. Recent optogenetics techniques have enabled patterned perturbations, in which specific patterns of activity can be invoked in identified target neurons to reveal more specific cortical function. Here, we argue that patterned perturbation of neurons is in fact necessary to reveal the specific dynamics of inhibitory stabilization, emerging in cortical networks with strong excitatory and inhibitory functional subnetworks, as recently reported in mouse visual cortex. We propose a specific perturbative signature of these networks and investigate how this can be measured under different experimental conditions. Functionally, rapid spontaneous transitions between selective ensembles of neurons emerge in such networks, consistent with experimental results. Our study outlines the dynamical and functional properties of feature-specific inhibitory-stabilized networks, and suggests experimental protocols that can be used to detect them in the intact cortex.
-Some of the original MATLAB code was provided on ModelDB. This code was
-successfully rerun and reproduced some of the figures in the original
-paper. However this was a small subset of all the figures in the paper.
+Some of the original MATLAB code was provided on ModelDB. This code was successfully rerun and reproduced some of the figures in the original paper. However this was a small subset of all the figures in the paper.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-We developed a neural network model that can account for major
-elements common to human focal seizures. These include the tonic-clonic
-transition, slow advance of clinical semiology and corresponding seizure
-territory expansion, widespread EEG synchronization, and slowing of the
-ictal rhythm as the seizure approaches termination. These were
-reproduced by incorporating usage-dependent exhaustion of inhibition in
-an adaptive neural network that receives global feedback inhibition in
-addition to local recurrent projections. Our model proposes mechanisms
-that may underline common EEG seizure onset patterns and status
-epilepticus, and postulates a role for synaptic plasticity in the
-emergence of epileptic foci. Complex patterns of seizure activity and
-bi-stable seizure end-points arise when stochastic noise is included.
-With the rapid advancement of clinical and experimental tools, we
-believe that this model can provide a roadmap and potentially an in
-silico testbed for future explorations of seizure mechanisms and
-clinical therapies.
+We developed a neural network model that can account for major elements common to human focal seizures. These include the tonic-clonic transition, slow advance of clinical semiology and corresponding seizure territory expansion, widespread EEG synchronization, and slowing of the ictal rhythm as the seizure approaches termination. These were reproduced by incorporating usage-dependent exhaustion of inhibition in an adaptive neural network that receives global feedback inhibition in addition to local recurrent projections. Our model proposes mechanisms that may underline common EEG seizure onset patterns and status epilepticus, and postulates a role for synaptic plasticity in the emergence of epileptic foci. Complex patterns of seizure activity and bi-stable seizure end-points arise when stochastic noise is included. With the rapid advancement of clinical and experimental tools, we believe that this model can provide a roadmap and potentially an in silico testbed for future explorations of seizure mechanisms and clinical therapies.
-All code to run the neural network models discussed in the paper was
-successfully executed. Some results could be read off these models in
-action. The code to reproduce the figures given in the paper had more
-difficulties, with only some figures successfully recreated.
+All code to run the neural network models discussed in the paper was successfully executed. Some results could be read off these models in action. The code to reproduce the figures given in the paper had more difficulties, with only some figures successfully recreated.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-AbstractThis paper reflects on a number
-of trends towards a more open and reproducible approach to geographic
-and spatial data science over recent years. In particular, it considers
-trends towards Big Data, and the impacts this is having
-onspatialdata analysis and modelling. It
-identifies a turn in academia towards coding as a core analytic tool,
-and away from proprietary software tools offering ‘black boxes’ where
-the internal workings of the analysis are not revealed. It is argued
-that this closed form software is problematic and considers a number of
-ways in which issues identified in spatial data analysis (such as the
-MAUP) could be overlooked when working with closed tools, leading to
-problems of interpretation and possibly inappropriate actions and
-policies based on these. In addition, this paper considers the role that
-reproducible and open spatial science may play in such an approach,
-taking into account the issues raised. It highlights the dangers of
-failing to account for the geographical properties of data, now that all
-data are spatial (they are collected
-somewhere), the problems of a desire
-fornn = allobservations
-in data science and it identifies the need for a critical approach. This
-is one in which openness, transparency, sharing and reproducibility
-provide a mantra for defensible and robust spatial data
-science.
+AbstractThis paper reflects on a number of trends towards a more open and reproducible approach to geographic and spatial data science over recent years. In particular, it considers trends towards Big Data, and the impacts this is having onspatialdata analysis and modelling. It identifies a turn in academia towards coding as a core analytic tool, and away from proprietary software tools offering ‘black boxes’ where the internal workings of the analysis are not revealed. It is argued that this closed form software is problematic and considers a number of ways in which issues identified in spatial data analysis (such as the MAUP) could be overlooked when working with closed tools, leading to problems of interpretation and possibly inappropriate actions and policies based on these. In addition, this paper considers the role that reproducible and open spatial science may play in such an approach, taking into account the issues raised. It highlights the dangers of failing to account for the geographical properties of data, now that all data are spatial (they are collected somewhere), the problems of a desire for n n = allobservations in data science and it identifies the need for a critical approach. This is one in which openness, transparency, sharing and reproducibility provide a mantra for defensible and robust spatial data science.
-A small R script to render a map and two tables. Minor code adjustments
-were made, but reproduction of results (one figure, two tables) was
-successful.
+A small R script to render a map and two tables. Minor code adjustments were made, but reproduction of results (one figure, two tables) was successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-AbstractTwenty years have passed since
-Bivand and Gebhardt (J Geogr Syst 2(3):307–317,
-2000.10.1007/PL00011460)
-indicated that there was a good match between the then nascent
-open-source R programming language and environment and the needs of
-researchers analysing spatial data. Recalling the development of classes
-for spatial data presented in book form in Bivand et al. (Applied
-spatial data analysis with R. Springer, New York, 2008, Applied spatial
-data analysis with R, 2nd edn. Springer, New York, 2013), it is
-important to present the progress now occurring in representation of
-spatial data, and possible consequences for spatial data handling and
-the statistical analysis of spatial data. Beyond this, it is imperative
-to discuss the relationships between R-spatial software and the larger
-open-source geospatial software community on whose work R packages
-crucially depend.
+AbstractTwenty years have passed since Bivand and Gebhardt (J Geogr Syst 2(3):307–317, 2000.10.1007/PL00011460) indicated that there was a good match between the then nascent open-source R programming language and environment and the needs of researchers analysing spatial data. Recalling the development of classes for spatial data presented in book form in Bivand et al. (Applied spatial data analysis with R. Springer, New York, 2008, Applied spatial data analysis with R, 2nd edn. Springer, New York, 2013), it is important to present the progress now occurring in representation of spatial data, and possible consequences for spatial data handling and the statistical analysis of spatial data. Beyond this, it is imperative to discuss the relationships between R-spatial software and the larger open-source geospatial software community on whose work R packages crucially depend.
-Successful check of well-organised R script. All figures match the ones
-provided by the author.
+Successful check of well-organised R script. All figures match the ones provided by the author.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. With new forms of digital spatial data driving new
-applications for monitoring and understanding environmental change,
-there are growing demands on traditional GIS tools for spatial data
-storage, management and processing. Discrete Global Grid System (DGGS)
-are methods to tessellate globe into multiresolution grids, which
-represent a global spatial fabric capable of storing heterogeneous
-spatial data, and improved performance in data access, retrieval, and
-analysis. While DGGS-based GIS may hold potential for next-generation
-big data GIS platforms, few of studies have tried to implement them as a
-framework for operational spatial analysis. Cellular Automata (CA) is a
-classic dynamic modeling framework which has been used with traditional
-raster data model for various environmental modeling such as wildfire
-modeling, urban expansion modeling and so on. The main objectives of
-this paper are to (i) investigate the possibility of using DGGS for
-running dynamic spatial analysis, (ii) evaluate CA as a generic data
-model for dynamic phenomena modeling within a DGGS data model and (iii)
-evaluate an in-database approach for CA modelling. To do so, a case
-study into wildfire spread modelling is developed. Results demonstrate
-that using a DGGS data model not only provides the ability to integrate
-different data sources, but also provides a framework to do spatial
-analysis without using geometry-based analysis. This results in a
-simplified architecture and common spatial fabric to support development
-of a wide array of spatial algorithms. While considerable work remains
-to be done, CA modelling within a DGGS-based GIS is a robust and
-flexible modelling framework for big-data GIS analysis in an
-environmental monitoring context.
+Abstract. With new forms of digital spatial data driving new applications for monitoring and understanding environmental change, there are growing demands on traditional GIS tools for spatial data storage, management and processing. Discrete Global Grid System (DGGS) are methods to tessellate globe into multiresolution grids, which represent a global spatial fabric capable of storing heterogeneous spatial data, and improved performance in data access, retrieval, and analysis. While DGGS-based GIS may hold potential for next-generation big data GIS platforms, few of studies have tried to implement them as a framework for operational spatial analysis. Cellular Automata (CA) is a classic dynamic modeling framework which has been used with traditional raster data model for various environmental modeling such as wildfire modeling, urban expansion modeling and so on. The main objectives of this paper are to (i) investigate the possibility of using DGGS for running dynamic spatial analysis, (ii) evaluate CA as a generic data model for dynamic phenomena modeling within a DGGS data model and (iii) evaluate an in-database approach for CA modelling. To do so, a case study into wildfire spread modelling is developed. Results demonstrate that using a DGGS data model not only provides the ability to integrate different data sources, but also provides a framework to do spatial analysis without using geometry-based analysis. This results in a simplified architecture and common spatial fabric to support development of a wide array of spatial algorithms. While considerable work remains to be done, CA modelling within a DGGS-based GIS is a robust and flexible modelling framework for big-data GIS analysis in an environmental monitoring context.
-The check was straightforward as all material was provided and
-documented well, but computations took about 3 hours to run.
+The check was straightforward as all material was provided and documented well, but computations took about 3 hours to run.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Fully autonomously driving vehicles are expected to be
-a widely available technology in the near future. Privately owned cars,
-which remain parked for the majority of their lifetime, may therefore be
-capable of driving independently during their usual long parking periods
-(e.g. their owners working hours). Our analysis aims to focus on the
-potential of a privately owned shared car concept as transition period
-between the present usages of privately owned cars towards a
-transportation paradigm of privately owned shared autonomous vehicles.
-We propose two methods in the field of reachability analysis to evaluate
-the impact of such vehicles during parking periods. Our proposed methods
-are applied to a dataset of parking times of users of a telematics
-service provider in the Munich area (Germany). We show the impact of
-time and location dependent effects on the analyzed service coverage,
-such as business week rush hours or cover age divergence between urban
-and suburban regions.
+Abstract. Fully autonomously driving vehicles are expected to be a widely available technology in the near future. Privately owned cars, which remain parked for the majority of their lifetime, may therefore be capable of driving independently during their usual long parking periods (e.g. their owners working hours). Our analysis aims to focus on the potential of a privately owned shared car concept as transition period between the present usages of privately owned cars towards a transportation paradigm of privately owned shared autonomous vehicles. We propose two methods in the field of reachability analysis to evaluate the impact of such vehicles during parking periods. Our proposed methods are applied to a dataset of parking times of users of a telematics service provider in the Munich area (Germany). We show the impact of time and location dependent effects on the analyzed service coverage, such as business week rush hours or cover age divergence between urban and suburban regions.
-After initial problems because of absence of documentation, the
-reproduction was successful for some of the paper’s figures, but not the
-maps.
+After initial problems because of absence of documentation, the reproduction was successful for some of the paper’s figures, but not the maps.
Authors: Tobias Werner, Thomas Brinkhoff
@@ -262,28 +257,11 @@
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Unmanned aerial and submersible vehicles are used in
-an increasing number of applications especially for data collection in
-misanthropic environments. During a mission, such vehicles generate
-multiple spatio-temporal data streams suitable to be processed by data
-stream management systems (DSMS). The main approach of a DSMS is
-limiting the elements of a stream by using sliding and tilting windows
-with time intervals as temporal condition. However, due to varying
-vehicle speed and limited on-board resources, such temporal windows do
-not provide adequate support for spatio-temporal problems. For solving
-this problem, we propose a set of six new spatio-temporal window
-operators in this paper. This set comprises of sliding distance, tilting
-distance, tilting waypoint, session distance, jumping distance and an
-area window to limit stream elements based on spatial conditions. Each
-of the listed operators provides an individual behaviour to support
-sophisticated applications like spatial interpolation and forecasting.
-An evaluation based on an example trajectory shows the benefit of the
-presented operators for spatio-temporal applications.
+Abstract. Unmanned aerial and submersible vehicles are used in an increasing number of applications especially for data collection in misanthropic environments. During a mission, such vehicles generate multiple spatio-temporal data streams suitable to be processed by data stream management systems (DSMS). The main approach of a DSMS is limiting the elements of a stream by using sliding and tilting windows with time intervals as temporal condition. However, due to varying vehicle speed and limited on-board resources, such temporal windows do not provide adequate support for spatio-temporal problems. For solving this problem, we propose a set of six new spatio-temporal window operators in this paper. This set comprises of sliding distance, tilting distance, tilting waypoint, session distance, jumping distance and an area window to limit stream elements based on spatial conditions. Each of the listed operators provides an individual behaviour to support sophisticated applications like spatial interpolation and forecasting. An evaluation based on an example trajectory shows the benefit of the presented operators for spatio-temporal applications.
-Based on an updated data and code archive provided by the authors, we
-were able to deploy a database with the new functions, insert test data,
-and recreate all but one data-based figure with the provided scripts.
+Based on an updated data and code archive provided by the authors, we were able to deploy a database with the new functions, insert test data, and recreate all but one data-based figure with the provided scripts.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Discourse may contain both named and nominal entities.
-Most common nouns or nominal mentions in natural language do not have a
-single, simple meaning but rather a number of related meanings. This
-form of ambiguity led to the development of a task in natural language
-processing known as Word Sense Disambiguation. Recognition and
-categorisation of named and nominal entities is an essential step for
-Word Sense Disambiguation methods. Up to now, named entity recognition
-and categorisation systems mainly focused on the annotation,
-categorisation and identification of named entities. This paper focuses
-on the annotation and the identification of spatial nominal entities. We
-explore the combination of Transfer Learning principle and supervised
-learning algorithms, in order to build a system to detect spatial
-nominal entities. For this purpose, different supervised learning
-algorithms are evaluated with three different context sizes on two
-manually annotated datasets built from Wikipedia articles and hiking
-description texts. The studied algorithms have been selected for one or
-more of their specific properties potentially useful in solving our
-problem. The results of the first phase of experiments reveal that the
-selected algorithms have similar performances in terms of ability to
-detect spatial nominal entities. The study also confirms the importance
-of the size of the window to describe the context, when word-embedding
-principle is used to represent the semantics of each word.
+Abstract. Discourse may contain both named and nominal entities. Most common nouns or nominal mentions in natural language do not have a single, simple meaning but rather a number of related meanings. This form of ambiguity led to the development of a task in natural language processing known as Word Sense Disambiguation. Recognition and categorisation of named and nominal entities is an essential step for Word Sense Disambiguation methods. Up to now, named entity recognition and categorisation systems mainly focused on the annotation, categorisation and identification of named entities. This paper focuses on the annotation and the identification of spatial nominal entities. We explore the combination of Transfer Learning principle and supervised learning algorithms, in order to build a system to detect spatial nominal entities. For this purpose, different supervised learning algorithms are evaluated with three different context sizes on two manually annotated datasets built from Wikipedia articles and hiking description texts. The studied algorithms have been selected for one or more of their specific properties potentially useful in solving our problem. The results of the first phase of experiments reveal that the selected algorithms have similar performances in terms of ability to detect spatial nominal entities. The study also confirms the importance of the size of the window to describe the context, when word-embedding principle is used to represent the semantics of each word.
-After some adjustments of the computational environment, the commendable
-material compiled by the authors lead to a mostly successful
-reproduction.
+After some adjustments of the computational environment, the commendable material compiled by the authors lead to a mostly successful reproduction.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Understanding syntactic and semantic structure of
-geographic questions is a necessary step towards true geographic
-question-answering (GeoQA) machines. The empirical basis for the
-understanding of the capabilities expected from GeoQA systems are
-geographic question corpora. Available corpora in English have been
-mostly drawn from generic Web search logs or limited user studies,
-supporting the focus of GeoQA systems on retrieving factoids: factual
-knowledge about particular places and everyday processes. Yet, the
-majority of questions enquired about in the spatial sciences go beyond
-simple place facts, with more complex analytical intents informing the
-questions. In this paper, we introduce a new corpus of geo-analytic
-questions drawn from English textbooks and scientific articles. We
-analyse and compare this corpus with two general-purpose GeoQA corpora
-in terms of grammatical complexity and semantic concepts, using a new
-parsing method that allows us to differentiate and quantify patterns of
-a question’s intent.
+Abstract. Understanding syntactic and semantic structure of geographic questions is a necessary step towards true geographic question-answering (GeoQA) machines. The empirical basis for the understanding of the capabilities expected from GeoQA systems are geographic question corpora. Available corpora in English have been mostly drawn from generic Web search logs or limited user studies, supporting the focus of GeoQA systems on retrieving factoids: factual knowledge about particular places and everyday processes. Yet, the majority of questions enquired about in the spatial sciences go beyond simple place facts, with more complex analytical intents informing the questions. In this paper, we introduce a new corpus of geo-analytic questions drawn from English textbooks and scientific articles. We analyse and compare this corpus with two general-purpose GeoQA corpora in terms of grammatical complexity and semantic concepts, using a new parsing method that allows us to differentiate and quantify patterns of a question’s intent.
-The workflow could be executed using the provided instructions and the
-provided scripts created a subset of the included figures. Although some
-key figures were not created by the provided data and code, the
-reproduction was partially successful.
+The workflow could be executed using the provided instructions and the provided scripts created a subset of the included figures. Although some key figures were not created by the provided data and code, the reproduction was partially successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. GDELT is a machine coded database of events that uses
-both foreign and domestic news feeds and contains over a quarter of a
-billion worldwide event records categorized into three hundred
-categories. This paper compares the spatial footprint of GDELT event
-mentions with those of event related geo-tagged tweets for Hurricane
-Dorian in the South-Eastern United States. Besides examining event
-related GDELT and Twitter data abundance, the study relates areas of
-elevated GDELT news and tweeting activities to the locations of the
-hurricane track over a six-day period, and statistically analyzes
-distances between daily GDELT event mentions and tweets, and the
-hurricane center on different days. It assesses the potential role of
-the geographic coverage of the cone in hurricane prediction maps on the
-level of event related news and tweeting activities. The study also
-discusses pros and cons of both data sources for event tracking with
-regards to data abundance, spatial and temporal resolution, and thematic
-accuracy.
+Abstract. GDELT is a machine coded database of events that uses both foreign and domestic news feeds and contains over a quarter of a billion worldwide event records categorized into three hundred categories. This paper compares the spatial footprint of GDELT event mentions with those of event related geo-tagged tweets for Hurricane Dorian in the South-Eastern United States. Besides examining event related GDELT and Twitter data abundance, the study relates areas of elevated GDELT news and tweeting activities to the locations of the hurricane track over a six-day period, and statistically analyzes distances between daily GDELT event mentions and tweets, and the hurricane center on different days. It assesses the potential role of the geographic coverage of the cone in hurricane prediction maps on the level of event related news and tweeting activities. The study also discusses pros and cons of both data sources for event tracking with regards to data abundance, spatial and temporal resolution, and thematic accuracy.
-After initial problems because of absence of documentation, the
-reproduction was successful for some of the paper’s figures, but not the
-maps.
+After initial problems because of absence of documentation, the reproduction was successful for some of the paper’s figures, but not the maps.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract
-BackgroundThe amount of data and
-behavior changes in society happens at a swift pace in this
-interconnected world. Consequently, machine learning algorithms lose
-accuracy because they do not know these new patterns. This change in the
-data pattern is known as concept drift. There exist many approaches for
-dealing with these drifts. Usually, these methods are costly to
-implement because they require (i) knowledge of drift detection
-algorithms, (ii) software engineering strategies, and (iii) continuous
-maintenance concerning new drifts.
-ResultsThis article proposes to create
-Driftage: a new framework using multi-agent systems to simplify the
-implementation of concept drift detectors considerably and divide
-concept drift detection responsibilities between agents, enhancing
-explainability of each part of drift detection. As a case study, we
-illustrate our strategy using a muscle activity monitor of
-electromyography. We show a reduction in the number of false-positive
-drifts detected, improving detection interpretability, and enabling
-concept drift detectors’ interactivity with other knowledge
-bases.
-ConclusionWe conclude that using
-Driftage, arises a new paradigm to implement concept drift algorithms
-with multi-agent architecture that contributes to split drift detection
-responsability, algorithms interpretability and more dynamic algorithms
-adaptation.
+AbstractBackgroundThe amount of data and behavior changes in society happens at a swift pace in this interconnected world. Consequently, machine learning algorithms lose accuracy because they do not know these new patterns. This change in the data pattern is known as concept drift. There exist many approaches for dealing with these drifts. Usually, these methods are costly to implement because they require (i) knowledge of drift detection algorithms, (ii) software engineering strategies, and (iii) continuous maintenance concerning new drifts.ResultsThis article proposes to create Driftage: a new framework using multi-agent systems to simplify the implementation of concept drift detectors considerably and divide concept drift detection responsibilities between agents, enhancing explainability of each part of drift detection. As a case study, we illustrate our strategy using a muscle activity monitor of electromyography. We show a reduction in the number of false-positive drifts detected, improving detection interpretability, and enabling concept drift detectors’ interactivity with other knowledge bases.ConclusionWe conclude that using Driftage, arises a new paradigm to implement concept drift algorithms with multi-agent architecture that contributes to split drift detection responsability, algorithms interpretability and more dynamic algorithms adaptation.
-Abstract: Obtained from OpenAlex
+Abstract: Obtained from OpenAlex
-Global and local analyses of spatial autocorrelation are commonplace in
-spatial archaeology. However, they are exclusively focused on continuous
-numerical parameters, even though logical (presence/absence) and
-categorical parameters are equally frequent in archaeological research.
-Global tests of spatial dependence for categorical data are routinely
-used in other fields, and local versions of these tests (known as LICD)
-have recently been developed. This paper provides a detailed description
-of such methods, and presents the first adaptation and application of
-LICD to archaeological data. Different LICD versions have been tested on
-two case-studies: (a) an archaeological grid, with object presence or
-absence recorded for each cell; (b) Historic Landscape Characterisation,
-with the origin of character types (mediaeval, post-mediaeval or modern)
-recorded for each region. These examples seek to showcase and promote
-the use of LICD in landscape and intra-site archaeology.
+Global and local analyses of spatial autocorrelation are commonplace in spatial archaeology. However, they are exclusively focused on continuous numerical parameters, even though logical (presence/absence) and categorical parameters are equally frequent in archaeological research. Global tests of spatial dependence for categorical data are routinely used in other fields, and local versions of these tests (known as LICD) have recently been developed. This paper provides a detailed description of such methods, and presents the first adaptation and application of LICD to archaeological data. Different LICD versions have been tested on two case-studies: (a) an archaeological grid, with object presence or absence recorded for each cell; (b) Historic Landscape Characterisation, with the origin of character types (mediaeval, post-mediaeval or modern) recorded for each region. These examples seek to showcase and promote the use of LICD in landscape and intra-site archaeology.
-This workflow was very straightforward to check following the authors’
-README. All figures stored in the repository could be recreated and
-match the ones given in the manuscript.
+This workflow was very straightforward to check following the authors’ README. All figures stored in the repository could be recreated and match the ones given in the manuscript.
-The authors provided all material and documented the process well, the
-check was therefore straightforward. Due to long computation times, only
-a subset of the results could be checked. Reproducing the results in the
-repository was successful, with non-significant numerical discrepancies.
-However, a small number of minor differences with the results in the
-arXiv preprint merit clarification.
+The authors provided all material and documented the process well, the check was therefore straightforward. Due to long computation times, only a subset of the results could be checked. Reproducing the results in the repository was successful, with non-significant numerical discrepancies. However, a small number of minor differences with the results in the arXiv preprint merit clarification.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Detecting changes is an important task to update
-databases and find irregularities in spatial data. Every couple of
-years, national mapping agencies (NMAs) acquire nation-wide point cloud
-data from Airborne Laser Scanning (ALS) as well as from Dense Image
-Matching (DIM) using aerial images. Besides deriving several other
-products such as Digital Elevation Models (DEMs) from them, those point
-clouds also offer the chance to detect changes between two points in
-time on a large scale. Buildings are an important object class in the
-context of change detection to update cadastre data. As detecting
-changes manually is very time consuming, the aim of this study is to
-provide reliable change detections for different building sizes in order
-to support NMAs in their task to update their databases. As datasets of
-different times may have varying point densities due to technological
-advancements or different sensors, we propose a raster-based approach,
-which is independent of the point density altogether. Within a raster
-cell, our approach considers the height distribution of all points for
-two points in time by exploiting the Jensen-Shannon distance to measure
-their similarity. Our proposed method outperforms simple threshold
-methods on detecting building changes with respect to the same or
-different point cloud types. In combination with our proposed class
-change detection approach, we achieve a change detection performance
-measured by the mean F1-Score of about 71% between two ALS and about 60%
-between ALS and DIM point clouds acquired at different times.
+Abstract. Detecting changes is an important task to update databases and find irregularities in spatial data. Every couple of years, national mapping agencies (NMAs) acquire nation-wide point cloud data from Airborne Laser Scanning (ALS) as well as from Dense Image Matching (DIM) using aerial images. Besides deriving several other products such as Digital Elevation Models (DEMs) from them, those point clouds also offer the chance to detect changes between two points in time on a large scale. Buildings are an important object class in the context of change detection to update cadastre data. As detecting changes manually is very time consuming, the aim of this study is to provide reliable change detections for different building sizes in order to support NMAs in their task to update their databases. As datasets of different times may have varying point densities due to technological advancements or different sensors, we propose a raster-based approach, which is independent of the point density altogether. Within a raster cell, our approach considers the height distribution of all points for two points in time by exploiting the Jensen-Shannon distance to measure their similarity. Our proposed method outperforms simple threshold methods on detecting building changes with respect to the same or different point cloud types. In combination with our proposed class change detection approach, we achieve a change detection performance measured by the mean F1-Score of about 71% between two ALS and about 60% between ALS and DIM point clouds acquired at different times.
-The reproduction was partially successful. The paper data and software
-are not publicly available due to licence issues with the cooperating
-parties. For the scope of this reproduction however, the authors
-provided a synthetic data set, a script to generating a synthetic data
-set from a publicly available data source, and the analysis code. Using
-the provided synthetic data set the executability of the provided
-analysis code was confirmed. The methodology behind all figures has been
-reproduced.
+The reproduction was partially successful. The paper data and software are not publicly available due to licence issues with the cooperating parties. For the scope of this reproduction however, the authors provided a synthetic data set, a script to generating a synthetic data set from a publicly available data source, and the analysis code. Using the provided synthetic data set the executability of the provided analysis code was confirmed. The methodology behind all figures has been reproduced.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The prominence of landmarks in aiding pedestrian
-navigation has been highlighted in various studies; people rely strongly
-on visual landmarks, especially when navigating in unfamiliar
-environments. The paper describes the design and implementation of a
-study for assessing drivers’ spatial abilities, when navigating in an
-unfamiliar environment. Two types of route directions based on
-references to either landmarks or street names were given to two groups
-of participants. Three geospatial learning tasks are used to evaluate
-these abilities: map sketching, distance, and direction estimation. The
-findings showed that landmark-based route instructions help drivers
-develop a better cognitive map of the route. On the other hand,
-instructions either based on landmarks or on street information do not
-have an effect on distance or direction estimates. Nonetheless,
-qualitative analysis of directions and distances estimations gave
-interesting results. Findings associated with self-assessment of
-environmental spatial abilities using the Santa Barbara Sense of
-Direction Scale (SBSOD) seem to support prediction of at least one of
-the drivers’ abilities among those assessed in this study.
+Abstract. The prominence of landmarks in aiding pedestrian navigation has been highlighted in various studies; people rely strongly on visual landmarks, especially when navigating in unfamiliar environments. The paper describes the design and implementation of a study for assessing drivers’ spatial abilities, when navigating in an unfamiliar environment. Two types of route directions based on references to either landmarks or street names were given to two groups of participants. Three geospatial learning tasks are used to evaluate these abilities: map sketching, distance, and direction estimation. The findings showed that landmark-based route instructions help drivers develop a better cognitive map of the route. On the other hand, instructions either based on landmarks or on street information do not have an effect on distance or direction estimates. Nonetheless, qualitative analysis of directions and distances estimations gave interesting results. Findings associated with self-assessment of environmental spatial abilities using the Santa Barbara Sense of Direction Scale (SBSOD) seem to support prediction of at least one of the drivers’ abilities among those assessed in this study.
-The updated submission contains a DASA section and provides the analysis
-script, dataset and questionnaires. The provided R script computes all
-statistical analyses presented in the paper and generates the key figure
-and data for both presented tables. The reproduction was successful.
