SoftwareX最新文献_第3页

A Kokkos-accelerated Moment Tensor Potential implementation for LAMMPS 一种用于LAMMPS的kokkos -加速矩张量势实现

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2026-02-02 DOI: 10.1016/j.softx.2026.102524

Zijian Meng , Karim Zongo , Edmanuel Torres , Christopher Maxwell , Ryan Grant , Laurent Karim Béland

引用次数: 0

Local software: Integrated design and geo-computing workflows for urban design 本地软件：城市设计的集成设计和地理计算工作流程

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2025-12-03 DOI: 10.1016/j.softx.2025.102457

Carlos Sandoval Olascoaga , Nicholas de Monchaux

{"title":"Local software: Integrated design and geo-computing workflows for urban design","authors":"Carlos Sandoval Olascoaga , Nicholas de Monchaux","doi":"10.1016/j.softx.2025.102457","DOIUrl":"10.1016/j.softx.2025.102457","url":null,"abstract":"<div><div>While architects and planners routinely rely on Geospatial Information Systems (GIS) and Computer Aided Design (CAD) tools, both types of tools are infrastructurally incompatible leading to cumbersome workarounds, lack of adoption in practice, and missed opportunities to incorporate the large-scale geographic insights of GIS with the building-scale precision of CAD into a seamless design process. Local Software (LS) inquires into how bringing together CAD and GIS tools and workflows can lead to more sustainable urban design proposals. The framework introduces Site Packages (SP), a cross-platform information model based on GeoJSON that enables seamless integration between design and analysis tools and a new design methodology that connects large scale modeling with small scale design decisions. LS provides a web interface and open-source plugins for Grasshopper and QGIS, that allow designers to parametrically generate networked urban interventions while evaluating their ecological and social impacts through GIS. Case studies have demonstrated that proposals created with the LS framework can replace 88–96 % of traditional stormwater systems at 50 % lower cost of underground work, while enhancing urban resilience, reducing heat island effects, and providing community benefits.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102457"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PhishingWebCollector: Async python library for automated phishing feed collection PhishingWebCollector：用于自动网络钓鱼提要收集的异步python库

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2025-12-05 DOI: 10.1016/j.softx.2025.102463

Damian Frąszczak, Edyta Frąszczak

引用次数: 0

FibreApp: Mobile machine learning tool for fruit and vegetable fiber content FibreApp：果蔬纤维含量的移动机器学习工具

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2026-01-23 DOI: 10.1016/j.softx.2026.102528

Vadym Chibrikov, Justyna Cybulska, Artur Zdunek

{"title":"FibreApp: Mobile machine learning tool for fruit and vegetable fiber content","authors":"Vadym Chibrikov, Justyna Cybulska, Artur Zdunek","doi":"10.1016/j.softx.2026.102528","DOIUrl":"10.1016/j.softx.2026.102528","url":null,"abstract":"<div><div>The issue of food quality and its control has become a daily routine for humanity, driven by both health and economic reasons. Among other components, plant cell wall components—such as cellulose, hemicellulose, and pectin—have several pro-health roles in the human organism that are barely discussed in public. To address this, there is a clear need for a portable digital framework built on accurate, accessible, and scientifically-proven data. Here, our commitment was the development of <em>FibreApp</em>, an Android/iOS mobile application that helps users obtain data on the chemical composition of common fruit and vegetable species available on the European market. <em>FibreApp</em>'s architecture was designed as a hybrid local/offline system that integrates on-device machine learning for visual identification with a pre-loaded, unified database of fruit and vegetable compositional parameters. A machine learning-powered livestream tool for image classification of fruits and vegetables was included in the app by rigorously following a systematic image acquisition protocol, coupled with a transfer learning approach using pre-trained feature extractors to train the machine learning models. The latter performed well despite significant changes in lighting and diverse polar orientations, as well as during polyclass image classification. <em>FibreApp</em> was released and field-tested, positioning it to capture a niche in improving public awareness of fruits and vegetables as a source of functional polysaccharides.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102528"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DiLLeMa: An extensible and scalable framework for distributed large language models (LLMs) inference on multi-GPU clusters DiLLeMa：一个可扩展和可伸缩的框架，用于在多gpu集群上进行分布式大型语言模型（llm）推理

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2026-01-29 DOI: 10.1016/j.softx.2026.102537

Robby Ulung Pambudi, Ary Mazharuddin Shiddiqi, Royyana Muslim Ijtihadie, Muhammad Nabil Akhtar Raya Amoriza, Hardy Tee, Fadhl Akmal Madany, Rizky Januar Akbar, Dini Adni Navastara

{"title":"DiLLeMa: An extensible and scalable framework for distributed large language models (LLMs) inference on multi-GPU clusters","authors":"Robby Ulung Pambudi, Ary Mazharuddin Shiddiqi, Royyana Muslim Ijtihadie, Muhammad Nabil Akhtar Raya Amoriza, Hardy Tee, Fadhl Akmal Madany, Rizky Januar Akbar, Dini Adni Navastara","doi":"10.1016/j.softx.2026.102537","DOIUrl":"10.1016/j.softx.2026.102537","url":null,"abstract":"<div><div>The increasing demand for scalable and responsive Large Language Model (LLM) applications has accelerated the need for distributed inference systems capable of handling high concurrency and heterogeneous GPU resources. This paper introduces DiLLeMa, an extensible framework for distributed LLM deployment on multi-GPU clusters, designed to improve inference efficiency through workload parallelization and adaptive resource management. Built upon the Ray distributed computing framework, DiLLeMa orchestrates LLM inference across multiple nodes while maintaining balanced GPU utilization and low-latency response. The system integrates a <em>FastAPI</em>-based backend for coordination and API management, a <em>React</em>-based frontend for interactive access, and a vLLM inference engine optimized for high-throughput execution. Complementary modules for data preprocessing, semantic embedding, and vector-based retrieval further enhance contextual relevance during response generation. Illustrative examples demonstrate that DiLLeMa effectively reduces inference latency and scales efficiently.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102537"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Version [2.0]-[NeoCoMM: Neocortical neuro-inspired computational model for realistic microscale simulations] 版本[2.0]-[NeoCoMM：用于现实微观模拟的新皮层神经启发计算模型]

