Pub Date : 2025-06-01Epub Date: 2025-04-22DOI: 10.1016/j.simpa.2025.100752
Soham Patel , Kailas Patil , Prawit Chumchu
OBSERVER is a browser extension intended to record user interactions and their associated DOM structures in real time. It records activities including clicks, inputs, and scrolling, extracts contextual information, and exports it in JSON format. The tool improves test automation, synthetic monitoring, and debugging by offering accurate and reusable interaction data. OBSERVER employs a start-and-stop method to facilitate effective data gathering while reducing overhead. This study examines its design, applications, and prospective research prospects, emphasizing its contributions to automated testing, observability, and performance enhancement in web applications.
{"title":"OBSERVER: Observing Browser Synthetic Environments for Robotization, Verification, Efficiency, and Resilience","authors":"Soham Patel , Kailas Patil , Prawit Chumchu","doi":"10.1016/j.simpa.2025.100752","DOIUrl":"10.1016/j.simpa.2025.100752","url":null,"abstract":"<div><div>OBSERVER is a browser extension intended to record user interactions and their associated DOM structures in real time. It records activities including clicks, inputs, and scrolling, extracts contextual information, and exports it in JSON format. The tool improves test automation, synthetic monitoring, and debugging by offering accurate and reusable interaction data. OBSERVER employs a start-and-stop method to facilitate effective data gathering while reducing overhead. This study examines its design, applications, and prospective research prospects, emphasizing its contributions to automated testing, observability, and performance enhancement in web applications.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100752"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-05-05DOI: 10.1016/j.simpa.2025.100761
Achour Khaoula , Lachgar Mohamed , Elloubab Aya , Ait Ouahda Younes , Laanaoui My Driss , Ourahay Mustapha
EduXgame is a gamified mobile application designed to enhance the learning experience of secondary education students. The application integrates AI-driven content generation, gamification features, and interactive learning tools such as quizzes, flipcards, and matching games. It provides educators with a web interface to upload chapters, which are processed by an AI model to generate learning material dynamically. eduXgame transforms traditional learning methods into engaging, competitive, and interactive experiences, making education more accessible and enjoyable for students.
{"title":"EduXgame: Gamified learning for secondary education","authors":"Achour Khaoula , Lachgar Mohamed , Elloubab Aya , Ait Ouahda Younes , Laanaoui My Driss , Ourahay Mustapha","doi":"10.1016/j.simpa.2025.100761","DOIUrl":"10.1016/j.simpa.2025.100761","url":null,"abstract":"<div><div>EduXgame is a gamified mobile application designed to enhance the learning experience of secondary education students. The application integrates AI-driven content generation, gamification features, and interactive learning tools such as quizzes, flipcards, and matching games. It provides educators with a web interface to upload chapters, which are processed by an AI model to generate learning material dynamically. eduXgame transforms traditional learning methods into engaging, competitive, and interactive experiences, making education more accessible and enjoyable for students.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100761"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-28DOI: 10.1016/j.simpa.2025.100762
Annice Najafi, Shokoufeh Mirzaei
Multi-Criteria Decision Making (MCDM) is a branch of operations research used in a variety of domains from health care to engineering to facilitate decision-making among multiple options based on specific criteria. Several R packages have been developed for the application of traditional MCDM approaches. However, as the discipline has advanced, many new approaches have emerged, necessitating the development of innovative and comprehensive tools to enhance the accessibility of these methodologies. Here, we introduce RMCDA, a comprehensive and universal R package that offers access to a variety of established MCDM approaches (e.g., AHP, TOPSIS, PROMETHEE, and VIKOR), along with newer techniques such as Stratified MCDM (SMCDM) and the Stratified Best–Worst Method (SBWM). Our open source software intends to broaden the practical use of these methods through supplementary visualization tools and straightforward installation.