+The updated submission contains a DASA section and provides the analysis script, dataset and questionnaires. The provided R script computes all statistical analyses presented in the paper and generates the key figure and data for both presented tables. The reproduction was successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. This paper explores the role deep convolutional neural
-networks play in automated extraction of linear structures using
-semantic segmentation techniques in Digital Terrain Models (DTMs). DTM
-is a regularly gridded raster created from laser scanning point clouds
-and represents elevations of the bare earth surface with respect to a
-reference. Recent advances in Deep Learning (DL) have made it possible
-to explore the use of semantic segmentation for detection of terrain
-structures in DTMs. This research examines two novel and practical deep
-convolutional neural network architectures i.e. an encoder-decoder
-network named as SegNet and the recent state-of-the-art high-resolution
-network (HRNet). This paper initially focuses on the pixel-wise binary
-classification in order to validate the applicability of the proposed
-approaches. The networks are trained to distinguish between points
-belonging to linear structures and those belonging to background. In the
-second step, multi-class segmentation is carried out on the same DTM
-dataset. The model is trained to not only detect a linear feature, but
-also to categorize it as one of the classes: hollow ways, roads, forest
-paths, historical paths, and streams. Results of the experiment in
-addition to the quantitative and qualitative analysis show the
-applicability of deep neural networks for detection of terrain
-structures in DTMs. From the deep learning models utilized, HRNet gives
-better results.
+Abstract. This paper explores the role deep convolutional neural networks play in automated extraction of linear structures using semantic segmentation techniques in Digital Terrain Models (DTMs). DTM is a regularly gridded raster created from laser scanning point clouds and represents elevations of the bare earth surface with respect to a reference. Recent advances in Deep Learning (DL) have made it possible to explore the use of semantic segmentation for detection of terrain structures in DTMs. This research examines two novel and practical deep convolutional neural network architectures i.e. an encoder-decoder network named as SegNet and the recent state-of-the-art high-resolution network (HRNet). This paper initially focuses on the pixel-wise binary classification in order to validate the applicability of the proposed approaches. The networks are trained to distinguish between points belonging to linear structures and those belonging to background. In the second step, multi-class segmentation is carried out on the same DTM dataset. The model is trained to not only detect a linear feature, but also to categorize it as one of the classes: hollow ways, roads, forest paths, historical paths, and streams. Results of the experiment in addition to the quantitative and qualitative analysis show the applicability of deep neural networks for detection of terrain structures in DTMs. From the deep learning models utilized, HRNet gives better results.
-The provided workflow was partially reproduced. Based on the provided
-test file and instructions, we were able to recreate the computing
-environment and run the segmentation models. Relevant tables from the
-paper could be recreated. The training and validation part of the
-workflow is irreproducible because of proprietary data, therefore no
-figures could be recreated.
+The provided workflow was partially reproduced. Based on the provided test file and instructions, we were able to recreate the computing environment and run the segmentation models. Relevant tables from the paper could be recreated. The training and validation part of the workflow is irreproducible because of proprietary data, therefore no figures could be recreated.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Metadata is key to effective knowledge organization,
-and designing user interfaces that maximize user performance and user
-experience during metadata creation would benefit several areas of
-GIScience. Yet, empirically-derived guidelines for user interfaces
-supporting GI-metadata creation are still scarce. As a step towards
-mitigating that gap, this work has implemented and evaluated a prototype
-that produces semantically-rich metadata for web maps via one of two
-input modalities: typing or speech. A controlled experiment (N=12) to
-investigate the merits of both modalities has revealed that (i) typing
-and speech were comparable as far as input duration time is concerned;
-and (ii) they received opposed ratings concerning their pragmatic and
-hedonic qualities. Combining both might thus be beneficial for
-GI-metadata creation user interfaces. The findings are useful to ongoing
-work on semantic enablement for spatial data infrastructure and
-note-taking during visual analytics.
+Abstract. Metadata is key to effective knowledge organization, and designing user interfaces that maximize user performance and user experience during metadata creation would benefit several areas of GIScience. Yet, empirically-derived guidelines for user interfaces supporting GI-metadata creation are still scarce. As a step towards mitigating that gap, this work has implemented and evaluated a prototype that produces semantically-rich metadata for web maps via one of two input modalities: typing or speech. A controlled experiment (N=12) to investigate the merits of both modalities has revealed that (i) typing and speech were comparable as far as input duration time is concerned; and (ii) they received opposed ratings concerning their pragmatic and hedonic qualities. Combining both might thus be beneficial for GI-metadata creation user interfaces. The findings are useful to ongoing work on semantic enablement for spatial data infrastructure and note-taking during visual analytics.
-The paper presents the results of a user experiment to improve
-GI-metadata using speech. A complete reproduction is practically
-impossible to achieve. This reproducibility report therefore
-investigated two components: First, whether sufficient information is
-provided to replicate the experiment elsewhere with a different group of
-participants. Second, whether sufficient information is provided to
-reproduce the analysis of the experimental results. The conclusion is
-positive for both. The original prototype is accessible online at the
-time of this writing. To reproduce the results, the provided input data,
-R code, and Excel spreadsheet lead to the same results as given in the
-paper and the prototype for the user experiment could be run locally.
+The paper presents the results of a user experiment to improve GI-metadata using speech. A complete reproduction is practically impossible to achieve. This reproducibility report therefore investigated two components: First, whether sufficient information is provided to replicate the experiment elsewhere with a different group of participants. Second, whether sufficient information is provided to reproduce the analysis of the experimental results. The conclusion is positive for both. The original prototype is accessible online at the time of this writing. To reproduce the results, the provided input data, R code, and Excel spreadsheet lead to the same results as given in the paper and the prototype for the user experiment could be run locally.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Identifying determinants of tourist destination choice
-is an important task in the study of nature-based tourism.
-Traditionally, the study of tourist behavior relies on survey data and
-travel logs, which are labor-intensive and time-consuming. Thanks to
-location-based social networks, more detailed data is available at a
-finer grained spatio-temporal scale. This allows for better insights
-into travel patterns and interactions between attractions, e.g., parks.
-Meanwhile, such data sources also bring along a novel social influence
-component that has not yet been widely studied in terms of travel
-decisions. For example, social influencers post about certain places,
-which tend to influence destination choices of tourists. Therefore, in
-this paper, we propose a socially aware Huff model to account for this
-social factor in the study of destination choice. Moreover, with
-fine-grained social media data, interactions between attractions (i.e.,
-the neighboring effects) can be better quantified and thus integrated
-into models as another factor. In our experiment, we calibrate a model
-by using trip sequences extracted from geotagged Flickr photos within
-two national parks in the United States. Our results demonstrate that
-the socially aware Huff model better simulates tourist travel
-preferences. In addition, we explore the significance of each factor and
-summarize the spatial-temporal travel pattern for each attraction. The
-socially aware Huff model and the calibration method can be applied to
-other fields such as promotional marketing.
+Abstract. Identifying determinants of tourist destination choice is an important task in the study of nature-based tourism. Traditionally, the study of tourist behavior relies on survey data and travel logs, which are labor-intensive and time-consuming. Thanks to location-based social networks, more detailed data is available at a finer grained spatio-temporal scale. This allows for better insights into travel patterns and interactions between attractions, e.g., parks. Meanwhile, such data sources also bring along a novel social influence component that has not yet been widely studied in terms of travel decisions. For example, social influencers post about certain places, which tend to influence destination choices of tourists. Therefore, in this paper, we propose a socially aware Huff model to account for this social factor in the study of destination choice. Moreover, with fine-grained social media data, interactions between attractions (i.e., the neighboring effects) can be better quantified and thus integrated into models as another factor. In our experiment, we calibrate a model by using trip sequences extracted from geotagged Flickr photos within two national parks in the United States. Our results demonstrate that the socially aware Huff model better simulates tourist travel preferences. In addition, we explore the significance of each factor and summarize the spatial-temporal travel pattern for each attraction. The socially aware Huff model and the calibration method can be applied to other fields such as promotional marketing.
-The code, sample API query, and downloaded data were published in a
-public GitHub repository with a working Binder link. All files
-containing the code could be executed and all tables presented in the
-paper could be reproduced with only minor changes to the code. However,
-the code does not create figures contained in the paper and an attempt
-to change the results of the model evaluation by changing its numerical
-assumption was unsuccessful. The authors demonstrate concern for the
-reproducibility of their work and actively improved the reproducibility
-workflow throughout the reproducibility review process.
+The code, sample API query, and downloaded data were published in a public GitHub repository with a working Binder link. All files containing the code could be executed and all tables presented in the paper could be reproduced with only minor changes to the code. However, the code does not create figures contained in the paper and an attempt to change the results of the model evaluation by changing its numerical assumption was unsuccessful. The authors demonstrate concern for the reproducibility of their work and actively improved the reproducibility workflow throughout the reproducibility review process.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Historical maps are frequently neither readable,
-searchable nor analyzable by machines due to lacking databases or
-ancillary information about their content. Identifying and annotating
-map labels is seen as a first step towards an automated legibility of
-those. This article investigates a universal and transferable
-methodology for the work with large-scale historical maps and their
-comparability to others while reducing manual intervention to a minimum.
-We present an end-to-end approach which increases the number of true
-positive identified labels by combining available text detection,
-recognition, and similarity measuring tools with own enhancements. The
-comparison of recognized historical with current street names produces a
-satisfactory accordance which can be used to assign their point-like
-representatives within a final rough georeferencing. The demonstrated
-workflow facilitates a spatial orientation within large-scale historical
-maps by enabling the establishment of relating databases. Assigning the
-identified labels to the geometries of related map features may
-contribute to machine-readable and analyzable historical maps.
+Abstract. Historical maps are frequently neither readable, searchable nor analyzable by machines due to lacking databases or ancillary information about their content. Identifying and annotating map labels is seen as a first step towards an automated legibility of those. This article investigates a universal and transferable methodology for the work with large-scale historical maps and their comparability to others while reducing manual intervention to a minimum. We present an end-to-end approach which increases the number of true positive identified labels by combining available text detection, recognition, and similarity measuring tools with own enhancements. The comparison of recognized historical with current street names produces a satisfactory accordance which can be used to assign their point-like representatives within a final rough georeferencing. The demonstrated workflow facilitates a spatial orientation within large-scale historical maps by enabling the establishment of relating databases. Assigning the identified labels to the geometries of related map features may contribute to machine-readable and analyzable historical maps.
-The provided workflow could be partially reproduced, notably the text
-detection and string similarity calculations could be executed and
-provide sufficiently similar results. Some manual steps were included
-which could not be reproduced, as well as a final step due to long
-execution time. The software stack was challenging to install but
-overall well documented.
+The provided workflow could be partially reproduced, notably the text detection and string similarity calculations could be executed and provide sufficiently similar results. Some manual steps were included which could not be reproduced, as well as a final step due to long execution time. The software stack was challenging to install but overall well documented.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Climate change leads to an increasing number of flood
-events that poses threats to a large share of the global population. In
-addition to direct effects, flooding leads to indirect effect due to
-damages of the road infrastructure that might limit accessibility of
-health sites. For disaster preparedness it is important to know how
-flood events impact accessibility in that respect. We analyzed this at
-the example of the capital of Indonesia, Jakarta based on the flood
-event of 2013. The analysis was based on information about the road
-network and health sites from OpenStreetMap. We assessed impacts of the
-flood event by comparing centrality indicators of the road network as
-well as by an accessibility analysis of health sites before and during
-the event. The flooded areas were home to 2.75 million inhabitants and
-hosted 79 clinics and hospitals. The flood split the road network into
-several subgraphs. The city center maintained its importance for
-time-efficient routing as well as for easily accessible healthcare but
-might be prone to traffic congestion after such an event. Indirect
-effects via interrupted road traffic through flooded areas affected
-around 1.5 million inhabitants and led to an increase of travel time to
-the nearest hospital by five minutes based on normal traffic
-conditions.
+Abstract. Climate change leads to an increasing number of flood events that poses threats to a large share of the global population. In addition to direct effects, flooding leads to indirect effect due to damages of the road infrastructure that might limit accessibility of health sites. For disaster preparedness it is important to know how flood events impact accessibility in that respect. We analyzed this at the example of the capital of Indonesia, Jakarta based on the flood event of 2013. The analysis was based on information about the road network and health sites from OpenStreetMap. We assessed impacts of the flood event by comparing centrality indicators of the road network as well as by an accessibility analysis of health sites before and during the event. The flooded areas were home to 2.75 million inhabitants and hosted 79 clinics and hospitals. The flood split the road network into several subgraphs. The city center maintained its importance for time-efficient routing as well as for easily accessible healthcare but might be prone to traffic congestion after such an event. Indirect effects via interrupted road traffic through flooded areas affected around 1.5 million inhabitants and led to an increase of travel time to the nearest hospital by five minutes based on normal traffic conditions.
-The provided workflow was partially reproduced. The reproduction
-described in this report uses the Python code provided in the Github.com
-repo and data provided by the authors via email. The figures generated
-using this source code are not identical to the figures in the paper.
-However, many of the results reported in the paper could be reproduced.
+The provided workflow was partially reproduced. The reproduction described in this report uses the Python code provided in the Github.com repo and data provided by the authors via email. The figures generated using this source code are not identical to the figures in the paper. However, many of the results reported in the paper could be reproduced.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Data produced by social networks may contain weak
-signals of possible epidemic outbreaks. In this paper, we focus on
-Twitter data during the waiting period before the appearance of COVID-19
-first cases outside China. Among the huge flow of tweets that reflects a
-global growing concern in all countries, we propose to analyze such data
-with an adaptation of the TF-IDF measure. It allows the users to extract
-the discriminant vocabularies used across time and space. The results
-are then discussed to show how the specific spatio-temporal anchoring of
-the extracted terms make it possible to follow the crisis dynamics on
-different scales of time and space.
+Abstract. Data produced by social networks may contain weak signals of possible epidemic outbreaks. In this paper, we focus on Twitter data during the waiting period before the appearance of COVID-19 first cases outside China. Among the huge flow of tweets that reflects a global growing concern in all countries, we propose to analyze such data with an adaptation of the TF-IDF measure. It allows the users to extract the discriminant vocabularies used across time and space. The results are then discussed to show how the specific spatio-temporal anchoring of the extracted terms make it possible to follow the crisis dynamics on different scales of time and space.
-The authors provide a well documented workflow analysing a large number
-of Tweets over a considerable time span. Because of the data size, the
-authors provided instructions for a data subset, for which the code
-could be executed successfully and the created figures match the
-provided baseline, and also confirm that data can be created and the
-code is available for the results reported in the paper.
+The authors provide a well documented workflow analysing a large number of Tweets over a considerable time span. Because of the data size, the authors provided instructions for a data subset, for which the code could be executed successfully and the created figures match the provided baseline, and also confirm that data can be created and the code is available for the results reported in the paper.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. During spatial decision making, the quality of the
-utilized data is of high importance. During navigation these decisions
-are crucial for being routed to the desired destination (usually going
-by the shortest or fastest route). Road networks, the main data source
-for routing, are prone to changes which can have a big impact on the
-computed route and therefore on travel time. For instance, routes
-computed using an outdated street network can result in longer travel
-times, in longer distance, as well in cases where the desired
-destination might not be anymore reachable via the computed route. Data
-from OpenStreetMap with different timestamps allows us to download road
-network snapshots from different years, i.e., from 2014 to 2020. On each
-of those datasets the fastest route between 500 randomly chosen point
-pairs in Vienna, Austria, was computed. These routes were also
-reconstructed on the most recent dataset for evaluation reasons. The
-resulting travel times, travel length as well as feasibility of the
-route were compared with the most recent dataset. The results provide a
-first assessment of temporal quality based on the currentness of a
-dataset.
+Abstract. During spatial decision making, the quality of the utilized data is of high importance. During navigation these decisions are crucial for being routed to the desired destination (usually going by the shortest or fastest route). Road networks, the main data source for routing, are prone to changes which can have a big impact on the computed route and therefore on travel time. For instance, routes computed using an outdated street network can result in longer travel times, in longer distance, as well in cases where the desired destination might not be anymore reachable via the computed route. Data from OpenStreetMap with different timestamps allows us to download road network snapshots from different years, i.e., from 2014 to 2020. On each of those datasets the fastest route between 500 randomly chosen point pairs in Vienna, Austria, was computed. These routes were also reconstructed on the most recent dataset for evaluation reasons. The resulting travel times, travel length as well as feasibility of the route were compared with the most recent dataset. The results provide a first assessment of temporal quality based on the currentness of a dataset.
-The reproduction was successful. All provided scripts could be execute
-after clarification with the authors using the provided data. Some
-manual steps could not be reproduced, but all code and data are shared.
-The script outputs match what is presented in the paper considering the
-randomness in the workflow. Relevant figures and tables could be
-recreated successfully.
+The reproduction was successful. All provided scripts could be execute after clarification with the authors using the provided data. Some manual steps could not be reproduced, but all code and data are shared. The script outputs match what is presented in the paper considering the randomness in the workflow. Relevant figures and tables could be recreated successfully.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Point clouds data provides new potentials for
-automated construction of more geometrically accurate and semantically
-rich 3D models for indoor environments. Recent advances in deep learning
-methods on point cloud semantic segmentation demonstrated impressive
-accuracy in labeling points of 3D surfaces with object classes. However,
-it remains challenging to reconstruct the shape of semantic objects from
-semantically-labeled 3D points, due to imperfection of such data and the
-under-determination of object construction algorithms. We have little
-empirical knowledge about how data imperfections affect the
-reconstruction of 3D indoor room objects. This paper contributes to
-understanding the nature of such imperfection of 3D point cloud data and
-semantic segmentation algorithms by analyzing the reconstructability of
-indoor room objects from semantically-labeled point cloud. 181 rooms
-from Stanford Large-Scale 3D Indoor Spaces Dataset (S3DIS) were used in
-our experiment. After generating semantic labels on point-clouds using
-PointNet++ segmentic segmentation algorithm, we use human coders to
-judge the reconstructability of indoor objects, following a qualitative
-coding scheme. Human exploration of object shape imperfection was
-assisted by a visual analytic tool in making their judgement. We found
-that high point-level accuracy achieved through semantic segmentation of
-point cloud data does not guarantee high object-level accuracy. The
-extent of this problem varies widely among different spatial settings
-and configurations. We discuss the significance of these findings on the
-choice of 3D reconstruction methods.
+Abstract. Point clouds data provides new potentials for automated construction of more geometrically accurate and semantically rich 3D models for indoor environments. Recent advances in deep learning methods on point cloud semantic segmentation demonstrated impressive accuracy in labeling points of 3D surfaces with object classes. However, it remains challenging to reconstruct the shape of semantic objects from semantically-labeled 3D points, due to imperfection of such data and the under-determination of object construction algorithms. We have little empirical knowledge about how data imperfections affect the reconstruction of 3D indoor room objects. This paper contributes to understanding the nature of such imperfection of 3D point cloud data and semantic segmentation algorithms by analyzing the reconstructability of indoor room objects from semantically-labeled point cloud. 181 rooms from Stanford Large-Scale 3D Indoor Spaces Dataset (S3DIS) were used in our experiment. After generating semantic labels on point-clouds using PointNet++ segmentic segmentation algorithm, we use human coders to judge the reconstructability of indoor objects, following a qualitative coding scheme. Human exploration of object shape imperfection was assisted by a visual analytic tool in making their judgement. We found that high point-level accuracy achieved through semantic segmentation of point cloud data does not guarantee high object-level accuracy. The extent of this problem varies widely among different spatial settings and configurations. We discuss the significance of these findings on the choice of 3D reconstruction methods.
-The code and data provided by the authors allow to partially reproduce
-the computational work presented in the Section 4.4 of the paper. The
-model training (PointNet++) and the input data for Section 4.4 are not
-reproducible with the provided code but the authors added a note, in the
-GitHub repository of their project, explaining how the data was
-generated. Three figures in Section 4.4 are fully reproducible (5, 6,
-and 7), 2 partially (4 and 8) and 4 are not (3, 9, 10, and 11).
+The code and data provided by the authors allow to partially reproduce the computational work presented in the Section 4.4 of the paper. The model training (PointNet++) and the input data for Section 4.4 are not reproducible with the provided code but the authors added a note, in the GitHub repository of their project, explaining how the data was generated. Three figures in Section 4.4 are fully reproducible (5, 6, and 7), 2 partially (4 and 8) and 4 are not (3, 9, 10, and 11).
-Authors: Haojun Cai, Yanan Xin, Henry Martin, Martin
-Raubal
+Authors: Haojun Cai, Yanan Xin, Henry Martin, Martin Raubal
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The number of electric vehicles (EVs) has been rapidly
-increasing over the last decade, motivated by the effort to decrease
-greenhouse gas emissions and the fast development of battery technology.
-This trend challenges distribution grids since EVs will bring
-significant stress if the charging of many EVs is not coordinated. Among
-the many strategies to cope with this challenge, next-day EV energy
-demand forecasting plays a key role. Existing studies have focused on
-predicting the next-day energy demand of EVs on the aggregated and
-individual levels. However, these studies have not yet extensively
-considered individual user mobility behaviors, which exhibit a high
-level of predictability. In this study, we consider several mobility
-features of individual users when forecasting the next-day energy demand
-of individual EVs. Three types of quantile regression models are used to
-generate probabilistic forecasts of energy demand, particularly the
-next-day energy consumption and parking duration. Based on the
-prediction results, two time-shifting smart charging strategies are
-designed: unidirectional and bidirectional smart charging. These two
-strategies are compared with an uncontrolled charging baseline to
-evaluate their financial benefits and peak-shaving effects. Our results
-show that human mobility features can partially improve the prediction
-of next-day individual EV energy demand. Additionally, users and
-distribution grids can benefit from smart charging strategies both
-financially and technically.
+Abstract. The number of electric vehicles (EVs) has been rapidly increasing over the last decade, motivated by the effort to decrease greenhouse gas emissions and the fast development of battery technology. This trend challenges distribution grids since EVs will bring significant stress if the charging of many EVs is not coordinated. Among the many strategies to cope with this challenge, next-day EV energy demand forecasting plays a key role. Existing studies have focused on predicting the next-day energy demand of EVs on the aggregated and individual levels. However, these studies have not yet extensively considered individual user mobility behaviors, which exhibit a high level of predictability. In this study, we consider several mobility features of individual users when forecasting the next-day energy demand of individual EVs. Three types of quantile regression models are used to generate probabilistic forecasts of energy demand, particularly the next-day energy consumption and parking duration. Based on the prediction results, two time-shifting smart charging strategies are designed: unidirectional and bidirectional smart charging. These two strategies are compared with an uncontrolled charging baseline to evaluate their financial benefits and peak-shaving effects. Our results show that human mobility features can partially improve the prediction of next-day individual EV energy demand. Additionally, users and distribution grids can benefit from smart charging strategies both financially and technically.
-The authors included a link to an anonymous GitHb repository containing
-detailed instructions and an entry point (main script) to
-run the entire analysis. The authors claimed that input data cannot be
-disclosed. They provided me a few synthetic input samples (CSV format)
-to run the probabilistic models and charging strategies for simulation
-and evaluation, so there are differences between the results of the
-reproduction and the ones in the original paper. The reproduction
-described in this report uses the Python code provided. Even though the
-reproduction exercise with synthetic data failed during the last step of
-the script, I consider the paper was partially reproducible based on the
-synthetic data.
+The authors included a link to an anonymous GitHb repository containing detailed instructions and an entry point (main script) to run the entire analysis. The authors claimed that input data cannot be disclosed. They provided me a few synthetic input samples (CSV format) to run the probabilistic models and charging strategies for simulation and evaluation, so there are differences between the results of the reproduction and the ones in the original paper. The reproduction described in this report uses the Python code provided. Even though the reproduction exercise with synthetic data failed during the last step of the script, I consider the paper was partially reproducible based on the synthetic data.
Authors: Jean-Marie Favreau, Jérémy Kalsron
@@ -262,34 +257,11 @@
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The increase of accessibility and pedestrian data in
-geographic databases such as OpenStreetMap brings with it the
-possibility to find a number of applications for pedestrian users.The
-way in which different urban spaces are crossed obviously depends on
-their nature. In particular, crossing an intersection is not the same as
-walking along a street. Intersections are particularly complex areas,
-where crossing is almost mandatory, often with several possible
-routes.Although there are various works in the literature that are
-interested in locating these intersections in a road network, to our
-knowledge there is no work that deals with the precise segmentation of
-intersections at the scale of pedestrian use.In this article, we propose
-an approach that allows us to segment the OpenStreetMap street network
-at the pedestrian level, by precisely identifying the boundaries between
-intersections and other spaces.By combining the geometry, topology and
-semantics of the urban automobile network of OpenStreetMap, we propose
-an algorithm for locating elementary intersections, and then
-successively assembling them in a multi-scale approach, in order to
-obtain the intersections as they are considered by pedestrians during
-their movements. In particular, our approach relies on the elements that
-constitute the boundaries of these intersections, such as pedestrian
-crossings and traffic lights.After presenting an implementation of this
-approach, we offer a number of results that illustrate the robustness of
-the proposed approach.
+Abstract. The increase of accessibility and pedestrian data in geographic databases such as OpenStreetMap brings with it the possibility to find a number of applications for pedestrian users.The way in which different urban spaces are crossed obviously depends on their nature. In particular, crossing an intersection is not the same as walking along a street. Intersections are particularly complex areas, where crossing is almost mandatory, often with several possible routes.Although there are various works in the literature that are interested in locating these intersections in a road network, to our knowledge there is no work that deals with the precise segmentation of intersections at the scale of pedestrian use.In this article, we propose an approach that allows us to segment the OpenStreetMap street network at the pedestrian level, by precisely identifying the boundaries between intersections and other spaces.By combining the geometry, topology and semantics of the urban automobile network of OpenStreetMap, we propose an algorithm for locating elementary intersections, and then successively assembling them in a multi-scale approach, in order to obtain the intersections as they are considered by pedestrians during their movements. In particular, our approach relies on the elements that constitute the boundaries of these intersections, such as pedestrian crossings and traffic lights.After presenting an implementation of this approach, we offer a number of results that illustrate the robustness of the proposed approach.
-The updated submission contains a DASA section and links to two
-repositories on GitHub, which have been updated by the author during the
-reproducibility review process. The first repository contains all
-necessary files and code for implementing the segmentation process,
-while the second, comprises all files necessary for using the evaluation
-tool. The reproduction was successful.
+The updated submission contains a DASA section and links to two repositories on GitHub, which have been updated by the author during the reproducibility review process. The first repository contains all necessary files and code for implementing the segmentation process, while the second, comprises all files necessary for using the evaluation tool. The reproduction was successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Accurate and consistent estimations on the present and
-future population distribution, at fine spatial resolution, are
-fundamental to support a variety of activities. However, the sampling
-regime, sample size, and methods used to collect census data are
-heterogeneous across temporal periods and/or geographic regions.
-Moreover, the data is usually only made available in aggregated form, to
-ensure privacy. In an attempt to address these issues, several previous
-initiatives have addressed the use of spatial disaggregation methods to
-produce high-resolution gridded datasets describing the human population
-distribution, although these projects have usually not addressed
-specific population subgroups. This paper describes a spatial
-disaggregation method based on self-training regression models,
-innovating over previous studies in the simultaneous prediction of
-disaggregated counts for multiple inter-related variables, by leveraging
-multi-output models based on gradient tree boosting. We report on
-experiments for two case studies, using high-resolution data (i.e.,
-counts for different subgroups available at a resolution of 100 meters)
-for the municipality of Amsterdam and the region of Greater Copenhagen.
-Results show that the proposed approach can capture spatial
-heterogeneity and the dependency on local factors, outperforming
-alternatives (e.g., seminal disaggregation algorithms, or approaches
-leveraging individual regression models for each variable) in terms of
-averaged error metrics, and also upon visual inspection of spatial
-variation in the resulting maps.
+Abstract. Accurate and consistent estimations on the present and future population distribution, at fine spatial resolution, are fundamental to support a variety of activities. However, the sampling regime, sample size, and methods used to collect census data are heterogeneous across temporal periods and/or geographic regions. Moreover, the data is usually only made available in aggregated form, to ensure privacy. In an attempt to address these issues, several previous initiatives have addressed the use of spatial disaggregation methods to produce high-resolution gridded datasets describing the human population distribution, although these projects have usually not addressed specific population subgroups. This paper describes a spatial disaggregation method based on self-training regression models, innovating over previous studies in the simultaneous prediction of disaggregated counts for multiple inter-related variables, by leveraging multi-output models based on gradient tree boosting. We report on experiments for two case studies, using high-resolution data (i.e., counts for different subgroups available at a resolution of 100 meters) for the municipality of Amsterdam and the region of Greater Copenhagen. Results show that the proposed approach can capture spatial heterogeneity and the dependency on local factors, outperforming alternatives (e.g., seminal disaggregation algorithms, or approaches leveraging individual regression models for each variable) in terms of averaged error metrics, and also upon visual inspection of spatial variation in the resulting maps.