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2026-01-07 DOI: 10.1016/j.softx.2025.102505

M. Yochum , F. Karimi , F. Wendling, M. Al Harrach

引用次数: 0

HySim-IRIS: Hybrid similarity interactive restoration and inpainting suite HySim-IRIS：混合相似性交互式修复和喷漆套件

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2025-12-17 DOI: 10.1016/j.softx.2025.102484

Saad Noufel, Nadir Maaroufi, Mehdi Najib, Mohamed Bakhouya

引用次数: 0

Mobile2D-3D-RoboticSim: A robotic platform for computational thinking assessment in STEM and STEAM education Mobile2D-3D-RoboticSim：用于STEM和STEAM教育中计算思维评估的机器人平台

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2025-12-09 DOI: 10.1016/j.softx.2025.102473

José Hugo Barrón-Zambrano , Marco Aurelio Nuño-Maganda , Melchor Hernández-Díaz , José de Jesús Rangel-Magdaleno , Yahir Hernández-Mier

{"title":"Mobile2D-3D-RoboticSim: A robotic platform for computational thinking assessment in STEM and STEAM education","authors":"José Hugo Barrón-Zambrano , Marco Aurelio Nuño-Maganda , Melchor Hernández-Díaz , José de Jesús Rangel-Magdaleno , Yahir Hernández-Mier","doi":"10.1016/j.softx.2025.102473","DOIUrl":"10.1016/j.softx.2025.102473","url":null,"abstract":"<div><div>Education in Science, Technology, Engineering, Arts, and Mathematics (STEAM) is crucial for developing essential skills in today’s society. A key issue for researchers in the Education and Behavioral Sciences (EBS) fields is to assess the evolution of Computational Thinking (CT) in learners through the use of educational robotics, which is a powerful tool that enhances learning by allowing students to apply theoretical knowledge to real-world scenarios. In this article, we propose a 2D-3D virtual and physical robotic platform for STEM/STEAM education, enabling users to interact with a low-cost line-following educational robotic platform, equipped with an onboard computer, sensors, and actuators. The platform is user-programmable and integrates the ROS operating system to define the robot’s movement and path, as well as to visualize the robot’s movement in real-time. The platform is also accessible to educators and the general public for exploratory and pedagogical use. We report results related to the application of the competent Computational Thinking Test (cCTt) instrument to a small group of students, which may be of particular relevance to the Education and Behavioral Sciences (EBS) community for validating the acquisition of CT skills through the proposed platform for larger learner groups.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102473"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dropout insight: Educational risk dashboard with counterfactual explanations 辍学洞察：带有反事实解释的教育风险仪表板

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2026-02-05 DOI: 10.1016/j.softx.2026.102551

Marta Muñoz-Muñoz, Christian Luna, Juan A. Lara, C Romero

{"title":"Dropout insight: Educational risk dashboard with counterfactual explanations","authors":"Marta Muñoz-Muñoz, Christian Luna, Juan A. Lara, C Romero","doi":"10.1016/j.softx.2026.102551","DOIUrl":"10.1016/j.softx.2026.102551","url":null,"abstract":"<div><div>The prediction and prevention of students at risk of dropout are two of the most important challenges in the educational domain. Although some commercial predictive tools support at-risk estimation and provide explanations of the associated factors, none of them offer recommendations to address or reverse potential dropout cases. This paper proposes Dropout Insight as a prescriptive web-based interactive tool that automates the entire data-mining process to suggest specific decisions. It supports the loading and processing of student data, the selection of the best predictive model, and the visualization of results through interpretation techniques based on explainers. The tool provides a clear and visually intuitive interface that enables users to explore risk factors and simulate alternative scenarios, including instructors and other stakeholders, without prior knowledge of data mining. It offers not only traditional individual counterfactual explanations, but also novel group counterfactuals, which generate hypothetical clusters or groups of students with similar behavioral profiles. These groups help recover the largest possible number of at-risk students with less effort and cost by offering a single, shared recommendation for intervention. By integrating automated prediction tools with visual, explainable artificial intelligence methods and counterfactual reasoning, the tool becomes a highly valuable and innovative resource to support pedagogical decision-making and guide proactive educational policies aimed at preventing dropout.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102551"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PyCompact: An integrated workflow for discrete element method–multi-particle finite element method for powder compaction simulation PyCompact：一个集成的离散元方法工作流-粉末压实模拟的多粒子有限元方法

IF 2.4 4区计算机科学

SoftwareX Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.softx.2025.102495

Majid Mohammadhosseinzadeh, Hossein Ghorbani-Menghari, Ji Hoon Kim

引用次数: 0