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Corrigendum to `Gdistns: R package for maximum goodness-of-fit estimates of the generalized G distributions' [SoftwareX 27 (2024) 101886] 对 "Gdistns：用于广义G分布最大拟合优度估计的R软件包' [SoftwareX 27 (2024) 101886]
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-23 DOI: 10.1016/j.softx.2024.101904
M. Hussein , A. Al Mutairi , M.S. Mustafa , H. Elsayed
{"title":"Corrigendum to `Gdistns: R package for maximum goodness-of-fit estimates of the generalized G distributions' [SoftwareX 27 (2024) 101886]","authors":"M. Hussein , A. Al Mutairi , M.S. Mustafa , H. Elsayed","doi":"10.1016/j.softx.2024.101904","DOIUrl":"10.1016/j.softx.2024.101904","url":null,"abstract":"","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101904"},"PeriodicalIF":2.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721301","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
EcgScorer: An open source MATLAB toolbox for ECG signal quality assessment EcgScorer：用于心电信号质量评估的开源 MATLAB 工具箱
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-23 DOI: 10.1016/j.softx.2024.101900
Noura Alexendre , Fotsing Kuetche , Ntsama Eloundou Pascal , Simo Thierry
{"title":"EcgScorer: An open source MATLAB toolbox for ECG signal quality assessment","authors":"Noura Alexendre ,&nbsp;Fotsing Kuetche ,&nbsp;Ntsama Eloundou Pascal ,&nbsp;Simo Thierry","doi":"10.1016/j.softx.2024.101900","DOIUrl":"10.1016/j.softx.2024.101900","url":null,"abstract":"<div><div>Cardiovascular diseases claim over 17 million lives annually. Prevention involves adopting healthy habits and regular check-ups, ideally outside hospitals to reduce healthcare costs, leveraging telemedicine tools. However, diagnosing CVDs outside hospitals can be challenging due to noise interference in electrocardiograms (ECGs), necessitating the use of Signal Quality Assessment (SQA) systems. This paper presents a MATLAB toolbox for automated ECG Signal Quality Assessment, featuring a novel method. Furthermore, the toolbox can extract up to 37 Signal Quality Indices (SQIs), commonly used as features in machine learning-based SQA. Therefore, our software has the potential to facilitate the healthcare process, resulting in efficient and cost-effective cardiovascular care.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101900"},"PeriodicalIF":2.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S235271102400270X/pdfft?md5=ce3ba818258ed3d32c231a2f0aec98c6&pid=1-s2.0-S235271102400270X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142310591","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
E2SCAPy: Electric and electronic symbolic circuit analysis in python E2SCAPy：用 python 进行电气和电子符号电路分析
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-21 DOI: 10.1016/j.softx.2024.101910
Luis Cortés Ramírez , Luis A. Sánchez-Gaspariano , Israel Vivaldo-de-la-Cruz , Carlos Muñiz-Montero , Alejandro I. Bautista-Castillo
{"title":"E2SCAPy: Electric and electronic symbolic circuit analysis in python","authors":"Luis Cortés Ramírez ,&nbsp;Luis A. Sánchez-Gaspariano ,&nbsp;Israel Vivaldo-de-la-Cruz ,&nbsp;Carlos Muñiz-Montero ,&nbsp;Alejandro I. Bautista-Castillo","doi":"10.1016/j.softx.2024.101910","DOIUrl":"10.1016/j.softx.2024.101910","url":null,"abstract":"<div><div>Recently Python has become relevant for many tasks in a variety of disciplines leading to the development of various open source libraries. Our contribution to that cluster of tools is <span><math><msup><mrow><mi>E</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>SCAPy, a useful program for the symbolic computation of analog circuits. The most appealing feature of <span><math><msup><mrow><mi>E</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>SCAPy lies in its ability to solve large circuits with several nodes in few milliseconds due to its DDD algorithm, which drives to the fast solution of the system of equations of the circuit. To show the <span><math><msup><mrow><mi>E</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>SCAPy performance, three nonclassical circuit examples are reported: a WTA/LTA filter, a Memristor and a Fractional Integrator.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101910"},"PeriodicalIF":2.4,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002802/pdfft?md5=8278592a9cef40ab7f05b6e33803fdd0&pid=1-s2.0-S2352711024002802-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142310590","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
Coastal dynamics analyzer (CDA): A QGIS plugin for transect based analysis of coastal erosion 海岸动力学分析器（CDA）：基于横断面的海岸侵蚀分析 QGIS 插件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-20 DOI: 10.1016/j.softx.2024.101894
Pietro Scala, Giorgio Manno, Giuseppe Ciraolo
