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PINNs-MPF: An Efficient Physics-Informed Machine Learning-based Solver for Multi-Phase-Field Simulations using Tensorflow pass - mpf：一个高效的基于物理信息的基于机器学习的求解器，用于使用Tensorflow进行多相场模拟
IF 1.3
Software Impacts Pub Date : 2025-05-02 DOI: 10.1016/j.simpa.2025.100753
Seifallah Elfetni , Reza Darvishi Kamachali
{"title":"PINNs-MPF: An Efficient Physics-Informed Machine Learning-based Solver for Multi-Phase-Field Simulations using Tensorflow","authors":"Seifallah Elfetni ,&nbsp;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":"2025-05-02","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}
引用次数: 0
Nomad Analytix: Text-rich visual reasoning using vision models for insights and recommendations Nomad Analytix：使用视觉模型进行文本丰富的视觉推理，以获得见解和建议
IF 1.3
Software Impacts Pub Date : 2025-04-29 DOI: 10.1016/j.simpa.2025.100765
Sai Jeevan Puchakayala , Allen Bijo T. , Aswathy Ravikumar , Harini Sriraman
{"title":"Nomad Analytix: Text-rich visual reasoning using vision models for insights and recommendations","authors":"Sai Jeevan Puchakayala ,&nbsp;Allen Bijo T. ,&nbsp;Aswathy Ravikumar ,&nbsp;Harini Sriraman","doi":"10.1016/j.simpa.2025.100765","DOIUrl":"10.1016/j.simpa.2025.100765","url":null,"abstract":"<div><div>Nomad Analytix is an innovative business intelligence tool that uses state-of-the-art vision models to transform data analysis. This software automates complex tasks traditionally handled by data analysts, empowering non-technical teams such as marketing and sales to access advanced data analysis easily. By using natural language prompts, users can interact with data intuitively and gain valuable insights without needing extensive technical expertise. A prototype of the software, built on the Streamlit platform, will showcase its ability to generate visualizations from various data sources, including CSV, JSON, SQLite, Excel, and databases, with potential extensions to data warehouses. The integration of Vision Language Models GPT 4 Omni and GPT 4 Turbo- with this framework provides a seamless interface for data querying, visualization creation, and recommendation generation. Nomad Analytix serves as an inclusive, intelligent, and intuitive solution, bridging the gap between data and decision-making across diverse industries.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100765"},"PeriodicalIF":1.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903526","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}
引用次数: 0
An automated parameter optimizer for data transfer performance testing 用于数据传输性能测试的自动参数优化器
IF 1.3
Software Impacts Pub Date : 2025-04-29 DOI: 10.1016/j.simpa.2025.100764
Daqing Yun , Liudong Zuo , Yi Gu , Chase Wu
{"title":"An automated parameter optimizer for data transfer performance testing","authors":"Daqing Yun ,&nbsp;Liudong Zuo ,&nbsp;Yi Gu ,&nbsp;Chase Wu","doi":"10.1016/j.simpa.2025.100764","DOIUrl":"10.1016/j.simpa.2025.100764","url":null,"abstract":"<div><div>This work presents an automated tool for optimizing control parameters in performance testing of big data transfer over long-fat network connections. Supporting both TCP and UDT protocols, the tool identifies the optimal configurations to enhance the efficiency of large-scale data transfers. A stochastic approximation algorithm is employed for parameter optimization, streamlining the protocol and parameter selection. The tool has been evaluated in various network scenarios, including long-haul connections in real-world high-performance networks. Its modular design also enables straightforward integration of additional data transfer protocols and alternative optimization methods.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100764"},"PeriodicalIF":1.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903527","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}
引用次数: 0
FeVAcS: A package for visualizing acoustic scattering from 1D periodic obstacles FeVAcS：一个用于显示一维周期性障碍物声散射的软件包
IF 1.3
Software Impacts Pub Date : 2025-04-28 DOI: 10.1016/j.simpa.2025.100756
Mete Öğüç , Ali Fethi Okyar , Tahsin Khajah
{"title":"FeVAcS: A package for visualizing acoustic scattering from 1D periodic obstacles","authors":"Mete Öğüç ,&nbsp;Ali Fethi Okyar ,&nbsp;Tahsin Khajah","doi":"10.1016/j.simpa.2025.100756","DOIUrl":"10.1016/j.simpa.2025.100756","url":null,"abstract":"<div><div>FeVAcS is an open-source finite element software specializing in one dimensional periodic acoustic analyses with scattering obstacles. Leveraging FEniCS Project’s computational capabilities, it solves the Helmholtz equation variational form. This tool simplifies mesh generation, enhances acoustic visualization, and enables easy parameter manipulation for obstacle and domain geometries, along with wave property adjustments. Featuring a user-friendly browser interface, FeVAcS improves accessibility and result sharing. It serves as a vital tool for understanding complexities within exterior acoustic analyses.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100756"},"PeriodicalIF":1.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888040","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}
引用次数: 0
RMCDA: The comprehensive R library for applying Multi-Criteria Decision Analysis methods RMCDA：用于应用多标准决策分析方法的综合R库
IF 1.3
Software Impacts Pub Date : 2025-04-28 DOI: 10.1016/j.simpa.2025.100762
Annice Najafi, Shokoufeh Mirzaei
