PeerJ Computer Science
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ Computer Science
publisher: PeerJ Inc.
publication name: PeerJ Computer Science
issn: 2376-5992
items: The doctor’s digital double: how warmth, competence, and animation promote adherence intention
items: Convolutional ensembles for Arabic Handwritten Character and Digit Recognition
items: Adaptive automation: automatically (dis)engaging automation during visually distracted driving
items: Tools4MSP: an open source software package to support Maritime Spatial Planning
items: 20 GB in 10 minutes: a case for linking major biodiversity databases using an open socio-technical infrastructure and a pragmatic, cross-institutional collaboration
items: Towards computational reproducibility: researcher perspectives on the use and sharing of software
items: Performance, workload, and usability in a multiscreen, multi-device, information-rich environment
items: An integrated platform for intuitive mathematical programming modeling using LaTeX
items: Parallelisation of equation-based simulation programs on heterogeneous computing systems
items: Temporal constrained objects for modelling neuronal dynamics

The doctor’s digital double: how warmth, competence, and animation promote adherence intention
type: item
type: AcademicArticle
description: Background Each year, patient nonadherence to treatment advice costs the US healthcare system more than $300 billion and results in 250,000 deaths. Developing virtual consultations to promote adherence could improve public health while cutting healthcare costs and usage. However, inconsistencies in the realism of computer-animated humans may cause them to appear eerie, a phenomenon termed the uncanny valley. Eeriness could reduce a virtual doctor’s credibility and patients’ adherence. Methods In a 2 × 2 × 2 between-groups posttest-only experiment, 738 participants played the role of a patient in a hypothetical virtual consultation with a doctor. The consultation varied in the doctor’s Character (good or poor bedside manner), Outcome (received a fellowship or sued for malpractice), and Depiction (a recorded video of a real human actor or of his 3D computer-animated double). Character, Outcome, and Depiction were designed to manipulate the doctor’s level of warmth, competence, and realism, respectively. Results Warmth and competence increased adherence intention and consultation enjoyment, but realism did not. On the contrary, the computer-animated doctor increased adherence intention and consultation enjoyment significantly more than the doctor portrayed by a human actor. We propose that enjoyment of the animated consultation caused the doctor to appear warmer and more real, compensating for his realism inconsistency. Expressed as a path model, this explanation fit the data. Discussion The acceptance and effectiveness of the animation should encourage the development of virtual consultations, which have advantages over creating content with human actors including ease of scenario revision, internationalization, localization, personalization, and web distribution.
format: application/pdf
format: text/html
creator: Zhengyan Dai
creator: Karl F. MacDorman
subject: Human-Computer Interaction
subject: Agents and Multi-Agent Systems
subject: Graphics
subject: Multimedia
subject: Social Computing
description: doi:10.7717/peerj-cs.168
publisher: PeerJ Inc.
rights: © 2018 Dai and MacDorman
abstract: Background Each year, patient nonadherence to treatment advice costs the US healthcare system more than $300 billion and results in 250,000 deaths. Developing virtual consultations to promote adherence could improve public health while cutting healthcare costs and usage. However, inconsistencies in the realism of computer-animated humans may cause them to appear eerie, a phenomenon termed the uncanny valley. Eeriness could reduce a virtual doctor’s credibility and patients’ adherence. Methods In a 2 × 2 × 2 between-groups posttest-only experiment, 738 participants played the role of a patient in a hypothetical virtual consultation with a doctor. The consultation varied in the doctor’s Character (good or poor bedside manner), Outcome (received a fellowship or sued for malpractice), and Depiction (a recorded video of a real human actor or of his 3D computer-animated double). Character, Outcome, and Depiction were designed to manipulate the doctor’s level of warmth, competence, and realism, respectively. Results Warmth and competence increased adherence intention and consultation enjoyment, but realism did not. On the contrary, the computer-animated doctor increased adherence intention and consultation enjoyment significantly more than the doctor portrayed by a human actor. We propose that enjoyment of the animated consultation caused the doctor to appear warmer and more real, compensating for his realism inconsistency. Expressed as a path model, this explanation fit the data. Discussion The acceptance and effectiveness of the animation should encourage the development of virtual consultations, which have advantages over creating content with human actors including ease of scenario revision, internationalization, localization, personalization, and web distribution.