{"title":"Coastal dynamics analyzer (CDA): A QGIS plugin for transect based analysis of coastal erosion","authors":"Pietro Scala,&nbsp;Giorgio Manno,&nbsp;Giuseppe Ciraolo","doi":"10.1016/j.softx.2024.101894","DOIUrl":"10.1016/j.softx.2024.101894","url":null,"abstract":"<div><div>Coastal erosion is a critical issue affecting shorelines worldwide, imposing effective monitoring and management strategies. We present the Coastal Dynamics Analyzer (CDA), a newly developed QGIS plugin designed for transect-based analysis of shoreline changes, enhancing both the accuracy and efficiency of coastal erosion studies. CDA seamlessly integrates into QGIS, providing an open-source, user-friendly tool that automates the calculation of key shoreline change metrics, including End Point Rate (EPR), Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), and Linear Regression Rate (LRR). This paper presents the motivation behind the CDA's development, its importance in addressing the limitations of existing tools such as the Digital Shoreline Analysis System (DSAS) and Analyzing Moving Boundaries Using R (AMBUR) and details its implementation. The plugin's functionalities are demonstrated through a case study in the Mediterranean Sea, showing its ability to generate accurate and reliable data for coastal management. By providing high quality results with considerable speed, CDA is promising to become a resource for researchers, coastal engineers, and policy makers involved in coastal erosion management and climate change adaptation planning.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101894"},"PeriodicalIF":2.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002644/pdfft?md5=749400015d4540df975d910059e0ab47&pid=1-s2.0-S2352711024002644-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142310589","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
The Forest Conservation Evaluation Tool: Accessible impact evaluation for Latin America 森林保护评估工具：拉丁美洲影响评估
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-17 DOI: 10.1016/j.softx.2024.101892
Allen Blackman
{"title":"The Forest Conservation Evaluation Tool: Accessible impact evaluation for Latin America","authors":"Allen Blackman","doi":"10.1016/j.softx.2024.101892","DOIUrl":"10.1016/j.softx.2024.101892","url":null,"abstract":"<div><p>The Forest Conservation Evaluation Tool is a user-friendly webtool that measures the effect on tree cover loss of place-based conservation policies such as protected areas and payments for environmental services. It allows nontechnical users to conduct impact evaluations using high spatial resolution satellite data on tree cover loss along with statistical techniques that control for confounding factors. Because it has all requisite data on board and features a map- and menu-based interface, most users can generate intuitive results in single short session.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101892"},"PeriodicalIF":2.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002620/pdfft?md5=d9d67ae67b04b8b2cd4defc2effb3cc8&pid=1-s2.0-S2352711024002620-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240059","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
Subgroups: A Python library for Subgroup Discovery 子群：用于发现子群的 Python 库
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-17 DOI: 10.1016/j.softx.2024.101895
Antonio Lopez-Martinez-Carrasco , Jose M. Juarez , Manuel Campos , Francisco Mora-Caselles
{"title":"Subgroups: A Python library for Subgroup Discovery","authors":"Antonio Lopez-Martinez-Carrasco ,&nbsp;Jose M. Juarez ,&nbsp;Manuel Campos ,&nbsp;Francisco Mora-Caselles","doi":"10.1016/j.softx.2024.101895","DOIUrl":"10.1016/j.softx.2024.101895","url":null,"abstract":"<div><p>This manuscript introduces Subgroups, an openly accessible Python library designed to ease the use of Subgroup Discovery (SD) algorithms for machine learning and data science. The Subgroups Library offers several advantages: (1) Efficiency Enhancement: Developed in native Python, unlike other software available, the library prioritizes efficiency to ensure seamless execution of SD algorithms; (2) User-Friendly Interface: Modeled after the popular scikit-learn framework, the library boasts an intuitive interface, streamlining the utilization process for practitioners and non-expert programmers; (3) Trustworthy Algorithm Implementations: Drawing from scientific publications authored by leading experts, the Subgroups Library incorporates rigorously tested algorithmic implementations, ensuring reliability and accuracy in results; (4) Customization and Expansion: The modular architecture of the library facilitates effortless integration of additional quality measures, data structures, and SD algorithms, empowering users to tailor their analyses to specific needs and explore new avenues of research. Furthermore, the Subgroups Library has been successfully employed in diverse scientific papers and projects, underscoring its efficacy and versatility as a valuable tool for SD exploration and application.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101895"},"PeriodicalIF":2.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002656/pdfft?md5=ea31e6714690c56a422c9c3856fba64f&pid=1-s2.0-S2352711024002656-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240081","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
Ichnos: A universal parallel particle tracking tool for groundwater flow simulations Ichnos：用于地下水流模拟的通用并行粒子跟踪工具
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-17 DOI: 10.1016/j.softx.2024.101893
Georgios Kourakos, Thomas Harter, Helen E. Dahlke
{"title":"Ichnos: A universal parallel particle tracking tool for groundwater flow simulations","authors":"Georgios Kourakos,&nbsp;Thomas Harter,&nbsp;Helen E. Dahlke","doi":"10.1016/j.softx.2024.101893","DOIUrl":"10.1016/j.softx.2024.101893","url":null,"abstract":"<div><p>Particle tracking is a common post processing method in groundwater hydrology. In this paper we describe Ichnos, a particle tracking code able to work with flow simulations obtained from either finite difference, finite element, adaptive mesh, or mesh free methods. Ichnos can trace virtual particles (streamlines) in flow fields of any fluid dynamics context, but its application is here focused on groundwater-based flow fields. The code is written in C++ and the structure of the code allows for it to be easily extended. In this study we describe the main features of the code and present several illustrations.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101893"},"PeriodicalIF":2.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002632/pdfft?md5=a4ff28e822d315abd8c6972af5da4569&pid=1-s2.0-S2352711024002632-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240058","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
