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The R package infiltrodiscR: A package for infiltrometer data analysis and an experience for improving data reproducibility in soil physics R 软件包 infiltrodiscR：入渗仪数据分析软件包和提高土壤物理学数据重现性的经验
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-07 DOI: 10.1016/j.softx.2024.101916
{"title":"The R package infiltrodiscR: A package for infiltrometer data analysis and an experience for improving data reproducibility in soil physics","authors":"","doi":"10.1016/j.softx.2024.101916","DOIUrl":"10.1016/j.softx.2024.101916","url":null,"abstract":"<div><div>This paper discusses the interest in utilizing R, a programming language, in soil physics for enhanced data reproducibility. Reproducibility is challenging across scientific disciplines, including soil science, and it is encouraged by demands for transparency from funding bodies and governments. Open and reproducible soil physics research can benefit the scientific community. With a focus on open science practices, the authors developed {infiltrodiscR}, leveraging existing R knowledge in soil physics. The package facilitates analysis of infiltration data, demonstrated through analysing changes in infiltration using published data. Results align with previous findings, showcasing {infiltrodiscR}'s potential in promoting reproducibility in soil science research.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ARTDET: Machine learning software for automated detection of art deterioration in easel paintings ARTDET：用于自动检测架上绘画艺术品劣化的机器学习软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-05 DOI: 10.1016/j.softx.2024.101917
{"title":"ARTDET: Machine learning software for automated detection of art deterioration in easel paintings","authors":"","doi":"10.1016/j.softx.2024.101917","DOIUrl":"10.1016/j.softx.2024.101917","url":null,"abstract":"<div><div>The increasing interest in digital preservation of cultural heritage has led to ARTDET, a machine learning software for automated detection of deterioration in easel paintings. This web application uses a pre-trained Mask R-CNN model to detect Lacune (areas of missing paint, resulting in visible support panel) from the loss of the Painting Layer (LPL) and stucco repairs. ARTDET leverages high-resolution images annotated by expert restorers. The software achieved 80.4 % recall for LPL and stucco, with a 99 % confidence score in detected damages. Available as open access resource, ARTDET aids conservators and researchers in preserving invaluable artworks.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DGE-ontology: A quick and simple gene set enrichment analysis and visualisation tool DGE-ontology：快速简单的基因组富集分析和可视化工具
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-04 DOI: 10.1016/j.softx.2024.101899
{"title":"DGE-ontology: A quick and simple gene set enrichment analysis and visualisation tool","authors":"","doi":"10.1016/j.softx.2024.101899","DOIUrl":"10.1016/j.softx.2024.101899","url":null,"abstract":"<div><div>High-throughput quantification techniques provide considerable amounts of data. Making sense of such data requires not only thorough statistical analysis but a logical approach to data visualisation. DGE-ontology is software that has been primarily designed for transcriptomics, however it may be utilised for any data that express fold change of relative or absolute quantity measures of multiple entities, such as transcripts, proteins or metabolites. The software integrates results of differential and functional analyses in order to produce a single circular, highly informative and visually appealing chart. The chart simultaneously depicts numbers of quantified entities, their assignment to functional categories, singles out statistically over-represented categories, and visualises quantity fold change values. The presented approach to data visualisation considerably facilitates communication of experimental results as well as inference from large omic data sets.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Numba-MPI v1.0: Enabling MPI communication within Numba/LLVM JIT-compiled Python code Numba-MPI v1.0：在Numba/LLVM JIT编译的Python代码中启用MPI通信
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-04 DOI: 10.1016/j.softx.2024.101897
{"title":"Numba-MPI v1.0: Enabling MPI communication within Numba/LLVM JIT-compiled Python code","authors":"","doi":"10.1016/j.softx.2024.101897","DOIUrl":"10.1016/j.softx.2024.101897","url":null,"abstract":"<div><div>The <span>numba-mpi</span> package offers access to the Message Passing Interface (MPI) routines from Python code that uses the Numba just-in-time (JIT) compiler. As a result, high-performance and multi-threaded Python code may utilize MPI communication facilities without leaving the JIT-compiled code blocks, which is not possible with the <span>mpi4py</span> package, a higher-level Python interface to MPI. For debugging or code-coverage analysis purposes, <span>numba-mpi</span> retains full functionality of the code even if the JIT compilation is disabled. The <span>numba-mpi</span> API constitutes a thin wrapper around the C API of MPI and is built around Numpy arrays including handling of non-contiguous views over array slices. Project development is hosted at GitHub leveraging the <span>mpi4py/setup-mpi</span> workflow enabling continuous integration tests on Linux (<span>MPICH</span>, <span>OpenMPI</span> &amp; <span>Intel MPI</span>), macOS (<span>MPICH</span> &amp; <span>OpenMPI</span>) and Windows (<span>MS MPI</span>). The paper covers an overview of the package features, architecture and performance. As of v1.0, the following MPI routines are exposed and covered by unit tests: <span>size</span>/<span>rank</span>, <span>[i]send</span>/<span>[i]recv</span>, <span>wait[all|any]</span>, <span>test[all|any]</span>, <span>allreduce</span>, <span>bcast</span>, <span>barrier</span>, <span>scatter/[all]gather</span> &amp; <span>wtime</span>. The package is implemented in pure Python and depends on <span>numpy</span>, <span>numba</span> and <span>mpi4py</span> (the latter used at initialization and as a source of utility routines only). The performance advantage of using <span>numba-mpi</span> compared to <span>mpi4py</span> is depicted with a simple example, with entirety of the code included in listings discussed in the text. Application of <span>numba-mpi</span> for handling domain decomposition in numerical solvers for partial differential equations is presented using two external packages that depend on <span>numba-mpi</span>: <span>py-pde</span> and <span>PyMPDATA-MPI</span>.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PC-TRT: A Test Case Reuse and generation Tool to achieve high path coverage for Unit Test PC-TRT：实现单元测试高路径覆盖率的测试用例重用和生成工具
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-04 DOI: 10.1016/j.softx.2024.101918
{"title":"PC-TRT: A Test Case Reuse and generation Tool to achieve high path coverage for Unit Test","authors":"","doi":"10.1016/j.softx.2024.101918","DOIUrl":"10.1016/j.softx.2024.101918","url":null,"abstract":"<div><div>After software or program updates, it is crucial to establish a new set of test cases. Reusing parts of the old test case set in unit testing is a cost-effective, efficient, and common approach. However, only a few commercial software are utilized for this purpose, and their techniques for reusing test cases are not publicly available. PC-TRT is a test case reuse tool primarily designed for software and programs written in the C language. PC-TRT reuses test cases from historical program versions and generates test data for uncovered paths, resulting in a high path coverage test case set. Its key functions include analyzing test case path coverage information, selecting reusable cases from old test case sets based on path similarity, and generating test data for uncovered paths. PC-TRT significantly improves both the efficiency and reliability of software testing.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Neper-Mosaic: Seamless generation of periodic representative volume elements on unit domains Neper-Mosaic：在单位域上无缝生成周期性代表性体元
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-03 DOI: 10.1016/j.softx.2024.101912
{"title":"Neper-Mosaic: Seamless generation of periodic representative volume elements on unit domains","authors":"","doi":"10.1016/j.softx.2024.101912","DOIUrl":"10.1016/j.softx.2024.101912","url":null,"abstract":"<div><div>The effective macroscopic behaviour of a material is a manifestation of the underlying microstructure and microscale processes. This renders the generation of highly accurate digital microstructure twins indispensable for multiscale simulations. <span>Mosaic</span> is a Python-based, open-source software tool designed to address the challenge of incorporating non-planar, periodic microstructures generated by the software <span>Neper</span> into simulations that require periodic boundary conditions. <span>Mosaic</span> transforms these complex microstructures into rectilinear periodic equivalents and, additionally, makes it possible to account for material interfaces such as grain and phase boundaries. This transformation enables continuous integration with various simulation tools and workflows, facilitating accurate and efficient simulations of the effective material response.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MixtureMetrics: A comprehensive package to develop additive numerical features to describe complex materials for machine learning modeling MixtureMetrics：一个综合软件包，用于开发描述复杂材料的加法数值特征，以进行机器学习建模
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-01 DOI: 10.1016/j.softx.2024.101911