bibliographic citation: Dai et al. (2018) The doctor’s digital double: how warmth, competence, and animation promote adherence intention. PeerJ Computer Science 4:e168 https://doi.org/10.7717/peerj-cs.168
date submitted: 2018-08-01
date accepted: 2018-09-30
issued: 2018-11-12
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Dai
  given name: Zhengyan
author list: Agent
  family name: MacDorman
  given name: Karl F.
doi: 10.7717/peerj-cs.168
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-11-12
copyright: © 2018 Dai and MacDorman
attribution name: Dai and MacDorman

Convolutional ensembles for Arabic Handwritten Character and Digit Recognition
type: item
type: AcademicArticle
description: A learning algorithm is proposed for the task of Arabic Handwritten Character and Digit recognition. The architecture consists on an ensemble of different Convolutional Neural Networks. The proposed training algorithm uses a combination of adaptive gradient descent on the first epochs and regular stochastic gradient descent in the last epochs, to facilitate convergence. Different validation strategies are tested, namely Monte Carlo Cross-Validation and K-fold Cross Validation. Hyper-parameter tuning was done by using the MADbase digits dataset. State of the art validation and testing classification accuracies were achieved, with average values of 99.74% and 99.47% respectively. The same algorithm was then trained and tested with the AHCD character dataset, also yielding state of the art validation and testing classification accuracies: 98.60% and 98.42% respectively.
format: application/pdf
format: text/html
creator: Iam Palatnik de Sousa
subject: Algorithms and Analysis of Algorithms
subject: Artificial Intelligence
subject: Computer Vision
subject: Data Mining and Machine Learning
description: doi:10.7717/peerj-cs.167
publisher: PeerJ Inc.
rights: © 2018 Palatnik de Sousa
abstract: A learning algorithm is proposed for the task of Arabic Handwritten Character and Digit recognition. The architecture consists on an ensemble of different Convolutional Neural Networks. The proposed training algorithm uses a combination of adaptive gradient descent on the first epochs and regular stochastic gradient descent in the last epochs, to facilitate convergence. Different validation strategies are tested, namely Monte Carlo Cross-Validation and K-fold Cross Validation. Hyper-parameter tuning was done by using the MADbase digits dataset. State of the art validation and testing classification accuracies were achieved, with average values of 99.74% and 99.47% respectively. The same algorithm was then trained and tested with the AHCD character dataset, also yielding state of the art validation and testing classification accuracies: 98.60% and 98.42% respectively.
bibliographic citation: Palatnik de Sousa (2018) Convolutional ensembles for Arabic Handwritten Character and Digit Recognition. PeerJ Computer Science 4:e167 https://doi.org/10.7717/peerj-cs.167
date submitted: 2018-06-13
date accepted: 2018-09-24
issued: 2018-10-15
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Palatnik de Sousa
  given name: Iam
doi: 10.7717/peerj-cs.167
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-10-15
copyright: ©2018 Palatnik de Sousa
attribution name: Palatnik de Sousa

Adaptive automation: automatically (dis)engaging automation during visually distracted driving
type: item
type: AcademicArticle
description: Background Automated driving is often proposed as a solution to human errors. However, fully automated driving has not yet reached the point where it can be implemented in real traffic. This study focused on adaptively allocating steering control either to the driver or to an automated pilot based on momentary driver distraction measured from an eye tracker. Methods Participants (N = 31) steered a simulated vehicle with a fixed speed, and at specific moments were required to perform a visual secondary task (i.e., changing a CD). Three conditions were tested: (1) Manual driving (Manual), in which participants steered themselves. (2) An automated backup (Backup) condition, consisting of manual steering except during periods of visual distraction, where the driver was backed up by automated steering. (3) A forced manual drive (Forced) condition, consisting of automated steering except during periods of visual distraction, where the driver was forced into manual steering. In all three conditions, the speed of the vehicle was automatically kept at 70 km/h throughout the drive. Results The Backup condition showed a decrease in mean and maximum absolute lateral error compared to the Manual condition. The Backup condition also showed the lowest self-reported workload ratings and yielded a higher acceptance rating than the Forced condition. The Forced condition showed a higher maximum absolute lateral error than the Backup condition. Discussion In conclusion, the Backup condition was well accepted, and significantly improved performance when compared to the Manual and Forced conditions. Future research could use a higher level of simulator fidelity and a higher-quality eye-tracker.