-The paper presents an extensive quantitative study that consists of
-numerous (pre-)processing steps involving multiple input data sets of
-different types (e.g., CSV, remotely sensed imagery, and geographic
-vector data). The input data is not provided but sufficiently documented
-to be recreatable or retrievable from other sources. Unfortunately,
-despite great support from the corresponding author, the time
-constraints of this review, coupled with the need to organize the data
-and the complexity of the workflow, allowed only a partial reproduction
-of the processing pipeline: the initial dasymetric mapping to generate
-the first inputs of disaggregated population density, and one of the
-multiple analysis on that data for the city of Amsterdam. However, a
-careful evaluation of the available code led this reviewer to the
-conclusion that with more time, a successful reproduction of the entire
-workflow is highly likely. In any case, there is sufficient information
-to replicate the study for a different geographic area or with different
-methods or parameters.
+The paper presents an extensive quantitative study that consists of numerous (pre-)processing steps involving multiple input data sets of different types (e.g., CSV, remotely sensed imagery, and geographic vector data). The input data is not provided but sufficiently documented to be recreatable or retrievable from other sources. Unfortunately, despite great support from the corresponding author, the time constraints of this review, coupled with the need to organize the data and the complexity of the workflow, allowed only a partial reproduction of the processing pipeline: the initial dasymetric mapping to generate the first inputs of disaggregated population density, and one of the multiple analysis on that data for the city of Amsterdam. However, a careful evaluation of the available code led this reviewer to the conclusion that with more time, a successful reproduction of the entire workflow is highly likely. In any case, there is sufficient information to replicate the study for a different geographic area or with different methods or parameters.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Nitrogen dioxide is one of the most hazardous
-pollutants identified by the World Health Organisation. Predicting and
-reducing pollutants is becoming a very urgent task and many methods have
-been used to predict their concentration, such as physical or machine
-learning models. In addition to choosing the right model, it is also
-critical to choose the appropriate features. This work focuses on the
-spatiotemporal prediction of nitrogen dioxide concentration using
-Bidirectional Convolutional LSTM integrated with the exploration of
-nitrogen dioxide and associated features, as well as the implementation
-of feature selection methods. The Root Mean Square Error and the Mean
-Absolute Error were used to evaluate the proposed approach.
+Abstract. Nitrogen dioxide is one of the most hazardous pollutants identified by the World Health Organisation. Predicting and reducing pollutants is becoming a very urgent task and many methods have been used to predict their concentration, such as physical or machine learning models. In addition to choosing the right model, it is also critical to choose the appropriate features. This work focuses on the spatiotemporal prediction of nitrogen dioxide concentration using Bidirectional Convolutional LSTM integrated with the exploration of nitrogen dioxide and associated features, as well as the implementation of feature selection methods. The Root Mean Square Error and the Mean Absolute Error were used to evaluate the proposed approach.
-The paper evaluates the competence of selected features in the
-prediction of Nitrogen Dioxide with Machine Learning. For this
-reproduciblity review, the Figures and Tables of “Section 5 -
-Experiments and Results” were considered, while the Figures of “Section
-3 - Exploratory Analysis”” were not. The code of the corresponding
-analysis was provided as a GitHub repository and the data that is
-necessary to run the code were provided through a Zenodo repository. The
-reproduced results were in accordance with the ones reported in the
-paper, so the reproduction of the paper is considered successful.
+The paper evaluates the competence of selected features in the prediction of Nitrogen Dioxide with Machine Learning. For this reproduciblity review, the Figures and Tables of “Section 5 - Experiments and Results” were considered, while the Figures of “Section 3 - Exploratory Analysis”" were not. The code of the corresponding analysis was provided as a GitHub repository and the data that is necessary to run the code were provided through a Zenodo repository. The reproduced results were in accordance with the ones reported in the paper, so the reproduction of the paper is considered successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Geoparsing, the task of extracting toponyms from texts
-and associating them with geographic locations, has witnessed remarkable
-progress over the past years. However, despite its intrinsically
-geospatial nature, existing evaluations tend to focus on overall
-performance while paying little attention to its variation across
-geographic space. In this work, we attempt to answer the question
-whether geoparsing is solved or biased by conducting a
-spatially-explicit evaluation, namely an evaluation of the regional
-variability in geoparsing performance. Particularly, we will analyze the
-spatial autocorrelation underlying this regional variability. By
-performing hot and cold spot detection over results of several
-open-source geoparsers, we observe that none of them performs equally
-well across geographic space, and some are geographically biased towards
-some regions but against others. We also carry out a comparative
-experiment showing that stateof- the-art geoparsers developed with
-neural networks do not necessarily outperform the off-the-shelf tools
-across geographic space. To understand the implications behind this
-observed regional variability, we evaluate geographic biases involved in
-geoparsing research centered around data contribution and usage,
-algorithm design, and performance evaluations. Particularly, our
-spatially-explicit performance evaluation serves as an approach to
-evaluation bias mitigation in geoparsing.We conclude that previous
-performance evaluations published in the literature are overly
-optimistic, thus hiding the fact that geoparsing is far from solved, and
-geoparsers require debiasing in addition to further considerations when
-being applied to (geospatial) downstream tasks.
+Abstract. Geoparsing, the task of extracting toponyms from texts and associating them with geographic locations, has witnessed remarkable progress over the past years. However, despite its intrinsically geospatial nature, existing evaluations tend to focus on overall performance while paying little attention to its variation across geographic space. In this work, we attempt to answer the question whether geoparsing is solved or biased by conducting a spatially-explicit evaluation, namely an evaluation of the regional variability in geoparsing performance. Particularly, we will analyze the spatial autocorrelation underlying this regional variability. By performing hot and cold spot detection over results of several open-source geoparsers, we observe that none of them performs equally well across geographic space, and some are geographically biased towards some regions but against others. We also carry out a comparative experiment showing that stateof- the-art geoparsers developed with neural networks do not necessarily outperform the off-the-shelf tools across geographic space. To understand the implications behind this observed regional variability, we evaluate geographic biases involved in geoparsing research centered around data contribution and usage, algorithm design, and performance evaluations. Particularly, our spatially-explicit performance evaluation serves as an approach to evaluation bias mitigation in geoparsing.We conclude that previous performance evaluations published in the literature are overly optimistic, thus hiding the fact that geoparsing is far from solved, and geoparsers require debiasing in addition to further considerations when being applied to (geospatial) downstream tasks.
-The article presents an evaluation of geoparsing performance using a
-number of different datasets and methods from various sources. Though
-preprocessing steps and a core analysis step based on proprietary
-software could not be evaluated, one of two toponym resolution models
-could be executed successfully. The provided notebooks for exploratory
-analysis, calculating statistical values, and geographic bias evaluation
-could be run and the outputs match the data and figures presented in the
-paper. Therefore, this reproducibility report can confirm a partially
-successful reproduction of a complex pipeline, for which authors provide
-reasonable but improvable documentation and share all details (code,
-data) of their computational workflow.
+The article presents an evaluation of geoparsing performance using a number of different datasets and methods from various sources. Though preprocessing steps and a core analysis step based on proprietary software could not be evaluated, one of two toponym resolution models could be executed successfully. The provided notebooks for exploratory analysis, calculating statistical values, and geographic bias evaluation could be run and the outputs match the data and figures presented in the paper. Therefore, this reproducibility report can confirm a partially successful reproduction of a complex pipeline, for which authors provide reasonable but improvable documentation and share all details (code, data) of their computational workflow.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Recent developments in image recognition technology
-including artificial intelligence and machine learning led to an
-intensified research in computer vision models. This progress also
-allows advances for the collection of spatio-temporal data on Invasive
-Alien Species (IAS), in order to understand their geographical
-distribution and impact on the biodiversity loss. Citizen Science (CS)
-approaches already show successful solutions how the public can be
-involved in collecting spatio-temporal data on IAS, e.g. by using mobile
-applications for monitoring. Our work analyzes recently developed
-image-based species recognition models suitable for the monitoring of
-IAS in CS applications. We demonstrate how computer vision models can be
-benchmarked for such a use case and how their accuracy can be evaluated
-by testing them with IAS of European Union concern. We found out that
-available models have different strengths. Depending on which criteria
-(e.g. high species coverage, costs, maintenance, high accuracies) are
-considered as most important, it needs to be decided individually which
-model fits best. Using only one model alone may not necessarily be the
-best solution, thus combining multiple models or developing a new custom
-model can be desirable. Generally, cooperation with the model providers
-can be advantageous.
+Abstract. Recent developments in image recognition technology including artificial intelligence and machine learning led to an intensified research in computer vision models. This progress also allows advances for the collection of spatio-temporal data on Invasive Alien Species (IAS), in order to understand their geographical distribution and impact on the biodiversity loss. Citizen Science (CS) approaches already show successful solutions how the public can be involved in collecting spatio-temporal data on IAS, e.g. by using mobile applications for monitoring. Our work analyzes recently developed image-based species recognition models suitable for the monitoring of IAS in CS applications. We demonstrate how computer vision models can be benchmarked for such a use case and how their accuracy can be evaluated by testing them with IAS of European Union concern. We found out that available models have different strengths. Depending on which criteria (e.g. high species coverage, costs, maintenance, high accuracies) are considered as most important, it needs to be decided individually which model fits best. Using only one model alone may not necessarily be the best solution, thus combining multiple models or developing a new custom model can be desirable. Generally, cooperation with the model providers can be advantageous.
-The article presents a comparison of seven image-based species
-recognition models, which were benchmarked against a set of species.
-Selected model executions were successfully reproduced. The outputs were
-manually compared on a sample basis and match the result data shared
-privately by the authors; no summary statistics were recalculated. The
-authors provided the used data privately, but all code and good
-documentation is available online and properly deposited and cited using
-a data repository. Only two of the four online classification APIs were
-tested due to the requirement of registering accounts, therefore this
-reproduction is only partially complete.
+The article presents a comparison of seven image-based species recognition models, which were benchmarked against a set of species. Selected model executions were successfully reproduced. The outputs were manually compared on a sample basis and match the result data shared privately by the authors; no summary statistics were recalculated. The authors provided the used data privately, but all code and good documentation is available online and properly deposited and cited using a data repository. Only two of the four online classification APIs were tested due to the requirement of registering accounts, therefore this reproduction is only partially complete.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Most navigation systems for pedestrians output the
-shortest route. However, there are findings that travellers do not use
-the shortest route when free to choose. One alternative to minimising
-spatial distance is the incorporation of landmark information in a
-shortest route algorithm. Yet, we do not know whether pedestrians prefer
-such a landmark route over the shortest route. Therefore, we perform a
-survey and show participants videos of a shortest and a landmark route.
-We let participants answer questions concerning navigation satisfaction,
-route communication, and route comparison. Our findings show that the
-landmark route is more favourable.
+Abstract. Most navigation systems for pedestrians output the shortest route. However, there are findings that travellers do not use the shortest route when free to choose. One alternative to minimising spatial distance is the incorporation of landmark information in a shortest route algorithm. Yet, we do not know whether pedestrians prefer such a landmark route over the shortest route. Therefore, we perform a survey and show participants videos of a shortest and a landmark route. We let participants answer questions concerning navigation satisfaction, route communication, and route comparison. Our findings show that the landmark route is more favourable.
-The paper presents a type of study that is highly valuable as a
-scientific contribution yet almost impossible to reproduce: a survey and
-user study involving participants from a convenience sample of a
-university course, implemented in several phases and using a particular
-geographic locale. The study aims to learn more about user preferences
-on route choice, i.e., whether users prefer the shortest route or a
-slightly longer route including landmarks. However, the difficult
-pandemic conditions under which the study had to be carried out had at
-least one positive aspect on replicability: The entire communication and
-survey had to be carried out online, facilitating a similar setup
-elsewhere. This review there fore attempts not a full reproduction of
-the study, but evaluates two distinct things: First, whether there is
-sufficient information available to replicate the study elsewhere and
-compare results. Second, whether the statistical analysis of the survey
-and experimental data is indeed reproducible. The evaluation for both is
-positive.
+The paper presents a type of study that is highly valuable as a scientific contribution yet almost impossible to reproduce: a survey and user study involving participants from a convenience sample of a university course, implemented in several phases and using a particular geographic locale. The study aims to learn more about user preferences on route choice, i.e., whether users prefer the shortest route or a slightly longer route including landmarks. However, the difficult pandemic conditions under which the study had to be carried out had at least one positive aspect on replicability: The entire communication and survey had to be carried out online, facilitating a similar setup elsewhere. This review there fore attempts not a full reproduction of the study, but evaluates two distinct things: First, whether there is sufficient information available to replicate the study elsewhere and compare results. Second, whether the statistical analysis of the survey and experimental data is indeed reproducible. The evaluation for both is positive.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Although Global Positioning System (GPS) is widely
-used in outdoor location-based services, it still lacks precision due to
-obstacles that reduce its performance, such as near tall buildings, with
-bad weather conditions, and under tree canopies. In some situations,
-inaccurate localization or delay in getting location locks can adversely
-affect some location-based services’ functionality. Furthermore, it
-might make these services less efficient or even completely useless,
-especially when the receiver device has no SIM card or when the service
-requires a precision higher than three meters. As a solution to this
-issue, this study designs, develops, and evaluates a prototype
-location-based system that uses Bluetooth Low Energy beacons for
-short-range positioning in outdoor environments as a GPS alternative.
-The proposed system is a game that includes navigational tasks, which
-can be accomplished by reaching the proximity of two meters from the
-beacon’s location. The study involved conducting an experiment outdoors
-with a focus on areas where GPS signals are degraded to assess our
-proposed system’s efficiency and feasibility compared to the usage of
-GPS. The results proved BLE beacons’ ability to provide better
-positioning results than GPS, not only in terms of accuracy but also in
-terms of stability of positioning results over time. Based on the
-findings, the study outlines a set of guidelines to be considered in
-choosing a suitable positioning technology.
+Abstract. Although Global Positioning System (GPS) is widely used in outdoor location-based services, it still lacks precision due to obstacles that reduce its performance, such as near tall buildings, with bad weather conditions, and under tree canopies. In some situations, inaccurate localization or delay in getting location locks can adversely affect some location-based services’ functionality. Furthermore, it might make these services less efficient or even completely useless, especially when the receiver device has no SIM card or when the service requires a precision higher than three meters. As a solution to this issue, this study designs, develops, and evaluates a prototype location-based system that uses Bluetooth Low Energy beacons for short-range positioning in outdoor environments as a GPS alternative. The proposed system is a game that includes navigational tasks, which can be accomplished by reaching the proximity of two meters from the beacon’s location. The study involved conducting an experiment outdoors with a focus on areas where GPS signals are degraded to assess our proposed system’s efficiency and feasibility compared to the usage of GPS. The results proved BLE beacons’ ability to provide better positioning results than GPS, not only in terms of accuracy but also in terms of stability of positioning results over time. Based on the findings, the study outlines a set of guidelines to be considered in choosing a suitable positioning technology.
-The article present an experimental evaluation of a positioning system.
-Naturally, the physical/practical experiments could not be reproduced as
-part of this check of the computational reproducibility. However, the
-one figure in the article that is based on the data from the experiment,
-as well as the software for running the experiment shown in screenshots
-in the paper could be reproduced by me. With respect to the
-computational aspects and data visualisation, the given paper is
-reproducible.
+The article present an experimental evaluation of a positioning system. Naturally, the physical/practical experiments could not be reproduced as part of this check of the computational reproducibility. However, the one figure in the article that is based on the data from the experiment, as well as the software for running the experiment shown in screenshots in the paper could be reproduced by me. With respect to the computational aspects and data visualisation, the given paper is reproducible.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Given aggregated mobile device data, the goal is to
-understand the impact of COVID-19 policy interventions on mobility. This
-problem is vital due to important societal use cases, such as safely
-reopening the economy. Challenges include understanding and interpreting
-questions of interest to policymakers, cross-jurisdictional variability
-in choice and time of interventions, the large data volume, and unknown
-sampling bias. The related work has explored the COVID-19 impact on
-travel distance, time spent at home, and the number of visitors at
-different points of interest. However, many policymakers are interested
-in long-duration visits to high-risk business categories and
-understanding the spatial selection bias to interpret summary reports.
-We provide an Entity Relationship diagram, system architecture, and
-implementation to support queries on long-duration visits in addition to
-fine resolution device count maps to understand spatial bias. We closely
-collaborated with policymakers to derive the system requirements and
-evaluate the system components, the summary reports, and visualizations.
-
+Abstract. Given aggregated mobile device data, the goal is to understand the impact of COVID-19 policy interventions on mobility. This problem is vital due to important societal use cases, such as safely reopening the economy. Challenges include understanding and interpreting questions of interest to policymakers, cross-jurisdictional variability in choice and time of interventions, the large data volume, and unknown sampling bias. The related work has explored the COVID-19 impact on travel distance, time spent at home, and the number of visitors at different points of interest. However, many policymakers are interested in long-duration visits to high-risk business categories and understanding the spatial selection bias to interpret summary reports. We provide an Entity Relationship diagram, system architecture, and implementation to support queries on long-duration visits in addition to fine resolution device count maps to understand spatial bias. We closely collaborated with policymakers to derive the system requirements and evaluate the system components, the summary reports, and visualizations.
-The software of the paper under reproduction is publicly available on
-GitHub. The majority of data sets are publicly available in a Google
-Drive folder. One data set is not available due to privacy policy
-concerns. Out of the 17 Figures in the paper, 10 are eligible for
-reproduction. Out of the 10 eligible Figures, 8 Figures where
-successfully reproduced, one Figure was partially reproduced and one
-Figure was not reproducible. Reproduction was partially successful.
+The software of the paper under reproduction is publicly available on GitHub. The majority of data sets are publicly available in a Google Drive folder. One data set is not available due to privacy policy concerns. Out of the 17 Figures in the paper, 10 are eligible for reproduction. Out of the 10 eligible Figures, 8 Figures where successfully reproduced, one Figure was partially reproduced and one Figure was not reproducible. Reproduction was partially successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Active travel provides significant public health
-benefits including improving physical and mental health and air quality.
-Given the geography of congested roads, availability of required
-infrastructure and cost of transportation in cities, promoting active
-travel, including cycling, can be a good solution for commuting within
-built environments. Having a better understanding of the key drivers
-that may influence bike ridership can help with designing cities that
-accommodate cyclists’ needs for healthier citizens. This paper examines
-the built environment features that may affect commuting cyclists. We
-respectively employ Ordinary Linear Square (OLS) regression and
-Geographically Weighted Regression (GWR) for 136 Intermediate Zones of
-the city of Glasgow, UK. The results of GWR show that the significant
-local variation in green areas suggests that even though the global
-regression showed a negative association between the greenness and
-commute cycling, over half of the IZ areas had a strong positive
-association with the green areas. Building height and Public Transport
-Availability Index show geographic patterns where the residuals are
-fairly stationary across the study area with some clusters of high
-residuals. Performance wise, the results from GWR provided an R2 of 0.73
-which was higher than OLS at 0.3. Our results can provide insights into
-how to use crowdsourced cycling data when there are spatially and
-temporally limited resources available.
+Abstract. Active travel provides significant public health benefits including improving physical and mental health and air quality. Given the geography of congested roads, availability of required infrastructure and cost of transportation in cities, promoting active travel, including cycling, can be a good solution for commuting within built environments. Having a better understanding of the key drivers that may influence bike ridership can help with designing cities that accommodate cyclists’ needs for healthier citizens. This paper examines the built environment features that may affect commuting cyclists. We respectively employ Ordinary Linear Square (OLS) regression and Geographically Weighted Regression (GWR) for 136 Intermediate Zones of the city of Glasgow, UK. The results of GWR show that the significant local variation in green areas suggests that even though the global regression showed a negative association between the greenness and commute cycling, over half of the IZ areas had a strong positive association with the green areas. Building height and Public Transport Availability Index show geographic patterns where the residuals are fairly stationary across the study area with some clusters of high residuals. Performance wise, the results from GWR provided an R2 of 0.73 which was higher than OLS at 0.3. Our results can provide insights into how to use crowdsourced cycling data when there are spatially and temporally limited resources available.
-The authors provide all the data and code in their GitHub repository.
-From a fresh install of R, the software environment is easily set up.
-The authors provide one R script and one computational notebook, which
-could be executed successfully to create all the paper’s figures.
+The authors provide all the data and code in their GitHub repository. From a fresh install of R, the software environment is easily set up. The authors provide one R script and one computational notebook, which could be executed successfully to create all the paper’s figures.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Spatial information has gained more attention in
-natural language processing tasks in different interdisciplinary
-domains. Moreover, the spatial information is available in two forms:
-Absolute Spatial Information (ASI) e.g., Paris, London, and Germany and
-Relative Spatial Information (RSI) e.g., south of Paris, north Madrid
-and 80 km from Rome. Therefore, it is challenging to extract RSI from
-textual data and compute its geotagging. This paper presents two
-strategies and the associated prototypes to address the following tasks:
-1) extraction of relative spatial information from textual data and 2)
-geotagging of this relative spatial information. Experiments show
-promising results for RSI extraction and tagging.
+Abstract. Spatial information has gained more attention in natural language processing tasks in different interdisciplinary domains. Moreover, the spatial information is available in two forms: Absolute Spatial Information (ASI) e.g., Paris, London, and Germany and Relative Spatial Information (RSI) e.g., south of Paris, north Madrid and 80 km from Rome. Therefore, it is challenging to extract RSI from textual data and compute its geotagging. This paper presents two strategies and the associated prototypes to address the following tasks: 1) extraction of relative spatial information from textual data and 2) geotagging of this relative spatial information. Experiments show promising results for RSI extraction and tagging.
-The main contribution of the paper are two web applications on the
-streamlit.io platform. The paper includes the DASA section and links to
-live online instances of the applications, as well as to GitHub
-repositories with the code and data. The repositories are well
-documented. I was able to clone the repositories and run the code,
-reproducing examples demonstrated on figures in the paper. One of the
-reproduced figures differed from the one presented in the paper. The
-tables demonstrating results of the evaluation of the app were partially
-reproducible but returned slightly different values. The paper has been
-partially reproduced.
+The main contribution of the paper are two web applications on the streamlit.io platform. The paper includes the DASA section and links to live online instances of the applications, as well as to GitHub repositories with the code and data. The repositories are well documented. I was able to clone the repositories and run the code, reproducing examples demonstrated on figures in the paper. One of the reproduced figures differed from the one presented in the paper. The tables demonstrating results of the evaluation of the app were partially reproducible but returned slightly different values. The paper has been partially reproduced.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The increase of recreational activities in the
-mountains and a growing amount of websites proposing geographic data,
-offer new opportunities for societal needs such as mountain rescue,
-biodiversity monitoring, outdoor activities. However, the main issue
-with the websites data is the lack of metadata that minimizes its reuse
-outside the community that produced the data. The goal of this paper is
-to study and generate quality and descriptive metadata using ISO
-standards. To this end, we propose a method based on a common vocabulary
-such as an ontology and a data matching process. The first one allows to
-associate to each type of feature from an available geographic dataset
-an ontology class that will facilitate data matching, reproducibility of
-results and minimize semantic heterogeneity. The second one allows to
-define matching links between features representing the same entity in
-the real world and compute quality indicators based on the validated
-links. Finally, at the end of this process, we are able to generate
-descriptive and quality metadata. By following ISO standards and using
-the QualityML dictionary for measures, the metadata is serialized to XML
-and can finally be published as open source. Our approach was applied to
-five different landmark datasets in the French Alps region. New insights
-were acquired regarding positional accuracy and semantic granularity.
-
+Abstract. The increase of recreational activities in the mountains and a growing amount of websites proposing geographic data, offer new opportunities for societal needs such as mountain rescue, biodiversity monitoring, outdoor activities. However, the main issue with the websites data is the lack of metadata that minimizes its reuse outside the community that produced the data. The goal of this paper is to study and generate quality and descriptive metadata using ISO standards. To this end, we propose a method based on a common vocabulary such as an ontology and a data matching process. The first one allows to associate to each type of feature from an available geographic dataset an ontology class that will facilitate data matching, reproducibility of results and minimize semantic heterogeneity. The second one allows to define matching links between features representing the same entity in the real world and compute quality indicators based on the validated links. Finally, at the end of this process, we are able to generate descriptive and quality metadata. By following ISO standards and using the QualityML dictionary for measures, the metadata is serialized to XML and can finally be published as open source. Our approach was applied to five different landmark datasets in the French Alps region. New insights were acquired regarding positional accuracy and semantic granularity.
-The software of the paper under reproduction is publicly available on
-GitHub. The data sets are publicly available in a zenodo project. Out of
-the four Figures and four Tables, two Figures and two Tables are
-eligible for reproduction. Both eligible Figures have been successfully
-reproduced. Both eligible Tables have been partially reproduced. The
-reproduction of Table 3 and 4 was partial as the provided software
-scripts comprise reproduction of one out of the four data columns. The
-remaining columns are expected to be reproducible after adjusting the
-scripts with references to the remaining data sets. The authors showed
-concern and dedication to improve reproducibility of their work.
-Reproduction was partially successful.
+The software of the paper under reproduction is publicly available on GitHub. The data sets are publicly available in a zenodo project. Out of the four Figures and four Tables, two Figures and two Tables are eligible for reproduction. Both eligible Figures have been successfully reproduced. Both eligible Tables have been partially reproduced. The reproduction of Table 3 and 4 was partial as the provided software scripts comprise reproduction of one out of the four data columns. The remaining columns are expected to be reproducible after adjusting the scripts with references to the remaining data sets. The authors showed concern and dedication to improve reproducibility of their work. Reproduction was partially successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Planning and operations in urban spaces are strongly
-affected by human mobility behavior. A better understanding of
-individual mobility is key to improve transportation systems and to
-guide the allocation of public space. Previous studies have discovered
-statistical laws of travel distances, but the topology of movement
-between places has received little attention. We propose to employ
-network modelling methods to analyze the effect of spatial and context
-attributes on individual movement patterns. The perspective of mobility
-as a network allows to explicitly regard dyadic dependencies of
-sequential location visits. Here, we consider two methods developed for
-social networks and provide a formulation of mobility networks to
-justify their applicability. First, we use the Multiple Regression
-Quadratic Assignment Procedure to test hypotheses on the influence of
-location attributes on mobility behavior. Secondly, Stochastic
-Actor-Oriented Models are applied to model the evolution of mobility
-networks over time. As a proof-of-concept study, we transform data from
-one GNSS-based and one check-in based dataset into mobility networks and
-present results from both methods. We find relations that appear for a
-majority of samples and thus seem inherent to mobility networks. The
-differences between individuals and the available datasets are further
-quantified and discussed. We conclude that the transfer of network
-modeling methods is an interesting opportunity to study network-related
-phenomena in geographic information science.
+Abstract. Planning and operations in urban spaces are strongly affected by human mobility behavior. A better understanding of individual mobility is key to improve transportation systems and to guide the allocation of public space. Previous studies have discovered statistical laws of travel distances, but the topology of movement between places has received little attention. We propose to employ network modelling methods to analyze the effect of spatial and context attributes on individual movement patterns. The perspective of mobility as a network allows to explicitly regard dyadic dependencies of sequential location visits. Here, we consider two methods developed for social networks and provide a formulation of mobility networks to justify their applicability. First, we use the Multiple Regression Quadratic Assignment Procedure to test hypotheses on the influence of location attributes on mobility behavior. Secondly, Stochastic Actor-Oriented Models are applied to model the evolution of mobility networks over time. As a proof-of-concept study, we transform data from one GNSS-based and one check-in based dataset into mobility networks and present results from both methods. We find relations that appear for a majority of samples and thus seem inherent to mobility networks. The differences between individuals and the available datasets are further quantified and discussed. We conclude that the transfer of network modeling methods is an interesting opportunity to study network-related phenomena in geographic information science.
-The paper provides a link to a GitHub repository that was initially
-difficult to use but was promptly improved by the authors after an email
-exchange. The repository contains only one out of two datasets presented
-in the paper but most results based on this dataset have been
-successfully reproduced with minor disparities due to automated scaling
-of graphs. In sum, the manuscript has been partially reproduced. The
-repository is well-documented, it includes the documentation of required
-software versions, and the authors’ response to questions and bugs has
-been prompt and helpful.
+The paper provides a link to a GitHub repository that was initially difficult to use but was promptly improved by the authors after an email exchange. The repository contains only one out of two datasets presented in the paper but most results based on this dataset have been successfully reproduced with minor disparities due to automated scaling of graphs. In sum, the manuscript has been partially reproduced. The repository is well-documented, it includes the documentation of required software versions, and the authors’ response to questions and bugs has been prompt and helpful.
-Authors: Pengxiang Zhao, Aoyong Li, Petter Pilesjö, Ali
-Mansourian
+Authors: Pengxiang Zhao, Aoyong Li, Petter Pilesjö, Ali Mansourian
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Shared electric scooters (e-scooters) have been
-rapidly growing in popularity across Europe over the past three years,
-which can bring various environmental and socioeconomic benefits.
