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Cyber4OT dataset: Network traces for cyber-security vulnerability evaluation in industrial control systems Cyber4OT数据集：用于工业控制系统中网络安全漏洞评估的网络痕迹
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-30 DOI: 10.1016/j.softx.2025.102196
Krzysztof Cabaj , Sebastian Plamowski , Patryk Chaber , Maciej Ławryńczuk , Piotr Marusak , Robert Nebeluk , Andrzej Wojtulewicz , Krzysztof Zarzycki
{"title":"Cyber4OT dataset: Network traces for cyber-security vulnerability evaluation in industrial control systems","authors":"Krzysztof Cabaj ,&nbsp;Sebastian Plamowski ,&nbsp;Patryk Chaber ,&nbsp;Maciej Ławryńczuk ,&nbsp;Piotr Marusak ,&nbsp;Robert Nebeluk ,&nbsp;Andrzej Wojtulewicz ,&nbsp;Krzysztof Zarzycki","doi":"10.1016/j.softx.2025.102196","DOIUrl":"10.1016/j.softx.2025.102196","url":null,"abstract":"<div><div>The article introduces the Cyber4OT dataset containing network traces concerning normal and simulated attacker-hostile activity in an Industrial Control System (ICS) environment. As many as 96 traces contain over 4.25 million packets and have over 385 MB capacity. The simulated attacks have been performed on a dedicated laboratory testbed. The testbed mimics industrial plants’ Information Technology (IT) and Operational Technology (OT) infrastructure. The testbed deliberately uses continuous and binary control processes of fast and slow dynamics. Industrial Programmable Logic Controllers (PLCs) are used to control the processes. A dedicated industrial network provides the communication between the ICS equipment, Supervisory Control and Data Acquisition (SCADA) system and Human Machine Interface (HMI) panels. The communication is configured to test multiple communication protocols, including the standard industrial Modbus protocol. The entire industrial infrastructure is connected to an external office network. Since the infrastructure and its components are typical of industrial solutions, the described dataset collected using such a realistic testbed could be beneficial for a broad scope of researchers to evaluate the vulnerability of ICSs to cyber attacks using classical and artificial intelligence methods.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102196"},"PeriodicalIF":2.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167994","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
PostForecasts.jl: A Julia package for probabilistic forecasting by postprocessing point predictions PostForecasts。一个Julia包，用于通过后处理点预测进行概率预测
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-29 DOI: 10.1016/j.softx.2025.102200
Arkadiusz Lipiecki, Rafał Weron
{"title":"PostForecasts.jl: A Julia package for probabilistic forecasting by postprocessing point predictions","authors":"Arkadiusz Lipiecki,&nbsp;Rafał Weron","doi":"10.1016/j.softx.2025.102200","DOIUrl":"10.1016/j.softx.2025.102200","url":null,"abstract":"<div><div>Postprocessing of point predictions is a relatively simple and efficient way to compute probabilistic forecasts, which are the basis of uncertainty assessment for decision support and risk management. The <em>PostForecasts.jl</em> package in Julia provides types and functions to easily convert point forecasts into probabilistic ones using Historical Simulation, Conformal Prediction, Isotonic Distributional Regression, and variants of Quantile Regression Averaging. By leveraging the developments in the point forecasting literature, it offers a set of easy-to-use, computationally undemanding, and robust tools to derive predictive distributions.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102200"},"PeriodicalIF":2.4,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167966","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
“SFM”: An R package for Skew Factor Models “SFM”：一个用于倾斜因子模型的R包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-28 DOI: 10.1016/j.softx.2025.102205
Yu Jin, Guangbao Guo