format: application/pdf
format: text/html
creator: Christopher D.D. Cabrall
creator: Nico M. Janssen
creator: Joost C.F. de Winter
subject: Human-Computer Interaction
subject: Multimedia
description: doi:10.7717/peerj-cs.166
publisher: PeerJ Inc.
rights: © 2018 Cabrall et al.
abstract: Background Automated driving is often proposed as a solution to human errors. However, fully automated driving has not yet reached the point where it can be implemented in real traffic. This study focused on adaptively allocating steering control either to the driver or to an automated pilot based on momentary driver distraction measured from an eye tracker. Methods Participants (N = 31) steered a simulated vehicle with a fixed speed, and at specific moments were required to perform a visual secondary task (i.e., changing a CD). Three conditions were tested: (1) Manual driving (Manual), in which participants steered themselves. (2) An automated backup (Backup) condition, consisting of manual steering except during periods of visual distraction, where the driver was backed up by automated steering. (3) A forced manual drive (Forced) condition, consisting of automated steering except during periods of visual distraction, where the driver was forced into manual steering. In all three conditions, the speed of the vehicle was automatically kept at 70 km/h throughout the drive. Results The Backup condition showed a decrease in mean and maximum absolute lateral error compared to the Manual condition. The Backup condition also showed the lowest self-reported workload ratings and yielded a higher acceptance rating than the Forced condition. The Forced condition showed a higher maximum absolute lateral error than the Backup condition. Discussion In conclusion, the Backup condition was well accepted, and significantly improved performance when compared to the Manual and Forced conditions. Future research could use a higher level of simulator fidelity and a higher-quality eye-tracker.
bibliographic citation: Cabrall et al. (2018) Adaptive automation: automatically (dis)engaging automation during visually distracted driving. PeerJ Computer Science 4:e166 https://doi.org/10.7717/peerj-cs.166
date submitted: 2018-04-18
date accepted: 2018-09-05
issued: 2018-10-01
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Cabrall
  given name: Christopher D.D.
author list: Agent
  family name: Janssen
  given name: Nico M.
author list: Agent
  family name: de Winter
  given name: Joost C.F.
doi: 10.7717/peerj-cs.166
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-10-01
copyright: ©2018 Cabrall et al.
attribution name: Cabrall et al.

Tools4MSP: an open source software package to support Maritime Spatial Planning
type: item
type: AcademicArticle
description: This paper presents the Tools4MSP software package, a Python-based Free and Open Source Software (FOSS) for geospatial analysis in support of Maritime Spatial Planning (MSP) and marine environmental management. The suite was initially developed within the ADRIPLAN data portal, that has been recently upgraded into the Tools4MSP Geoplatform (data.tools4msp.eu), an integrated web platform that supports MSP through the application of different tools, e.g., collaborative geospatial modelling of cumulative effects assessment (CEA) and marine use conflict (MUC) analysis. The package can be used as stand-alone library or as collaborative webtool, providing user-friendly interfaces appropriate to decision-makers, regional authorities, academics and MSP stakeholders. An effective MSP-oriented integrated system of web-based software, users and services is proposed. It includes four components: the Tools4MSP Geoplatform for interoperable and collaborative sharing of geospatial datasets and for MSP-oriented analysis, the Tools4MSP package as stand-alone library for advanced geospatial and statistical analysis, the desktop applications to simplify data curation and the third party data repositories for multidisciplinary and multilevel geospatial datasets integration. The paper presents an application example of the Tools4MSP GeoNode plugin and an example of Tools4MSP stand-alone library for CEA in the Adriatic Sea. The Tools4MSP and the developed software have been released as FOSS under the GPL 3 license and are currently under further development.
format: application/pdf
format: text/html
creator: Stefano Menegon
creator: Alessandro Sarretta
creator: Daniel Depellegrin
creator: Giulio Farella
creator: Chiara Venier
creator: Andrea Barbanti
subject: Data Science
subject: Scientific Computing and Simulation
subject: Spatial and Geographic Information Systems
description: doi:10.7717/peerj-cs.165
publisher: PeerJ Inc.
rights: © 2018 Menegon et al.