Version [1.3]- [pyrepo-mcda - Reference objects based MCDA software package] 版本 [1.3]- [pyrepo-mcda - 基于参照对象的 MCDA 软件包］
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-17 DOI: 10.1016/j.softx.2024.101876
Aleksandra Bączkiewicz , Jarosław Wątróbski , Kesra Nermend , Wojciech Sałabun
{"title":"Version [1.3]- [pyrepo-mcda - Reference objects based MCDA software package]","authors":"Aleksandra Bączkiewicz ,&nbsp;Jarosław Wątróbski ,&nbsp;Kesra Nermend ,&nbsp;Wojciech Sałabun","doi":"10.1016/j.softx.2024.101876","DOIUrl":"10.1016/j.softx.2024.101876","url":null,"abstract":"<div><p>This paper presents the pyrepo-mcda Python package upgrade with the implementation of the Preference Vector Method (PVM) multi-criteria method. This upgrade extends the scope of multi-criteria decision analysis offered by this package. Several advantages of the PVM method, such as the reduction of the participation of decision-makers, the possibility of giving individual preference vectors, and the possibility of modification and further development, are in the interest of decision-makers in various multi-criteria decision analysis problems, particularly in the sustainability assessment.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101876"},"PeriodicalIF":2.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002462/pdfft?md5=119956504419246ac277ccf3452803dd&pid=1-s2.0-S2352711024002462-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240060","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
DSIPTS: A high productivity environment for time series forecasting models DSIPTS：时间序列预测模型的高生产率环境
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-16 DOI: 10.1016/j.softx.2024.101875
Andrea Gobbi, Andrea Martinelli, Marco Cristoforetti
{"title":"DSIPTS: A high productivity environment for time series forecasting models","authors":"Andrea Gobbi,&nbsp;Andrea Martinelli,&nbsp;Marco Cristoforetti","doi":"10.1016/j.softx.2024.101875","DOIUrl":"10.1016/j.softx.2024.101875","url":null,"abstract":"<div><p>Several Python libraries have been released for training time series forecasting models in the last few years. Most include classical statistical approaches, machine learning models, and recent deep learning architectures. Despite the great work for releasing such open-source resources, a tool that allows testing Deep Learning architectures in a framework that guarantees transparent input output management, reproducibility of the results, and expandability of the supported models is still lacking. With DSIPTS, we fill this gap, providing the community with a tool for training and comparing Deep Learning models in the time series forecasting field.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101875"},"PeriodicalIF":2.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002450/pdfft?md5=454bb7299198d1b8e383b94efbb603e5&pid=1-s2.0-S2352711024002450-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240079","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
Towards digital health: Integrating federated learning and crowdsensing through the Contigo app 迈向数字健康：通过 Contigo 应用程序整合联合学习和群体感知技术
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2024-09-16 DOI: 10.1016/j.softx.2024.101885
Daniel Flores-Martin , Sergio Laso , Javier Berrocal , Juan M. Murillo
{"title":"Towards digital health: Integrating federated learning and crowdsensing through the Contigo app","authors":"Daniel Flores-Martin ,&nbsp;Sergio Laso ,&nbsp;Javier Berrocal ,&nbsp;Juan M. Murillo","doi":"10.1016/j.softx.2024.101885","DOIUrl":"10.1016/j.softx.2024.101885","url":null,"abstract":"<div><p>The growing demand for effective healthcare has driven advances in digital health. This digitization supposes a challenge from the point of view of privacy and the treatment of sensitive personal data while providing non-intrusive and easy-to-use digital mechanisms. This paper presents Contigo: a health monitoring system that integrates a mobile application and a web platform for detecting anomalies using Federated Learning techniques. The mobile application collects health and personal data to train a personal predictive model. It is then anonymized and aggregated into a global model to improve efficiency, reducing adoption time for new users. At the same time, the web platform allows healthcare professionals to access the data for its analysis and validation. Contigo addresses the need for user-friendly digital mechanisms in healthcare, addressing privacy concerns while improving data-driven decision-making for professionals and personalized patient care. This approach ensures privacy and facilitates continuous model improvement, providing personalized, proactive, and non-intrusive patient health analytics.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101885"},"PeriodicalIF":2.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002553/pdfft?md5=60c024f87dfd92cb589b68abcccf3426&pid=1-s2.0-S2352711024002553-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240080","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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