{"title":"RMCDA: The comprehensive R library for applying Multi-Criteria Decision Analysis methods","authors":"Annice Najafi, Shokoufeh Mirzaei","doi":"10.1016/j.simpa.2025.100762","DOIUrl":"10.1016/j.simpa.2025.100762","url":null,"abstract":"<div><div>Multi-Criteria Decision Making (MCDM) is a branch of operations research used in a variety of domains from health care to engineering to facilitate decision-making among multiple options based on specific criteria. Several <span>R</span> packages have been developed for the application of traditional MCDM approaches. However, as the discipline has advanced, many new approaches have emerged, necessitating the development of innovative and comprehensive tools to enhance the accessibility of these methodologies. Here, we introduce <span>RMCDA</span>, a comprehensive and universal <span>R</span> package that offers access to a variety of established MCDM approaches (e.g., <span>AHP</span>, <span>TOPSIS</span>, <span>PROMETHEE</span>, and <span>VIKOR</span>), along with newer techniques such as Stratified MCDM (<span>SMCDM</span>) and the Stratified Best–Worst Method (<span>SBWM</span>). Our open source software intends to broaden the practical use of these methods through supplementary visualization tools and straightforward installation.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100762"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-05-15DOI: 10.1016/j.simpa.2025.100768
Muhamad Keenan Ario , Muhammad Fikri Hasani , Khairatul Balqis , Messya Carment
Extended reality in education has advanced, offering safe, immersive simulations. Agriculture, a key area, lacks urban exposure. HoloFarm, a VR-based farming simulation, addresses this gap using Unity and C#. It integrates physical movement, joystick navigation, and spatial audio for crop cultivation. Evaluated with 27 urban users via the Igroup Presence Questionnaire, it showed strong spatial (M=5.59) and general presence (M=5.81), though realism (M=4.10) and involvement (M=4.77). Future updates will enhance realism and enable collaborative learning, bridging theoretical and practical agricultural knowledge.
{"title":"HoloFarm: Enhancing agricultural learning through immersive technology","authors":"Muhamad Keenan Ario , Muhammad Fikri Hasani , Khairatul Balqis , Messya Carment","doi":"10.1016/j.simpa.2025.100768","DOIUrl":"10.1016/j.simpa.2025.100768","url":null,"abstract":"<div><div>Extended reality in education has advanced, offering safe, immersive simulations. Agriculture, a key area, lacks urban exposure. HoloFarm, a VR-based farming simulation, addresses this gap using Unity and C#. It integrates physical movement, joystick navigation, and spatial audio for crop cultivation. Evaluated with 27 urban users via the Igroup Presence Questionnaire, it showed strong spatial (M=5.59) and general presence (M=5.81), though realism (M=4.10) and involvement (M=4.77). Future updates will enhance realism and enable collaborative learning, bridging theoretical and practical agricultural knowledge.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100768"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-28DOI: 10.1016/j.simpa.2025.100757
Irsyad Fikriansyah Ramadhan , Ntivuguruzwa Jean De La Croix , Tohari Ahmad
Ensuring secure data transmission has become crucial in modern digital communication, especially with rising risks of interception and manipulation. Steganography is vital in protecting sensitive information by embedding it within digital images without compromising their visual quality. This paper introduces IrsyadStego, an open-source using a Difference Expansion method with customized pixel difference to improve payload capacity and image fidelity. Experimental results show high PSNR and SSIM values, with a 100 dB PSNR between the cover image and the image recovered from extraction—demonstrating full reversibility. IrsyadStego supports further research, contributing to robust, secure, and efficient steganographic techniques in digital security.
{"title":"IrsyadStego: An open-source code to secure data using pixel differencing paradigm within the neighboring pixels of a digital image","authors":"Irsyad Fikriansyah Ramadhan , Ntivuguruzwa Jean De La Croix , Tohari Ahmad","doi":"10.1016/j.simpa.2025.100757","DOIUrl":"10.1016/j.simpa.2025.100757","url":null,"abstract":"<div><div>Ensuring secure data transmission has become crucial in modern digital communication, especially with rising risks of interception and manipulation. Steganography is vital in protecting sensitive information by embedding it within digital images without compromising their visual quality. This paper introduces IrsyadStego, an open-source using a Difference Expansion method with customized pixel difference to improve payload capacity and image fidelity. Experimental results show high PSNR and SSIM values, with a 100 dB PSNR between the cover image and the image recovered from extraction—demonstrating full reversibility. IrsyadStego supports further research, contributing to robust, secure, and efficient steganographic techniques in digital security.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100757"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-05-02DOI: 10.1016/j.simpa.2025.100753
Seifallah Elfetni , Reza Darvishi Kamachali
This paper introduces PINNs-MPF, a novel Machine Learning-based solver designed for Multi-Phase-Field (MPF) and diffuse interface simulations, offering innovative approaches to address complex challenges in addressing microstructure evolution in polycrystalline materials using Machine Learning. The framework not only surpasses current limitations in handling multi-phase problems but also allows for potential upscaling to tackle more intricate scenarios. Developed in Python, the related code leverages optimized libraries like TensorFlow, showcasing efficiency and potential scalability in materials science and engineering simulations. This framework, integrating advanced techniques such as multi-networking and training optimization, setting a new standard in predictive capabilities and understanding complex physical phenomena.