{"title":"RMCDA: The comprehensive R library for applying Multi-Criteria Decision Analysis methods","authors":"Annice Najafi,&nbsp;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":"2025-04-28","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}
引用次数: 0
IrsyadStego: An open-source code to secure data using pixel differencing paradigm within the neighboring pixels of a digital image IrsyadStego：一个在数字图像的相邻像素内使用像素差异范例来保护数据的开源代码
IF 1.3
Software Impacts Pub Date : 2025-04-28 DOI: 10.1016/j.simpa.2025.100757
Irsyad Fikriansyah Ramadhan , Ntivuguruzwa Jean De La Croix , Tohari Ahmad
{"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 ,&nbsp;Ntivuguruzwa Jean De La Croix ,&nbsp;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":"2025-04-28","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}
引用次数: 0
BRS: A tool for detecting biocide resistance in mobile elements BRS：一种检测移动元件中杀菌剂耐药性的工具
IF 1.3
Software Impacts Pub Date : 2025-04-28 DOI: 10.1016/j.simpa.2025.100758
Frederico Schmitt Kremer, João Pedro Gomes Greco, Elias Eduardo Barbosa da Rosa
{"title":"BRS: A tool for detecting biocide resistance in mobile elements","authors":"Frederico Schmitt Kremer,&nbsp;João Pedro Gomes Greco,&nbsp;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":"2025-04-28","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}
引用次数: 0
WECS: A wavelet energy correlation screening based method for unsupervised change detection using remote sensing image series 基于小波能量相关筛选的遥感图像序列无监督变化检测方法
IF 1.3
Software Impacts Pub Date : 2025-04-28 DOI: 10.1016/j.simpa.2025.100750
João Pedro M. Saraiva , Rodney V. Fonseca , Rogério G. Negri , Aluísio Pinheiro
{"title":"WECS: A wavelet energy correlation screening based method for unsupervised change detection using remote sensing image series","authors":"João Pedro M. Saraiva ,&nbsp;Rodney V. Fonseca ,&nbsp;Rogério G. Negri ,&nbsp;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":"2025-04-28","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}
引用次数: 0
Infinite Type Centroid java library: An implementation of parameterized coordinates for an enhanced centroid calculation during K-means classification 无限型质心java库：参数化坐标的实现，用于在K-means分类期间增强质心计算
IF 1.3
Software Impacts Pub Date : 2025-04-28 DOI: 10.1016/j.simpa.2025.100751
Victor Hugo Silva-Blancas , José Manuel Álvarez-Alvarado , Hugo Jiménez-Hernández , Ana Marcela Herrera-Navarro , Diana Margarita Córdova-Esparza , Juvenal Rodríguez-Reséndiz
{"title":"Infinite Type Centroid java library: An implementation of parameterized coordinates for an enhanced centroid calculation during K-means classification","authors":"Victor Hugo Silva-Blancas ,&nbsp;José Manuel Álvarez-Alvarado ,&nbsp;Hugo Jiménez-Hernández ,&nbsp;Ana Marcela Herrera-Navarro ,&nbsp;Diana Margarita Córdova-Esparza ,&nbsp;Juvenal Rodríguez-Reséndiz","doi":"10.1016/j.simpa.2025.100751","DOIUrl":"10.1016/j.simpa.2025.100751","url":null,"abstract":"<div><div>InfiniteTypeCentroid presents a theorem design to enhance centroid calculation on the K-means algorithm by integrating a parameters list that produces hidden information and offers improved results choose in the course of research. It shows a capacity for universalization and adaptability to address any mathematical analysis and it can be used in any Java compiler a parent class. Data analysis on use cases results in 18.22% improved accuracy and data behavior for a specific dataverse produces seven tendency charts with enriched significance. Improves data structures by debugging non-significant values and offering an improved methodology for hypothesis definition.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100751"},"PeriodicalIF":1.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895941","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}
引用次数: 0
Symptom-based early detection and classification of plant diseases using AI-driven CNN+KNN Fusion Software (ACKFS) 基于ai驱动的CNN+KNN融合软件（ACKFS）基于症状的植物病害早期检测与分类
IF 1.3
Software Impacts Pub Date : 2025-04-26 DOI: 10.1016/j.simpa.2025.100755
Jayswal Hardik , Rishi Sanjaykumar Patel , Hetvi Desai , Hasti Vakani , Mithil Mistry , Nilesh Dubey
{"title":"Symptom-based early detection and classification of plant diseases using AI-driven CNN+KNN Fusion Software (ACKFS)","authors":"Jayswal Hardik ,&nbsp;Rishi Sanjaykumar Patel ,&nbsp;Hetvi Desai ,&nbsp;Hasti Vakani ,&nbsp;Mithil Mistry ,&nbsp;Nilesh Dubey","doi":"10.1016/j.simpa.2025.100755","DOIUrl":"10.1016/j.simpa.2025.100755","url":null,"abstract":"<div><div>This paper investigates and introduce an AI-driven CNN-KNN Fusion Software (ACKFS) for symptom-based early detection and classification of plant diseases. The approach integrates Convolutional Neural Networks and K-Nearest Neighbor’s to enhance classification accuracy. This research follows a structured four-phase process: pre-processing, segmentation, feature extraction, and classification. Using two datasets, ACKFS significantly improved accuracy to 94.56% and 87.52%, respectively. These results surpass the performance reported by previous researcher’s, demonstrating the effectiveness of CNN-KNN fusion for real-time plant disease detection on smart devices, contributing to precision agriculture and enhanced plant health monitoring.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"24 ","pages":"Article 100755"},"PeriodicalIF":1.3,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888039","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}
引用次数: 0
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