abstract: This paper presents the Tools4MSP software package, a Python-based Free and Open Source Software (FOSS) for geospatial analysis in support of Maritime Spatial Planning (MSP) and marine environmental management. The suite was initially developed within the ADRIPLAN data portal, that has been recently upgraded into the Tools4MSP Geoplatform (data.tools4msp.eu), an integrated web platform that supports MSP through the application of different tools, e.g., collaborative geospatial modelling of cumulative effects assessment (CEA) and marine use conflict (MUC) analysis. The package can be used as stand-alone library or as collaborative webtool, providing user-friendly interfaces appropriate to decision-makers, regional authorities, academics and MSP stakeholders. An effective MSP-oriented integrated system of web-based software, users and services is proposed. It includes four components: the Tools4MSP Geoplatform for interoperable and collaborative sharing of geospatial datasets and for MSP-oriented analysis, the Tools4MSP package as stand-alone library for advanced geospatial and statistical analysis, the desktop applications to simplify data curation and the third party data repositories for multidisciplinary and multilevel geospatial datasets integration. The paper presents an application example of the Tools4MSP GeoNode plugin and an example of Tools4MSP stand-alone library for CEA in the Adriatic Sea. The Tools4MSP and the developed software have been released as FOSS under the GPL 3 license and are currently under further development.
bibliographic citation: Menegon et al. (2018) Tools4MSP: an open source software package to support Maritime Spatial Planning. PeerJ Computer Science 4:e165 https://doi.org/10.7717/peerj-cs.165
date submitted: 2018-03-13
date accepted: 2018-09-04
issued: 2018-10-01
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Menegon
  given name: Stefano
author list: Agent
  family name: Sarretta
  given name: Alessandro
author list: Agent
  family name: Depellegrin
  given name: Daniel
author list: Agent
  family name: Farella
  given name: Giulio
author list: Agent
  family name: Venier
  given name: Chiara
author list: Agent
  family name: Barbanti
  given name: Andrea
doi: 10.7717/peerj-cs.165
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-10-01
copyright: ©2018 Menegon et al.
attribution name: Menegon et al.

20 GB in 10 minutes: a case for linking major biodiversity databases using an open socio-technical infrastructure and a pragmatic, cross-institutional collaboration
type: item
type: AcademicArticle
description: Biodiversity information is made available through numerous databases that each have their own data models, web services, and data types. Combining data across databases leads to new insights, but is not easy because each database uses its own system of identifiers. In the absence of stable and interoperable identifiers, databases are often linked using taxonomic names. This labor intensive, error prone, and lengthy process relies on accessible versions of nomenclatural authorities and fuzzy-matching algorithms. To approach the challenge of linking diverse data, more than technology is needed. New social collaborations like the Global Unified Open Data Architecture (GUODA) that combines skills from diverse groups of computer engineers from iDigBio, server resources from the Advanced Computing and Information Systems (ACIS) Lab, global-scale data presentation from EOL, and independent developers and researchers are what is needed to make concrete progress on finding relationships between biodiversity datasets. This paper will discuss a technical solution developed by the GUODA collaboration for faster linking across databases with a use case linking Wikidata and the Global Biotic Interactions database (GloBI). The GUODA infrastructure is a 12-node, high performance computing cluster made up of about 192 threads with 12 TB of storage and 288 GB memory. Using GUODA, 20 GB of compressed JSON from Wikidata was processed and linked to GloBI in about 10–11 min. Instead of comparing name strings or relying on a single identifier, Wikidata and GloBI were linked by comparing graphs of biodiversity identifiers external to each system. This method resulted in adding 119,957 Wikidata links in GloBI, an increase of 13.7% of all outgoing name links in GloBI. Wikidata and GloBI were compared to Open Tree of Life Reference Taxonomy to examine consistency and coverage. The process of parsing Wikidata, Open Tree of Life Reference Taxonomy and GloBI archives and calculating consistency…
format: application/pdf
format: text/html
creator: Anne E. Thessen
creator: Jorrit H. Poelen
creator: Matthew Collins
creator: Jen Hammock
subject: Bioinformatics
subject: Databases
description: doi:10.7717/peerj-cs.164
publisher: PeerJ Inc.
rights: © 2018 Thessen et al.
