Pub Date : 2024-10-19DOI: 10.1016/j.simpa.2024.100710
Johnny Chan, Shohil Kishore, Xin Yang
This paper introduces a cyberbully checker, an AI-driven tool designed for real-time detection and mitigation of cyberbullying. Serenity, a chat application prototype, demonstrates the checker’s capabilities by using Google’s Perspective API to analyse message toxicity instantly. The application offers user-defined toxicity tolerance levels and alerts both senders and receivers before harmful interactions occur. By integrating these features, Serenity showcases how AI can enhance online safety, empowering users and providing guardian oversight without compromising privacy. This work highlights the potential of AI-driven solutions to create safer digital communication environments for adolescents and vulnerable populations.
{"title":"A real-time cyberbully checker","authors":"Johnny Chan, Shohil Kishore, Xin Yang","doi":"10.1016/j.simpa.2024.100710","DOIUrl":"10.1016/j.simpa.2024.100710","url":null,"abstract":"<div><div>This paper introduces a cyberbully checker, an AI-driven tool designed for real-time detection and mitigation of cyberbullying. Serenity, a chat application prototype, demonstrates the checker’s capabilities by using Google’s Perspective API to analyse message toxicity instantly. The application offers user-defined toxicity tolerance levels and alerts both senders and receivers before harmful interactions occur. By integrating these features, Serenity showcases how AI can enhance online safety, empowering users and providing guardian oversight without compromising privacy. This work highlights the potential of AI-driven solutions to create safer digital communication environments for adolescents and vulnerable populations.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100710"},"PeriodicalIF":1.3,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Graph-based models are relevant tools for analyzing the structure and inherent relationships among spatial entities. Here, we introduce ShpStreetGraph, a software designed to construct geographical graphs using shapefiles, explicitly focusing on street datasets. In this framework, nodes represent streets, and links are geographical relations such as intersections or proximity. The tool provides a range of criteria for network construction, enabling users to model and analyze urban street networks efficiently. ShpStreetGraph has proven to be faster than a similar tool when dealing with large networks, thus evidencing its scalability.
{"title":"ShpStreetGraph: From spatial relations of streets to graph representations","authors":"Pablo V.R. Silva , Aurelienne A.S. Jorge , Leonardo B.L. Santos , Vander L.S. Freitas","doi":"10.1016/j.simpa.2024.100711","DOIUrl":"10.1016/j.simpa.2024.100711","url":null,"abstract":"<div><div>Graph-based models are relevant tools for analyzing the structure and inherent relationships among spatial entities. Here, we introduce ShpStreetGraph, a software designed to construct geographical graphs using shapefiles, explicitly focusing on street datasets. In this framework, nodes represent streets, and links are geographical relations such as intersections or proximity. The tool provides a range of criteria for network construction, enabling users to model and analyze urban street networks efficiently. ShpStreetGraph has proven to be faster than a similar tool when dealing with large networks, thus evidencing its scalability.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100711"},"PeriodicalIF":1.3,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents HoughVG (Hough transform on Virtual Grid), a toolbox that improves on the Hough transform method, originally developed in 1962, by optimizing it for straight line detection and fingerprint recognition. Drawing on innovative approaches such as the rectangular, triangular, hexagonal and octagonal Hough transforms, as well as the generalized Hough transform, HoughVG significantly improves detection accuracy and processing speed. The toolbox is designed with a modular architecture, offering both sequential and parallelized functions. HoughVG’s test results indicate its potential impact on various fields, from academic research to industrial applications, while taking into account the limitations associated with pattern detection and parameter tuning.