-However, how to further improve the usage efficiency of shared
-e-scooters is still a major concern for micro-mobility operators and
-city planners. This paper proposes a machine learning based approach to
-predict the usage efficiency of shared e-scooters using GPS-based
-vehicle availability data. First, the usage efficiency of shared
-e-scooters is measured with the indicator Time to Booking at the trip
-level. Second, ten exploratory variables in time and space are
-calculated as features for the prediction based on the e-scooter trips
-and other related data. Last, three typical machine learning methods,
-including logistical regression, artificial neural network and random
-forest are applied to predict the usage efficiency by inputting the
-features. Besides, the variable importance is evaluated by taking the
-random forest model as an example. The results show that the random
-forest model yields the best prediction performance (accuracy = 71.2%,
-F1 = 78.0%), and the variables like the hour of day and POI density
-present high variable importance. The findings of this study will be
-beneficial for micro-mobility operators and city planners to design
-policies and strategies for further improving the usage efficiency of
-e-scooter sharing services.
+Abstract. Shared electric scooters (e-scooters) have been rapidly growing in popularity across Europe over the past three years, which can bring various environmental and socioeconomic benefits. However, how to further improve the usage efficiency of shared e-scooters is still a major concern for micro-mobility operators and city planners. This paper proposes a machine learning based approach to predict the usage efficiency of shared e-scooters using GPS-based vehicle availability data. First, the usage efficiency of shared e-scooters is measured with the indicator Time to Booking at the trip level. Second, ten exploratory variables in time and space are calculated as features for the prediction based on the e-scooter trips and other related data. Last, three typical machine learning methods, including logistical regression, artificial neural network and random forest are applied to predict the usage efficiency by inputting the features. Besides, the variable importance is evaluated by taking the random forest model as an example. The results show that the random forest model yields the best prediction performance (accuracy = 71.2%, F1 = 78.0%), and the variables like the hour of day and POI density present high variable importance. The findings of this study will be beneficial for micro-mobility operators and city planners to design policies and strategies for further improving the usage efficiency of e-scooter sharing services.
-The provided workflow was partially reproduced. Access to a processed
-data set of the e-scooter sharing vehicle data Service in Stockholm,
-Sweden, is provided along with Python scripts to run three machine
-learning methods based on the Python library Scikit-learn. The results
-reported here refer to Figure 5, which is a bar chart comparing the
-performance evaluation metrics (accuracy, F1, precision and recall) of
-the three ML methods. Nevertheless, no code is provided to visually
-recreate the figure, but the scripts produce the required data to create
-that figure. For the rest of figures and tables, no code is provided.
+The provided workflow was partially reproduced. Access to a processed data set of the e-scooter sharing vehicle data Service in Stockholm, Sweden, is provided along with Python scripts to run three machine learning methods based on the Python library Scikit-learn. The results reported here refer to Figure 5, which is a bar chart comparing the performance evaluation metrics (accuracy, F1, precision and recall) of the three ML methods. Nevertheless, no code is provided to visually recreate the figure, but the scripts produce the required data to create that figure. For the rest of figures and tables, no code is provided.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. This article presents a method for traffic control
-recognition at junctions (traffic lights, stop, priority and right of
-way rule) using crowd-sensed GPS data (vehicle trajectories), as well as
-features extracted from OpenStreetMap. Traffic regulators are not mapped
-in most maps, although the way they regulate traffic at intersections
-affects the traffic flow and therefore the vehicle idle time at
-intersections, the fuel consumption, the CO2 emissions, and the arrival
-time at a destination. Because of the controlled interaction that road
-users have with each other at intersections, driving safety or
-assistance applications can be enabled if intersection regulators are
-mapped. In order to verify the proposed method two sets of trajectories
-were used, one of which is an open dataset, from two different cities,
-Hannover and Chicago. Two classification methods were tested, random
-forest and gradient boosting, using exclusively either dynamic features
-(trajectories), or static (only data from OSM) or a combination of the
-dynamic and static features (hybrid model). The results show that the
-gradient boosting classification with hybrid features can predict
-traffic regulations with high accuracy (93% in Chicago and 94% in
-Hannover), outperforming the other detection models (static and
-dynamic). At the end directions for further research on this topic are
-proposed.
+Abstract. This article presents a method for traffic control recognition at junctions (traffic lights, stop, priority and right of way rule) using crowd-sensed GPS data (vehicle trajectories), as well as features extracted from OpenStreetMap. Traffic regulators are not mapped in most maps, although the way they regulate traffic at intersections affects the traffic flow and therefore the vehicle idle time at intersections, the fuel consumption, the CO2 emissions, and the arrival time at a destination. Because of the controlled interaction that road users have with each other at intersections, driving safety or assistance applications can be enabled if intersection regulators are mapped. In order to verify the proposed method two sets of trajectories were used, one of which is an open dataset, from two different cities, Hannover and Chicago. Two classification methods were tested, random forest and gradient boosting, using exclusively either dynamic features (trajectories), or static (only data from OSM) or a combination of the dynamic and static features (hybrid model). The results show that the gradient boosting classification with hybrid features can predict traffic regulations with high accuracy (93% in Chicago and 94% in Hannover), outperforming the other detection models (static and dynamic). At the end directions for further research on this topic are proposed.
-The paper compares several models for traffic control recognition at
-junctions, which are built upon Random Forest and Gradient Boosting
-classifiers. The analysis makes use of 2 datasets, which correspond to
-the cities of Chicago and Hannover. The authors agreed to share
-confidentially all their materials (data and code) with the
-Reproducibility Committee for the needs of the review. For the needs of
-this review, we reproduced all the Tables and Figures of ‘Section 5 -
-Results’ and of the Appendix. The reproduced results were in accordance
-with the final uploaded version of the manuscript. Therefore, the
-reproduction of the paper is considered successful.
+The paper compares several models for traffic control recognition at junctions, which are built upon Random Forest and Gradient Boosting classifiers. The analysis makes use of 2 datasets, which correspond to the cities of Chicago and Hannover. The authors agreed to share confidentially all their materials (data and code) with the Reproducibility Committee for the needs of the review. For the needs of this review, we reproduced all the Tables and Figures of ‘Section 5 - Results’ and of the Appendix. The reproduced results were in accordance with the final uploaded version of the manuscript. Therefore, the reproduction of the paper is considered successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
- Nuclear integration of mitochondrial genomes and retrocopied
-transcript insertion are biologically important but often-overlooked
-aspects of structural variant (SV) annotation. While tools for their
-detection exist, these typically rely on reanalysis of primary data
-using specialised detectors rather than leveraging calls from general
-purpose structural variant callers. Such reanalysis potentially leads to
-additional computational expense and does not take advantage of advances
-in general purpose structural variant calling. Here, we present svaRetro
-and svaNUMT; R packages that provide functions for annotating novel
-genomic events, such as nonreference retrocopied transcripts and nuclear
-integration of mitochondrial DNA. The packages were developed to work
-within the Bioconductor framework. We evaluate the performance of these
-packages to detect events using simulations and public benchmarking
-datasets, and annotate processed transcripts in a public structural
-variant database. svaRetro and svaNUMT provide modular, SV-caller
-agnostic tools for downstream annotation of structural variant calls.
-
+ Nuclear integration of mitochondrial genomes and retrocopied transcript insertion are biologically important but often-overlooked aspects of structural variant (SV) annotation. While tools for their detection exist, these typically rely on reanalysis of primary data using specialised detectors rather than leveraging calls from general purpose structural variant callers. Such reanalysis potentially leads to additional computational expense and does not take advantage of advances in general purpose structural variant calling. Here, we present svaRetro and svaNUMT; R packages that provide functions for annotating novel genomic events, such as nonreference retrocopied transcripts and nuclear integration of mitochondrial DNA. The packages were developed to work within the Bioconductor framework. We evaluate the performance of these packages to detect events using simulations and public benchmarking datasets, and annotate processed transcripts in a public structural variant database. svaRetro and svaNUMT provide modular, SV-caller agnostic tools for downstream annotation of structural variant calls.
-Only visualisation steps performed. All created figures match those in
-the article.
+Only visualisation steps performed. All created figures match those in the article.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Conventional navigation systems use visually
-perceptible landmarks to navigate their users from a starting point to a
-destination. However, sometimes visual information is not enough for
-route guidance. Visually-impaired or elderly people may not be able to
-navigate using the visual sense. Furthermore, there may exist no
-outstanding (i.e., salient) visual landmarks that could be used to
-navigate. In such a case auditory information may be a helpful guide. We
-performed two online studies and a focus-group interview to identify
-possible sound classes in an urban environment. Based on our results, we
-gathered sounds in Augsburg and classified them according to their
-source. The findings support our notion that auditory information can be
-useful for spatial orientation and guidance in addition to or even
-replacing visual information.
+Abstract. Conventional navigation systems use visually perceptible landmarks to navigate their users from a starting point to a destination. However, sometimes visual information is not enough for route guidance. Visually-impaired or elderly people may not be able to navigate using the visual sense. Furthermore, there may exist no outstanding (i.e., salient) visual landmarks that could be used to navigate. In such a case auditory information may be a helpful guide. We performed two online studies and a focus-group interview to identify possible sound classes in an urban environment. Based on our results, we gathered sounds in Augsburg and classified them according to their source. The findings support our notion that auditory information can be useful for spatial orientation and guidance in addition to or even replacing visual information.
-The data of the paper under reproduction is published on figshare under
-a CC-BY-4.0 license. In total, three tables, three figures, and two data
-points embedded into the text are eligible for reproduction. All have
-been successfully reproduced. The authors showed concern and dedication
-to support reproducibility of their work. Reproduction was successful.
+The data of the paper under reproduction is published on figshare under a CC-BY-4.0 license. In total, three tables, three figures, and two data points embedded into the text are eligible for reproduction. All have been successfully reproduced. The authors showed concern and dedication to support reproducibility of their work. Reproduction was successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Given the challenge of visualising 3D space on a 2D
-map, maps used for in-flight navigation by pilots should be designed
-especially carefully. This paper studies, based on existing aeronautical
-charts, the visualisation, interaction, and interpretation of airspace
-structures with aviation infrastructure and the base map.We first
-developed a three-tiered evaluation grid for a cartographic analysis of
-existing aeronautical charts. Subsequently, we evaluated four countries’
-maps based on our evaluation grid. To validate our analysis, we
-conducted a user study with 27 pilots, the users of aeronautical
-charts.The results of our cartographic analysis show that aeronautical
-charts produced by different countries all fulfil the need of pilots
-being able to orient themselves. According to our evaluation, the Swiss
-aeronautical chart scored slightly more favourably than the other
-evaluated charts for effective map-reading. These findings were
-confirmed in the results of the user study.The major contribution of
-this work is the evaluation grid for the cartographic analysis. With its
-different layers, adaptable main- and sub-topics, it can be used to
-compare and improve the design not only of aeronautical charts, but for
-a broad spectrum of thematic maps.
+Abstract. Given the challenge of visualising 3D space on a 2D map, maps used for in-flight navigation by pilots should be designed especially carefully. This paper studies, based on existing aeronautical charts, the visualisation, interaction, and interpretation of airspace structures with aviation infrastructure and the base map.We first developed a three-tiered evaluation grid for a cartographic analysis of existing aeronautical charts. Subsequently, we evaluated four countries’ maps based on our evaluation grid. To validate our analysis, we conducted a user study with 27 pilots, the users of aeronautical charts.The results of our cartographic analysis show that aeronautical charts produced by different countries all fulfil the need of pilots being able to orient themselves. According to our evaluation, the Swiss aeronautical chart scored slightly more favourably than the other evaluated charts for effective map-reading. These findings were confirmed in the results of the user study.The major contribution of this work is the evaluation grid for the cartographic analysis. With its different layers, adaptable main- and sub-topics, it can be used to compare and improve the design not only of aeronautical charts, but for a broad spectrum of thematic maps.
-The purpose of the reviewed article is to evaluate and compare airspace
-structure visualization and perception on digital aeronautical charts.
-To do so, the authors propose two ways. The first one aims to define an
-evaluation grid on which they rely, as experts, to establish a
-cartographic analysis (they authors provide an access to their
-analysis). The second is a survey of 27 airplane pilots to collect their
-perceptions about different maps. Therefore, the reproducibility review
-process focused on reproducing the result visualizations of both
-analyses (the experts and the survey). To do so, the authors shared
-manually constructed data files as well as code files to reproduce the
-figures. The provided code and data allow to fully and easily reproduce
-the three figures of the reviewed article.
+The purpose of the reviewed article is to evaluate and compare airspace structure visualization and perception on digital aeronautical charts. To do so, the authors propose two ways. The first one aims to define an evaluation grid on which they rely, as experts, to establish a cartographic analysis (they authors provide an access to their analysis). The second is a survey of 27 airplane pilots to collect their perceptions about different maps. Therefore, the reproducibility review process focused on reproducing the result visualizations of both analyses (the experts and the survey). To do so, the authors shared manually constructed data files as well as code files to reproduce the figures. The provided code and data allow to fully and easily reproduce the three figures of the reviewed article.
-Authors: Simon Groß, Benjamin Herfort,
-Sabrina Marx, Alexander Zipf
+Authors: Simon Groß, Benjamin Herfort, Sabrina Marx, Alexander Zipf
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Fast and reliable geographic information is vital in
-disaster management. In the late 2000s, crowdsourcing emerged as a
-powerful method to provide this information. Base mapping through
-crowdsourcing is already well-established in relief workflows. However,
-crowdsourced post-disaster damage assessment is researched but not yet
-institutionalized. Based on MapSwipe, an established mobile application
-for crowdsourced base mapping, a damage assessment approach was
-developed and tested for a case study after the 2021 Haiti earthquake.
-First, MapSwipe’s damage mapping results are assessed for quality by
-using a reference dataset in regard to different aggregation methods.
-Then, the MapSwipe data was compared to an already established rapid
-damage assessment method by the Copernicus Emergency Management Service
-(CEMS). Crowdsourced building damage mapping achieved a maximum F1-score
-of 0.63 in comparison to the reference data set. MapSwipe and CEMS data
-showed only slight agreement with Cohen’s Kappa values reaching a
-maximum of 0.16. The results highlight the potential of crowdsourcing
-damage assessment as well as the importance for a scientific evaluation
-of the quality of CEMS data. Next steps for further integrating the
-presented workflow into MapSwipe are discussed.
+Abstract. Fast and reliable geographic information is vital in disaster management. In the late 2000s, crowdsourcing emerged as a powerful method to provide this information. Base mapping through crowdsourcing is already well-established in relief workflows. However, crowdsourced post-disaster damage assessment is researched but not yet institutionalized. Based on MapSwipe, an established mobile application for crowdsourced base mapping, a damage assessment approach was developed and tested for a case study after the 2021 Haiti earthquake. First, MapSwipe’s damage mapping results are assessed for quality by using a reference dataset in regard to different aggregation methods. Then, the MapSwipe data was compared to an already established rapid damage assessment method by the Copernicus Emergency Management Service (CEMS). Crowdsourced building damage mapping achieved a maximum F1-score of 0.63 in comparison to the reference data set. MapSwipe and CEMS data showed only slight agreement with Cohen’s Kappa values reaching a maximum of 0.16. The results highlight the potential of crowdsourcing damage assessment as well as the importance for a scientific evaluation of the quality of CEMS data. Next steps for further integrating the presented workflow into MapSwipe are discussed.
-The paper comes with a GitHub repository that mainly includes a jupyter
-notebook for reproducing the results. The notebook could be executed
-right away and is very well-documented. The outputs of the notebook
-include examplary data as well as all main plots from the paper. On
-request, the authors further added the raw QGIS files for reproducing
-map-based visualizations, and deposited the code with a DOI (https://zenodo.org/badge/latestdoi/581154837). Overall,
-the paper is fully reproducible.
+The paper comes with a GitHub repository that mainly includes a jupyter notebook for reproducing the results. The notebook could be executed right away and is very well-documented. The outputs of the notebook include examplary data as well as all main plots from the paper. On request, the authors further added the raw QGIS files for reproducing map-based visualizations, and deposited the code with a DOI (https://zenodo.org/badge/latestdoi/581154837). Overall, the paper is fully reproducible.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. We present the design and implementation of an
-empirical synchronous remote study for exploring the relation between
-spatial ability and performance on web-mapping services involving
-undergraduate University students; digital natives. The study exploits
-Spatial Thinking Ability Test to assess participants’ spatial ability
-and to reveal if and to what extent it is related to their ability to
-perform tasks on popular web-mapping services. Participants’ performance
-was assessed on the basis (a) of successfully executing tasks and (b) of
-how much time participants needed to properly perform tasks. A usability
-scale was used to measure participants’ subjective perceptions of
-web-mapping services usability. Moreover, participants were
-self-assessed in digital skills using the Digital Natives Assessment
-Scale. Results reveal differences among services in task accuracy
-indicating that not only the web-mapping service but also the nature of
-tasks guide participants’ performance. Correlations between spatial
-ability, digital skills, system usability, familiarity, and performance
-using web mapping services tend to be low and not significant leading to
-the assumption that success when interacting with a web mapping service
-is underlined by other factors as well.
+Abstract. We present the design and implementation of an empirical synchronous remote study for exploring the relation between spatial ability and performance on web-mapping services involving undergraduate University students; digital natives. The study exploits Spatial Thinking Ability Test to assess participants’ spatial ability and to reveal if and to what extent it is related to their ability to perform tasks on popular web-mapping services. Participants’ performance was assessed on the basis (a) of successfully executing tasks and (b) of how much time participants needed to properly perform tasks. A usability scale was used to measure participants’ subjective perceptions of web-mapping services usability. Moreover, participants were self-assessed in digital skills using the Digital Natives Assessment Scale. Results reveal differences among services in task accuracy indicating that not only the web-mapping service but also the nature of tasks guide participants’ performance. Correlations between spatial ability, digital skills, system usability, familiarity, and performance using web mapping services tend to be low and not significant leading to the assumption that success when interacting with a web mapping service is underlined by other factors as well.
-The authors provided code and data were able to partially reproduce the
-results presented in the figures and tables of the reviewed paper, but
-some of the tables were not fully reproduced. The paper includes the
-DASA section. The author provide all the data and code through figshare.
-Both R and RStudio are required for the reproductions of the authors
-work. For the reproducibility of the work, the authors provided R script
-survey_2021.R along with having data in dataset.7z.
+The authors provided code and data were able to partially reproduce the results presented in the figures and tables of the reviewed paper, but some of the tables were not fully reproduced. The paper includes the DASA section. The author provide all the data and code through figshare. Both R and RStudio are required for the reproductions of the authors work. For the reproducibility of the work, the authors provided R script survey_2021.R along with having data in dataset.7z.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The recent influx of remote and proximal sensing data
-provides new opportunities to understand environmental processes. A
-potential application of these datasets is to facilitate forestry
-operations. However, forest management decision-making through sensing
-techniques faces many challenges, partly due to the involvement of
-stakeholders with different knowledge levels and objectives. We present
-a virtual reality application developed for forest monitoring and
-assessment to address some of these challenges. First, a workflow for
-visualizing different sources of environmental sensing data is
-introduced to reconstruct digitally forest and terrain characteristics.
-Then, the VR experience is introduced in which users can observe,
-manipulate, and measure LiDAR-derived forest and tree models in
-immersive virtual environments. Finally, a heuristic expert evaluation
-to assess the overall user experience and the usability of individual
-application features is reported. We also gathered open-ended responses
-from domain experts to reflect on the potential and actual uses of the
-application in forest-related practices.
+Abstract. The recent influx of remote and proximal sensing data provides new opportunities to understand environmental processes. A potential application of these datasets is to facilitate forestry operations. However, forest management decision-making through sensing techniques faces many challenges, partly due to the involvement of stakeholders with different knowledge levels and objectives. We present a virtual reality application developed for forest monitoring and assessment to address some of these challenges. First, a workflow for visualizing different sources of environmental sensing data is introduced to reconstruct digitally forest and terrain characteristics. Then, the VR experience is introduced in which users can observe, manipulate, and measure LiDAR-derived forest and tree models in immersive virtual environments. Finally, a heuristic expert evaluation to assess the overall user experience and the usability of individual application features is reported. We also gathered open-ended responses from domain experts to reflect on the potential and actual uses of the application in forest-related practices.
-The data of the paper under reproduction is partially published on
-Zenodo under a CC-BY-4.0 license. Data on the selected plots displayed
-in Figure 1 is not available due to intellectual property concerns. The
-developed VR application is not available due to size and time
-constraints, therefore neither Figure 1 or 2 could be reproduced.
-Statistical analyses presented in Section 2.2 and Section 3 have been
-successfully reproduced. The authors showed dedication to support
-reproducibility of their work. Reproduction was partially successful.
+The data of the paper under reproduction is partially published on Zenodo under a CC-BY-4.0 license. Data on the selected plots displayed in Figure 1 is not available due to intellectual property concerns. The developed VR application is not available due to size and time constraints, therefore neither Figure 1 or 2 could be reproduced. Statistical analyses presented in Section 2.2 and Section 3 have been successfully reproduced. The authors showed dedication to support reproducibility of their work. Reproduction was partially successful.
-Authors: Enkhbold Nyamsuren, Haiqi Xu, Eric J. Top,
-Simon Scheider, Niels Steenbergen
+Authors: Enkhbold Nyamsuren, Haiqi Xu, Eric J. Top, Simon Scheider, Niels Steenbergen
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. There is an increasing trend of applying AIbased
-automated methods to geoscience problems. An important example is a
-geographic question answering (geoQA) focused on answer generation via
-GIS workflows rather than retrieval of a factual answer. However, a
-representative question corpus is necessary for developing, testing, and
-validating such generative geoQA systems. We compare five manually
-constructed geographical question corpora, GeoAnQu, Giki, GeoCLEF,
-GeoQuestions201, and Geoquery, by applying a conceptual transformation
-parser. The parser infers geo-analytical concepts and their
-transformations from a geographical question, akin to an abstract GIS
-workflow. Transformations thus represent the complexity of
-geo-analytical operations necessary to answer a question. By estimating
-the variety of concepts and the number of transformations for each
-corpus, the five corpora can be compared on the level of geo-analytical
-complexity, which cannot be done with purely NLP-based methods. Results
-indicate that the questions in GeoAnQu, which were compiled from GIS
-literature, require a higher number as well as more diverse
-geo-analytical operations than questions from the four other corpora.
-Furthermore, constructing a corpus with a sufficient representation
-(including GIS) may require an approach targeting a uniquely qualified
-group of users as a source. In contrast, sampling questions from
-large-scale online repositories like Google, Microsoft, and Yahoo may
-not provide the quality necessary for testing generative geoQA systems.
-
+Abstract. There is an increasing trend of applying AIbased automated methods to geoscience problems. An important example is a geographic question answering (geoQA) focused on answer generation via GIS workflows rather than retrieval of a factual answer. However, a representative question corpus is necessary for developing, testing, and validating such generative geoQA systems. We compare five manually constructed geographical question corpora, GeoAnQu, Giki, GeoCLEF, GeoQuestions201, and Geoquery, by applying a conceptual transformation parser. The parser infers geo-analytical concepts and their transformations from a geographical question, akin to an abstract GIS workflow. Transformations thus represent the complexity of geo-analytical operations necessary to answer a question. By estimating the variety of concepts and the number of transformations for each corpus, the five corpora can be compared on the level of geo-analytical complexity, which cannot be done with purely NLP-based methods. Results indicate that the questions in GeoAnQu, which were compiled from GIS literature, require a higher number as well as more diverse geo-analytical operations than questions from the four other corpora. Furthermore, constructing a corpus with a sufficient representation (including GIS) may require an approach targeting a uniquely qualified group of users as a source. In contrast, sampling questions from large-scale online repositories like Google, Microsoft, and Yahoo may not provide the quality necessary for testing generative geoQA systems.
-The data and software of the paper under reproduction is published on
-GitHub under an MIT license. All figures, tables, and embedded data
-points have been reproduced. The authors showed dedication and concern
-to support reproducibility of their work. Reproduction was successful.
+The data and software of the paper under reproduction is published on GitHub under an MIT license. All figures, tables, and embedded data points have been reproduced. The authors showed dedication and concern to support reproducibility of their work. Reproduction was successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Heatwaves are increasing around the world and cause a
-range of devastating societal impacts. Effective communication during a
-heatwave enables the general public to prepare and, if possible, take
-the necessary actions. In many African countries, the recognition of
-heatwaves and appropriate action to reduce heat risk remains absent. In
-this study, extreme heat and heat-related impacts across Mozambique were
-analyzed across space and time by using text from media sources. Alerts
-were obtained by performing a broad word search across four popular
-media outlets (Club of Mozambique, Rádio Moçambique, O País, and
-Televisão de Moçambique). Between 2016 and 2022, 79 heat alerts and 12
-posts on impacts were found. When mapped, a disproportionate number of
-articles were found for Southern provinces compared to Northern
-provinces. Communication of heat alerts were consistent across media
-outlets and included the maximum temperature forecasted and geographic
-locations affected. A majority of the messages (91%) did not include
-information on how to respond and the type of actions to take to reduce
-risk. Our findings provide spatio-temporal insights into extreme heat
-and impacts, and highlight the urgent need for an improved heatwave
-early warning system across Mozambique.
+Abstract. Heatwaves are increasing around the world and cause a range of devastating societal impacts. Effective communication during a heatwave enables the general public to prepare and, if possible, take the necessary actions. In many African countries, the recognition of heatwaves and appropriate action to reduce heat risk remains absent. In this study, extreme heat and heat-related impacts across Mozambique were analyzed across space and time by using text from media sources. Alerts were obtained by performing a broad word search across four popular media outlets (Club of Mozambique, Rádio Moçambique, O País, and Televisão de Moçambique). Between 2016 and 2022, 79 heat alerts and 12 posts on impacts were found. When mapped, a disproportionate number of articles were found for Southern provinces compared to Northern provinces. Communication of heat alerts were consistent across media outlets and included the maximum temperature forecasted and geographic locations affected. A majority of the messages (91%) did not include information on how to respond and the type of actions to take to reduce risk. Our findings provide spatio-temporal insights into extreme heat and impacts, and highlight the urgent need for an improved heatwave early warning system across Mozambique.
-The paper elaborates on the data collection about extreme heat alerts in
-Mozambique from different media sources and subsequently overlays the
-collected datasets. After manual data collection, the data were gathered
-and analysed in spreadsheets and then shared via Github under CC BY 4.0.
-For this reproducibility review, we attempted to reproduce Figures 1-4
-and Table 2. Since the data processing steps were not detailed enough in
-the README files provided by the corresponding author, in most cases we
-managed to do a verification of the results, rather than a reproduction.
-For this reason, the reproduction of this paper can be considered only
-partially successful.
+The paper elaborates on the data collection about extreme heat alerts in Mozambique from different media sources and subsequently overlays the collected datasets. After manual data collection, the data were gathered and analysed in spreadsheets and then shared via Github under CC BY 4.0. For this reproducibility review, we attempted to reproduce Figures 1-4 and Table 2. Since the data processing steps were not detailed enough in the README files provided by the corresponding author, in most cases we managed to do a verification of the results, rather than a reproduction. For this reason, the reproduction of this paper can be considered only partially successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. City streets that feel safe and attractive motivate
-active travel behaviour and promote people’s well-being. However,
-determining what makes a street safe and attractive is a challenging
-task because subjective qualities of the streetscape are difficult to
-quantify. Existing evidence typically focuses on how different street
-features influence perceived safety or attractiveness, but little is
-known about what influences both. To fill this knowledge gap, we
-developed a crowdsourcing tool and conducted a study with 403
-participants, who were asked to virtually navigate city streets in
-Frankfurt, Germany, through a sequence of street-level images, rate
-locations based on perceived safety and attractiveness, and explain
-their ratings. Our results contribute new insights regarding the key
-similarities and differences between the factors influencing perceived
-safety and attractiveness. We show that the presence of human activity
-is strongly related to perceived safety, whereas attractiveness is
-influenced primarily by aesthetic qualities, as well as the number and
-type of amenities along a street. Moreover, we demonstrate that the
-presence of construction sites and underpasses has a disproportionately
-negative impact on perceived safety and attractiveness, outweighing the
-influence of any other features. We use the results to make
-evidence-informed recommendations for designing safer and more
-attractive streets that encourage active travel modes and promote
-well-being.
