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A short tutorial for multivariate time series explanation using tsCaptum 使用 tsCaptum 解释多元时间序列的简短教程
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100723
Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim
{"title":"A short tutorial for multivariate time series explanation using tsCaptum","authors":"Davide Italo Serramazza,&nbsp;Thach Le Nguyen,&nbsp;Georgiana Ifrim","doi":"10.1016/j.simpa.2024.100723","DOIUrl":"10.1016/j.simpa.2024.100723","url":null,"abstract":"<div><div>tsCaptum is a Python library that enables explainability for time series classification and regression using saliency maps (i.e., attribution-based explanation). It bridges the gap between popular time series frameworks (e.g., aeon, sktime, sklearn) and explanation libraries like Captum. tsCaptum tackles the computational complexity of explaining long time series by employing chunking techniques, significantly reducing the number of model evaluations required. This allows users to easily apply Captum explainers to any univariate or multivariate time series model or pipeline built using the aforementioned frameworks. tsCaptum is readily available on pypi.org and can be installed with a simple ”pip install tsCaptum” command.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100723"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723884","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}
引用次数: 0
LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond LandSin：支持差异化 ML 和谷歌 API 的网络服务器，用于实时洞察土地及其他情况
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100718
Alauddin Sabari , Imran Hasan , Salem A. Alyami , Pietro Liò , Md. Sadek Ali , Mohammad Ali Moni , AKM Azad
{"title":"LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond","authors":"Alauddin Sabari ,&nbsp;Imran Hasan ,&nbsp;Salem A. Alyami ,&nbsp;Pietro Liò ,&nbsp;Md. Sadek Ali ,&nbsp;Mohammad Ali Moni ,&nbsp;AKM Azad","doi":"10.1016/j.simpa.2024.100718","DOIUrl":"10.1016/j.simpa.2024.100718","url":null,"abstract":"<div><div><em>LandSin</em>, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenities and property details, <em>LandSin</em> offers key features, e.g., accurate land value and price predictions, affordability and habitability analysis, and terrain insights using Google Maps. In addition, it facilitates useful infographics, helping stakeholders identify economically deprived but habitable areas for balanced regional development. It also supports real estate agencies and community planners in finding habitable land by making data-driven decisions regarding land investments and regional planning, ensuring informed and strategic choices.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100718"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654390","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}
引用次数: 0
driftViewer: Optimization of drifter trajectory search and export of oceanographic parameters driftViewer：漂浮物轨迹搜索优化和海洋参数输出
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100719
H.L. Varona , C. Noriega , S. Herold-Garcia , S.M.A. Lira , M. Araujo , F. Hernandez
{"title":"driftViewer: Optimization of drifter trajectory search and export of oceanographic parameters","authors":"H.L. Varona ,&nbsp;C. Noriega ,&nbsp;S. Herold-Garcia ,&nbsp;S.M.A. Lira ,&nbsp;M. Araujo ,&nbsp;F. Hernandez","doi":"10.1016/j.simpa.2024.100719","DOIUrl":"10.1016/j.simpa.2024.100719","url":null,"abstract":"<div><div>The study and analysis of drifter trajectories, such as buoys and floating devices, have become fundamental to understanding oceanographic phenomena. The detailed analysis of oceanographic parameters using specialized software allows researchers to study environmental changes on different temporal and spatial scales. This article explores the importance and functionalities of this type of software, highlighting its role in improving research methodologies and generating scientific knowledge applicable to oceanography and meteorology. drifViewer is a MATLAB package designed to optimize the search for drift trajectories and analyze oceanographic parameters. It allows researchers to search for drift trajectories in the AOML dataset quickly, create summary tables, and export data to MATLAB and NetCDF formats. driftViewer contributes to scientific research in oceanography and marine geology by improving the ability to model and predict drifting currents, which is essential for studies on climate change, ocean current dynamics, and marine habitat conservation. It is also a useful tool for studying the trajectories of oil slicks, microplastics, and chemical and living species.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100719"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743489","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}
引用次数: 0
PostgreSQL: Relational database structures application on capacitated lot-sizing for pharmaceutical tablets manufacturing processes PostgreSQL：关系型数据库结构在药物片剂生产过程中的容许批量大小上的应用
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100720
Michael Simonis , Stefan Nickel