abstract: Biodiversity information is made available through numerous databases that each have their own data models, web services, and data types. Combining data across databases leads to new insights, but is not easy because each database uses its own system of identifiers. In the absence of stable and interoperable identifiers, databases are often linked using taxonomic names. This labor intensive, error prone, and lengthy process relies on accessible versions of nomenclatural authorities and fuzzy-matching algorithms. To approach the challenge of linking diverse data, more than technology is needed. New social collaborations like the Global Unified Open Data Architecture (GUODA) that combines skills from diverse groups of computer engineers from iDigBio, server resources from the Advanced Computing and Information Systems (ACIS) Lab, global-scale data presentation from EOL, and independent developers and researchers are what is needed to make concrete progress on finding relationships between biodiversity datasets. This paper will discuss a technical solution developed by the GUODA collaboration for faster linking across databases with a use case linking Wikidata and the Global Biotic Interactions database (GloBI). The GUODA infrastructure is a 12-node, high performance computing cluster made up of about 192 threads with 12 TB of storage and 288 GB memory. Using GUODA, 20 GB of compressed JSON from Wikidata was processed and linked to GloBI in about 10–11 min. Instead of comparing name strings or relying on a single identifier, Wikidata and GloBI were linked by comparing graphs of biodiversity identifiers external to each system. This method resulted in adding 119,957 Wikidata links in GloBI, an increase of 13.7% of all outgoing name links in GloBI. Wikidata and GloBI were compared to Open Tree of Life Reference Taxonomy to examine consistency and coverage. The process of parsing Wikidata, Open Tree of Life Reference Taxonomy and GloBI archives and calculating consistency…
bibliographic citation: Thessen et al. (2018) 20 GB in 10 minutes: a case for linking major biodiversity databases using an open socio-technical infrastructure and a pragmatic, cross-institutional collaboration. PeerJ Computer Science 4:e164 https://doi.org/10.7717/peerj-cs.164
date submitted: 2018-05-17
date accepted: 2018-08-29
issued: 2018-09-17
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Thessen
  given name: Anne E.
author list: Agent
  family name: Poelen
  given name: Jorrit H.
author list: Agent
  family name: Collins
  given name: Matthew
author list: Agent
  family name: Hammock
  given name: Jen
doi: 10.7717/peerj-cs.164
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-09-17
copyright: ©2018 Thessen et al.
attribution name: Thessen et al.

Towards computational reproducibility: researcher perspectives on the use and sharing of software
type: item
type: AcademicArticle
description: Research software, which includes both source code and executables used as part of the research process, presents a significant challenge for efforts aimed at ensuring reproducibility. In order to inform such efforts, we conducted a survey to better understand the characteristics of research software as well as how it is created, used, and shared by researchers. Based on the responses of 215 participants, representing a range of research disciplines, we found that researchers create, use, and share software in a wide variety of forms for a wide variety of purposes, including data collection, data analysis, data visualization, data cleaning and organization, and automation. More participants indicated that they use open source software than commercial software. While a relatively small number of programming languages (e.g., Python, R, JavaScript, C++, MATLAB) are used by a large number, there is a long tail of languages used by relatively few. Between-group comparisons revealed that significantly more participants from computer science write source code and create executables than participants from other disciplines. Differences between researchers from computer science and other disciplines related to the knowledge of best practices of software creation and sharing were not statistically significant. While many participants indicated that they draw a distinction between the sharing and preservation of software, related practices and perceptions were often not aligned with those of the broader scholarly communications community.
format: application/pdf
format: text/html
creator: Yasmin AlNoamany
creator: John A. Borghi
subject: Digital Libraries
description: doi:10.7717/peerj-cs.163
publisher: PeerJ Inc.
rights: © 2018 AlNoamany and Borghi
abstract: Research software, which includes both source code and executables used as part of the research process, presents a significant challenge for efforts aimed at ensuring reproducibility. In order to inform such efforts, we conducted a survey to better understand the characteristics of research software as well as how it is created, used, and shared by researchers. Based on the responses of 215 participants, representing a range of research disciplines, we found that researchers create, use, and share software in a wide variety of forms for a wide variety of purposes, including data collection, data analysis, data visualization, data cleaning and organization, and automation. More participants indicated that they use open source software than commercial software. While a relatively small number of programming languages (e.g., Python, R, JavaScript, C++, MATLAB) are used by a large number, there is a long tail of languages used by relatively few. Between-group comparisons revealed that significantly more participants from computer science write source code and create executables than participants from other disciplines. Differences between researchers from computer science and other disciplines related to the knowledge of best practices of software creation and sharing were not statistically significant. While many participants indicated that they draw a distinction between the sharing and preservation of software, related practices and perceptions were often not aligned with those of the broader scholarly communications community.