{"title":"“SFM”: An R package for Skew Factor Models","authors":"Yu Jin,&nbsp;Guangbao Guo","doi":"10.1016/j.softx.2025.102205","DOIUrl":"10.1016/j.softx.2025.102205","url":null,"abstract":"<div><div>The goal of the Skew Factor Model (SFM) package is to analyze datasets where factor loading matrices exhibit skewed distributions, providing efficient estimation methods for SFM. The proposed R package, called SFM, is specifically designed for estimating skewed factor structures and handling high-dimensional data with non-Gaussian distributions.It achieves this by implementing multiple principal component methods, including Sparse Online Principal Component, Incremental Principal Component, Projected Principal Component, Stochastic Approximation Principal Component, Sparse Principal Component and other Principal Component methods. Additionally, SFM package provides evaluation metrics such as mean squared error, relative error, and sparsity of the loading matrix, ensuring robust parameter estimation.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102205"},"PeriodicalIF":2.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144148027","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
REVOL-E-TION: A flexible and scalable investment optimization toolbox for local energy systems incorporating electric vehicle fleets revolution - e - tion：一个灵活、可扩展的投资优化工具箱，适用于包含电动汽车车队的地方能源系统
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-27 DOI: 10.1016/j.softx.2025.102178
Philipp Rosner , Brian Dietermann , Marcel Brödel, Anna Paper, Markus Lienkamp
{"title":"REVOL-E-TION: A flexible and scalable investment optimization toolbox for local energy systems incorporating electric vehicle fleets","authors":"Philipp Rosner ,&nbsp;Brian Dietermann ,&nbsp;Marcel Brödel,&nbsp;Anna Paper,&nbsp;Markus Lienkamp","doi":"10.1016/j.softx.2025.102178","DOIUrl":"10.1016/j.softx.2025.102178","url":null,"abstract":"<div><div>Electric vehicles (EVs) interact with their energy supply systems fundamentally differently than conventional internal combustion engine vehicles (ICEVs). Therefore, only joint consideration can leverage all integration synergies and show the most valuable transition pathway, accelerating EV proliferation, especially for commercial applications recharging in depots. However, openly available toolboxes lack easy-to-use functions for vehicle and mobile storage fleet modeling as well as multi-scenario investment decision making. With REVOL-E-TION, we present an open source local energy system investment optimization toolbox based on the open source oemof framework in Python, filling these gaps. This publication presents both the application spectrum and setup of REVOL-E-TION, and demonstrates its use in a hypothetical municipal fleet depot electrification.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102178"},"PeriodicalIF":2.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137838","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
sprynger: Scriptable bibliometrics using a Python interface to Springer Nature sprynger：使用Python接口施普林格Nature的可编写的文献计量学
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-27 DOI: 10.1016/j.softx.2025.102186
Nils A. Herrmann , Michael E. Rose
{"title":"sprynger: Scriptable bibliometrics using a Python interface to Springer Nature","authors":"Nils A. Herrmann ,&nbsp;Michael E. Rose","doi":"10.1016/j.softx.2025.102186","DOIUrl":"10.1016/j.softx.2025.102186","url":null,"abstract":"<div><div>We present a wrapper for the Springer Nature RESTful API written for Python 3. The wrapper allows users to access their free-to-use endpoints via user-friendly interfaces and can be used without prior knowledge of RESTful APIs. The APIs allow users to query metadata and open-access full-text of articles, conference proceedings and books published with Springer Nature. Files are cached to speed up subsequent analysis. The package addresses all users of scientific full-text, such as researchers working in Science of Science or evaluators. It facilitates reproducibility of research projects and enhances data integrity for researchers using Springer Nature data.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102186"},"PeriodicalIF":2.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137840","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
Efficient hierarchical CNN model with self-attention for three-category facial emotion tracking in healthcare applications 具有自注意的高效层次CNN模型用于医疗保健应用中的三类面部情绪跟踪
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-27 DOI: 10.1016/j.softx.2025.102213
Long Duongthang , Dung Trantien , Hung Tranduy , Bien Dohoai