{"title":"HoughVG:Hough Transform Toolbox for Straight-Line Detection and Fingerprint Recognition","authors":"Moïse Ouedraogo , Abdoulaye Sere , Cheick Amed Diloma Gabriel Traore","doi":"10.1016/j.simpa.2024.100709","DOIUrl":"10.1016/j.simpa.2024.100709","url":null,"abstract":"<div><div>This paper presents HoughVG (Hough transform on Virtual Grid), a toolbox that improves on the Hough transform method, originally developed in 1962, by optimizing it for straight line detection and fingerprint recognition. Drawing on innovative approaches such as the rectangular, triangular, hexagonal and octagonal Hough transforms, as well as the generalized Hough transform, HoughVG significantly improves detection accuracy and processing speed. The toolbox is designed with a modular architecture, offering both sequential and parallelized functions. HoughVG’s test results indicate its potential impact on various fields, from academic research to industrial applications, while taking into account the limitations associated with pattern detection and parameter tuning.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100709"},"PeriodicalIF":1.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.simpa.2024.100708
A.K.M. Azad
Differential expression analysis of biomarkers followed by the enrichment tests identifies the roles of enriched pathways or functional terms in a univariate manner. Cross-talks among enriched pathways are also key to better deciphering the complexity of tumor micro-environment and underlying mechanisms of its metastasization and/or drug resistance. Here we develop the rXTalkViz R package that facilitates an unmet need for quantifying and producing publication-ready visualization for functional cross-talk in a novel manner. We hypothesize that using rXTalkViz may enhance our understanding of the contribution of functional cross-talks in cancer progression and seamlessly aid further downstream analysis of biomarker.
对生物标志物进行差异表达分析，然后进行富集测试，以单变量方式确定富集通路或功能术语的作用。富集通路之间的交叉对话也是更好地解读肿瘤微环境的复杂性及其转移和/或耐药性潜在机制的关键。在这里，我们开发了 rXTalkViz R 软件包，它以一种新颖的方式满足了量化和制作可发表的功能交叉对话可视化的需求。我们假设，使用 rXTalkViz 可以增强我们对功能性交叉对话在癌症进展中的贡献的理解，并无缝地帮助进一步的生物标记下游分析。
{"title":"rXTalkViz: A R package to quantify, visualize, and report carcinogenic footprints of functional pathway cross-talks","authors":"A.K.M. Azad","doi":"10.1016/j.simpa.2024.100708","DOIUrl":"10.1016/j.simpa.2024.100708","url":null,"abstract":"<div><div>Differential expression analysis of biomarkers followed by the enrichment tests identifies the roles of enriched pathways or functional terms in a univariate manner. Cross-talks among enriched pathways are also key to better deciphering the complexity of tumor micro-environment and underlying mechanisms of its metastasization and/or drug resistance. Here we develop the rXTalkViz R package that facilitates an unmet need for quantifying and producing publication-ready visualization for functional cross-talk in a novel manner. We hypothesize that using rXTalkViz may enhance our understanding of the contribution of functional cross-talks in cancer progression and seamlessly aid further downstream analysis of biomarker.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100708"},"PeriodicalIF":1.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.simpa.2024.100707
Daffa Tristan Firdaus , Ntivuguruzwa Jean De La Croix , Tohari Ahmad
Data concealment proves to be significantly important when dealing with sensitive information. More effective data hiding methods must be analyzed to counter the threats that pose risks to its security. AudioSecure offers a security measure for concealing data using audio files as covers. It uses linear interpolation and multi-layering techniques to prevent attacks. This software uses Python-based programming to guarantee ease of use and large library selection, allowing scientists to gain valuable technical insights related to audio steganography. It improves the quality of produced stego and increases the capacity of sample spaces.
{"title":"AudioSecure: An open-source code to secure data using interpolation and multi-layering techniques within audio covers","authors":"Daffa Tristan Firdaus , Ntivuguruzwa Jean De La Croix , Tohari Ahmad","doi":"10.1016/j.simpa.2024.100707","DOIUrl":"10.1016/j.simpa.2024.100707","url":null,"abstract":"<div><div>Data concealment proves to be significantly important when dealing with sensitive information. More effective data hiding methods must be analyzed to counter the threats that pose risks to its security. AudioSecure offers a security measure for concealing data using audio files as covers. It uses linear interpolation and multi-layering techniques to prevent attacks. This software uses Python-based programming to guarantee ease of use and large library selection, allowing scientists to gain valuable technical insights related to audio steganography. It improves the quality of produced stego and increases the capacity of sample spaces.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100707"},"PeriodicalIF":1.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.simpa.2024.100706
José Piña-Flores , Antonio García-Jerez , Francisco J. Sánchez-Sesma , Francisco Luzón , Sergio Márquez-Domínguez
The relationship between the horizontal-to-vertical spectral ratio of ambient seismic noise and the elastic Green’s function has been established based on the principles of seismic interferometry. We have developed HV-Inv, a software designed in MATLAB for the forward and inverse calculations of the Horizontal-to-Vertical spectral ratio of ambient seismic noise (H/V) under the theory of diffuse fields. HV-Inv features both global and local inversion methods, supporting the simultaneous inversion of Rayleigh and Love wave dispersion curves with H/V. The goal is for it to be an effective tool for passive seismic exploration.