+Abstract. City streets that feel safe and attractive motivate active travel behaviour and promote people’s well-being. However, determining what makes a street safe and attractive is a challenging task because subjective qualities of the streetscape are difficult to quantify. Existing evidence typically focuses on how different street features influence perceived safety or attractiveness, but little is known about what influences both. To fill this knowledge gap, we developed a crowdsourcing tool and conducted a study with 403 participants, who were asked to virtually navigate city streets in Frankfurt, Germany, through a sequence of street-level images, rate locations based on perceived safety and attractiveness, and explain their ratings. Our results contribute new insights regarding the key similarities and differences between the factors influencing perceived safety and attractiveness. We show that the presence of human activity is strongly related to perceived safety, whereas attractiveness is influenced primarily by aesthetic qualities, as well as the number and type of amenities along a street. Moreover, we demonstrate that the presence of construction sites and underpasses has a disproportionately negative impact on perceived safety and attractiveness, outweighing the influence of any other features. We use the results to make evidence-informed recommendations for designing safer and more attractive streets that encourage active travel modes and promote well-being.
-The code and data provided by the authors allow to fully reproduce their
-work as presented in the reviewed paper. The authors shared two
-repositories through github. The first one, called subjectivity, aims to
-build and run a whole web application (with database and a front web
-application). This web application allows to collect annotations from
-surveyed persons by proposing them different pictures of places through
-a track (see Fig. 1). The screenshot from the manuscript Figure 1 could
-be partially reproduced by this web application since the data used by
-the authors are not publicy available. The second repository,
-streetception, proposes two notebook in order to reproduce the analysis
-of the data collected by the authors through their web application. The
-authors have made significant efforts to improve their code and data
-sharing through the AGILE reproducibility process!
+The code and data provided by the authors allow to fully reproduce their work as presented in the reviewed paper. The authors shared two repositories through github. The first one, called subjectivity, aims to build and run a whole web application (with database and a front web application). This web application allows to collect annotations from surveyed persons by proposing them different pictures of places through a track (see Fig. 1). The screenshot from the manuscript Figure 1 could be partially reproduced by this web application since the data used by the authors are not publicy available. The second repository, streetception, proposes two notebook in order to reproduce the analysis of the data collected by the authors through their web application. The authors have made significant efforts to improve their code and data sharing through the AGILE reproducibility process!
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Cycling practice has been constantly increasing for
-several years and the COVID crisis has just accelerated the process.
-Indeed, more and more municipalities have developed new cycle paths to
-facilitate cycling. Considering this increasing interest for cycling, it
-makes sense to study how this recent evolution is reflected in the
-underlying representation of the cycling network in the geographic
-databases. Main studies analysing the evolution of the road network
-focus on the motor vehicle network in the major cities of the world.
-These studies do not seem applicable to cycling network specially to
-some low population density areas or even to smaller cities. This paper
-analyses the changes in the cycling network through OSM data from a data
-freshness perspective. These changes can be either updates from changes
-in the real-world network or upgrades to the network. To these end, we
-propose a method using a Monte Carlo simulation (MCS) to analyse the
-frequency of changes in cycling routes in several areas with different
-population density, all in the Loire Valley region in France. We also
-define the cycling network, which is a very complex concept and we
-explain how it is represented in OSM data and suffers from different
-data quality issues. Results show that the number of changes across time
-are similar in areas having a similar population density, while being
-lower in low population density areas. These phenomena is higher in the
-cycling network compared to other networks.
+Abstract. Cycling practice has been constantly increasing for several years and the COVID crisis has just accelerated the process. Indeed, more and more municipalities have developed new cycle paths to facilitate cycling. Considering this increasing interest for cycling, it makes sense to study how this recent evolution is reflected in the underlying representation of the cycling network in the geographic databases. Main studies analysing the evolution of the road network focus on the motor vehicle network in the major cities of the world. These studies do not seem applicable to cycling network specially to some low population density areas or even to smaller cities. This paper analyses the changes in the cycling network through OSM data from a data freshness perspective. These changes can be either updates from changes in the real-world network or upgrades to the network. To these end, we propose a method using a Monte Carlo simulation (MCS) to analyse the frequency of changes in cycling routes in several areas with different population density, all in the Loire Valley region in France. We also define the cycling network, which is a very complex concept and we explain how it is represented in OSM data and suffers from different data quality issues. Results show that the number of changes across time are similar in areas having a similar population density, while being lower in low population density areas. These phenomena is higher in the cycling network compared to other networks.
-The authors execute their study fully within a framework of open source
-geospatial software. The study is reproducible and the authors provide
-provide 2 scripts that query and subsequently visualise aspects of the
-data. Furthermore, they provide a How-to / Readme file that made it easy
-to reproduce. The main challenges in reproduction were related to
-acquiring the correct data and the handling of the OSRM software. This
-was overcome jointly through authors communication and fortunate
-experience with the Docker ecosystem of the reviewer. The data analysis
-and visualisation was straightforward and the results were consistent
-with the original paper. Figures 4a and 4b are reproduced.
+The authors execute their study fully within a framework of open source geospatial software. The study is reproducible and the authors provide provide 2 scripts that query and subsequently visualise aspects of the data. Furthermore, they provide a How-to / Readme file that made it easy to reproduce. The main challenges in reproduction were related to acquiring the correct data and the handling of the OSRM software. This was overcome jointly through authors communication and fortunate experience with the Docker ecosystem of the reviewer. The data analysis and visualisation was straightforward and the results were consistent with the original paper. Figures 4a and 4b are reproduced.
-Authors: Ioannis Dardavesis, Edward Verbree, Azarakhsh
-Rafiee
+Authors: Ioannis Dardavesis, Edward Verbree, Azarakhsh Rafiee
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Localisation and navigation technologies have vastly
-evolved during the last years, facilitating users’ guidance in various
-environments. Unlike outdoor environments where GNSS comprises a
-universal solution, in indoor environments various localisation
-techniques have been used, each one with its drawbacks. Thus, this
-research investigates the reliability of the ceilings towards indoor
-localisation, by using components that are included in a simple mobile
-device. The choice of ceilings lies in their advantages, which include
-the incorporation of various characteristic components, as well as the
-absence of obstacles between them and the sensor. Indoor localisation is
-achieved based on LiDAR point clouds and images from RGB sensors of
-mobile devices. Additionally, this research involves location tracking
-of different users, to discover different movement patterns in an indoor
-facility. The proposed methodology revealed the robustness of the
-Coloured ICP algorithm for in-door localisation based on point clouds,
-both in terms of time efficiency and quality, while the combination of
-the SURF feature detector and SIFT descriptor provides the optimal
-indoor localisation results with image data. The proposed pipeline
-revealed encouraging results for use in emergencies, based on static
-data acquisition of a user, while it is also suitable for dynamic
-applications, in case a sensor is mounted on an automated device for
-indoor mapping operations. The captured point clouds of the ceilings can
-also be used as a reference to CAD and BIM models, to help the modelling
-of the existing utilities and their components in an indoor facility.
-
+Abstract. Localisation and navigation technologies have vastly evolved during the last years, facilitating users’ guidance in various environments. Unlike outdoor environments where GNSS comprises a universal solution, in indoor environments various localisation techniques have been used, each one with its drawbacks. Thus, this research investigates the reliability of the ceilings towards indoor localisation, by using components that are included in a simple mobile device. The choice of ceilings lies in their advantages, which include the incorporation of various characteristic components, as well as the absence of obstacles between them and the sensor. Indoor localisation is achieved based on LiDAR point clouds and images from RGB sensors of mobile devices. Additionally, this research involves location tracking of different users, to discover different movement patterns in an indoor facility. The proposed methodology revealed the robustness of the Coloured ICP algorithm for in-door localisation based on point clouds, both in terms of time efficiency and quality, while the combination of the SURF feature detector and SIFT descriptor provides the optimal indoor localisation results with image data. The proposed pipeline revealed encouraging results for use in emergencies, based on static data acquisition of a user, while it is also suitable for dynamic applications, in case a sensor is mounted on an automated device for indoor mapping operations. The captured point clouds of the ceilings can also be used as a reference to CAD and BIM models, to help the modelling of the existing utilities and their components in an indoor facility.
-The paper is accompanied by a GitHub repository with front end and back
-end code of their indoor localization app. The code was not executable
-first, but installation instructions were added and file paths were
-fixed upon exchange with the authors. The results reported in the paper
-are partially reproducible with the provided code. The code mainly
-yields examples that are similar but not the same as in the paper, due
-to randomness in the algorithms. One script allows to reproduce a figure
-exactly, while other quantitative results (tables in the paper) can not
-be created with the code. However, given the instructions in the README
-and the example data, the repository can be very useful for researchers
-who want to apply the pipeline on their own data.
+The paper is accompanied by a GitHub repository with front end and back end code of their indoor localization app. The code was not executable first, but installation instructions were added and file paths were fixed upon exchange with the authors. The results reported in the paper are partially reproducible with the provided code. The code mainly yields examples that are similar but not the same as in the paper, due to randomness in the algorithms. One script allows to reproduce a figure exactly, while other quantitative results (tables in the paper) can not be created with the code. However, given the instructions in the README and the example data, the repository can be very useful for researchers who want to apply the pipeline on their own data.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-AbstractThe complexity of the human
-shoulder girdle enables the large mobility of the upper extremity, but
-also introduces instability of the glenohumeral (GH) joint. Shoulder
-movements are generated by coordinating large superficial and deeper
-stabilizing muscles spanning numerous degrees-of-freedom. How shoulder
-muscles are coordinated to stabilize the movement of the GH joint
-remains widely unknown. Musculoskeletal simulations are powerful tools
-to gain insights into the actions of individual muscles and particularly
-of those that are difficult to measure. In this study, we analyze how
-enforcement of GH joint stability in a musculoskeletal model affects the
-estimates of individual muscle activity during shoulder movements. To
-estimate both muscle activity and GH stability from recorded shoulder
-movements, we developed a Rapid Muscle Redundancy (RMR) solver to
-include constraints on joint reaction forces (JRFs) from a
-musculoskeletal model. The RMR solver yields muscle activations and
-joint forces by minimizing the weighted sum of squared-activations,
-while matching experimental motion. We implemented three new features:
-first, computed muscle forces include active and passive fiber
-contributions; second, muscle activation rates are enforced to be
-physiological, and third, JRFs are efficiently formulated as linear
-functions of activations. Muscle activity from the RMR solver without GH
-stability was not different from the computed muscle control (CMC)
-algorithm and electromyography of superficial muscles. The efficiency of
-the solver enabled us to test 3600 trials sampled within the uncertainty
-of the experimental movements to test the differences in muscle activity
-with and without GH joint stability enforced. We found that enforcing GH
-stability significantly increases the estimated activity of the rotator
-cuff muscles but not of most superficial muscles. Therefore, a
-comparison of shoulder model muscle activity to EMG measurements of
-superficial muscles alone is insufficient to validate the activity of
-rotator cuff muscles estimated from musculoskeletal models.
+AbstractThe complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the movement of the GH joint remains widely unknown. Musculoskeletal simulations are powerful tools to gain insights into the actions of individual muscles and particularly of those that are difficult to measure. In this study, we analyze how enforcement of GH joint stability in a musculoskeletal model affects the estimates of individual muscle activity during shoulder movements. To estimate both muscle activity and GH stability from recorded shoulder movements, we developed a Rapid Muscle Redundancy (RMR) solver to include constraints on joint reaction forces (JRFs) from a musculoskeletal model. The RMR solver yields muscle activations and joint forces by minimizing the weighted sum of squared-activations, while matching experimental motion. We implemented three new features: first, computed muscle forces include active and passive fiber contributions; second, muscle activation rates are enforced to be physiological, and third, JRFs are efficiently formulated as linear functions of activations. Muscle activity from the RMR solver without GH stability was not different from the computed muscle control (CMC) algorithm and electromyography of superficial muscles. The efficiency of the solver enabled us to test 3600 trials sampled within the uncertainty of the experimental movements to test the differences in muscle activity with and without GH joint stability enforced. We found that enforcing GH stability significantly increases the estimated activity of the rotator cuff muscles but not of most superficial muscles. Therefore, a comparison of shoulder model muscle activity to EMG measurements of superficial muscles alone is insufficient to validate the activity of rotator cuff muscles estimated from musculoskeletal models.
-Codecheck performed interactively as part of the Delft 2023 workshop.
-The codecheck was undertaken with the first author observing and able to
-help fix issues. This meant that the codecheck was fairly quick and any
-issues were resolved fairly quickly. With some fixes, the code was
-confirmed to work and Figure 3 could be reproduced with some visual
-differences due to post-processing of the figures before publication, as
-was confirmed by the author.
+Codecheck performed interactively as part of the Delft 2023 workshop. The codecheck was undertaken with the first author observing and able to help fix issues. This meant that the codecheck was fairly quick and any issues were resolved fairly quickly. With some fixes, the code was confirmed to work and Figure 3 could be reproduced with some visual differences due to post-processing of the figures before publication, as was confirmed by the author.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-AbstractLight exposure is an essential
-driver of health and well-being, and individual behaviours during rest
-and activity modulate physiologically relevant aspects of light
-exposure. Further understanding the behaviours that influence individual
-photic exposure patterns may provide insight into the volitional
-contributions to the physiological effects of light and guide
-behavioural points of intervention. Here, we present a novel,
-self-reported and psychometrically validated inventory to capture light
-exposure-related behaviour, the Light Exposure Behaviour Assessment
-(LEBA). An expert panel prepared the initial 48-item pool spanning
-different light exposure-related behaviours. Responses, consisting of
-rating the frequency of engaging in the per-item behaviour on a
-five-point Likert-type scale, were collected in an online survey
-yielding responses from a geographically unconstrained sample (690
-completed responses, 74 countries, 28 time zones). The exploratory
-factor analysis (EFA) on an initial subsample (n = 428) rendered a
-five-factor solution with 25 items (wearing blue light filters, spending
-time outdoors, using a phone and smartwatch in bed, using light before
-bedtime, using light in the morning and during daytime). In a
-confirmatory factor analysis (CFA) performed on an independent subset of
-participants (n = 262), we removed two additional items to attain the
-best fit for the five-factor solution (CFI = 0.95, TLI = 0.95, RMSEA =
-0.06). The internal consistency reliability coefficient for the total
-instrument yielded McDonald’s Omega = 0.68. Measurement model invariance
-analysis between native and non-native English speakers showed our model
-attained the highest level of invariance (residual invariance CFI =
-0.95, TLI = 0.95, RMSEA = 0.05). Lastly, a short form of the LEBA (n =
-18 items) was developed using Item Response Theory on the complete
-sample (n = 690). The psychometric properties of the LEBA indicate the
-usability for measuring light exposure-related behaviours. The
-instrument may offer a scalable solution to characterise behaviours that
-influence individual photic exposure patterns in remote samples. The
-LEBA inventory is available under the open-access CC-BY license.
-Instrument
-webpage:https://leba-instrument.org/GitHub
-repository containing this
-manuscript:https://github.com/leba-instrument/leba-manuscript.
+AbstractLight exposure is an essential driver of health and well-being, and individual behaviours during rest and activity modulate physiologically relevant aspects of light exposure. Further understanding the behaviours that influence individual photic exposure patterns may provide insight into the volitional contributions to the physiological effects of light and guide behavioural points of intervention. Here, we present a novel, self-reported and psychometrically validated inventory to capture light exposure-related behaviour, the Light Exposure Behaviour Assessment (LEBA). An expert panel prepared the initial 48-item pool spanning different light exposure-related behaviours. Responses, consisting of rating the frequency of engaging in the per-item behaviour on a five-point Likert-type scale, were collected in an online survey yielding responses from a geographically unconstrained sample (690 completed responses, 74 countries, 28 time zones). The exploratory factor analysis (EFA) on an initial subsample (n = 428) rendered a five-factor solution with 25 items (wearing blue light filters, spending time outdoors, using a phone and smartwatch in bed, using light before bedtime, using light in the morning and during daytime). In a confirmatory factor analysis (CFA) performed on an independent subset of participants (n = 262), we removed two additional items to attain the best fit for the five-factor solution (CFI = 0.95, TLI = 0.95, RMSEA = 0.06). The internal consistency reliability coefficient for the total instrument yielded McDonald’s Omega = 0.68. Measurement model invariance analysis between native and non-native English speakers showed our model attained the highest level of invariance (residual invariance CFI = 0.95, TLI = 0.95, RMSEA = 0.05). Lastly, a short form of the LEBA (n = 18 items) was developed using Item Response Theory on the complete sample (n = 690). The psychometric properties of the LEBA indicate the usability for measuring light exposure-related behaviours. The instrument may offer a scalable solution to characterise behaviours that influence individual photic exposure patterns in remote samples. The LEBA inventory is available under the open-access CC-BY license. Instrument webpage:https://leba-instrument.org/GitHub repository containing this manuscript:https://github.com/leba-instrument/leba-manuscript.
-Comprehensive reproduction of RMarkdown document; biggest concerns found
-with Linux versions of R package “gt”.
+Comprehensive reproduction of RMarkdown document; biggest concerns found with Linux versions of R package “gt”.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
- Vision is mediated by light passing through the pupil, which
-changes in diameter from approximately 2 to 8 mm between bright and dark
-illumination. With age, mean pupil size declines. In laboratory
-experiments, factors affecting pupil size can be experimentally
-controlled. How the pupil reflects the change in retinal input from the
-visual environment under natural viewing conditions is unclear. We
-address this question in a field experiment (
-N = 83, 43 female, 18–87 years) using a
-custom-made wearable video-based eye tracker with a spectroradiometer
-measuring near-corneal spectral irradiance. Participants moved in and
-between indoor and outdoor environments varying in spectrum and engaged
-in a range of everyday tasks. Our data confirm that light-adapted pupil
-size is determined by light level, with a better model fit of melanopic
-over photopic units, and that it decreased with increasing age, yielding
-steeper slopes at lower light levels. We found no indication that sex,
-iris colour or reported caffeine consumption affects pupil size. Our
-exploratory results point to a role of photoreceptor integration in
-controlling steady-state pupil size. The data provide evidence for
-considering age in personalized lighting solutions and against the use
-of photopic illuminance alone to assess the impact of real-world
-lighting conditions.
+ Vision is mediated by light passing through the pupil, which changes in diameter from approximately 2 to 8 mm between bright and dark illumination. With age, mean pupil size declines. In laboratory experiments, factors affecting pupil size can be experimentally controlled. How the pupil reflects the change in retinal input from the visual environment under natural viewing conditions is unclear. We address this question in a field experiment ( N = 83, 43 female, 18–87 years) using a custom-made wearable video-based eye tracker with a spectroradiometer measuring near-corneal spectral irradiance. Participants moved in and between indoor and outdoor environments varying in spectrum and engaged in a range of everyday tasks. Our data confirm that light-adapted pupil size is determined by light level, with a better model fit of melanopic over photopic units, and that it decreased with increasing age, yielding steeper slopes at lower light levels. We found no indication that sex, iris colour or reported caffeine consumption affects pupil size. Our exploratory results point to a role of photoreceptor integration in controlling steady-state pupil size. The data provide evidence for considering age in personalized lighting solutions and against the use of photopic illuminance alone to assess the impact of real-world lighting conditions.
-Matlab code, requiring 3 additional toolboxes. Case study 2 only. Full
-reproduction possible, takes about 2 hours to run
+Matlab code, requiring 3 additional toolboxes. Case study 2 only. Full reproduction possible, takes about 2 hours to run
-Authors: Leonie Dudda, Eva Kormann, Magdalena Kozula,
-Nicholas J. DeVito, Thomas Klebe, Ayu P.M. Dewi, René Spijker, Inge
-Stegeman, Veerle Van den Eynden, Tony Ross-Hellauer, Mariska M.G.
-Leeflang
+Authors: Leonie Dudda, Eva Kormann, Magdalena Kozula, Nicholas J. DeVito, Thomas Klebe, Ayu P.M. Dewi, René Spijker, Inge Stegeman, Veerle Van den Eynden, Tony Ross-Hellauer, Mariska M.G. Leeflang
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Various interventions – especially those related to open science – have
-been proposed to improve the reproducibility and replicability of
-scientific research. To assess whether and which interventions have been
-formally tested for their effectiveness in improving reproducibility and
-replicability, we conducted a scoping review of the literature on
-interventions to improve reproducibility. We systematically searched
-Medline, Embase, Web of Science, PsycINFO, Scopus and Eric, on August
-18, 2023. Grey literature was requested from experts in the fields of
-reproducibility and open science. Any study empirically evaluating the
-effectiveness of interventions aimed at improving the reproducibility or
-replicability of scientific methods and findings was included. An
-intervention could be any action taken by either individual researchers
-or scientific institutions (e.g., research institutes, publishers and
-funders). We summarized the retrieved evidence narratively and in an
-evidence gap map. Of the 104 distinct studies we included, 15 directly
-measured the effect of an intervention on reproducibility or
-replicability, while the other research questions addressed a proxy
-outcome that might be expected to increase reproducibility or
-replicability, such as data sharing, methods transparency or
-preregistration. Thirty research questions within included studies were
-non-comparative and 27 were comparative but cross-sectional, precluding
-any causal inference. Possible limitations of our review may be the
-search and selection strategy, which was done by a large team including
-researchers from different disciplines and different expertise levels.
-Despite studies investigating a range of interventions and addressing
-various outcomes, our findings indicate that in general the
-evidence-base for which various interventions to improve reproducibility
-of research remains remarkably limited in many respects.
+Various interventions – especially those related to open science – have been proposed to improve the reproducibility and replicability of scientific research. To assess whether and which interventions have been formally tested for their effectiveness in improving reproducibility and replicability, we conducted a scoping review of the literature on interventions to improve reproducibility. We systematically searched Medline, Embase, Web of Science, PsycINFO, Scopus and Eric, on August 18, 2023. Grey literature was requested from experts in the fields of reproducibility and open science. Any study empirically evaluating the effectiveness of interventions aimed at improving the reproducibility or replicability of scientific methods and findings was included. An intervention could be any action taken by either individual researchers or scientific institutions (e.g., research institutes, publishers and funders). We summarized the retrieved evidence narratively and in an evidence gap map. Of the 104 distinct studies we included, 15 directly measured the effect of an intervention on reproducibility or replicability, while the other research questions addressed a proxy outcome that might be expected to increase reproducibility or replicability, such as data sharing, methods transparency or preregistration. Thirty research questions within included studies were non-comparative and 27 were comparative but cross-sectional, precluding any causal inference. Possible limitations of our review may be the search and selection strategy, which was done by a large team including researchers from different disciplines and different expertise levels. Despite studies investigating a range of interventions and addressing various outcomes, our findings indicate that in general the evidence-base for which various interventions to improve reproducibility of research remains remarkably limited in many respects.
-Codecheck performed on two .qmd files containing R code from a public
-GitHub repository for a scoping review pre-print.
+Codecheck performed on two .qmd files containing R code from a public GitHub repository for a scoping review pre-print.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Task-related functional MRI (fMRI) studies need to be properly powered
-with an adequate sample size to reliably detect effects of interest. But
-for most fMRI studies, it is not straightforward to determine a proper
-sample size using power calculations based on published effect sizes.
-Here, we present an alternative approach of sample size estimation with
-empirical Bayesian updating. First, this method provides an estimate of
-the required sample size using existing data from a similar task and
-similar region of interest. Using this estimate researchers can plan
-their research project, and report empirically determined sample size
-estimations in their research proposal or pre-registration. Second,
-researchers can expand the sample size estimations with new data. We
-illustrate this approach using four existing fMRI data sets where
-Cohen’s d is the effect size of interest for the hemodynamic response in
-the task condition of interest versus a control condition, and where a
-Pearson correlation between task effect and age is the covariate of
-interest. We show that sample sizes to reliably detect effects differ
-between various tasks and regions of interest. We provide an R package
-to allow researchers to use Bayesian updating with other task-related
-fMRI studies.A reproducible version of this manuscript including
-associated code notebooks is available here: https://eduardklap.github.io/sample-size-fmri/
+Task-related functional MRI (fMRI) studies need to be properly powered with an adequate sample size to reliably detect effects of interest. But for most fMRI studies, it is not straightforward to determine a proper sample size using power calculations based on published effect sizes. Here, we present an alternative approach of sample size estimation with empirical Bayesian updating. First, this method provides an estimate of the required sample size using existing data from a similar task and similar region of interest. Using this estimate researchers can plan their research project, and report empirically determined sample size estimations in their research proposal or pre-registration. Second, researchers can expand the sample size estimations with new data. We illustrate this approach using four existing fMRI data sets where Cohen’s d is the effect size of interest for the hemodynamic response in the task condition of interest versus a control condition, and where a Pearson correlation between task effect and age is the covariate of interest. We show that sample sizes to reliably detect effects differ between various tasks and regions of interest. We provide an R package to allow researchers to use Bayesian updating with other task-related fMRI studies.A reproducible version of this manuscript including associated code notebooks is available here: https://eduardklap.github.io/sample-size-fmri/
-This report checks the code of the article Sample size estimation for
-task-related functional MRI studies using Bayesian updating. (https://doi.org/10.31234/osf.io/cz32t (currently under
-review at Developmental Cognitive Neuroscience)). See section Notes for
-details about running the code. The CODECHECK was successful. The
-created figures figures_cohens_d.html and figures-correlations.html are
-visually very close to the one in the repository. The reproduction of
-the figures from the repository was easy due to the workflow and
-integration with Quarto and RStudio.
+This report checks the code of the article Sample size estimation for task-related functional MRI studies using Bayesian updating. (https://doi.org/10.31234/osf.io/cz32t (currently under review at Developmental Cognitive Neuroscience)). See section Notes for details about running the code. The CODECHECK was successful. The created figures figures_cohens_d.html and figures-correlations.html are visually very close to the one in the repository. The reproduction of the figures from the repository was easy due to the workflow and integration with Quarto and RStudio.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Current point cloud data management systems and
-formats are heavily specialized and targeted solely towards
-visualization purposes and fail to address the diverse needs of
-progressive point cloud workflows like for example semantic segmentation
-using machine learning. We therefore propose a distributed data
-infrastructure for dynamic point cloud data management that can support
-interactive real-time visualization at scale while simultaneously
-serving as a platform for analytical tasks. By introducing random data
-distribution, we show that simple query fragmentation and efficient and
-effective parallelism at scale are possible. At the same time, arbitrary
-queries in space and time can be efficiently run over the infrastructure
-including query semantics which returns only a random sample of the
-query results or preferred points based on an importance dimension
-calculated, for example, from a local point density information as
-commonly done in point cloud visualization. To cope with the unknown
-amount of user-specific attributes and to support even multiple ways of
-deciding the importance of a given point (ground point removal, coverage
-of space, random subset) the system is designed to support all of them
-transparently as multidimensional range queries backed by spatial
-indices.
+Abstract. Current point cloud data management systems and formats are heavily specialized and targeted solely towards visualization purposes and fail to address the diverse needs of progressive point cloud workflows like for example semantic segmentation using machine learning. We therefore propose a distributed data infrastructure for dynamic point cloud data management that can support interactive real-time visualization at scale while simultaneously serving as a platform for analytical tasks. By introducing random data distribution, we show that simple query fragmentation and efficient and effective parallelism at scale are possible. At the same time, arbitrary queries in space and time can be efficiently run over the infrastructure including query semantics which returns only a random sample of the query results or preferred points based on an importance dimension calculated, for example, from a local point density information as commonly done in point cloud visualization. To cope with the unknown amount of user-specific attributes and to support even multiple ways of deciding the importance of a given point (ground point removal, coverage of space, random subset) the system is designed to support all of them transparently as multidimensional range queries backed by spatial indices.
-The workflow provided was partially reproduced in the sense that I was
-able to reproduce the system reported in the paper qualitatively. That
-is, I did not reproduce the experiment or other results (figures, etc.)
-included in the article, but I was able to set up and run the system
-described in the paper and test it with some query samples. Therefore,
-by doing this, this report ensures that the system works as described in
-the manuscript.
+The workflow provided was partially reproduced in the sense that I was able to reproduce the system reported in the paper qualitatively. That is, I did not reproduce the experiment or other results (figures, etc.) included in the article, but I was able to set up and run the system described in the paper and test it with some query samples. Therefore, by doing this, this report ensures that the system works as described in the manuscript.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Current research has investigated freehand gestures
-for Pan and Zoom operations on maps on large screens. Freehand gestures
-for Retrieve operations, however, have remained largely unexplored. To
-address this gap, this work introduced two mechanisms for Retrieve on
-large displays in a research-through-design study: Pointer-to-Feature
-(i.e. moving a pointer to a geographic feature and then performing a
-hand gesture to achieve Retrieve) and Feature-to-Pointer (i.e. moving a
-geographic feature to a stationary pointer at the screen’s centre
-through panning/ zooming of the map, before performing a hand gesture to
-achieve Retrieve). The evaluation of a prototype (FreeMapRetrieve)
-regarding usability and data exploration utility showed that both
-mechanisms work well. The two techniques are comparable for large
-polygons but Pointer-to-Feature is slightly more efficient for smaller
-polygons. Reflections on the design process yield lessons learned that
-are relevant to designers of gesture-based interaction for maps on large
-displays.