{"title":"Efficient hierarchical CNN model with self-attention for three-category facial emotion tracking in healthcare applications","authors":"Long Duongthang ,&nbsp;Dung Trantien ,&nbsp;Hung Tranduy ,&nbsp;Bien Dohoai","doi":"10.1016/j.softx.2025.102213","DOIUrl":"10.1016/j.softx.2025.102213","url":null,"abstract":"<div><div>Facial emotion recognition (FER) is a transformative tool for advancing healthcare, particularly in telehealth, where non-verbal communication is limited. This paper introduces Facial Emotion Tracking for Healthcare Applications (FET4H), a lightweight and effective FER system that leverages a hierarchical CNN architecture with integrated self-attention mechanisms to achieve high accuracy in recognizing key emotional states—negative, neutral, and positive. It also addresses challenges such as lighting variability, pose differences, and facial obstructions. Validated on real-world datasets, including RAF-DB, FER+, and AffectNet, FET4H demonstrates superior performance compared to existing methods. Integrated into user-friendly software, FET4H supports real-time emotion tracking, data logging, and telehealth integration, aiding providers in assessing satisfaction, detecting distress, and personalizing care. Its flexibility for retraining and customization ensures adaptability across scenarios, while its efficiency reduces operational costs for healthcare organizations. FET4H also serves as a benchmark for FER research, inspiring advancements in technology and interdisciplinary collaboration, ultimately enhancing telehealth outcomes and enabling equitable, high-quality remote healthcare.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102213"},"PeriodicalIF":2.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137839","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
SmartControl: Interactive PID controller design powered by LLM agents and control system expertise SmartControl：由LLM代理和控制系统专业知识驱动的交互式PID控制器设计
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-26 DOI: 10.1016/j.softx.2025.102194
Kadir Tohma , Halil İbrahim Okur , Handan Gürsoy-Demir , Merve Nilay Aydın , Celaleddin Yeroğlu
{"title":"SmartControl: Interactive PID controller design powered by LLM agents and control system expertise","authors":"Kadir Tohma ,&nbsp;Halil İbrahim Okur ,&nbsp;Handan Gürsoy-Demir ,&nbsp;Merve Nilay Aydın ,&nbsp;Celaleddin Yeroğlu","doi":"10.1016/j.softx.2025.102194","DOIUrl":"10.1016/j.softx.2025.102194","url":null,"abstract":"<div><div>SmartControl is an interactive PID controller design tool powered by the novel integration of Large Language Model (LLM) agents and control system expertise. Users articulate system performance requirements in natural language, which the software converts into numerical targets. Optimal PID gains are determined using Particle Swarm Optimization and Differential Evolution algorithms, and the system’s step response is simulated and presented graphically. The result evaluation module analyses performance data via an LLM agent, providing interactive feedback and educational support. Furthermore, the tool generates MATLAB code and PDF reports, thereby focusing its utility on efficient control system design workflows in academic research and simulation-driven design studies.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102194"},"PeriodicalIF":2.4,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134928","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
CGNLib: A Python library for Girvan–Newman community detection with customizable node-based centrality metrics CGNLib：一个Python库，用于Girvan-Newman社区检测，具有可定制的基于节点的中心性指标
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-24 DOI: 10.1016/j.softx.2025.102193
T. Punnapathiran , C. Angsuchotmetee , P. Kaewkarndee , K. Lavangnananda
{"title":"CGNLib: A Python library for Girvan–Newman community detection with customizable node-based centrality metrics","authors":"T. Punnapathiran ,&nbsp;C. Angsuchotmetee ,&nbsp;P. Kaewkarndee ,&nbsp;K. Lavangnananda","doi":"10.1016/j.softx.2025.102193","DOIUrl":"10.1016/j.softx.2025.102193","url":null,"abstract":"<div><div>CGNLib is a Python library designed to enhance the performance of community detection in networks using the Girvan–Newman algorithm. Traditional implementations of this algorithm typically rely solely on edge betweenness centrality, limiting the potential for optimization. CGNLib overcomes this by transforming edges into nodes within an in-memory auxiliary graph, enabling the use of any node-centric centrality metric on edges, which is not typically possible. This approach allows researchers to explore a wider range of centrality measures, potentially improving community detection outcomes. Additionally, CGNLib supports community visualization and evaluation through metrics like modularity, conductance and coverage. The included CGNExp wrapper simplifies testing various centrality metrics with minimal code, making CGNLib an invaluable tool for researchers in fields such as social network analysis, biology, and other networked systems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102193"},"PeriodicalIF":2.4,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124113","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
