Software ImpactsPub Date : 2024-10-11DOI: 10.1016/j.simpa.2024.100709
{"title":"HoughVG:Hough Transform Toolbox for Straight-Line Detection and Fingerprint Recognition","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-10-09DOI: 10.1016/j.simpa.2024.100708
{"title":"rXTalkViz: A R package to quantify, visualize, and report carcinogenic footprints of functional pathway cross-talks","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-10-09DOI: 10.1016/j.simpa.2024.100707
{"title":"AudioSecure: An open-source code to secure data using interpolation and multi-layering techniques within audio covers","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-10-09DOI: 10.1016/j.simpa.2024.100706
{"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":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-10-05DOI: 10.1016/j.simpa.2024.100705
{"title":"FEGC 1.0: Flow Energy Gradient Calculator as a toolbox for predicting fluid flow instability initiation locus","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-09-14DOI: 10.1016/j.simpa.2024.100701
{"title":"Enhanced leaf disease detection: UNet for segmentation and optimized EfficientNet for disease classification","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-09-07DOI: 10.1016/j.simpa.2024.100700
{"title":"CALDINTAV: A simple software for dynamic analysis of high-speed railway bridges using the semi-analytical modal method","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-09-07DOI: 10.1016/j.simpa.2024.100702
{"title":"FlowTransformer: A flexible python framework for flow-based network data analysis","authors":"","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":null,"pages":null},"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}
Software ImpactsPub Date : 2024-09-04DOI: 10.1016/j.simpa.2024.100703
{"title":"QF-LCS: Quantum Field Lens Coding Simulator and Game Tool for Strong System State Predictions","authors":"","doi":"10.1016/j.simpa.2024.100703","DOIUrl":"10.1016/j.simpa.2024.100703","url":null,"abstract":"<div><p>A quantum field lens coding simulator (QF-LCS) is presented on a high-level end-user application software run by CLI <span><math><mo>⟷</mo></math></span> GUI with custom commands input by the user to process, analyze, validate QF-LC algorithm (QF-LCA) datasets in a QF-LC Python game. On the low-level system software, measurement data are acquired from quantum computers. The datasets contain these measurement data, processed and classified according to QF-LCA circuit design and steps determining system states and their prediction. This software, impacts advances made in applied sciences, statistics, law and physics, where data validation of samples including system simulation projecting and predicting events are achieved.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000915/pdfft?md5=26159ec90a7b21591fdb9f85ac7e00fd&pid=1-s2.0-S2665963824000915-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271741","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}
Software ImpactsPub Date : 2024-09-01DOI: 10.1016/j.simpa.2024.100692
{"title":"Assessing and improving the quality of Fortran code in scientific software: FortranAnalyser","authors":"","doi":"10.1016/j.simpa.2024.100692","DOIUrl":"10.1016/j.simpa.2024.100692","url":null,"abstract":"<div><p>Despite its age, Fortran remains essential in many scientific fields. Ensuring code quality in long-term projects with evolving standards is critical, but few tools analyse Fortran, and they are not free. We present FortranAnalyser, a multi-platform, static analysis tool designed to enhance Fortran code quality. This paper outlines its development, features, and comparison with other tools. Additionally, we demonstrate its effectiveness through real-world applications, such as improving the Fortran code in a major global climate model.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000800/pdfft?md5=b4cfcaaeff8f22b78ef9129f05f9279d&pid=1-s2.0-S2665963824000800-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136553","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}