+Abstract. Current research has investigated freehand gestures for Pan and Zoom operations on maps on large screens. Freehand gestures for Retrieve operations, however, have remained largely unexplored. To address this gap, this work introduced two mechanisms for Retrieve on large displays in a research-through-design study: Pointer-to-Feature (i.e. moving a pointer to a geographic feature and then performing a hand gesture to achieve Retrieve) and Feature-to-Pointer (i.e. moving a geographic feature to a stationary pointer at the screen’s centre through panning/ zooming of the map, before performing a hand gesture to achieve Retrieve). The evaluation of a prototype (FreeMapRetrieve) regarding usability and data exploration utility showed that both mechanisms work well. The two techniques are comparable for large polygons but Pointer-to-Feature is slightly more efficient for smaller polygons. Reflections on the design process yield lessons learned that are relevant to designers of gesture-based interaction for maps on large displays.
-The workflow provided was partially reproduced in the sense that I was
-able to reproduce the data analysis of the user assessment. The
-manuscript also described a prototype system that required specific
-hardware, therefore, I skipped this part.
+The workflow provided was partially reproduced in the sense that I was able to reproduce the data analysis of the user assessment. The manuscript also described a prototype system that required specific hardware, therefore, I skipped this part.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Urban Green Spaces (UGS) play a crucial role in
-enhancing the quality of life in cities by providing numerous
-environmental, social, and health benefits. Among these green spaces,
-allotment gardens stand out as a unique type that contributes to
-ecological services, preservation of biodiversity, and the overall
-well-being of urban dwellers. Unfortunately, the significance of
-allotment gardens as a specific type of UGS is still disregarded and
-they are not recognized as a separate category in land use / land cover
-maps or city maps of green spaces. This is mainly due to the mixed use
-of allotment areas, their small size and absence of tailored
-identification or mapping workflows. In this research, we address the
-latter one by proposing an approach that utilizes various semantic
-characteristics of allotment gardens to create distinctive spatial
-representations. The semantic characteristics we consider include the
-presence, density, and height of garden huts, proximity to water bodies
-and railroads, as well as the presence of pathways within the allotment
-gardens. Allotments are delineated using a three-step procedure. This
-involves utilizing a Random Forest machine learning classifier to create
-maps of the distribution of green spaces, extracting garden huts
-employing a threshold, and demarcating the area using a density based
-clustering technique. Furthermore, we repeat the same workflow in a new
-study area to assess the applicability of the proposed workflow. With
-the established workflow, we are able to accurately identify 78% of
-allotments in Augsburg and 88% in Wuerzburg respectively. Our results
-demonstrate that the proposed workflow can be a useful approach to
-validate and extend existing land use and land cover data sets while
-remaining time and cost effective.
+Abstract. Urban Green Spaces (UGS) play a crucial role in enhancing the quality of life in cities by providing numerous environmental, social, and health benefits. Among these green spaces, allotment gardens stand out as a unique type that contributes to ecological services, preservation of biodiversity, and the overall well-being of urban dwellers. Unfortunately, the significance of allotment gardens as a specific type of UGS is still disregarded and they are not recognized as a separate category in land use / land cover maps or city maps of green spaces. This is mainly due to the mixed use of allotment areas, their small size and absence of tailored identification or mapping workflows. In this research, we address the latter one by proposing an approach that utilizes various semantic characteristics of allotment gardens to create distinctive spatial representations. The semantic characteristics we consider include the presence, density, and height of garden huts, proximity to water bodies and railroads, as well as the presence of pathways within the allotment gardens. Allotments are delineated using a three-step procedure. This involves utilizing a Random Forest machine learning classifier to create maps of the distribution of green spaces, extracting garden huts employing a threshold, and demarcating the area using a density based clustering technique. Furthermore, we repeat the same workflow in a new study area to assess the applicability of the proposed workflow. With the established workflow, we are able to accurately identify 78% of allotments in Augsburg and 88% in Wuerzburg respectively. Our results demonstrate that the proposed workflow can be a useful approach to validate and extend existing land use and land cover data sets while remaining time and cost effective.
The paper addresses the issue that allotment gardens are not
-recognized as separate land use / land cover category, although they are
-unique among urban green spaces and provide highly significant benefits.
-The research uses a three-step procedure: First, a random forest
-classifier identifies green spaces from digital orthophotos; second,
-garden huts are extracted; and third, a density-based clustering
-identifies areas of allotment gardens. The computational environment
-relies on a mix of free and open source software (R software for the
-random forest classification) and proprietary GIS software (ESRI ArcGIS
-for the height thresholds, refinement of the classification, and
-density-based clustering).
-Upon request, the authors provided the digital orthophoto, training data
-and code for step one, as well as a sample data set (smaller area) and
-executable workflow for the ArcGIS Modelbuilder as an ArcGIS project
-package. The reproducibility review can confirm that that the analysis
-runs as intended, but not check the validity of the outputs shown in the
-paper. All the provided code was run and executes without errors,
-generating valid output. The clustering algorithm does not find any
-clusters, but that may be due to the small size of the sample area. This
-reproducibility review was thus able to validate the entire analysis
-workflow. With the provided documentation, code, and sample data (see
-references), other researchers should be able to succeed in replicating
-the results. The functionality used in the proprietary software is
-available in free and open software packages and can thus be implemented
-without access to ArcGIS.
+
The paper addresses the issue that allotment gardens are not recognized as separate land use / land cover category, although they are unique among urban green spaces and provide highly significant benefits. The research uses a three-step procedure: First, a random forest classifier identifies green spaces from digital orthophotos; second, garden huts are extracted; and third, a density-based clustering identifies areas of allotment gardens. The computational environment relies on a mix of free and open source software (R software for the random forest classification) and proprietary GIS software (ESRI ArcGIS for the height thresholds, refinement of the classification, and density-based clustering).
+Upon request, the authors provided the digital orthophoto, training data and code for step one, as well as a sample data set (smaller area) and executable workflow for the ArcGIS Modelbuilder as an ArcGIS project package. The reproducibility review can confirm that that the analysis runs as intended, but not check the validity of the outputs shown in the paper. All the provided code was run and executes without errors, generating valid output. The clustering algorithm does not find any clusters, but that may be due to the small size of the sample area. This reproducibility review was thus able to validate the entire analysis workflow. With the provided documentation, code, and sample data (see references), other researchers should be able to succeed in replicating the results. The functionality used in the proprietary software is available in free and open software packages and can thus be implemented without access to ArcGIS.
-Authors: Matias Cardoso1, Vasileios Milias, Maurice
-Harteveld
+Authors: Matias Cardoso1, Vasileios Milias, Maurice Harteveld
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The extent to which the built environment encourages
-people to walk in public spaces, hence the quality of being walkable or
-‘walkability’ has long been associated with positive outcomes on
-people’s health. While various studies have developed indices to assess
-walkability, limited attention has been given to indices that reflect
-the influence of specific city characteristics on walkability. This
-study showcases the development of a city-specific walkability index
-through a participatory approach using Amsterdam as a case study. It
-explores the viewpoints of urban designers and policy-makers who work or
-reside in Amsterdam on what constitutes a walkable street and identifies
-the most significant walkability factors for Amsterdam. These factors
-are then quantified based on open-access datasets and integrated into a
-street-level weighted walkability index. The resulting walkability index
-underscores the importance of factors such as traffic and crime safety,
-quality of the pedestrian infrastructure, and proximity to public
-amenities in shaping residents’ decisions to walk in specific public
-spaces. Finally, this research underscores the importance of involving
-individuals through participatory methods, considering subjective
-perspectives, and acknowledging shared experiences within particular
-groups and spaces when assessing walkability.
+Abstract. The extent to which the built environment encourages people to walk in public spaces, hence the quality of being walkable or ‘walkability’ has long been associated with positive outcomes on people’s health. While various studies have developed indices to assess walkability, limited attention has been given to indices that reflect the influence of specific city characteristics on walkability. This study showcases the development of a city-specific walkability index through a participatory approach using Amsterdam as a case study. It explores the viewpoints of urban designers and policy-makers who work or reside in Amsterdam on what constitutes a walkable street and identifies the most significant walkability factors for Amsterdam. These factors are then quantified based on open-access datasets and integrated into a street-level weighted walkability index. The resulting walkability index underscores the importance of factors such as traffic and crime safety, quality of the pedestrian infrastructure, and proximity to public amenities in shaping residents’ decisions to walk in specific public spaces. Finally, this research underscores the importance of involving individuals through participatory methods, considering subjective perspectives, and acknowledging shared experiences within particular groups and spaces when assessing walkability.
The paper investigates to improve on walkability indices that
-consider city-specifics. It employs a mixed methods approach, starting
-with a literature review to identify relevant elements, followed by
-participatory sessions with urban planners and policymakers to determine
-factors for the case study of Amsterdam. In a last step, the authors
-quantify these factors and calculate walkability scores for the study
-area. The first two steps in the research design are out of scope of
-this reproducibility review, which focuses on the computational
-reproducibility of the quantitative analysis (phase C in Figure 1 of the
-paper).
-
The authors provide data sets in the repository to execute the steps
-of normalization, calculation, and visualization. A visual inspection
-using QGIS shows similar patterns of walkability scores.
-This reproducibility review was thus only able to validate part of the
-workflow. However, given that the input data is in principle openly
-available, the manual analysis steps are standard operations with
-documented parameters, the computations are deterministic, and all tools
-and software are free and open source, this review can conclude that the
-quantitative analysis part of the paper is reproducible.
+
The paper investigates to improve on walkability indices that consider city-specifics. It employs a mixed methods approach, starting with a literature review to identify relevant elements, followed by participatory sessions with urban planners and policymakers to determine factors for the case study of Amsterdam. In a last step, the authors quantify these factors and calculate walkability scores for the study area. The first two steps in the research design are out of scope of this reproducibility review, which focuses on the computational reproducibility of the quantitative analysis (phase C in Figure 1 of the paper).
+
The authors provide data sets in the repository to execute the steps of normalization, calculation, and visualization. A visual inspection using QGIS shows similar patterns of walkability scores.
+This reproducibility review was thus only able to validate part of the workflow. However, given that the input data is in principle openly available, the manual analysis steps are standard operations with documented parameters, the computations are deterministic, and all tools and software are free and open source, this review can conclude that the quantitative analysis part of the paper is reproducible.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Geoparsing, the process of linking locations within
-text to sets of geographic coordinates, plays an important role in the
-extraction and analysis of information from unstructured textual data.
-With the rapid growth in availability of user-generated data from online
-sources, there is increasing demand for reliable geoparsing methods.
-Central to many of these methods is the accurate identification of
-toponyms within text. For some applications, however, simple
-identification of toponyms is insufficient. Problems which require the
-association of a piece of text containing multiple toponyms to a
-singular location require a more nuanced approach. In this paper, we
-show that a transformer based deep learning model, is able to identify
-the subject toponym within a given text, and classify other toponyms in
-terms of their spatial relationship with the subject. We curate a
-dataset of text taken from Wikipedia pages representing 5252 locations,
-and use OpenStreetMap data to classify toponyms within the text in terms
-of their spatial relationship with the subject of each article. This
-dataset is then used to train a transformer based deep-learning model.
-On a human labelled test set, our model achieves an F1 score of 0.916
-when identifying the subject toponym, and 0.884 and 0.793 when
-identifying toponyms representing parent and child locations of the
-subject, respectively. We also consider the more complex adjacent and
-crossing relationships - with the model achieving F1 scores of 0.548 and
-0.704 in these categories, respectively.
+Abstract. Geoparsing, the process of linking locations within text to sets of geographic coordinates, plays an important role in the extraction and analysis of information from unstructured textual data. With the rapid growth in availability of user-generated data from online sources, there is increasing demand for reliable geoparsing methods. Central to many of these methods is the accurate identification of toponyms within text. For some applications, however, simple identification of toponyms is insufficient. Problems which require the association of a piece of text containing multiple toponyms to a singular location require a more nuanced approach. In this paper, we show that a transformer based deep learning model, is able to identify the subject toponym within a given text, and classify other toponyms in terms of their spatial relationship with the subject. We curate a dataset of text taken from Wikipedia pages representing 5252 locations, and use OpenStreetMap data to classify toponyms within the text in terms of their spatial relationship with the subject of each article. This dataset is then used to train a transformer based deep-learning model. On a human labelled test set, our model achieves an F1 score of 0.916 when identifying the subject toponym, and 0.884 and 0.793 when identifying toponyms representing parent and child locations of the subject, respectively. We also consider the more complex adjacent and crossing relationships - with the model achieving F1 scores of 0.548 and 0.704 in these categories, respectively.
-As indicated in the Data and Software Availability section, the authors
-shared their code, data, and trained models through an OSF (Open Science
-Framework) repository. Through 4 notebooks, we were able to train two
-baseline models and then create a new training dataset to train the
-proposed model by the authors. These models were then compared with
-human evaluation (through shared data). Evaluating the reproducibility
-of this article was not an easy task. In fact, this processing chain
-requires a lot of computational resources and time for its execution.
-Another difficulty was that the notebooks and Python library developed
-by the authors and shared via OSF contained some errors. However, the
-authors accompanied me throughout this process, providing new versions
-of the code files to correct the errors I encountered. My feeling is
-that the reproducibility review process was beneficial. The scientific
-article was almost entirely reproduced
+As indicated in the Data and Software Availability section, the authors shared their code, data, and trained models through an OSF (Open Science Framework) repository. Through 4 notebooks, we were able to train two baseline models and then create a new training dataset to train the proposed model by the authors. These models were then compared with human evaluation (through shared data). Evaluating the reproducibility of this article was not an easy task. In fact, this processing chain requires a lot of computational resources and time for its execution. Another difficulty was that the notebooks and Python library developed by the authors and shared via OSF contained some errors. However, the authors accompanied me throughout this process, providing new versions of the code files to correct the errors I encountered. My feeling is that the reproducibility review process was beneficial. The scientific article was almost entirely reproduced
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Geographic information is vital for organising
-humanitarian campaigns and helping those in need. The leading
-Humanitarian OpenStreetMap Team (HOT) organises projects to create the
-necessary geographical information and connect to the organisations that
-need to make decisions on the ground. This work provides insights into
-project management dynamics and volunteers’ interaction with user
-interfaces in Volunteered Geographic Information (VGI) in a humanitarian
-context. We do so by conducting a process analysis of 746 completed,
-fully validated, and archived projects in the HOT Tasking Manager
-(HOT-TM) over the past two years. The analysis encompasses a process
-discovery stage from the perspectives of control flow, time,
-organisation, and outcome of the mapping tasks that comprise a project.
-The findings offer valuable implications for future project planning and
-execution in similar contexts. Our process mining exploration of the
-task states found a clear path that involves mapping and validation
-operations with minor deviations. However, we did find a major
-bottleneck from the mapping to the validation phase, which could reflect
-that validation capabilities are a scarce resource. Proactive
-notification for validators, artificial intelligence adoption for task
-planning, user interface redesign, and strategies for better harnessing
-the collective intelligence of volunteers could improve the process.
-
+Abstract. Geographic information is vital for organising humanitarian campaigns and helping those in need. The leading Humanitarian OpenStreetMap Team (HOT) organises projects to create the necessary geographical information and connect to the organisations that need to make decisions on the ground. This work provides insights into project management dynamics and volunteers’ interaction with user interfaces in Volunteered Geographic Information (VGI) in a humanitarian context. We do so by conducting a process analysis of 746 completed, fully validated, and archived projects in the HOT Tasking Manager (HOT-TM) over the past two years. The analysis encompasses a process discovery stage from the perspectives of control flow, time, organisation, and outcome of the mapping tasks that comprise a project. The findings offer valuable implications for future project planning and execution in similar contexts. Our process mining exploration of the task states found a clear path that involves mapping and validation operations with minor deviations. However, we did find a major bottleneck from the mapping to the validation phase, which could reflect that validation capabilities are a scarce resource. Proactive notification for validators, artificial intelligence adoption for task planning, user interface redesign, and strategies for better harnessing the collective intelligence of volunteers could improve the process.
-The authors made their code available through a GitHub repository. The
-Readme.md file provides clear instructions for executing the entire
-code. It is worth noting that the input data is available provided that
-accounts are created with HOTOSM and Bunting Labs. The data retrieval
-process takes a long time. Therefore, the authors provided me with all
-the input data for my review. I did not encounter any difficulties in
-executing the Python notebooks. As a result, I produced intermediate
-data (in 4 CSV files). Unfortunately, I encountered some blocking errors
-when executing the R Markdown (which is the notebook responsible for
-producing tables and figures of the manuscript). Assisted by the
-authors, we discovered that the errors were caused by the content of the
-intermediate files I had generated. Strictly speaking, since the authors
-shared all their input data with me, I should not have encountered these
-errors. To continue my review, the authors sent me their version of the
-intermediate files. Thanks to them, I was able to execute the entire R
-Markdown and generate all the tables and figures.
+The authors made their code available through a GitHub repository. The Readme.md file provides clear instructions for executing the entire code. It is worth noting that the input data is available provided that accounts are created with HOTOSM and Bunting Labs. The data retrieval process takes a long time. Therefore, the authors provided me with all the input data for my review. I did not encounter any difficulties in executing the Python notebooks. As a result, I produced intermediate data (in 4 CSV files). Unfortunately, I encountered some blocking errors when executing the R Markdown (which is the notebook responsible for producing tables and figures of the manuscript). Assisted by the authors, we discovered that the errors were caused by the content of the intermediate files I had generated. Strictly speaking, since the authors shared all their input data with me, I should not have encountered these errors. To continue my review, the authors sent me their version of the intermediate files. Thanks to them, I was able to execute the entire R Markdown and generate all the tables and figures.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. The transportation dynamics within a European city,
-Vienna, are examined using a multi-graph representation of the city’s
-network. The focus is on time-optimized routing algorithms and the
-effects of altering the average waiting penalty at traffic lights. The
-impact of these modifications, whether an increase to 60, 90, or even
-150 seconds or a decrease to 10 seconds, is observed in the selection of
-transportation modes and routes for identical origin and destination
-pairs. The investigation also extends to whether routes shift towards
-secondary street networks to avoid traffic lights as the waiting penalty
-increases. Experimental variations in average waiting time for cars aim
-to uncover detailed effects on transportation mode choices, route length
-and time changes, and variations in human energy expenditure. These
-findings could provide valuable insights into the transportation network
-and its possibilities and help in urban planning and policy development.
-The results indicate a shift in transportation mode as the waiting
-penalty for cars at traffic lights increases, and in some instances,
-routes are redirected to roads of lower importance such as residential
-or service roads.
+Abstract. The transportation dynamics within a European city, Vienna, are examined using a multi-graph representation of the city’s network. The focus is on time-optimized routing algorithms and the effects of altering the average waiting penalty at traffic lights. The impact of these modifications, whether an increase to 60, 90, or even 150 seconds or a decrease to 10 seconds, is observed in the selection of transportation modes and routes for identical origin and destination pairs. The investigation also extends to whether routes shift towards secondary street networks to avoid traffic lights as the waiting penalty increases. Experimental variations in average waiting time for cars aim to uncover detailed effects on transportation mode choices, route length and time changes, and variations in human energy expenditure. These findings could provide valuable insights into the transportation network and its possibilities and help in urban planning and policy development. The results indicate a shift in transportation mode as the waiting penalty for cars at traffic lights increases, and in some instances, routes are redirected to roads of lower importance such as residential or service roads.
-The paper investigates the impact of different traffic light waiting
-times on individuals’ choice of transportation mode (e.g., bicycle, bus,
-car, etc.). The calculations of this study are based on Open Street Map
-(OSM) data analysed with Dijkstra’s algorithm. The data, code, and
-intermediate results have been made publicly available by the authors
-under permissive licenses (CC BY 4.0 and MIT). For the purposes of this
-reproducibility review, we verified the functionality of all scripts and
-the reported results in Figures 1-5 and in Table 2. The reproduced
-results were in accordance with the reported results and therefore the
-reproduction of the paper is considered successful.
+The paper investigates the impact of different traffic light waiting times on individuals’ choice of transportation mode (e.g., bicycle, bus, car, etc.). The calculations of this study are based on Open Street Map (OSM) data analysed with Dijkstra’s algorithm. The data, code, and intermediate results have been made publicly available by the authors under permissive licenses (CC BY 4.0 and MIT). For the purposes of this reproducibility review, we verified the functionality of all scripts and the reported results in Figures 1-5 and in Table 2. The reproduced results were in accordance with the reported results and therefore the reproduction of the paper is considered successful.
-Abstract: Obtained from CrossRef
+Abstract: Obtained from CrossRef
-Abstract. Updating road networks in rapidly changing urban
-landscapes is an important but difficult task, often challenged by the
-complexity and errors of manual mapping processes. Traditional methods
-that primarily use RGB satellite imagery struggle with obstacles in the
-environment and varying road structures, leading to limitations in
-global data processing. This paper presents an innovative approach that
-utilizes deep learning and multispectral satellite imagery to improve
-road network extraction and mapping. By exploring U-Net models with
-DenseNet backbones and integrating different spectral bands we apply
-semantic segmentation and extensive post-processing techniques to create
-georeferenced road networks. We trained two identical models to evaluate
-the impact of using images created from specially selected multispectral
-bands rather than conventional RGB images. Our experiments demonstrate
-the positive impact of using multispectral bands, by improving the
-results of the metrics Intersection over Union (IoU) by 6.5%, F1 by
-5.4%, and the newly proposed relative graph edit distance (relGED) and
-topology metrics by 2.2% and 2.6% respectively.
+Abstract. Updating road networks in rapidly changing urban landscapes is an important but difficult task, often challenged by the complexity and errors of manual mapping processes. Traditional methods that primarily use RGB satellite imagery struggle with obstacles in the environment and varying road structures, leading to limitations in global data processing. This paper presents an innovative approach that utilizes deep learning and multispectral satellite imagery to improve road network extraction and mapping. By exploring U-Net models with DenseNet backbones and integrating different spectral bands we apply semantic segmentation and extensive post-processing techniques to create georeferenced road networks. We trained two identical models to evaluate the impact of using images created from specially selected multispectral bands rather than conventional RGB images. Our experiments demonstrate the positive impact of using multispectral bands, by improving the results of the metrics Intersection over Union (IoU) by 6.5%, F1 by 5.4%, and the newly proposed relative graph edit distance (relGED) and topology metrics by 2.2% and 2.6% respectively.
-The paper uses semantic segmentation to extract the road network from
-RGB and multi-spectral high resolution satellite imagery and applies
-post-processing to improve the segmentation results. The initial dataset
-is called SpaceNet (challenge 3) and is openly available, but the
-authors provided a small pre-processed subset of it in order to verify
-the functionality of the code. As we were able to confirm that the used
-data and code are available and reusable, but unable to verify the
-reported results (due to the lack of available computational resources
-on the side of the reviewer), the reproduction of the paper is
-considered partially successful.
+The paper uses semantic segmentation to extract the road network from RGB and multi-spectral high resolution satellite imagery and applies post-processing to improve the segmentation results. The initial dataset is called SpaceNet (challenge 3) and is openly available, but the authors provided a small pre-processed subset of it in order to verify the functionality of the code. As we were able to confirm that the used data and code are available and reusable, but unable to verify the reported results (due to the lack of available computational resources on the side of the reviewer), the reproduction of the paper is considered partially successful.
-Authors: D Paudel, H Baja1, R van Bree, M Kallenberg, S
-Ofori-Ampofo, A Potze, P Poudel, A Saleh, W Anderson, M von Bloh, A
-Castellano, O Ennaji, R Hamed, R Laudien, D Lee, I Luna, D Masiliunas, M
-Meroni, S Mkuhlani, J Mutuku, J Richetti, A Ruane, R Sahajpal, G Shuai,
-V Sitokonstantinou, R de S. Nóia Jr, A Srivastava, R Strong, L Sweet, P
-Vojnovic, A de Wit, M Zachow, N Athanasiadis
+Authors: D Paudel, H Baja1, R van Bree, M Kallenberg, S Ofori-Ampofo, A Potze, P Poudel, A Saleh, W Anderson, M von Bloh, A Castellano, O Ennaji, R Hamed, R Laudien, D Lee, I Luna, D Masiliunas, M Meroni, S Mkuhlani, J Mutuku, J Richetti, A Ruane, R Sahajpal, G Shuai, V Sitokonstantinou, R de S. Nóia Jr, A Srivastava, R Strong, L Sweet, P Vojnovic, A de Wit, M Zachow, N Athanasiadis
-Abstract: Obtained from abstractsource
+Abstract: Obtained from abstractsource
-The CODECHECK used a smaller sample dataset, since the original data set
-is quite large and would require several days of computation on the
-available hardware. However, the produced output matches that of the
-reported output with one exception.
+The CODECHECK used a smaller sample dataset, since the original data set is quite large and would require several days of computation on the available hardware. However, the produced output matches that of the reported output with one exception.
-The CODECHECK utilized the supplied dataset, but certain steps were
-omitted as they would take several hours to compute on the available
-hardware. Despite this, the generated output aligns with the reported
-results. However, it is not clear which output should be compared in the
-Python notebooks.
+The CODECHECK utilized the supplied dataset, but certain steps were omitted as they would take several hours to compute on the available hardware. Despite this, the generated output aligns with the reported results. However, it is not clear which output should be compared in the Python notebooks.
-Codecheck performed on the .nlogo and .Rproj files to generate Figures
-2-6 of the paper. The resulting figures were not an exact match due to
-stochasticity. However, the overall patterns of the figures were similar
-to the patterns of the paper’s figures.
+Codecheck performed on the .nlogo and .Rproj files to generate Figures 2-6 of the paper. The resulting figures were not an exact match due to stochasticity. However, the overall patterns of the figures were similar to the patterns of the paper’s figures.
@@ -372,7 +349,6 @@
});
-
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+CODECHECK Certificate 2024-017
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+Light exposure regulates the human circadian system and more widely affects health, well-being, and performance. As field studies examining how light exposure impacts these aspects in the real world increase in number, so does the amount of light exposure data collected using wearable light loggers. These data are considerably more complex compared to singular stationary measurements in the laboratory, and they require special consideration not only during analysis, but already at the design stage of a study. How to estimate the required sample size of study participants remains an open topic, as evidenced by the large variability of employed sample sizes in the small but growing published literature: sample sizes between 2 and 1,887 from a recent review of the field (median 37) and approaching 105 participants in first studies using national databases. Methods Here, we present a novel procedure based on robust bootstrapping to calculate statistical power and required sample size for wearable light logging data and derived summary metrics taking into account the hierarchical data structure (mixed-effect model). Alongside this method, we publish a dataset that serves as one possible basis to perform these calculations: one week of continuous data in winter and summer, respectively, for 13 participants (collected in Dortmund, Germany, lat. 51.514° N, lon. 7.468° E). Results Applying our method on the dataset for twelve different summary metrics (luminous exposure, geometric mean and standard deviation, timing/time above/below threshold, mean/midpoint of darkest/brightest hours, intradaily variability) with a target comparison across winter and summer, reveals a large range of required sample sizes from 3 to > 50. About half of the metrics – those that focus on the bright time of day – showed sufficient power already with the smallest sample, while metrics centered around the dark time of the day and daily patterns required higher sample sizes: mean timing of light below 10 lux (5), intradaily variability (17), mean of darkest 5 hours (24) and mean timing of light above 250 lux (45). Geometric standard deviation and midpoint of the darkest 5 hours did not reach the required power within the investigated sample size. Conclusions The results clearly show the importance of a sound theoretical basis for a study using wearable light loggers, as this dictates the type of metric to be used and, thus, sample size. Our method applies to other datasets that allow comparisons of scenarios beyond seasonal differences. With an ever-growing pool of data from the emerging literature, the utility of this method will increase and provide a solid statistical basis for the selection of sample sizes.
+
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+Heart rate (HR) and heart rate variability (HRV) are two key measures with significant relevance in psychophysiological studies, and their measurement has become more convenient due to advances in wearable technology. However, photoplethysmography(PPG)-based wearables pose critical validity concerns. In this study, we validated four PPG wearables to measure inter-beat intervals: three consumer-grade devices (Kyto2935, Schone Rhythm 24, and HeartMath Inner Balance Bluetooth) and one research-grade device (Empatica EmbracePlus). All devices were worn simultaneously by 40 healthy participants who underwent conditions commonly used in laboratory research (seated rest, arithmetic task, recovery, slow-paced breathing, a neuropsychological task, posture manipulation by standing up) and encountered in ambulatory-like settings (slow walking and stationary biking), compared against a criterion electrocardiography device, the Vrije Universiteit Ambulatory Monitoring System (VU-AMS). We determined the signal quality, the linear strength through regression analysis, the bias through Bland-Altman analysis, and the measurement error through mean arctangent absolute percentage error for each condition against the criterion device. We found that the research-grade device did not outperform the consumer-grade devices in laboratory conditions. It also did not show acceptable accuracy in ambulatory-like conditions. In general, devices captured HR more accurately compared to HRV. Finally, conditions that deviated from baseline settings and involved slight to high movement, negatively impacted the agreement between PPG devices and the criterion. We conclude that PPG devices, even those advertised and designed for research purposes, may pose validity concerns for HRV measurement in conditions other than those similar to resting states.
