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FARM-VSS: A web-based visualizer and summarizer suite with Gen-AI-enabled interpretation for Fuzzy association rule mining FARM-VSS：基于web的可视化工具和总结器套件，支持gen - ai的模糊关联规则挖掘解释
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-04-07 DOI: 10.1016/j.softx.2025.102154
Vartul Shrivastava , Shekhar Shukla
{"title":"FARM-VSS: A web-based visualizer and summarizer suite with Gen-AI-enabled interpretation for Fuzzy association rule mining","authors":"Vartul Shrivastava ,&nbsp;Shekhar Shukla","doi":"10.1016/j.softx.2025.102154","DOIUrl":"10.1016/j.softx.2025.102154","url":null,"abstract":"<div><div>In the current landscape of data analytics, Fuzzy Association Rule Mining (FARM) is being extensively employed to produce interpretable fuzzy rules. In the literature, various toolkits exist that assist practitioners in performing FARM-based inference on their dataset, but a comprehensive open-source GUI-enabled toolkit that facilitates Generative AI-based inference, customizable fuzzy partitioning and brute-force FARM Rules Explorer is scarce in existing toolkits. This research aims to bridge this gap by offering a comprehensive technical suite for FARM and Weighted FARM (WFARM) using the Fuzzy Apriori algorithm to aid researchers and practitioners.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102154"},"PeriodicalIF":2.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785139","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
Laser_RobMap: An open source ROS2 compatible tool for 3D mapping using a Mobile Robot and 2D LiDAR Laser_RobMap：一个开源的ROS2兼容工具，用于使用移动机器人和2D激光雷达进行3D测绘
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-04-05 DOI: 10.1016/j.softx.2025.102142
Daniel D. Yanyachi, Yamir H. Anco-Agüero, German A. Echaiz, Miguel A. Esquivel, Alfredo Mamani-Saico, Pablo R. Yanyachi
{"title":"Laser_RobMap: An open source ROS2 compatible tool for 3D mapping using a Mobile Robot and 2D LiDAR","authors":"Daniel D. Yanyachi,&nbsp;Yamir H. Anco-Agüero,&nbsp;German A. Echaiz,&nbsp;Miguel A. Esquivel,&nbsp;Alfredo Mamani-Saico,&nbsp;Pablo R. Yanyachi","doi":"10.1016/j.softx.2025.102142","DOIUrl":"10.1016/j.softx.2025.102142","url":null,"abstract":"<div><div>We propose a tool for implementing a low-cost 3D mapping system using a vertically mounted 2D LiDAR sensor on a mobile robot, compatible with ROS2. The tool adapts to any ROS2-enabled robot that provides inertial and odometry data, with configurable parameters to optimize performance on systems with limited computational resources. Its main objective is to deliver a cost-effective 3D mapping solution for autonomous navigation using 3D SLAM. The results can be exported as 3D point clouds in PCD, LAS, and PLY formats, with an optional voxelization feature for efficient data management.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102142"},"PeriodicalIF":2.4,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776602","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
pytopicgram: A library for data extraction and topic modeling from Telegram channels pytopicgram：用于从Telegram频道提取数据和主题建模的库
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-04-02 DOI: 10.1016/j.softx.2025.102141
Juan Gómez-Romero, Javier Cantón Correa, Rubén Pérez Mercado, Francisco Prados Abad, Miguel Molina-Solana, Waldo Fajardo
{"title":"pytopicgram: A library for data extraction and topic modeling from Telegram channels","authors":"Juan Gómez-Romero,&nbsp;Javier Cantón Correa,&nbsp;Rubén Pérez Mercado,&nbsp;Francisco Prados Abad,&nbsp;Miguel Molina-Solana,&nbsp;Waldo Fajardo","doi":"10.1016/j.softx.2025.102141","DOIUrl":"10.1016/j.softx.2025.102141","url":null,"abstract":"<div><div>Telegram is a popular platform for communication, generating large volumes of messages through its open channels. <span>pytopicgram</span> is a Python library designed to help researchers efficiently collect, organize, and analyze Telegram messages, addressing the increasing demand to understand online discourse. Key functionalities include efficient message retrieval, computation of engagement metrics, and advanced topic modeling. By automating the data extraction and analysis pipeline, <span>pytopicgram</span> simplifies the investigation of how content spreads, how topics evolve, and how audiences interact on Telegram. The library’s modular architecture ensures flexibility and scalability, making it suitable for diverse applications. This paper describes the design, main features, and illustrative examples that demonstrate <span>pytopicgram</span>’s practical effectiveness for studying public conversations.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102141"},"PeriodicalIF":2.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748050","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
Dynamical opinion clusters exploration suite: Modeling social media opinion dynamics 动态意见集群探索套件：建模社会媒体意见动态
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-04-01 DOI: 10.1016/j.softx.2025.102136
Henrique Ferraz de Arruda , Kleber Andrade Oliveira , Yamir Moreno