{"title":"PINNs-MPF: An Efficient Physics-Informed Machine Learning-based Solver for Multi-Phase-Field Simulations using Tensorflow","authors":"Seifallah Elfetni , Reza Darvishi Kamachali","doi":"10.1016/j.simpa.2025.100753","DOIUrl":"10.1016/j.simpa.2025.100753","url":null,"abstract":"<div><div>This paper introduces PINNs-MPF, a novel Machine Learning-based solver designed for Multi-Phase-Field (MPF) and diffuse interface simulations, offering innovative approaches to address complex challenges in addressing microstructure evolution in polycrystalline materials using Machine Learning. The framework not only surpasses current limitations in handling multi-phase problems but also allows for potential upscaling to tackle more intricate scenarios. Developed in Python, the related code leverages optimized libraries like TensorFlow, showcasing efficiency and potential scalability in materials science and engineering simulations. This framework, integrating advanced techniques such as multi-networking and training optimization, setting a new standard in predictive capabilities and understanding complex physical phenomena.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100753"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Structures based on Triply periodic minimal surfaces (TPMS) are employed in catalysis, energy storage, and tissue engineering for biomedical applications, among others. They excel in mechanical performance, surface area, and transport properties compared to traditional lattice structures. This work introduces a versatile tool designed to facilitate the creation and manipulation of TPMS-based structures. It provides total control over lattice properties, for 3D printing and Finite Element simulation purposes. By operating within a Python environment, ensuring accessibility and compatibility with both online and offline workflows, LisbonTPMS-tool aims to become a valuable resource to employ TPMS-based structures in practical applications.
{"title":"LISBON TPMS TOOL: An open-source tool for the design of TPMS structures for engineering applications","authors":"J.E. Santos , R.B. Ruben , P.R. Fernandes , A.P.G. Castro","doi":"10.1016/j.simpa.2025.100747","DOIUrl":"10.1016/j.simpa.2025.100747","url":null,"abstract":"<div><div>Structures based on Triply periodic minimal surfaces (TPMS) are employed in catalysis, energy storage, and tissue engineering for biomedical applications, among others. They excel in mechanical performance, surface area, and transport properties compared to traditional lattice structures. This work introduces a versatile tool designed to facilitate the creation and manipulation of TPMS-based structures. It provides total control over lattice properties, for 3D printing and Finite Element simulation purposes. By operating within a Python environment, ensuring accessibility and compatibility with both online and offline workflows, LisbonTPMS-tool aims to become a valuable resource to employ TPMS-based structures in practical applications.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100747"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-28DOI: 10.1016/j.simpa.2025.100758
Frederico Schmitt Kremer, João Pedro Gomes Greco, Elias Eduardo Barbosa da Rosa
Biocides play a critical role in controlling microorganisms, yet their widespread use has contributed to the emergence of bacterial resistance, often linked to antibiotic cross-resistance. Multidrug-resistant pathogens pose a growing public health concern due to their adaptability and presence in various environments, including hospitals. Previously, our group developed the Biocide Resistance Scanner (BRS), a bioinformatics pipeline designed to identify biocide resistance genes in the mobilome of ESKAPE strains isolated in Brazil. Now, we detail the implementation of BRS and extend its application to the analysis of the pathogen Campylobacter jejuni.