+
+This paper describes the scale and composition of emergency demand for police services in Detroit, United States. The contribution is made in replication and extension of analyses reported elsewhere in the United States. Findings indicate that police spend a considerable proportion of time performing a social service function. Just 51% of the total deployed time responding to 911 calls is consumed by crime incidents. The remainder is spent on quality of life (16%), traffic (15%), health (7%), community (5%), and proactive (4%) duties. A small number of incidents consume a disproportionately large amount of police officer time. Emergency demand is concentrated in time and space, and can differ between types of demand. The findings further highlight the potential implications of radically reforming police forces in the United States. The data and code used here are openly available for reproduction, reuse, and scrutiny.
+
+Physical activity of nursing home residents can be assessed with tools such as questionnaires and standardized fitness tests. For residents with dementia, however, those tools can be cognitively challenging and difficult to administer. Consumer wearables could potentially aid as an affordable tool for ubiquitous assessment. In this pilot study with 16 participants, we explore how measurements with an off-the-shelf wearable relate to structured observations of physical activity. We collected both processed and raw tri-axial accelerometer data from Samsung, wrist-worn fitness trackers. To anchor those data in the free living environment, we compare the measurements with the physical activity scale of the Medlo behavioral observation scheme. We show that consumer wearables are a valid tool for long term data collection in this vulnerable patient population. Regarding the movement intensity, the data collected by fitness trackers is overall in accordance with the data collected with the observational tool. Regarding the type of movement, we conclude that the automatic activity classification on the wearables is not yet ripe for use in a mostly sedentary patient population.
+
+This report checks the code of the article ‘Using Consumer Wearables to Measure Physical Activity of Nursing Home Residents with Dementia’. The CODECHECK was successful. Two of the three figures created were visually identical to those in the paper. The third figure visually matched the figure in the code repository. This figure was equivalent in content but different in design compared to the one presented in the paper.
+
+The image source method (ISM) is often used to simulate room acoustics due to its ease of use and computational efficiency. The standard ISM is limited to simulations of room impulse responses between point sources and omnidirectional receivers. In this work, the ISM is extended using spherical harmonic directivity coefficients to include acoustic diffraction effects. These effects occur in practice when transducers are mounted on audio devices of finite spatial extent, e.g., modern smart speakers with loudspeakers and microphones. The proposed method is verified using finite element simulations of various loudspeaker and microphone configurations in a shoebox-shaped room. It is shown that the accuracy of the proposed method is related to the sizes, shapes, number, and positions of the devices inside a room. A simplified version of the proposed method, which can significantly reduce computational effort, is also presented. The proposed method and its simplified version can simulate room transfer functions more accurately than currently available image source methods and can aid the development and evaluation of speech and acoustic signal processing algorithms, including speech enhancement, acoustic scene analysis, and acoustic parameter estimation.
+
+Full reproduction. After running two Python scripts (deism_JASA_fig8.py and deism_JASA_fig9.py in the examples folder) in a public GitHub repository, figures 8 and 9 were successfully reproduced (they seem to be identical to the paper at first glance). The repository did not provide code to reproduce other plots (Figs. 7, 10 and 11). Other figures (Figs 1-6) seem to only help illustrate the main body of the paper and are therefore not applicable for reproduction with the code.
+
*Note that the total number of codechecks is less than the
-collective sum of individual codecheckers’ number of codechecks. This is
-because some codechecks involved more than one codechecker.
+
*Note that the total number of codechecks is less than the collective sum of individual codecheckers’ number of codechecks. This is because some codechecks involved more than one codechecker.
diff --git a/docs/register.json b/docs/register.json
index 58a4efc..4677ccf 100644
--- a/docs/register.json
+++ b/docs/register.json
@@ -844,9 +844,19 @@
"Repository Link": "https://github.com/codecheckers/DementiaPhysicalActivity",
"Type": "community",
"Venue": "codecheck NL",
- "Report": "https://doi.org/10.5281/zenodo.14236507",
+ "Report": "https://doi.org/10.5281/zenodo.14261193",
"Title": "Using Consumer Wearables to Measure Physical Activity of Nursing Home Residents with Dementia",
"Paper reference": "https://doi.org/10.31234/osf.io/mqg86",
"Check date": "2024-11-28"
+ },
+ {
+ "Certificate": "[2024-022](https://codecheck.org.uk/register/certs/2024-022/)",
+ "Repository Link": "https://github.com/codecheckers/DEISM",
+ "Type": "codecheck NL",
+ "Venue": "136",
+ "Report": "http://doi.org/10.5281/zenodo.14273316",
+ "Title": "Simulating room transfer functions between transducers mounted on audio devices using a modified image source method",
+ "Paper reference": "https://doi.org/10.1121/10.0023935",
+ "Check date": "2024-12-05"
}
]
diff --git a/docs/register.md b/docs/register.md
index 4f80176..ae7031f 100644
--- a/docs/register.md
+++ b/docs/register.md
@@ -3,90 +3,91 @@ title: CODECHECK Register
---
-|Certificate |Paper Title |Type |Venue |Issue |Report |Check date |
+|Certificate |Paper Title |Type |Venue |Issue |Report |Check date |
|:-------|:---------------------------------------------|:------------------|:------------------|:---|:--------------------------|:------------------|
-|[2020-001](https://codecheck.org.uk/register/certs/2020-001/)|[ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data.](https://doi.org/10.1093/gigascience/giaa026) |journal |GigaScience |NA |http://doi.org/10.5281/zenodo.3674056 |2019-02-14 |
-|[2020-002](https://codecheck.org.uk/register/certs/2020-002/)|[The principal components of natural images](https://doi.org/10.1088/0954-898X_3_1_008) |community |codecheck |[2](https://github.com/codecheckers/register/issues/2)|http://doi.org/10.5281/zenodo.3750741 |2020-04-13 |
-|[2020-003](https://codecheck.org.uk/register/certs/2020-003/)|[Neural networks and physical systems with emergent collective computational abilities](https://doi.org/10.1073/pnas.79.8.2554) |community |codecheck |[1](https://github.com/codecheckers/register/issues/1)|https://doi.org/10.5281/zenodo.3741797 |2020-04-06 |
-|[2020-004](https://codecheck.org.uk/register/certs/2020-004/)|[Neuronlike adaptive elements that can solve difficult learning control problems](https://doi.org/10.1109/TSMC.1983.6313077) |community |codecheck |[4](https://github.com/codecheckers/register/issues/4)|https://doi.org/10.5281/zenodo.3827371 |2020-05-14 |
-|[2020-005](https://codecheck.org.uk/register/certs/2020-005/)|[[Re] Connectivity reflects coding: a model of voltage-based STDP with homeostasis ](https://doi.org/10.5281/zenodo.3538217) |community |codecheck |[5](https://github.com/codecheckers/register/issues/5)|https://doi.org/10.5281/zenodo.3959175 |2020-07-23 |
-|[2020-006](https://codecheck.org.uk/register/certs/2020-006/)|[[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviours ](https://doi.org/10.5281/zenodo.1003214) |community |codecheck |[6](https://github.com/codecheckers/register/issues/6)|https://doi.org/10.5281/zenodo.3948353 |2020-07-16 |
-|[2020-008](https://codecheck.org.uk/register/certs/2020-008/)|[The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study](https://cmmid.github.io/topics/covid19/control-measures/report/uk_scenario_modelling_preprint_2020_04_01.pdf)|community |preprint |[8](https://github.com/codecheckers/register/issues/8)|http://doi.org/10.5281/zenodo.3746024 |2020-04-09 |
-|[2020-009](https://codecheck.org.uk/register/certs/2020-009/)|[Model of isolation, contact tracing, and physical distancing (Preprint)](https://cmmid.github.io/topics/covid19/reports/bbc_contact_tracing.pdf) |community |preprint |[9](https://github.com/codecheckers/register/issues/9)|http://doi.org/10.5281/zenodo.3767060 |2020-04-26 |
-|[2020-010](https://codecheck.org.uk/register/certs/2020-010/)|[Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. March 16, 2020. ](https://doi.org/10.25561/77482)|community |preprint |[14](https://github.com/codecheckers/register/issues/14)|https://doi.org/10.5281/zenodo.3865491 |2020-05-29 |
-|[2020-011](https://codecheck.org.uk/register/certs/2020-011/)|[Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe ](http://doi.org/10.1038/s41586-020-2405-7) |community |in press |[18](https://github.com/codecheckers/register/issues/18)|https://doi.org/10.5281/zenodo.3893138 |2020-06-13 |
-|[2020-012](https://codecheck.org.uk/register/certs/2020-012/)|[Report 23: State-level tracking of COVID-19 in the United States version 2 (28-05-2020) ](https://doi.org/10.25561/79231) |community |preprint |[19](https://github.com/codecheckers/register/issues/19)|https://doi.org/10.5281/zenodo.3893617 |2020-06-14 |
-|[2020-013](https://codecheck.org.uk/register/certs/2020-013/)|[Rest-activity cycles and melatonin phase angle of circadian entrainment in people without cone-mediated vision ](https://doi.org/10.1101/2020.06.02.129502)|community |preprint |[20](https://github.com/codecheckers/register/issues/20)|https://doi.org/10.5281/zenodo.3947959 |2020-07-14 |
-|[2020-014](https://codecheck.org.uk/register/certs/2020-014/)|[Patterned perturbation of inhibition can reveal the dynamical structure of neural processing ](https://doi.org/10.7554/eLife.52757) |community |codecheck |[21](https://github.com/codecheckers/register/issues/21)|https://doi.org/10.5281/zenodo.3967326 |2020-07-28 |
-|[2020-015](https://codecheck.org.uk/register/certs/2020-015/)|[A model for focal seizure onset, propagation, evolution, and progression ](https://doi.org/10.7554/eLife.50927) |community |codecheck |[22](https://github.com/codecheckers/register/issues/22)|https://doi.org/10.5281/zenodo.3978402 |2020-08-04 |
-|[2020-016](https://codecheck.org.uk/register/certs/2020-016/)|[Opening practice: supporting reproducibility and critical spatial data science ](https://doi.org/10.1007/s10109-020-00334-2) |journal |J Geogr Syst |[15](https://github.com/codecheckers/register/issues/15)|https://doi.org/10.5281/zenodo.3981253 |2020-06-02 |
-|[2020-017](https://codecheck.org.uk/register/certs/2020-017/)|[Progress in the R ecosystem for representing and handling spatial data](https://doi.org/10.1007/s10109-020-00336-0) |journal |J Geogr Syst |[24](https://github.com/codecheckers/register/issues/24)|https://doi.org/10.5281/zenodo.4003848 |2020-08-27 |
-|[2020-018](https://codecheck.org.uk/register/certs/2020-018/)|[Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling](https://doi.org/10.5194/agile-giss-1-6-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/ZTC7M |2020-07-13 |
-|[2020-019](https://codecheck.org.uk/register/certs/2020-019/)|[What to do in the Meantime: A Service Coverage Analysis for Parked Autonomous Vehicles](https://doi.org/10.5194/agile-giss-1-7-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/5SVMT |2020-07-13 |
-|[2020-020](https://codecheck.org.uk/register/certs/2020-020/)|[Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles](https://doi.org/10.5194/agile-giss-1-21-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/7TWR2 |2020-07-13 |
-|[2020-021](https://codecheck.org.uk/register/certs/2020-021/)|[Comparing supervised learning algorithms for Spatial Nominal Entity recognition](https://doi.org/10.5194/agile-giss-1-15-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/SUWPJ |2020-07-13 |
-|[2020-022](https://codecheck.org.uk/register/certs/2020-022/)|[Extracting interrogative intents and concepts from geo-analytic questions.](https://doi.org/10.5194/agile-giss-1-23-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/7XRQG |2020-07-13 |
-|[2020-023](https://codecheck.org.uk/register/certs/2020-023/)|[Tracking Hurricane Dorian in GDELT and Twitter](https://doi.org/10.5194/agile-giss-1-19-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/XS5YR |2020-07-13 |
-|[2020-024](https://codecheck.org.uk/register/certs/2020-024/)|[Driftage: a multi-agent system framework for concept drift detection ](https://doi.org/10.1093/gigascience/giab030) |journal |GigaScience |[31](https://github.com/codecheckers/register/issues/31)|https://doi.org/10.5281/zenodo.4964880 |2020-12-07 |
-|[2020-025](https://codecheck.org.uk/register/certs/2020-025/)|[The application of Local Indicators for Categorical Data (LICD) to explore spatial dependence in archaeological spaces](https://doi.org/10.1016/j.jas.2020.105306)|journal |J Archaeol Sci |[29](https://github.com/codecheckers/register/issues/29)|https://doi.org/10.5281/zenodo.4279275 |2020-11-19 |
-|[2021-001](https://codecheck.org.uk/register/certs/2021-001/)|[Causality indices for bivariate time series data: a comparative review of performance](https://arxiv.org/abs/2104.00718) |community |preprint |[35](https://github.com/codecheckers/register/issues/35)|https://doi.org/10.5281/zenodo.4720843 |2021-04-27 |
-|[2021-002](https://codecheck.org.uk/register/certs/2021-002/)|[Building Change Detection of Airborne Laser Scanning and Dense Image Matching Point Clouds using Height and Class Information](https://doi.org/10.5194/agile-giss-2-10-2021)|conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/rsf4m |2021-06-10 |
-|[2021-003](https://codecheck.org.uk/register/certs/2021-003/)|[Investigating drivers’ geospatial abilities in unfamiliar environments](https://doi.org/10.5194/agile-giss-2-3-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/dx92a |2021-06-10 |
-|[2021-004](https://codecheck.org.uk/register/certs/2021-004/)|[Extraction of linear structures from digital terrain models using deep learning](https://doi.org/10.5194/agile-giss-2-11-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/2sc7g |2021-06-10 |
-|[2021-005](https://codecheck.org.uk/register/certs/2021-005/)|[A Comparative Study of Typing and Speech For Map Metadata Creation](https://doi.org/10.5194/agile-giss-2-7-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/7fqtm |2021-06-10 |
-|[2021-006](https://codecheck.org.uk/register/certs/2021-006/)|[A Socially Aware Huff Model for Destination Choice in Nature-based Tourism](https://doi.org/10.5194/agile-giss-2-14-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/OSF.IO/4CPM3 |2021-06-10 |
-|[2021-007](https://codecheck.org.uk/register/certs/2021-007/)|[Automated Extraction of Labels from Large-Scale Historical Maps](https://doi.org/10.5194/agile-giss-2-12-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/anv9r |2021-06-10 |
-|[2021-008](https://codecheck.org.uk/register/certs/2021-008/)|[Flood Impact Assessment on Road Network and Healthcare Access at the example of Jakarta, Indonesia](https://doi.org/10.5194/agile-giss-2-4-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/g4dcq |2021-06-10 |
-|[2021-009](https://codecheck.org.uk/register/certs/2021-009/)|[H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?](https://doi.org/10.5194/agile-giss-2-2-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/rdnyu |2021-06-10 |
-|[2021-010](https://codecheck.org.uk/register/certs/2021-010/)|[An Approach to Assess the Effect of Currentness of Spatial Data on Routing Quality](https://doi.org/10.5194/agile-giss-2-13-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/bdu28 |2021-06-10 |
-|[2022-001](https://codecheck.org.uk/register/certs/2022-001/)|[Geographically Weighted Regressions for prioritizing educational planning, policies, and interventions ](http://www.iiep.unesco.org/en/publication/geographically-weighted-regressions-prioritizing-educational-planning-policies-and)|community |codecheck |[40](https://github.com/codecheckers/register/issues/40)|https://doi.org/10.5281/zenodo.6040066 |2022-01-19 |
-|[2022-002](https://codecheck.org.uk/register/certs/2022-002/)|[Understanding the Imperfection of 3D point Cloud and Semantic Segmentation algorithms for 3D Models of Indoor Environment](https://doi.org/10.5194/agile-giss-3-2-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/z7p8k |2022-07-09 |
-|[2022-003](https://codecheck.org.uk/register/certs/2022-003/)|[Optimizing Electric Vehicle Charging Schedules Based on Probabilistic Forecast of Individual Mobility](https://doi.org/10.5194/agile-giss-3-3-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/JDTN3 |2022-07-09 |
-|[2022-004](https://codecheck.org.uk/register/certs/2022-004/)|[What are intersections for pedestrian users?](https://doi.org/10.5194/agile-giss-3-4-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/XPG6Y |2022-07-09 |
-|[2022-005](https://codecheck.org.uk/register/certs/2022-005/)|[Spatial Disaggregation of Population Subgroups Leveraging Self-Trained Multi-Output Gradient Boosted Regression Trees](https://doi.org/10.5194/agile-giss-3-5-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/cdfah |2022-07-09 |
-|[2022-006](https://codecheck.org.uk/register/certs/2022-006/)|[Exploratory Analysis and Feature Selection for the Prediction of Nitrogen Dioxide](https://doi.org/10.5194/agile-giss-3-6-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/W7VPH |2022-07-09 |
-|[2022-007](https://codecheck.org.uk/register/certs/2022-007/)|[Geoparsing: Solved or Biased? An Evaluation of Geographic Biases in Geoparsing](https://doi.org/10.5194/agile-giss-3-9-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/3DSMV |2022-07-09 |
-|[2022-008](https://codecheck.org.uk/register/certs/2022-008/)|[Benchmarking Invasive Alien Species Image Recognition Models for a Citizen Science Based Spatial Distribution Monitoring](https://doi.org/10.5194/agile-giss-3-10-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/K78EB |2022-07-09 |
-|[2022-009](https://codecheck.org.uk/register/certs/2022-009/)|["Landmark Route": A Comparison to the Shortest Route](https://doi.org/10.5194/agile-giss-3-12-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/94vnx |2022-07-09 |
-|[2022-010](https://codecheck.org.uk/register/certs/2022-010/)|[Experimental evaluation of using BLE beacon for outdoor positioning in GPS-denied environment](https://doi.org/10.5194/agile-giss-3-13-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/8b7mr |2022-07-09 |
-|[2022-011](https://codecheck.org.uk/register/certs/2022-011/)|[Understanding COVID-19 Effects on Mobility: A Community-Engaged Approach](https://doi.org/10.5194/agile-giss-3-14-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/kf8sr |2022-07-09 |
-|[2022-012](https://codecheck.org.uk/register/certs/2022-012/)|[The Impact of Built Environment on Bike Commuting: Utilising Strava Bike Data and Geographically Weighted Models](https://doi.org/10.5194/agile-giss-3-15-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/r6psq |2022-07-09 |
-|[2022-013](https://codecheck.org.uk/register/certs/2022-013/)|[GeoXTag: Relative Spatial Information Extraction and Tagging of Unstructured Text](https://doi.org/10.5194/agile-giss-3-16-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/3g9s8 |2022-07-09 |
-|[2022-014](https://codecheck.org.uk/register/certs/2022-014/)|[A method to produce metadata describing and assessing the quality of spatial landmark datasets in mountain area](https://doi.org/10.5194/agile-giss-3-17-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/6s2gp |2022-07-09 |
-|[2022-015](https://codecheck.org.uk/register/certs/2022-015/)|[Unlocking social network analysis methods for studying human mobility](https://doi.org/10.5194/agile-giss-3-19-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/mvqcw |2022-07-09 |
-|[2022-016](https://codecheck.org.uk/register/certs/2022-016/)|[A machine learning based approach for predicting usage efficiency of shared e-scooters using vehicle availability data](https://doi.org/10.5194/agile-giss-3-20-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/DJFC2 |2022-07-09 |
-|[2022-017](https://codecheck.org.uk/register/certs/2022-017/)|[Traffic Regulation Recognition using Crowd-Sensed GPS and Map Data: a Hybrid Approach](https://doi.org/10.5194/agile-giss-3-22-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/wncsm |2022-07-09 |
-|[2022-018](https://codecheck.org.uk/register/certs/2022-018/)|[svaRetro and svaNUMT: Modular packages for annotation of retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data](https://doi.org/10.46471/gigabyte.70)|journal |GigaByte |[44](https://github.com/codecheckers/register/issues/44)|https://doi.org/10.5281/zenodo.7084333 |2022-09-27 |
-|[2023-001](https://codecheck.org.uk/register/certs/2023-001/)|[Urban Sound Mapping for Wayfinding - A theoretical Approach and an empirical Study](https://doi.org/10.5194/agile-giss-4-9-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/c7vx3 |2023-06-13 |
-|[2023-002](https://codecheck.org.uk/register/certs/2023-002/)|[Evaluating and Comparing Airspace Structure Visualisation and Perception on Digital Aeronautical Chart](https://doi.org/10.5194/agile-giss-4-12-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/rbgvk |2023-06-13 |
-|[2023-003](https://codecheck.org.uk/register/certs/2023-003/)|[Exploring MapSwipe as a Crowdsourcing Tool for (Rapid) Damage Assessment: The Case of the 2021 Haiti Earthquake](https://doi.org/10.5194/agile-giss-4-5-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/m5bhk |2023-06-13 |
-|[2023-004](https://codecheck.org.uk/register/certs/2023-004/)|[Does spatial thinking ability relate to performance when using web-mapping services? A survey with digital natives](https://doi.org/10.5194/agile-giss-4-13-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/2em7v |2023-06-13 |
-|[2023-005](https://codecheck.org.uk/register/certs/2023-005/)|[Advancing Forest Monitoring and Assessment Through Immersive Virtual Reality](https://doi.org/10.5194/agile-giss-4-15-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/27wzp |2023-06-13 |
-|[2023-006](https://codecheck.org.uk/register/certs/2023-006/)|[Semantic complexity of geographic questions - A comparison in terms of conceptual transformations of answers](https://doi.org/10.5194/agile-giss-4-10-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/OSF.IO/D2SHF |2023-06-13 |
-|[2023-007](https://codecheck.org.uk/register/certs/2023-007/)|[Extreme heat alerts and impacts across Mozambique 2016 - 2022: gathering evidence from media articles](https://doi.org/10.5194/agile-giss-4-11-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/eu8kw |2023-06-13 |
-|[2023-008](https://codecheck.org.uk/register/certs/2023-008/)|[Is it safe to be attractive? Disentangling the influence of streetscape features on the perceived safety and attractiveness of city streets](https://doi.org/10.5194/agile-giss-4-8-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/aqgxr |2023-06-13 |
-|[2023-009](https://codecheck.org.uk/register/certs/2023-009/)|[Analysis of cycling network evolution in OpenStreetMap through a data quality prism](https://doi.org/10.5194/agile-giss-4-3-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/9kp7u |2023-06-13 |
-|[2023-010](https://codecheck.org.uk/register/certs/2023-010/)|[Indoor localisation and location tracking in indoor facilities based on LiDAR point clouds and images of the ceilings](https://doi.org/10.5194/agile-giss-4-4-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/8t3bh |2023-06-13 |
-|[2023-011](https://codecheck.org.uk/register/certs/2023-011/)|[Does enforcing glenohumeral joint stability matter? A new rapid muscle redundancy solver highlights the importance of non-superficial shoulder muscles ](https://doi.org/10.1101/2023.07.11.548542)|community |preprint |[56](https://github.com/codecheckers/register/issues/56)|https://doi.org/10.5281/zenodo.8359199 |2023-09-18 |
-|[2023-012](https://codecheck.org.uk/register/certs/2023-012/)|[An inventory of human light exposure related behaviour ](https://doi.org/10.1038/s41598-023-48241-y) |community |preprint |[59](https://github.com/codecheckers/register/issues/59)|https://doi.org/10.5281/zenodo.10213244 |2023-11-26 |
-|[2024-001](https://codecheck.org.uk/register/certs/2024-001/)|[Regulation of pupil size in natural vision across the human lifespan ](https://doi.org/10.1098/rsos.191613) |community |preprint |[60](https://github.com/codecheckers/register/issues/60)|https://doi.org/10.5281/zenodo.10823246 |2024-03-15 |
-|[2024-002](https://codecheck.org.uk/register/certs/2024-002/)|[Modeling spatiotemporal domestic wastewater variability: Implications for measuring treatment efficiency](https://doi.org/10.1016/j.jenvman.2023.119680) |community |codecheck NL |[61](https://github.com/codecheckers/register/issues/61)|https://doi.org/10.5281/zenodo.FIXME |2020-05-21 |
-|[2024-003](https://codecheck.org.uk/register/certs/2024-003/)|[State-Dependent Dynamic Tube MPC: A Novel Tube MPC Method with a Fuzzy Model of Disturbances ](https://arxiv.org/pdf/2310.19997) |community |codecheck NL |[66](https://github.com/codecheckers/register/issues/66)|https://doi.org/10.5281/zenodo.11403956 |2024-05-30 |
-|[2024-004](https://codecheck.org.uk/register/certs/2024-004/)|[Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint ](https://doi.org/10.31222/osf.io/a8rmu) |community |AUMC |[96](https://github.com/codecheckers/register/issues/96)|https://doi.org/10.5281/zenodo.13364677 |2024-08-01 |
-|[2024-006](https://codecheck.org.uk/register/certs/2024-006/)|[Random Data Distribution for Efficient Parallel Point Cloud Processing](https://doi.org/10.5194/agile-giss-5-15-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/OSF.IO/YMC3T |2024-05-23 |
-|[2024-007](https://codecheck.org.uk/register/certs/2024-007/)|[FreeMapRetrieve: Freehand Gestures for Retrieve Operations in Large-Screen Map Environments](https://doi.org/10.5194/agile-giss-5-7-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/OSF.IO/GVPD9 |2024-05-23 |
-|[2024-008](https://codecheck.org.uk/register/certs/2024-008/)|[Knowledge-Based Identification of Urban Green Spaces: Allotments](https://doi.org/10.5194/agile-giss-5-8-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/OSF.IO/3NBJW |2024-05-23 |
-|[2024-009](https://codecheck.org.uk/register/certs/2024-009/)|[Developing a city-specific walkability index through a participatory approach](https://doi.org/10.5194/agile-giss-5-2-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/CSB7R |2024-05-23 |
-|[2024-010](https://codecheck.org.uk/register/certs/2024-010/)|[Enhancing toponym identification: Leveraging Topo-BERT and open-source data to differentiate between toponyms and extract spatial relationships](https://doi.org/10.5194/agile-giss-5-12-2024)|conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/NBK57 |2024-05-27 |
-|[2024-011](https://codecheck.org.uk/register/certs/2024-011/)|[Process Analysis in Humanitarian Voluntary Geographic Information: the case of the HOT Tasking Manager](https://doi.org/10.5194/agile-giss-5-5-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/FMGB4 |2024-05-27 |
-|[2024-012](https://codecheck.org.uk/register/certs/2024-012/)|[The Impact of Traffic Lights on Modal Split and Route Choice: A use-case in Vienna](https://doi.org/10.5194/agile-giss-5-4-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/W42AD |2024-05-30 |
-|[2024-013](https://codecheck.org.uk/register/certs/2024-013/)|[Road Network Mapping from Multispectral Satellite Imagery: Leveraging Deep Learning and Spectral Bands](https://doi.org/10.5194/agile-giss-5-6-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/TXGZV |2024-05-31 |
-|[2024-005](https://codecheck.org.uk/register/certs/2024-005/)|[Sample size estimation for task-related functional MRI studies using Bayesian updating.](https://doi.org/10.31234/osf.io/cz32t) |community |codecheck |[100](https://github.com/codecheckers/register/issues/100)|https://doi.org/10.5281/zenodo.13945051 |2024-10-15 |
-|[2024-014](https://codecheck.org.uk/register/certs/2024-014/)|[CY-Bench : A comprehensive benchmark dataset for sub-national crop yield forecasting](https://www.overleaf.com/read/znytpcwfjrrf#a4ca1f) |community |codecheck NL |[124](https://github.com/codecheckers/register/issues/124)|https://doi.org/10.17605/OSF.IO/spxt5 |2024-09-26 |
-|[2024-015](https://codecheck.org.uk/register/certs/2024-015/)|[Landscape Character Assessment - Nigeria](https://doi.org/10.17605/OSF.IO/E2K73) |community |codecheck NL |[124](https://github.com/codecheckers/register/issues/124)|https://doi.org/10.17605/OSF.IO/mwbuq |2024-09-26 |