bibliographic citation: AlNoamany et al. (2018) Towards computational reproducibility: researcher perspectives on the use and sharing of software. PeerJ Computer Science 4:e163 https://doi.org/10.7717/peerj-cs.163
date submitted: 2018-03-16
date accepted: 2018-08-24
issued: 2018-09-17
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: AlNoamany
  given name: Yasmin
author list: Agent
  family name: Borghi
  given name: John A.
doi: 10.7717/peerj-cs.163
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-09-17
copyright: ©2018 AlNoamany and Borghi
attribution name: AlNoamany and Borghi

Performance, workload, and usability in a multiscreen, multi-device, information-rich environment
type: item
type: AcademicArticle
description: Potential benefits of multiscreen and multiple device environments were assessed using three different computing environments. A single factor, within-subject study was conducted with 18 engineering students in a laboratory experiment. Three levels for the computing environment factor included one with a desktop computer with a single monitor (control, condition A); one with a desktop with dual monitors, as well as a single tablet computer (condition B); and one with a desktop with a single monitor, as well as two tablet computers (condition C). There was no statistically significant difference in efficiency or workload when completing scenarios for the three computing environments. However, a dual monitor desktop with a single tablet computer (B) was the ideal computing environment for the information-rich engineering problem given to participants, supported by significantly fewer errors compared to condition C and significantly higher usability ratings compared to conditions A and C. A single desktop monitor with two tablet computers (C) did not provide any advantage compared to a single desktop monitor (A).
format: application/pdf
format: text/html
creator: Jason J. Saleem
creator: Dustin T. Weiler
subject: Human-Computer Interaction
subject: Mobile and Ubiquitous Computing
description: doi:10.7717/peerj-cs.162
publisher: PeerJ Inc.
rights: © 2018 Saleem and Weiler
abstract: Potential benefits of multiscreen and multiple device environments were assessed using three different computing environments. A single factor, within-subject study was conducted with 18 engineering students in a laboratory experiment. Three levels for the computing environment factor included one with a desktop computer with a single monitor (control, condition A); one with a desktop with dual monitors, as well as a single tablet computer (condition B); and one with a desktop with a single monitor, as well as two tablet computers (condition C). There was no statistically significant difference in efficiency or workload when completing scenarios for the three computing environments. However, a dual monitor desktop with a single tablet computer (B) was the ideal computing environment for the information-rich engineering problem given to participants, supported by significantly fewer errors compared to condition C and significantly higher usability ratings compared to conditions A and C. A single desktop monitor with two tablet computers (C) did not provide any advantage compared to a single desktop monitor (A).
bibliographic citation: Saleem et al. (2018) Performance, workload, and usability in a multiscreen, multi-device, information-rich environment. PeerJ Computer Science 4:e162 https://doi.org/10.7717/peerj-cs.162
date submitted: 2018-04-04
date accepted: 2018-08-22
issued: 2018-09-10
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Saleem
  given name: Jason J.
author list: Agent
  family name: Weiler
  given name: Dustin T.
doi: 10.7717/peerj-cs.162
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-09-10
copyright: ©2018 Saleem and Weiler
attribution name: Saleem and Weiler

An integrated platform for intuitive mathematical programming modeling using LaTeX
type: item
type: AcademicArticle
description: This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work.
format: application/pdf
format: text/html
creator: Charalampos P. Triantafyllidis
creator: Lazaros G. Papageorgiou
subject: Optimization Theory and Computation
subject: Scientific Computing and Simulation
subject: Programming Languages
subject: Software Engineering
description: doi:10.7717/peerj-cs.161
publisher: PeerJ Inc.
rights: © 2018 Triantafyllidis and Papageorgiou
abstract: This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work.