{"title":"BRS: A tool for detecting biocide resistance in mobile elements","authors":"Frederico Schmitt Kremer, João Pedro Gomes Greco, Elias Eduardo Barbosa da Rosa","doi":"10.1016/j.simpa.2025.100758","DOIUrl":"10.1016/j.simpa.2025.100758","url":null,"abstract":"<div><div>Biocides play a critical role in controlling microorganisms, yet their widespread use has contributed to the emergence of bacterial resistance, often linked to antibiotic cross-resistance. Multidrug-resistant pathogens pose a growing public health concern due to their adaptability and presence in various environments, including hospitals. Previously, our group developed the Biocide Resistance Scanner (BRS), a bioinformatics pipeline designed to identify biocide resistance genes in the mobilome of ESKAPE strains isolated in Brazil. Now, we detail the implementation of BRS and extend its application to the analysis of the pathogen <em>Campylobacter jejuni</em>.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100758"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-29DOI: 10.1016/j.simpa.2025.100766
Leandro Rodrigues da Silva Souza , Daniel Hilário da Silva , Caio Tonus Ribeiro , Daiane Alves da Silva , Slawomir J. Nasuto , Catherine M. Sweeney-Reed , Adriano de Oliveira Andrade , Adriano Alves Pereira
Bibliometric analyses often depend on extracting metadata from large scientific databases, a process that is still largely manual, repetitive, and error prone. This paper presents PubMedMetaTool, an open-source Python-based solution that automates the retrieval and transformation of bibliographic metadata from PubMed, using either article titles or Digital Object Identifiers as input. The tool implements a modular pipeline that extracts metadata using NCBI’s Entrez programming utilities and transforms it into formats compatible with tools such as Bibliometrix, VOSviewer, and pyBibX. Designed to be transparent and configurable, the tool improves bibliometric workflow efficiency, accuracy, and interoperability workflows.
{"title":"PubMedMetaTool: Automated metadata extraction from PubMed using Python for bibliometric analysis","authors":"Leandro Rodrigues da Silva Souza , Daniel Hilário da Silva , Caio Tonus Ribeiro , Daiane Alves da Silva , Slawomir J. Nasuto , Catherine M. Sweeney-Reed , Adriano de Oliveira Andrade , Adriano Alves Pereira","doi":"10.1016/j.simpa.2025.100766","DOIUrl":"10.1016/j.simpa.2025.100766","url":null,"abstract":"<div><div>Bibliometric analyses often depend on extracting metadata from large scientific databases, a process that is still largely manual, repetitive, and error prone. This paper presents PubMedMetaTool, an open-source Python-based solution that automates the retrieval and transformation of bibliographic metadata from PubMed, using either article titles or Digital Object Identifiers as input. The tool implements a modular pipeline that extracts metadata using NCBI’s Entrez programming utilities and transforms it into formats compatible with tools such as Bibliometrix, VOSviewer, and pyBibX. Designed to be transparent and configurable, the tool improves bibliometric workflow efficiency, accuracy, and interoperability workflows.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100766"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-28DOI: 10.1016/j.simpa.2025.100750
João Pedro M. Saraiva , Rodney V. Fonseca , Rogério G. Negri , Aluísio Pinheiro
This paper introduces an unsupervised method for detecting spatiotemporal changes in a series of remotely sensed images. Specifically, we employ a fully automatic, data-driven framework that incorporates wavelet approximation, wavelet energy apportionment, and high-dimensional correlation screening of wavelet coefficients. This approach processes sequences of images and produces a mapping of changed and non-changed locations over the analyzed period.
{"title":"WECS: A wavelet energy correlation screening based method for unsupervised change detection using remote sensing image series","authors":"João Pedro M. Saraiva , Rodney V. Fonseca , Rogério G. Negri , Aluísio Pinheiro","doi":"10.1016/j.simpa.2025.100750","DOIUrl":"10.1016/j.simpa.2025.100750","url":null,"abstract":"<div><div>This paper introduces an unsupervised method for detecting spatiotemporal changes in a series of remotely sensed images. Specifically, we employ a fully automatic, data-driven framework that incorporates wavelet approximation, wavelet energy apportionment, and high-dimensional correlation screening of wavelet coefficients. This approach processes sequences of images and produces a mapping of changed and non-changed locations over the analyzed period.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100750"},"PeriodicalIF":1.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143881638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号