-|[2024-016](https://codecheck.org.uk/register/certs/2024-016/)|[Integrating agent-based disease, mobility, and wastewater models: Dealing with differences in spatiotemporal resolutions](https://doi.org/10.5281/zenodo.13734819)|community |codecheck NL |[124](https://github.com/codecheckers/register/issues/124)|https://doi.org/10.17605/OSF.IO/6NGYC |2024-09-26 |
-|[2024-017](https://codecheck.org.uk/register/certs/2024-017/)|[Determination of a diffusion coefficient function for long rooms using a least square optimization approach ](https://pure.tue.nl/ws/portalfiles/portal/339520759/IN_2024_3491.pdf)|community |codecheck NL |[133](https://github.com/codecheckers/register/issues/133)|https://doi.org/10.5281/zenodo.14211707 |2024-11-22 |
-|[2024-018](https://codecheck.org.uk/register/certs/2024-018/)|[Power analysis for personal light exposure measurements and interventions ](https://doi.org/10.21203/rs.3.rs-3771881/v1) |community |codecheck NL |[132](https://github.com/codecheckers/register/issues/132)|https://doi.org/10.5281/zenodo.14235113 |2024-11-28 |
-|[2024-019](https://codecheck.org.uk/register/certs/2024-019/)|[Quality in Question: Assessing the accuracy of four heart rate wearables and the implications for psychophysiological research. ](https://doi.org/10.31219/osf.io/wkzsn)|community |codecheck NL |[134](https://github.com/codecheckers/register/issues/134)|https://doi.org/10.5281/zenodo.14279041 |2024-12-04 |
-|[2024-020](https://codecheck.org.uk/register/certs/2024-020/)|[Describing the scale and composition of calls for police service: a replication and extension using open data ](https://doi.org/10.1080/15614263.2022.2102494)|community |codecheck NL |[135](https://github.com/codecheckers/register/issues/135)|https://doi.org/10.5281/zenodo.14278912 |2024-11-28 |
-|[2024-021](https://codecheck.org.uk/register/certs/2024-021/)|[Using Consumer Wearables to Measure Physical Activity of Nursing Home Residents with Dementia ](https://doi.org/10.31234/osf.io/mqg86) |community |codecheck NL |[136](https://github.com/codecheckers/register/issues/136)|https://doi.org/10.5281/zenodo.14236507 |2024-11-28 |
+|[2020-001](https://codecheck.org.uk/register/certs/2020-001/)|[ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data.](https://doi.org/10.1093/gigascience/giaa026) |journal |GigaScience |NA |http://doi.org/10.5281/zenodo.3674056 |2019-02-14 |
+|[2020-002](https://codecheck.org.uk/register/certs/2020-002/)|[The principal components of natural images](https://doi.org/10.1088/0954-898X_3_1_008) |community |codecheck |[2](https://github.com/codecheckers/register/issues/2)|http://doi.org/10.5281/zenodo.3750741 |2020-04-13 |
+|[2020-003](https://codecheck.org.uk/register/certs/2020-003/)|[Neural networks and physical systems with emergent collective computational abilities](https://doi.org/10.1073/pnas.79.8.2554) |community |codecheck |[1](https://github.com/codecheckers/register/issues/1)|https://doi.org/10.5281/zenodo.3741797 |2020-04-06 |
+|[2020-004](https://codecheck.org.uk/register/certs/2020-004/)|[Neuronlike adaptive elements that can solve difficult learning control problems](https://doi.org/10.1109/TSMC.1983.6313077) |community |codecheck |[4](https://github.com/codecheckers/register/issues/4)|https://doi.org/10.5281/zenodo.3827371 |2020-05-14 |
+|[2020-005](https://codecheck.org.uk/register/certs/2020-005/)|[[Re] Connectivity reflects coding: a model of voltage-based STDP with homeostasis ](https://doi.org/10.5281/zenodo.3538217) |community |codecheck |[5](https://github.com/codecheckers/register/issues/5)|https://doi.org/10.5281/zenodo.3959175 |2020-07-23 |
+|[2020-006](https://codecheck.org.uk/register/certs/2020-006/)|[[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviours ](https://doi.org/10.5281/zenodo.1003214) |community |codecheck |[6](https://github.com/codecheckers/register/issues/6)|https://doi.org/10.5281/zenodo.3948353 |2020-07-16 |
+|[2020-008](https://codecheck.org.uk/register/certs/2020-008/)|[The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study](https://cmmid.github.io/topics/covid19/control-measures/report/uk_scenario_modelling_preprint_2020_04_01.pdf)|community |preprint |[8](https://github.com/codecheckers/register/issues/8)|http://doi.org/10.5281/zenodo.3746024 |2020-04-09 |
+|[2020-009](https://codecheck.org.uk/register/certs/2020-009/)|[Model of isolation, contact tracing, and physical distancing (Preprint)](https://cmmid.github.io/topics/covid19/reports/bbc_contact_tracing.pdf) |community |preprint |[9](https://github.com/codecheckers/register/issues/9)|http://doi.org/10.5281/zenodo.3767060 |2020-04-26 |
+|[2020-010](https://codecheck.org.uk/register/certs/2020-010/)|[Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. March 16, 2020. ](https://doi.org/10.25561/77482)|community |preprint |[14](https://github.com/codecheckers/register/issues/14)|https://doi.org/10.5281/zenodo.3865491 |2020-05-29 |
+|[2020-011](https://codecheck.org.uk/register/certs/2020-011/)|[Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe ](http://doi.org/10.1038/s41586-020-2405-7) |community |in press |[18](https://github.com/codecheckers/register/issues/18)|https://doi.org/10.5281/zenodo.3893138 |2020-06-13 |
+|[2020-012](https://codecheck.org.uk/register/certs/2020-012/)|[Report 23: State-level tracking of COVID-19 in the United States version 2 (28-05-2020) ](https://doi.org/10.25561/79231) |community |preprint |[19](https://github.com/codecheckers/register/issues/19)|https://doi.org/10.5281/zenodo.3893617 |2020-06-14 |
+|[2020-013](https://codecheck.org.uk/register/certs/2020-013/)|[Rest-activity cycles and melatonin phase angle of circadian entrainment in people without cone-mediated vision ](https://doi.org/10.1101/2020.06.02.129502)|community |preprint |[20](https://github.com/codecheckers/register/issues/20)|https://doi.org/10.5281/zenodo.3947959 |2020-07-14 |
+|[2020-014](https://codecheck.org.uk/register/certs/2020-014/)|[Patterned perturbation of inhibition can reveal the dynamical structure of neural processing ](https://doi.org/10.7554/eLife.52757) |community |codecheck |[21](https://github.com/codecheckers/register/issues/21)|https://doi.org/10.5281/zenodo.3967326 |2020-07-28 |
+|[2020-015](https://codecheck.org.uk/register/certs/2020-015/)|[A model for focal seizure onset, propagation, evolution, and progression ](https://doi.org/10.7554/eLife.50927) |community |codecheck |[22](https://github.com/codecheckers/register/issues/22)|https://doi.org/10.5281/zenodo.3978402 |2020-08-04 |
+|[2020-016](https://codecheck.org.uk/register/certs/2020-016/)|[Opening practice: supporting reproducibility and critical spatial data science ](https://doi.org/10.1007/s10109-020-00334-2) |journal |J Geogr Syst |[15](https://github.com/codecheckers/register/issues/15)|https://doi.org/10.5281/zenodo.3981253 |2020-06-02 |
+|[2020-017](https://codecheck.org.uk/register/certs/2020-017/)|[Progress in the R ecosystem for representing and handling spatial data](https://doi.org/10.1007/s10109-020-00336-0) |journal |J Geogr Syst |[24](https://github.com/codecheckers/register/issues/24)|https://doi.org/10.5281/zenodo.4003848 |2020-08-27 |
+|[2020-018](https://codecheck.org.uk/register/certs/2020-018/)|[Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling](https://doi.org/10.5194/agile-giss-1-6-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/ZTC7M |2020-07-13 |
+|[2020-019](https://codecheck.org.uk/register/certs/2020-019/)|[What to do in the Meantime: A Service Coverage Analysis for Parked Autonomous Vehicles](https://doi.org/10.5194/agile-giss-1-7-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/5SVMT |2020-07-13 |
+|[2020-020](https://codecheck.org.uk/register/certs/2020-020/)|[Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles](https://doi.org/10.5194/agile-giss-1-21-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/7TWR2 |2020-07-13 |
+|[2020-021](https://codecheck.org.uk/register/certs/2020-021/)|[Comparing supervised learning algorithms for Spatial Nominal Entity recognition](https://doi.org/10.5194/agile-giss-1-15-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/SUWPJ |2020-07-13 |
+|[2020-022](https://codecheck.org.uk/register/certs/2020-022/)|[Extracting interrogative intents and concepts from geo-analytic questions.](https://doi.org/10.5194/agile-giss-1-23-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/7XRQG |2020-07-13 |
+|[2020-023](https://codecheck.org.uk/register/certs/2020-023/)|[Tracking Hurricane Dorian in GDELT and Twitter](https://doi.org/10.5194/agile-giss-1-19-2020) |conference |AGILEGIS |[25](https://github.com/codecheckers/register/issues/25)|https://doi.org/10.17605/OSF.IO/XS5YR |2020-07-13 |
+|[2020-024](https://codecheck.org.uk/register/certs/2020-024/)|[Driftage: a multi-agent system framework for concept drift detection ](https://doi.org/10.1093/gigascience/giab030) |journal |GigaScience |[31](https://github.com/codecheckers/register/issues/31)|https://doi.org/10.5281/zenodo.4964880 |2020-12-07 |
+|[2020-025](https://codecheck.org.uk/register/certs/2020-025/)|[The application of Local Indicators for Categorical Data (LICD) to explore spatial dependence in archaeological spaces](https://doi.org/10.1016/j.jas.2020.105306)|journal |J Archaeol Sci |[29](https://github.com/codecheckers/register/issues/29)|https://doi.org/10.5281/zenodo.4279275 |2020-11-19 |
+|[2021-001](https://codecheck.org.uk/register/certs/2021-001/)|[Causality indices for bivariate time series data: a comparative review of performance](https://arxiv.org/abs/2104.00718) |community |preprint |[35](https://github.com/codecheckers/register/issues/35)|https://doi.org/10.5281/zenodo.4720843 |2021-04-27 |
+|[2021-002](https://codecheck.org.uk/register/certs/2021-002/)|[Building Change Detection of Airborne Laser Scanning and Dense Image Matching Point Clouds using Height and Class Information](https://doi.org/10.5194/agile-giss-2-10-2021)|conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/rsf4m |2021-06-10 |
+|[2021-003](https://codecheck.org.uk/register/certs/2021-003/)|[Investigating drivers’ geospatial abilities in unfamiliar environments](https://doi.org/10.5194/agile-giss-2-3-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/dx92a |2021-06-10 |
+|[2021-004](https://codecheck.org.uk/register/certs/2021-004/)|[Extraction of linear structures from digital terrain models using deep learning](https://doi.org/10.5194/agile-giss-2-11-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/2sc7g |2021-06-10 |
+|[2021-005](https://codecheck.org.uk/register/certs/2021-005/)|[A Comparative Study of Typing and Speech For Map Metadata Creation](https://doi.org/10.5194/agile-giss-2-7-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/7fqtm |2021-06-10 |
+|[2021-006](https://codecheck.org.uk/register/certs/2021-006/)|[A Socially Aware Huff Model for Destination Choice in Nature-based Tourism](https://doi.org/10.5194/agile-giss-2-14-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/OSF.IO/4CPM3 |2021-06-10 |
+|[2021-007](https://codecheck.org.uk/register/certs/2021-007/)|[Automated Extraction of Labels from Large-Scale Historical Maps](https://doi.org/10.5194/agile-giss-2-12-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/anv9r |2021-06-10 |
+|[2021-008](https://codecheck.org.uk/register/certs/2021-008/)|[Flood Impact Assessment on Road Network and Healthcare Access at the example of Jakarta, Indonesia](https://doi.org/10.5194/agile-giss-2-4-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/g4dcq |2021-06-10 |
+|[2021-009](https://codecheck.org.uk/register/certs/2021-009/)|[H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?](https://doi.org/10.5194/agile-giss-2-2-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/rdnyu |2021-06-10 |
+|[2021-010](https://codecheck.org.uk/register/certs/2021-010/)|[An Approach to Assess the Effect of Currentness of Spatial Data on Routing Quality](https://doi.org/10.5194/agile-giss-2-13-2021) |conference |AGILEGIS |[38](https://github.com/codecheckers/register/issues/38)|https://doi.org/10.17605/osf.io/bdu28 |2021-06-10 |
+|[2022-001](https://codecheck.org.uk/register/certs/2022-001/)|[Geographically Weighted Regressions for prioritizing educational planning, policies, and interventions ](http://www.iiep.unesco.org/en/publication/geographically-weighted-regressions-prioritizing-educational-planning-policies-and)|community |codecheck |[40](https://github.com/codecheckers/register/issues/40)|https://doi.org/10.5281/zenodo.6040066 |2022-01-19 |
+|[2022-002](https://codecheck.org.uk/register/certs/2022-002/)|[Understanding the Imperfection of 3D point Cloud and Semantic Segmentation algorithms for 3D Models of Indoor Environment](https://doi.org/10.5194/agile-giss-3-2-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/z7p8k |2022-07-09 |
+|[2022-003](https://codecheck.org.uk/register/certs/2022-003/)|[Optimizing Electric Vehicle Charging Schedules Based on Probabilistic Forecast of Individual Mobility](https://doi.org/10.5194/agile-giss-3-3-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/JDTN3 |2022-07-09 |
+|[2022-004](https://codecheck.org.uk/register/certs/2022-004/)|[What are intersections for pedestrian users?](https://doi.org/10.5194/agile-giss-3-4-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/XPG6Y |2022-07-09 |
+|[2022-005](https://codecheck.org.uk/register/certs/2022-005/)|[Spatial Disaggregation of Population Subgroups Leveraging Self-Trained Multi-Output Gradient Boosted Regression Trees](https://doi.org/10.5194/agile-giss-3-5-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/cdfah |2022-07-09 |
+|[2022-006](https://codecheck.org.uk/register/certs/2022-006/)|[Exploratory Analysis and Feature Selection for the Prediction of Nitrogen Dioxide](https://doi.org/10.5194/agile-giss-3-6-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/W7VPH |2022-07-09 |
+|[2022-007](https://codecheck.org.uk/register/certs/2022-007/)|[Geoparsing: Solved or Biased? An Evaluation of Geographic Biases in Geoparsing](https://doi.org/10.5194/agile-giss-3-9-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/3DSMV |2022-07-09 |
+|[2022-008](https://codecheck.org.uk/register/certs/2022-008/)|[Benchmarking Invasive Alien Species Image Recognition Models for a Citizen Science Based Spatial Distribution Monitoring](https://doi.org/10.5194/agile-giss-3-10-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/K78EB |2022-07-09 |
+|[2022-009](https://codecheck.org.uk/register/certs/2022-009/)|["Landmark Route": A Comparison to the Shortest Route](https://doi.org/10.5194/agile-giss-3-12-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/94vnx |2022-07-09 |
+|[2022-010](https://codecheck.org.uk/register/certs/2022-010/)|[Experimental evaluation of using BLE beacon for outdoor positioning in GPS-denied environment](https://doi.org/10.5194/agile-giss-3-13-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/8b7mr |2022-07-09 |
+|[2022-011](https://codecheck.org.uk/register/certs/2022-011/)|[Understanding COVID-19 Effects on Mobility: A Community-Engaged Approach](https://doi.org/10.5194/agile-giss-3-14-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/kf8sr |2022-07-09 |
+|[2022-012](https://codecheck.org.uk/register/certs/2022-012/)|[The Impact of Built Environment on Bike Commuting: Utilising Strava Bike Data and Geographically Weighted Models](https://doi.org/10.5194/agile-giss-3-15-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/r6psq |2022-07-09 |
+|[2022-013](https://codecheck.org.uk/register/certs/2022-013/)|[GeoXTag: Relative Spatial Information Extraction and Tagging of Unstructured Text](https://doi.org/10.5194/agile-giss-3-16-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/3g9s8 |2022-07-09 |
+|[2022-014](https://codecheck.org.uk/register/certs/2022-014/)|[A method to produce metadata describing and assessing the quality of spatial landmark datasets in mountain area](https://doi.org/10.5194/agile-giss-3-17-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/6s2gp |2022-07-09 |
+|[2022-015](https://codecheck.org.uk/register/certs/2022-015/)|[Unlocking social network analysis methods for studying human mobility](https://doi.org/10.5194/agile-giss-3-19-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/mvqcw |2022-07-09 |
+|[2022-016](https://codecheck.org.uk/register/certs/2022-016/)|[A machine learning based approach for predicting usage efficiency of shared e-scooters using vehicle availability data](https://doi.org/10.5194/agile-giss-3-20-2022)|conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/OSF.IO/DJFC2 |2022-07-09 |
+|[2022-017](https://codecheck.org.uk/register/certs/2022-017/)|[Traffic Regulation Recognition using Crowd-Sensed GPS and Map Data: a Hybrid Approach](https://doi.org/10.5194/agile-giss-3-22-2022) |conference |AGILEGIS |[41](https://github.com/codecheckers/register/issues/41)|https://doi.org/10.17605/osf.io/wncsm |2022-07-09 |
+|[2022-018](https://codecheck.org.uk/register/certs/2022-018/)|[svaRetro and svaNUMT: Modular packages for annotation of retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data](https://doi.org/10.46471/gigabyte.70)|journal |GigaByte |[44](https://github.com/codecheckers/register/issues/44)|https://doi.org/10.5281/zenodo.7084333 |2022-09-27 |
+|[2023-001](https://codecheck.org.uk/register/certs/2023-001/)|[Urban Sound Mapping for Wayfinding - A theoretical Approach and an empirical Study](https://doi.org/10.5194/agile-giss-4-9-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/c7vx3 |2023-06-13 |
+|[2023-002](https://codecheck.org.uk/register/certs/2023-002/)|[Evaluating and Comparing Airspace Structure Visualisation and Perception on Digital Aeronautical Chart](https://doi.org/10.5194/agile-giss-4-12-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/rbgvk |2023-06-13 |
+|[2023-003](https://codecheck.org.uk/register/certs/2023-003/)|[Exploring MapSwipe as a Crowdsourcing Tool for (Rapid) Damage Assessment: The Case of the 2021 Haiti Earthquake](https://doi.org/10.5194/agile-giss-4-5-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/m5bhk |2023-06-13 |
+|[2023-004](https://codecheck.org.uk/register/certs/2023-004/)|[Does spatial thinking ability relate to performance when using web-mapping services? A survey with digital natives](https://doi.org/10.5194/agile-giss-4-13-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/2em7v |2023-06-13 |
+|[2023-005](https://codecheck.org.uk/register/certs/2023-005/)|[Advancing Forest Monitoring and Assessment Through Immersive Virtual Reality](https://doi.org/10.5194/agile-giss-4-15-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/27wzp |2023-06-13 |
+|[2023-006](https://codecheck.org.uk/register/certs/2023-006/)|[Semantic complexity of geographic questions - A comparison in terms of conceptual transformations of answers](https://doi.org/10.5194/agile-giss-4-10-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/OSF.IO/D2SHF |2023-06-13 |
+|[2023-007](https://codecheck.org.uk/register/certs/2023-007/)|[Extreme heat alerts and impacts across Mozambique 2016 - 2022: gathering evidence from media articles](https://doi.org/10.5194/agile-giss-4-11-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/eu8kw |2023-06-13 |
+|[2023-008](https://codecheck.org.uk/register/certs/2023-008/)|[Is it safe to be attractive? Disentangling the influence of streetscape features on the perceived safety and attractiveness of city streets](https://doi.org/10.5194/agile-giss-4-8-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/aqgxr |2023-06-13 |
+|[2023-009](https://codecheck.org.uk/register/certs/2023-009/)|[Analysis of cycling network evolution in OpenStreetMap through a data quality prism](https://doi.org/10.5194/agile-giss-4-3-2023) |conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/9kp7u |2023-06-13 |
+|[2023-010](https://codecheck.org.uk/register/certs/2023-010/)|[Indoor localisation and location tracking in indoor facilities based on LiDAR point clouds and images of the ceilings](https://doi.org/10.5194/agile-giss-4-4-2023)|conference |AGILEGIS |[49](https://github.com/codecheckers/register/issues/49)|https://doi.org/10.17605/osf.io/8t3bh |2023-06-13 |
+|[2023-011](https://codecheck.org.uk/register/certs/2023-011/)|[Does enforcing glenohumeral joint stability matter? A new rapid muscle redundancy solver highlights the importance of non-superficial shoulder muscles ](https://doi.org/10.1101/2023.07.11.548542)|community |preprint |[56](https://github.com/codecheckers/register/issues/56)|https://doi.org/10.5281/zenodo.8359199 |2023-09-18 |
+|[2023-012](https://codecheck.org.uk/register/certs/2023-012/)|[An inventory of human light exposure related behaviour ](https://doi.org/10.1038/s41598-023-48241-y) |community |preprint |[59](https://github.com/codecheckers/register/issues/59)|https://doi.org/10.5281/zenodo.10213244 |2023-11-26 |
+|[2024-001](https://codecheck.org.uk/register/certs/2024-001/)|[Regulation of pupil size in natural vision across the human lifespan ](https://doi.org/10.1098/rsos.191613) |community |preprint |[60](https://github.com/codecheckers/register/issues/60)|https://doi.org/10.5281/zenodo.10823246 |2024-03-15 |
+|[2024-002](https://codecheck.org.uk/register/certs/2024-002/)|[Modeling spatiotemporal domestic wastewater variability: Implications for measuring treatment efficiency](https://doi.org/10.1016/j.jenvman.2023.119680) |community |codecheck NL |[61](https://github.com/codecheckers/register/issues/61)|https://doi.org/10.5281/zenodo.FIXME |2020-05-21 |
+|[2024-003](https://codecheck.org.uk/register/certs/2024-003/)|[State-Dependent Dynamic Tube MPC: A Novel Tube MPC Method with a Fuzzy Model of Disturbances ](https://arxiv.org/pdf/2310.19997) |community |codecheck NL |[66](https://github.com/codecheckers/register/issues/66)|https://doi.org/10.5281/zenodo.11403956 |2024-05-30 |
+|[2024-004](https://codecheck.org.uk/register/certs/2024-004/)|[Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint ](https://doi.org/10.31222/osf.io/a8rmu) |community |AUMC |[96](https://github.com/codecheckers/register/issues/96)|https://doi.org/10.5281/zenodo.13364677 |2024-08-01 |
+|[2024-006](https://codecheck.org.uk/register/certs/2024-006/)|[Random Data Distribution for Efficient Parallel Point Cloud Processing](https://doi.org/10.5194/agile-giss-5-15-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/OSF.IO/YMC3T |2024-05-23 |
+|[2024-007](https://codecheck.org.uk/register/certs/2024-007/)|[FreeMapRetrieve: Freehand Gestures for Retrieve Operations in Large-Screen Map Environments](https://doi.org/10.5194/agile-giss-5-7-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/OSF.IO/GVPD9 |2024-05-23 |
+|[2024-008](https://codecheck.org.uk/register/certs/2024-008/)|[Knowledge-Based Identification of Urban Green Spaces: Allotments](https://doi.org/10.5194/agile-giss-5-8-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/OSF.IO/3NBJW |2024-05-23 |
+|[2024-009](https://codecheck.org.uk/register/certs/2024-009/)|[Developing a city-specific walkability index through a participatory approach](https://doi.org/10.5194/agile-giss-5-2-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/CSB7R |2024-05-23 |
+|[2024-010](https://codecheck.org.uk/register/certs/2024-010/)|[Enhancing toponym identification: Leveraging Topo-BERT and open-source data to differentiate between toponyms and extract spatial relationships](https://doi.org/10.5194/agile-giss-5-12-2024)|conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/NBK57 |2024-05-27 |
+|[2024-011](https://codecheck.org.uk/register/certs/2024-011/)|[Process Analysis in Humanitarian Voluntary Geographic Information: the case of the HOT Tasking Manager](https://doi.org/10.5194/agile-giss-5-5-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/FMGB4 |2024-05-27 |
+|[2024-012](https://codecheck.org.uk/register/certs/2024-012/)|[The Impact of Traffic Lights on Modal Split and Route Choice: A use-case in Vienna](https://doi.org/10.5194/agile-giss-5-4-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/W42AD |2024-05-30 |
+|[2024-013](https://codecheck.org.uk/register/certs/2024-013/)|[Road Network Mapping from Multispectral Satellite Imagery: Leveraging Deep Learning and Spectral Bands](https://doi.org/10.5194/agile-giss-5-6-2024) |conference |AGILEGIS |[69](https://github.com/codecheckers/register/issues/69)|https://doi.org/10.17605/osf.io/TXGZV |2024-05-31 |
+|[2024-005](https://codecheck.org.uk/register/certs/2024-005/)|[Sample size estimation for task-related functional MRI studies using Bayesian updating.](https://doi.org/10.31234/osf.io/cz32t) |community |codecheck |[100](https://github.com/codecheckers/register/issues/100)|https://doi.org/10.5281/zenodo.13945051 |2024-10-15 |
+|[2024-014](https://codecheck.org.uk/register/certs/2024-014/)|[CY-Bench : A comprehensive benchmark dataset for sub-national crop yield forecasting](https://www.overleaf.com/read/znytpcwfjrrf#a4ca1f) |community |codecheck NL |[124](https://github.com/codecheckers/register/issues/124)|https://doi.org/10.17605/OSF.IO/spxt5 |2024-09-26 |
+|[2024-015](https://codecheck.org.uk/register/certs/2024-015/)|[Landscape Character Assessment - Nigeria](https://doi.org/10.17605/OSF.IO/E2K73) |community |codecheck NL |[124](https://github.com/codecheckers/register/issues/124)|https://doi.org/10.17605/OSF.IO/mwbuq |2024-09-26 |
+|[2024-016](https://codecheck.org.uk/register/certs/2024-016/)|[Integrating agent-based disease, mobility, and wastewater models: Dealing with differences in spatiotemporal resolutions](https://doi.org/10.5281/zenodo.13734819)|community |codecheck NL |[124](https://github.com/codecheckers/register/issues/124)|https://doi.org/10.17605/OSF.IO/6NGYC |2024-09-26 |
+|[2024-017](https://codecheck.org.uk/register/certs/2024-017/)|[Determination of a diffusion coefficient function for long rooms using a least square optimization approach ](https://pure.tue.nl/ws/portalfiles/portal/339520759/IN_2024_3491.pdf)|community |codecheck NL |[133](https://github.com/codecheckers/register/issues/133)|https://doi.org/10.5281/zenodo.14211707 |2024-11-22 |
+|[2024-018](https://codecheck.org.uk/register/certs/2024-018/)|[Power analysis for personal light exposure measurements and interventions ](https://doi.org/10.21203/rs.3.rs-3771881/v1) |community |codecheck NL |[132](https://github.com/codecheckers/register/issues/132)|https://doi.org/10.5281/zenodo.14235113 |2024-11-28 |
+|[2024-019](https://codecheck.org.uk/register/certs/2024-019/)|[Quality in Question: Assessing the accuracy of four heart rate wearables and the implications for psychophysiological research. ](https://doi.org/10.31219/osf.io/wkzsn)|community |codecheck NL |[134](https://github.com/codecheckers/register/issues/134)|https://doi.org/10.5281/zenodo.14279041 |2024-12-04 |
+|[2024-020](https://codecheck.org.uk/register/certs/2024-020/)|[Describing the scale and composition of calls for police service: a replication and extension using open data ](https://doi.org/10.1080/15614263.2022.2102494)|community |codecheck NL |[135](https://github.com/codecheckers/register/issues/135)|https://doi.org/10.5281/zenodo.14278912 |2024-11-28 |
+|[2024-021](https://codecheck.org.uk/register/certs/2024-021/)|[Using Consumer Wearables to Measure Physical Activity of Nursing Home Residents with Dementia ](https://doi.org/10.31234/osf.io/mqg86) |community |codecheck NL |[136](https://github.com/codecheckers/register/issues/136)|https://doi.org/10.5281/zenodo.14261193 |2024-11-28 |
+|[2024-022](https://codecheck.org.uk/register/certs/2024-022/)|[Simulating room transfer functions between transducers mounted on audio devices using a modified image source method ](https://doi.org/10.1121/10.0023935)|codecheck NL |136 |NA |http://doi.org/10.5281/zenodo.14273316 |2024-12-05 |
diff --git a/docs/stats.json b/docs/stats.json
index 1884dcc..7e8a8f0 100644
--- a/docs/stats.json
+++ b/docs/stats.json
@@ -1,4 +1,4 @@
{
"source": "https://codecheck.org.uk/register/register.json",
- "cert_count": 85
+ "cert_count": 86
}
diff --git a/docs/venues/136/featured.json b/docs/venues/136/featured.json
new file mode 100644
index 0000000..18c8e4c
--- /dev/null
+++ b/docs/venues/136/featured.json
@@ -0,0 +1,10 @@
+[
+ {
+ "Certificate": "[2024-022](https://codecheck.org.uk/register/certs/2024-022/)",
+ "Repository Link": "https://github.com/codecheckers/DEISM",
+ "Report": "http://doi.org/10.5281/zenodo.14273316",
+ "Title": "Simulating room transfer functions between transducers mounted on audio devices using a modified image source method",
+ "Paper reference": "https://doi.org/10.1121/10.0023935",
+ "Check date": "2024-12-05"
+ }
+]
diff --git a/docs/venues/136/index.html b/docs/venues/136/index.html
new file mode 100644
index 0000000..390ddf5
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+++ b/docs/venues/136/index.html
@@ -0,0 +1,276 @@
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+CODECHECK Register for codecheck NL (136)
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