bibliographic citation: Triantafyllidis et al. (2018) An integrated platform for intuitive mathematical programming modeling using LaTeX. PeerJ Computer Science 4:e161 https://doi.org/10.7717/peerj-cs.161
date submitted: 2018-06-03
date accepted: 2018-08-06
issued: 2018-09-10
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Triantafyllidis
  given name: Charalampos P.
author list: Agent
  family name: Papageorgiou
  given name: Lazaros G.
doi: 10.7717/peerj-cs.161
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-09-10
copyright: ©2018 Triantafyllidis and Papageorgiou
attribution name: Triantafyllidis and Papageorgiou

Parallelisation of equation-based simulation programs on heterogeneous computing systems
type: item
type: AcademicArticle
description: Numerical solutions of equation-based simulations require computationally intensive tasks such as evaluation of model equations, linear algebra operations and solution of systems of linear equations. The focus in this work is on parallel evaluation of model equations on shared memory systems such as general purpose processors (multi-core CPUs and manycore devices), streaming processors (Graphics Processing Units and Field Programmable Gate Arrays) and heterogeneous systems. The current approaches for evaluation of model equations are reviewed and their capabilities and shortcomings analysed. Since stream computing differs from traditional computing in that the system processes a sequential stream of elements, equations must be transformed into a data structure suitable for both types. The postfix notation expression stacks are recognised as a platform and programming language independent method to describe, store in computer memory and evaluate general systems of differential and algebraic equations of any size. Each mathematical operation and its operands are described by a specially designed data structure, and every equation is transformed into an array of these structures (a Compute Stack). Compute Stacks are evaluated by a stack machine using a Last In First Out queue. The stack machine is implemented in the DAE Tools modelling software in the C99 language using two Application Programming Interface (APIs)/frameworks for parallelism. The Open Multi-Processing (OpenMP) API is used for parallelisation on general purpose processors, and the Open Computing Language (OpenCL) framework is used for parallelisation on streaming processors and heterogeneous systems. The performance of the sequential Compute Stack approach is compared to the direct C++ implementation and to the previous approach that uses evaluation trees. The new approach is 45% slower than the C++ implementation and more than five times faster than the previous one. The OpenMP and OpenCL implementation…
format: application/pdf
format: text/html
creator: Dragan D. Nikolić
subject: Distributed and Parallel Computing
subject: Scientific Computing and Simulation
description: doi:10.7717/peerj-cs.160
publisher: PeerJ Inc.
rights: © 2018 Nikolic
abstract: Numerical solutions of equation-based simulations require computationally intensive tasks such as evaluation of model equations, linear algebra operations and solution of systems of linear equations. The focus in this work is on parallel evaluation of model equations on shared memory systems such as general purpose processors (multi-core CPUs and manycore devices), streaming processors (Graphics Processing Units and Field Programmable Gate Arrays) and heterogeneous systems. The current approaches for evaluation of model equations are reviewed and their capabilities and shortcomings analysed. Since stream computing differs from traditional computing in that the system processes a sequential stream of elements, equations must be transformed into a data structure suitable for both types. The postfix notation expression stacks are recognised as a platform and programming language independent method to describe, store in computer memory and evaluate general systems of differential and algebraic equations of any size. Each mathematical operation and its operands are described by a specially designed data structure, and every equation is transformed into an array of these structures (a Compute Stack). Compute Stacks are evaluated by a stack machine using a Last In First Out queue. The stack machine is implemented in the DAE Tools modelling software in the C99 language using two Application Programming Interface (APIs)/frameworks for parallelism. The Open Multi-Processing (OpenMP) API is used for parallelisation on general purpose processors, and the Open Computing Language (OpenCL) framework is used for parallelisation on streaming processors and heterogeneous systems. The performance of the sequential Compute Stack approach is compared to the direct C++ implementation and to the previous approach that uses evaluation trees. The new approach is 45% slower than the C++ implementation and more than five times faster than the previous one. The OpenMP and OpenCL implementation…
bibliographic citation: Nikolić (2018) Parallelisation of equation-based simulation programs on heterogeneous computing systems. PeerJ Computer Science 4:e160 https://doi.org/10.7717/peerj-cs.160
date submitted: 2018-03-22
date accepted: 2018-07-20
issued: 2018-08-13
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Nikolić
  given name: Dragan D.