{"title":"MixtureMetrics: A comprehensive package to develop additive numerical features to describe complex materials for machine learning modeling","authors":"","doi":"10.1016/j.softx.2024.101911","DOIUrl":"10.1016/j.softx.2024.101911","url":null,"abstract":"<div><div>Multi-component materials/compounds and polymeric/composite systems pose structural complexity that challenges the conventional methods of molecular representation in cheminformatics, which have limited applicability in such cases. Therefore, we have introduced an innovative structural representation technique tailored for complex materials. We implemented different mixing rules based on linear and nonlinear relationships’ additive effect of different components in composites treating each multi-component material as a mixture system. We developed and improved mixture descriptors based on 12 different mixture functions grouped into three main categories: property-based descriptors, concentration-weighted descriptors, and deviation-combination descriptors. A python package was developed for this purpose, allowing users to compute 12 different mixture-descriptors to use as input for the generation of mixture-based Quantitative Structure-Activity/Property Relationship (mxb-QSAR/QSPR) machine learning models for predicting a range of chemical and physical properties across various complex systems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PyWindAM: A Python software for wind field analysis and cloud-based data management PyWindAM：用于风场分析和云端数据管理的 Python 软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-10-01 DOI: 10.1016/j.softx.2024.101914
{"title":"PyWindAM: A Python software for wind field analysis and cloud-based data management","authors":"","doi":"10.1016/j.softx.2024.101914","DOIUrl":"10.1016/j.softx.2024.101914","url":null,"abstract":"<div><div>Given the substantial influence of wind loading on the structural performance of long-span bridges, continuous monitoring of wind field characteristics in their vicinity is paramount. PyWindAM is purpose-built web server software meticulously designed to simplify comprehensive wind data analysis and efficient management derived from on-site measurements. The software automates the retrieval of raw data from hardware devices and employs vector decomposition to extract essential wind parameters, including mean wind speed, wind direction, turbulence intensity, and more, from data collected at multiple measurement points. These critical wind parameters are securely stored in the InfluxDB database hosted on the server. In terms of user-friendliness, InfluxDB itself provides an intuitive interface, facilitating convenient data visualization and efficient management for researchers and technicians engaged in wind field analysis and structural safety assessments.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
core_api_client: An API for the CORE aggregation service for open access papers core_api_client：CORE 开放获取论文聚合服务的应用程序接口
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-28 DOI: 10.1016/j.softx.2024.101907
{"title":"core_api_client: An API for the CORE aggregation service for open access papers","authors":"","doi":"10.1016/j.softx.2024.101907","DOIUrl":"10.1016/j.softx.2024.101907","url":null,"abstract":"<div><div>Recent efforts to make research publications public have had a profound effect on the scientific publishing landscape. With a large influx in publicly available research contributions, the need for software tooling that supports information retrieval from indexing services is invaluable. Complementing well established indexing services such as Scopus, Web of Science, PubMed, etc. is CORE, which vows to provide a holistic view including contributions contained in aforementioned well established indexers. Conveniently, CORE offers an API for accessing data. This paper presents a client library that fully implements their API and enables quick and easy access to information, which is relevant for literature reviews as well as the scientific field of scientometrics.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Excursiona: A collaborative mobile application for excursions in nature Excursiona：自然游览协作移动应用程序
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-26 DOI: 10.1016/j.softx.2024.101908
{"title":"Excursiona: A collaborative mobile application for excursions in nature","authors":"","doi":"10.1016/j.softx.2024.101908","DOIUrl":"10.1016/j.softx.2024.101908","url":null,"abstract":"<div><div>This paper presents Excursiona, an application that provides substantial value to group excursions. Excursiona promotes collaboration and awareness during the excursion, as the group members navigate the map. Moreover, users can share pictures of interesting points they discover and interact in the chat room. The application has great potential in fields that benefit from outdoor collaboration, with application cases on children with special needs or firefighters. Regarding the technological approach, Excursiona has been developed in Flutter, making it compatible with iOS and Android operating systems, which along other technological tools has enhanced the possibilities of the project. Finally, an evaluation with users has allowed the testing of the system and the evaluation of the collaborative and awareness features.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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