{"title":"Dynamical opinion clusters exploration suite: Modeling social media opinion dynamics","authors":"Henrique Ferraz de Arruda ,&nbsp;Kleber Andrade Oliveira ,&nbsp;Yamir Moreno","doi":"10.1016/j.softx.2025.102136","DOIUrl":"10.1016/j.softx.2025.102136","url":null,"abstract":"<div><div>The escalating use of social media in recent years has made the study of opinion dynamics a crucial area for understanding societal trends. As digital communication platforms continue to shape collective consciousness, understanding the evolution, interaction, and spread of opinions has become imperative. Researchers have approached this phenomenon from a variety of perspectives, ranging from sociology to data analytics to computational simulation. To address the challenges posed by the multifaceted and multidisciplinary nature of this research, coupled with the recent scarcity of data, computational simulation has emerged as a key tool for understanding opinion dynamics in social networks. This paper presents a Python library, DOCES, designed to simulate essential features of real-world social networks. The library includes the simulation of a social network algorithm, user prioritization, and the ability to model changes in friendships.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102136"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738724","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
MCTS-NC: A thorough GPU parallelization of Monte Carlo Tree Search implemented in Python via numba.cuda MCTS-NC：通过numba.cuda在Python中实现的蒙特卡罗树搜索的彻底GPU并行化
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-04-01 DOI: 10.1016/j.softx.2025.102139
Przemysław Klęsk
{"title":"MCTS-NC: A thorough GPU parallelization of Monte Carlo Tree Search implemented in Python via numba.cuda","authors":"Przemysław Klęsk","doi":"10.1016/j.softx.2025.102139","DOIUrl":"10.1016/j.softx.2025.102139","url":null,"abstract":"<div><div>With CUDA computational model in mind, we introduce MCTS-NC (Monte Carlo Tree Search–<span>numba.cuda</span> ). It contains four, fast-operating and thoroughly parallel, variants of the MCTS algorithm. The design of MCTS-NC combines three parallelization levels (leaf<!--> <!-->/<!--> <!-->root<!--> <!-->/<!--> <!-->tree parallelizations). Additionally, all algorithmic stages – selections, expansions, playouts, backups – employ multiple GPU threads. We apply suitable <em>reduction</em> patterns to carry out summations or max<!--> <!-->/<!--> <!-->argmax operations. The implementation uses very few device-host memory transfers, no atomic operations (is lock-free), and takes advantage of threads cooperation. In the mathematical part of this article, we demonstrate how the confidence bounds on estimated action values become tightened by both the number of independent concurrent playouts and the number of independent concurrent trees. The experimental part reports the performance of MCTS-NC on two game examples: Connect4 and Gomoku. All computational results can be exactly reproduced.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102139"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738725","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
SARRA-Py: A Python-based geospatial simulation framework for agroclimatic modeling SARRA-Py：一个基于python的地理空间模拟框架，用于农业气候建模
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-03-29 DOI: 10.1016/j.softx.2025.102145
Jérémy Lavarenne , Asse Mbengue
{"title":"SARRA-Py: A Python-based geospatial simulation framework for agroclimatic modeling","authors":"Jérémy Lavarenne ,&nbsp;Asse Mbengue","doi":"10.1016/j.softx.2025.102145","DOIUrl":"10.1016/j.softx.2025.102145","url":null,"abstract":"<div><div>SARRA-Py is an open-source, Python-based adaptation of the long-standing SARRA crop model family–specifically building upon SARRA-H to enable spatially explicit agroclimatic simulations in tropical and data-limited environments. By leveraging Python's geospatial libraries (e.g., Xarray), SARRA-Py extends SARRA-H's proven crop physiology routines to large-scale, raster-based analyses, streamlines ingestion of diverse climate inputs with minimal preprocessing, and eases model customization via a modular code structure. Users interact with SARRA-Py primarily through Jupyter notebooks that provide guided workflows for data preparation, parameter configuration, and visualization of results. This design closes the gap between point-based crop models and broader geospatial frameworks, offering a practical tool for agricultural risk management, climate adaptation studies, and yield forecasting. Consequently, SARRA-Py fosters reproducible, scenario-based analyses and informs decision-making in vulnerable regions where water deficits, sparse ground observations, and climate variability threatens food security.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102145"},"PeriodicalIF":2.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724911","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
ReflectDetect: A software tool for AprilTag-guided in-flight radiometric calibration for UAV-mounted 2D snapshot multi-camera imagery ReflectDetect：一个软件工具，用于apriltag制导的飞行辐射校准，用于无人机安装的2D快照多摄像头图像
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-03-28 DOI: 10.1016/j.softx.2025.102150
Luca Joshua Francis , Lewis Gabriel B. Geissler , Nathan Okole , Bela Gipp , Cyrill Stachniss , René Heim