doi: 10.7717/peerj-cs.160
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-08-13
copyright: © 2018 Nikolic
attribution name: Nikolic

Temporal constrained objects for modelling neuronal dynamics
type: item
type: AcademicArticle
description: Background Several new programming languages and technologies have emerged in the past few decades in order to ease the task of modelling complex systems. Modelling the dynamics of complex systems requires various levels of abstractions and reductive measures in representing the underlying behaviour. This also often requires making a trade-off between how realistic a model should be in order to address the scientific questions of interest and the computational tractability of the model. Methods In this paper, we propose a novel programming paradigm, called temporal constrained objects, which facilitates a principled approach to modelling complex dynamical systems. Temporal constrained objects are an extension of constrained objects with a focus on the analysis and prediction of the dynamic behaviour of a system. The structural aspects of a neuronal system are represented using objects, as in object-oriented languages, while the dynamic behaviour of neurons and synapses are modelled using declarative temporal constraints. Computation in this paradigm is a process of constraint satisfaction within a time-based simulation. Results We identified the feasibility and practicality in automatically mapping different kinds of neuron and synapse models to the constraints of temporal constrained objects. Simple neuronal networks were modelled by composing circuit components, implicitly satisfying the internal constraints of each component and interface constraints of the composition. Simulations show that temporal constrained objects provide significant conciseness in the formulation of these models. The underlying computational engine employed here automatically finds the solutions to the problems stated, reducing the code for modelling and simulation control. All examples reported in this paper have been programmed and successfully tested using the prototype language called TCOB. The code along with the programming environment are available at http://github.com/compneuro/TCO…
format: application/pdf
format: text/html
creator: Manjusha Nair
creator: Jinesh Manchan Kannimoola
creator: Bharat Jayaraman
creator: Bipin Nair
creator: Shyam Diwakar
subject: Computational Biology
subject: Scientific Computing and Simulation
subject: Programming Languages
description: doi:10.7717/peerj-cs.159
publisher: PeerJ Inc.
rights: © 2018 Nair et al.
abstract: Background Several new programming languages and technologies have emerged in the past few decades in order to ease the task of modelling complex systems. Modelling the dynamics of complex systems requires various levels of abstractions and reductive measures in representing the underlying behaviour. This also often requires making a trade-off between how realistic a model should be in order to address the scientific questions of interest and the computational tractability of the model. Methods In this paper, we propose a novel programming paradigm, called temporal constrained objects, which facilitates a principled approach to modelling complex dynamical systems. Temporal constrained objects are an extension of constrained objects with a focus on the analysis and prediction of the dynamic behaviour of a system. The structural aspects of a neuronal system are represented using objects, as in object-oriented languages, while the dynamic behaviour of neurons and synapses are modelled using declarative temporal constraints. Computation in this paradigm is a process of constraint satisfaction within a time-based simulation. Results We identified the feasibility and practicality in automatically mapping different kinds of neuron and synapse models to the constraints of temporal constrained objects. Simple neuronal networks were modelled by composing circuit components, implicitly satisfying the internal constraints of each component and interface constraints of the composition. Simulations show that temporal constrained objects provide significant conciseness in the formulation of these models. The underlying computational engine employed here automatically finds the solutions to the problems stated, reducing the code for modelling and simulation control. All examples reported in this paper have been programmed and successfully tested using the prototype language called TCOB. The code along with the programming environment are available at http://github.com/compneuro/TCO…
bibliographic citation: Nair et al. (2018) Temporal constrained objects for modelling neuronal dynamics. PeerJ Computer Science 4:e159 https://doi.org/10.7717/peerj-cs.159
date submitted: 2018-03-02
date accepted: 2018-06-26
issued: 2018-07-23
is part of: PeerJ Computer Science
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Nair
  given name: Manjusha
author list: Agent
  family name: Manchan Kannimoola
  given name: Jinesh
author list: Agent
  family name: Jayaraman
  given name: Bharat
author list: Agent
  family name: Nair
  given name: Bipin
author list: Agent
  family name: Diwakar
  given name: Shyam
doi: 10.7717/peerj-cs.159
volume: 4
issn: 2376-5992
publication name: PeerJ Computer Science
publication date: 2018-07-23
copyright: © 2018 Nair et al.
attribution name: Nair et al.

PeerJ Computer Science
type: Periodical
uri: PeerJ Computer Science
issn: 2376-5992