{"title":"HV-Inv: A MATLAB-based graphical tool for the direct and inverse problems of the horizontal-to-vertical spectral ratio under the diffuse field theory","authors":"José Piña-Flores , Antonio García-Jerez , Francisco J. Sánchez-Sesma , Francisco Luzón , Sergio Márquez-Domínguez","doi":"10.1016/j.simpa.2024.100706","DOIUrl":"10.1016/j.simpa.2024.100706","url":null,"abstract":"<div><div>The relationship between the horizontal-to-vertical spectral ratio of ambient seismic noise and the elastic Green’s function has been established based on the principles of seismic interferometry. We have developed <em>HV-Inv</em>, a software designed in MATLAB for the forward and inverse calculations of the Horizontal-to-Vertical spectral ratio of ambient seismic noise (H/V) under the theory of diffuse fields. <em>HV-Inv</em> features both global and local inversion methods, supporting the simultaneous inversion of Rayleigh and Love wave dispersion curves with H/V. The goal is for it to be an effective tool for passive seismic exploration.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100706"},"PeriodicalIF":1.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-05DOI: 10.1016/j.simpa.2024.100705
Iman Farahbakhsh, Benyamin Barani Nia
The Flow Energy Gradient Calculator (FEGC) is a Fortran-based tool designed to analyze fluid instability by calculating the energy gradient ratio, offering insights into flow stability and identifying loci for instability initiation and chaos. FEGC 1.0 provides a robust algorithm for detailed energy gradient analysis in fluid dynamics, particularly in two-dimensional fields. However, it faces challenges such as limited scalability, lack of a graphical user interface (GUI), and restricted integration with other tools. Future developments will address these limitations, enhancing scalability, adding a GUI, and expanding applicability to three-dimensional flow fields.
{"title":"FEGC 1.0: Flow Energy Gradient Calculator as a toolbox for predicting fluid flow instability initiation locus","authors":"Iman Farahbakhsh, Benyamin Barani Nia","doi":"10.1016/j.simpa.2024.100705","DOIUrl":"10.1016/j.simpa.2024.100705","url":null,"abstract":"<div><div>The Flow Energy Gradient Calculator (<span>FEGC</span>) is a Fortran-based tool designed to analyze fluid instability by calculating the energy gradient ratio, offering insights into flow stability and identifying loci for instability initiation and chaos. <span>FEGC 1.0</span> provides a robust algorithm for detailed energy gradient analysis in fluid dynamics, particularly in two-dimensional fields. However, it faces challenges such as limited scalability, lack of a graphical user interface (GUI), and restricted integration with other tools. Future developments will address these limitations, enhancing scalability, adding a GUI, and expanding applicability to three-dimensional flow fields.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100705"},"PeriodicalIF":1.3,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This manuscript delineates the code developed for a published scholarly article aimed at supporting researchers in addressing plant leaf disease detection and classification (PLDC) challenges while evaluating the efficacy of various deep learning models. Furthermore, the research incorporates preprocessing strategies, correlation, segmentation employing the UNet model, feature extraction methods and EfficientNet model. The software model generates graphs such as confusion matrix, ROC curve (Receiver Operating Characteristic), and visual representations of loss and accuracy graphs. The initial research was disseminated in the Multimedia Tools and Applications journal, and the accompanying dataset was also introduced in the Data in Brief journal.