{"title":"ReflectDetect: A software tool for AprilTag-guided in-flight radiometric calibration for UAV-mounted 2D snapshot multi-camera imagery","authors":"Luca Joshua Francis ,&nbsp;Lewis Gabriel B. Geissler ,&nbsp;Nathan Okole ,&nbsp;Bela Gipp ,&nbsp;Cyrill Stachniss ,&nbsp;René Heim","doi":"10.1016/j.softx.2025.102150","DOIUrl":"10.1016/j.softx.2025.102150","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs) equipped with optical sensors have transformed remote sensing in vegetation science by providing high-resolution, on-demand data, enhancing studies in forestry, agriculture, and environmental monitoring. However, accurate radiometric calibration of UAV imagery remains challenging. A common practice, using a single calibration target while holding the UAV-mounted camera close above it, is being criticized as the hemisphere is invisibly shaded and the reference images are not collected under flight conditions. <em>ReflectDetect</em> addresses these challenges by allowing in-flight radiometric calibration through automated detection via two different approaches: 1) a geotagging approach leveraging high-precision coordinates of the reflectance targets and 2) AprilTag based detection, a visual fiducial system frequently used in robotics. A brief statistical analysis and example data is provided to reassure the quality of the calibration results. ReflectDetect is available through a command-line interface and open-source (<span><span>https://github.com/reflectdetect/reflectdetect</span><svg><path></path></svg></span>). It now enables users to design new in-flight calibration studies to eventually improve radiometric calibration in applied UAV remote sensing.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102150"},"PeriodicalIF":2.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715323","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 1.1.1 - TROVA: TRansport Of water VApor 版本1.1.1 - TROVA：水蒸气的传输
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-03-28 DOI: 10.1016/j.softx.2025.102135
José C. Fernández-Alvarez , Albenis Pérez-Alarcón , Raquel Nieto , Luis Gimeno
{"title":"Version 1.1.1 - TROVA: TRansport Of water VApor","authors":"José C. Fernández-Alvarez ,&nbsp;Albenis Pérez-Alarcón ,&nbsp;Raquel Nieto ,&nbsp;Luis Gimeno","doi":"10.1016/j.softx.2025.102135","DOIUrl":"10.1016/j.softx.2025.102135","url":null,"abstract":"<div><div>TROVA is a software tool implemented in Fortran and Python focused on the study of moisture sources and sinks using the main Lagrangian methodologies found in the literature. In this upgraded version 1.1.1, the following aspects have been improved: 1) the ability to be installed as a Python package in an Anaconda environment with an improved configuration description, 2) the option to study moisture sources and sinks in different layers of the atmospheric vertical column, 3) the inclusion of an adjustable tracking time for the particles along their trajectories, and 4) the calculation of the water vapor residence time in the atmosphere for all particles over a target region. These updates allow the study and characterization of moisture transport for different extreme events and climatological periods.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102135"},"PeriodicalIF":2.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715223","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
Atlantic cod growth model: Open source Python package for numerical growth experiments 大西洋鳕鱼生长模型：用于数值生长实验的开源Python包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-03-27 DOI: 10.1016/j.softx.2025.102113
Nadezhda Sokolova , Anja Rohner , Martin Butzin , Hans-Otto Pörtner , Gerrit Lohmann
{"title":"Atlantic cod growth model: Open source Python package for numerical growth experiments","authors":"Nadezhda Sokolova ,&nbsp;Anja Rohner ,&nbsp;Martin Butzin ,&nbsp;Hans-Otto Pörtner ,&nbsp;Gerrit Lohmann","doi":"10.1016/j.softx.2025.102113","DOIUrl":"10.1016/j.softx.2025.102113","url":null,"abstract":"<div><div>In this article we introduce an open source tool that is used to study growth of Atlantic cod <em>(Gadus morhua)</em>, an economically important fish species, in different temperature environments. It is a mechanistic physiology-based growth model that simulates growth in controlled laboratory experiments as well as in an open sea environment. The model can be used by universities, industrial, and research institutes as a tool for testing research hypotheses, and studying temperature-dependent growth in fishes.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102113"},"PeriodicalIF":2.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715324","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
PyMED-DX: A Python tool for diagnostic value evaluation of 2D medical images PyMED-DX：用于二维医学图像诊断价值评估的Python工具
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-03-26 DOI: 10.1016/j.softx.2025.102128
Gorana Gojić , Vladimir Vincan , Ognjen Kundačina , Saša Taloši , Dragiša Mišković
{"title":"PyMED-DX: A Python tool for diagnostic value evaluation of 2D medical images","authors":"Gorana Gojić ,&nbsp;Vladimir Vincan ,&nbsp;Ognjen Kundačina ,&nbsp;Saša Taloši ,&nbsp;Dragiša Mišković","doi":"10.1016/j.softx.2025.102128","DOIUrl":"10.1016/j.softx.2025.102128","url":null,"abstract":"<div><div>This paper presents a Python-based tool designed to simplify subjective assessment studies for diagnostic value assessment of 2D medical images. The tool facilitates rapid questionnaire generation, allowing users to integrate their data into predefined templates, and provides utilities to statistically and visually analyze collected responses. By reducing the technical overhead of study preparation, the tool allows users to focus on knowledge discovery while providing easy-to-use questionnaires for clinicians with no technical expertise required.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102128"},"PeriodicalIF":2.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706340","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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