A Matlab-based application for enhanced controller tuning in ArduSub ROVs: ATControlROV 一个基于matlab的应用程序，用于在arduusub rov中增强控制器调谐：ATControlROV
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-23 DOI: 10.1016/j.softx.2025.102189
Ana Isabel Vázquez Mejías, Juan Carlos de la Torre, Mariano Marcos-Pérez, Andrés Yáñez Escolano, Guillermo Bárcena-González
{"title":"A Matlab-based application for enhanced controller tuning in ArduSub ROVs: ATControlROV","authors":"Ana Isabel Vázquez Mejías,&nbsp;Juan Carlos de la Torre,&nbsp;Mariano Marcos-Pérez,&nbsp;Andrés Yáñez Escolano,&nbsp;Guillermo Bárcena-González","doi":"10.1016/j.softx.2025.102189","DOIUrl":"10.1016/j.softx.2025.102189","url":null,"abstract":"<div><div>Since the 20th century, underwater research has grown exponentially due to technological advances and financial support from governments and companies. Although some research initially lacks solid funding , unmanned underwater vehicles (UUVs) or underwater robots have become essential for efficient exploration. ArduSub, an open-source solution since 2017, facilitates the control of ROVs and AUVs by leveraging drone technologies. ArduPilot, initiated in 2007, has become a global benchmark in free software for unmanned vehicles. This paper introduces ATControlROV, a MATLAB-based application designed to optimize PID control parameters for ROVs built on the ArduSub platform. ATControlROV simplifies the tuning process through a structured interface, enabling users of all experience levels to achieve enhanced stability and performance in attitude control, including yaw, pitch, and roll. The application integrates empirical and model-based approaches to fine-tune inner and outer control loops, significantly improving system responsiveness to disturbances. By democratizing access to advanced control optimization tools, ATControlROV empowers researchers and practitioners to enhance the operational efficiency of underwater vehicles, fostering innovation in academic and professional applications, especially in the underwater robotics community.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102189"},"PeriodicalIF":2.4,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114978","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
wxgenR: An R package for stochastic weather generation with seasonality wxgenR：一个具有季节性的随机天气生成的R包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-05-23 DOI: 10.1016/j.softx.2025.102209
David Woodson , Subhrendu Gangopadhyay , Lindsay Bearup , Andrew Verdin , Eylon Shamir , Eve Halper , Marketa McGuire
{"title":"wxgenR: An R package for stochastic weather generation with seasonality","authors":"David Woodson ,&nbsp;Subhrendu Gangopadhyay ,&nbsp;Lindsay Bearup ,&nbsp;Andrew Verdin ,&nbsp;Eylon Shamir ,&nbsp;Eve Halper ,&nbsp;Marketa McGuire","doi":"10.1016/j.softx.2025.102209","DOIUrl":"10.1016/j.softx.2025.102209","url":null,"abstract":"<div><div>A stochastic weather generator was developed with the novel feature of considering seasonality of precipitation and temperature, motivated largely within the context of climate change adaptation and planning. The weather generator, <em>wxgenR</em>, is released as an R language package on the Comprehensive R Archive Network. <em>wxgenR</em> was tested using weather station data from nine locations in the continental United States with varied hydroclimatic regimes. <em>wxgenR</em> development was initiated by a hydroclimate analysis using areal average precipitation and temperature from the Lower Santa Cruz River Basin in Arizona, where representing monsoon moisture and changes therein is important for water supply planning. <em>wxgenR</em> performs well in the cross-validation with both in-sample and out-of-sample data.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102209"},"PeriodicalIF":2.4,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115983","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
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