{"title":"Enhanced leaf disease detection: UNet for segmentation and optimized EfficientNet for disease classification","authors":"Jameer Kotwal , Ramgopal Kashyap , Pathan Mohd Shafi , Vinod Kimbahune","doi":"10.1016/j.simpa.2024.100701","DOIUrl":"10.1016/j.simpa.2024.100701","url":null,"abstract":"<div><div>This manuscript delineates the code developed for a published scholarly article aimed at supporting researchers in addressing plant leaf disease detection and classification (PLDC) challenges while evaluating the efficacy of various deep learning models. Furthermore, the research incorporates preprocessing strategies, correlation, segmentation employing the UNet model, feature extraction methods and EfficientNet model. The software model generates graphs such as confusion matrix, ROC curve (Receiver Operating Characteristic), and visual representations of loss and accuracy graphs. The initial research was disseminated in the Multimedia Tools and Applications journal, and the accompanying dataset was also introduced in the Data in Brief journal.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100701"},"PeriodicalIF":1.3,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000897/pdfft?md5=aaec845754e88bf11d97594b0f75863a&pid=1-s2.0-S2665963824000897-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.simpa.2024.100702
Liam Daly Manocchio, Siamak Layeghy, Marius Portmann
FlowTransformer is a software framework tailored for building Machine Learning based Network Intrusion Detection Systems (NIDSs) leveraging transformer architectures known for their effectiveness in both NLP and more broadly for handling sequences of data. FlowTransformer is a flexible pipeline composed of a definable dataset definition, efficient preprocessing, and a flexible model construction, supporting different input-encodings, transformer models and classification heads. Furthermore, users can extend the framework by defining their own components. FlowTransformer’s contribution lies in its easy customisation, and ability to leverage transformers to enable enhanced long-term pattern detection, offering cybersecurity researchers and practitioners a valuable tool.
{"title":"FlowTransformer: A flexible python framework for flow-based network data analysis","authors":"Liam Daly Manocchio, Siamak Layeghy, Marius Portmann","doi":"10.1016/j.simpa.2024.100702","DOIUrl":"10.1016/j.simpa.2024.100702","url":null,"abstract":"<div><p>FlowTransformer is a software framework tailored for building Machine Learning based Network Intrusion Detection Systems (NIDSs) leveraging transformer architectures known for their effectiveness in both NLP and more broadly for handling sequences of data. FlowTransformer is a flexible pipeline composed of a definable dataset definition, efficient preprocessing, and a flexible model construction, supporting different input-encodings, transformer models and classification heads. Furthermore, users can extend the framework by defining their own components. FlowTransformer’s contribution lies in its easy customisation, and ability to leverage transformers to enable enhanced long-term pattern detection, offering cybersecurity researchers and practitioners a valuable tool.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100702"},"PeriodicalIF":1.3,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000903/pdfft?md5=0965be2b2008a97aa24469c5f4f84435&pid=1-s2.0-S2665963824000903-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.simpa.2024.100700
Khanh Nguyen , José M. Goicolea
The increasing prevalence of high-speed trains necessitates robust analysis tools to ensure the safety and reliability of railway bridges. This paper presents a user-friendly software application designed for the dynamic analysis of railway bridges subjected to high-speed train loadings. Leveraging the semi-analytical modal method, the software offers a balanced approach that combines computational efficiency with high accuracy. Key features include an intuitive interface, rapid analysis capabilities, and reliable prediction of bridge responses, facilitating design optimization and maintenance planning. This software is poised to become an indispensable tool for structural engineers, researchers, and infrastructure planners.
{"title":"CALDINTAV: A simple software for dynamic analysis of high-speed railway bridges using the semi-analytical modal method","authors":"Khanh Nguyen , José M. Goicolea","doi":"10.1016/j.simpa.2024.100700","DOIUrl":"10.1016/j.simpa.2024.100700","url":null,"abstract":"<div><p>The increasing prevalence of high-speed trains necessitates robust analysis tools to ensure the safety and reliability of railway bridges. This paper presents a user-friendly software application designed for the dynamic analysis of railway bridges subjected to high-speed train loadings. Leveraging the semi-analytical modal method, the software offers a balanced approach that combines computational efficiency with high accuracy. Key features include an intuitive interface, rapid analysis capabilities, and reliable prediction of bridge responses, facilitating design optimization and maintenance planning. This software is poised to become an indispensable tool for structural engineers, researchers, and infrastructure planners.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100700"},"PeriodicalIF":1.3,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000885/pdfft?md5=d1beb1441f35b71898713461a31ac898&pid=1-s2.0-S2665963824000885-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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