{"title":"PostgreSQL: Relational database structures application on capacitated lot-sizing for pharmaceutical tablets manufacturing processes","authors":"Michael Simonis ,&nbsp;Stefan Nickel","doi":"10.1016/j.simpa.2024.100720","DOIUrl":"10.1016/j.simpa.2024.100720","url":null,"abstract":"<div><div>Multi-level capacitated lot-sizing problems with linked lot sizes and backorders (MLCLSP-L-B) are used in pharmaceutical tablets manufacturing processes to right-size material production lots so that costs are kept at a minimum, production resource capacities are not exceeded, and customer demand is fulfilled. Uncertain demand behavior characterizes today’s global tablets market. Pharmaceutical companies request solution approaches that solve the MLCLSP-L-B with probabilistic demand. Implementing this model in industrial applications for tablets manufacturing systems requires efficient data processing due to the amount of data and the capability to store simulated demand scenarios. This paper covers the first integration of the MLCLSP-L-B with probabilistic demand and Relational Database Structures (RDS). Modeling techniques for the RDS to process massive data are outlined. A virtual environment provides the implementation software PostgreSQL and infrastructure environment. Additionally, numerical experiments with research data are used to evaluate the agility and efficiency of the developed RDS.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100720"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703378","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}
引用次数: 0
VulnMiner: A comprehensive framework for vulnerability collection from C/C++ source code projects 一个全面的框架，用于从C/ c++源代码项目中收集漏洞
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100713
Guru Bhandari, Nikola Gavric, Andrii Shalaginov
{"title":"VulnMiner: A comprehensive framework for vulnerability collection from C/C++ source code projects","authors":"Guru Bhandari,&nbsp;Nikola Gavric,&nbsp;Andrii Shalaginov","doi":"10.1016/j.simpa.2024.100713","DOIUrl":"10.1016/j.simpa.2024.100713","url":null,"abstract":"<div><div>The study introduces <em>VulnMiner</em>, a comprehensive framework encompassing a data extraction tool tailored for identifying vulnerabilities in C/C++ source code. Moreover, it unveils an initial release of a vulnerability dataset, curated from prevalent projects and annotated with vulnerable and benign instances. This dataset incorporates projects with vulnerabilities labeled as Common Weakness Enumeration (CWE) categories. The developed open-source extraction tool collects vulnerability data utilizing static security analyzers. The study also fosters the machine learning (ML) and natural language processing (NLP) model’s effectiveness in accurately classifying vulnerabilities, evidenced by its identification of numerous weaknesses in open-source projects.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100713"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142742851","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}
引用次数: 0
HCTF-PRO: A code for probabilistic analysis of process efficiency in helically coiled tube flocculators HCTF-PRO：螺旋卷管絮凝器工艺效率概率分析代码
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100717
Danieli Soares de Oliveira , Clainer Bravin Donadel
{"title":"HCTF-PRO: A code for probabilistic analysis of process efficiency in helically coiled tube flocculators","authors":"Danieli Soares de Oliveira ,&nbsp;Clainer Bravin Donadel","doi":"10.1016/j.simpa.2024.100717","DOIUrl":"10.1016/j.simpa.2024.100717","url":null,"abstract":"<div><div>In water treatment, ensuring adequate quantity and quality is crucial. The coagulation/flocculation stage is a focus of ongoing research, with novel methods being explored. Among these, the helically coiled tube flocculator (HCTF) has shown promising results in turbidity removal with reduced processing times. This study introduces a computational tool to determine the optimal HCTF length and conducts a probabilistic performance analysis. The analysis considers the uncertainties in hydraulic parameters following the definition of the flocculator’s geometric parameters, contributing to a deeper understanding and optimization of HCTF applications in water treatment.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100717"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724076","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}
引用次数: 0
IpyDisp v2 alias DuduTracker: A web-based version IpyDisp v2 别名 DuduTracker：网络版
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100722
Komi Mensah Agboka , Elfatih M. Abdel-Rahman , Samira A. Mohamed , Sunday Ekesi
{"title":"IpyDisp v2 alias DuduTracker: A web-based version","authors":"Komi Mensah Agboka ,&nbsp;Elfatih M. Abdel-Rahman ,&nbsp;Samira A. Mohamed ,&nbsp;Sunday Ekesi","doi":"10.1016/j.simpa.2024.100722","DOIUrl":"10.1016/j.simpa.2024.100722","url":null,"abstract":"<div><div>This study presents the updated <em>version v2</em> of IpyDisp named <em>DuduTracker</em> which improves on the window-only-requirement of <em>IpyDisp</em>. The updated version is web-based that can be used in alternative operating systems like Ubuntu, Mac, Linux, and others. The update’s effectiveness was also evaluated using a survey involving a diverse range of users including students, data analysts, and academic researchers from different age groups, geographical locations, and computer literacy levels. Areas for future enhancement were identified, primarily focused on making the software responsive to various screen types and improving certain interface aspects.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100722"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723883","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}
引用次数: 0
Transformer-based deep learning architecture for time series forecasting 基于变换的时间序列预测深度学习架构
IF 1.3
Software Impacts Pub Date : 2024-11-01 DOI: 10.1016/j.simpa.2024.100716
G.H. Harish Nayak , Md Wasi Alam , G. Avinash , Rajeev Ranjan Kumar , Mrinmoy Ray , Samir Barman , K.N. Singh , B. Samuel Naik , Nurnabi Meherul Alam , Prasenjit Pal , Santosha Rathod , Jaiprakash Bisen
{"title":"Transformer-based deep learning architecture for time series forecasting","authors":"G.H. Harish Nayak ,&nbsp;Md Wasi Alam ,&nbsp;G. Avinash ,&nbsp;Rajeev Ranjan Kumar ,&nbsp;Mrinmoy Ray ,&nbsp;Samir Barman ,&nbsp;K.N. Singh ,&nbsp;B. Samuel Naik ,&nbsp;Nurnabi Meherul Alam ,&nbsp;Prasenjit Pal ,&nbsp;Santosha Rathod ,&nbsp;Jaiprakash Bisen","doi":"10.1016/j.simpa.2024.100716","DOIUrl":"10.1016/j.simpa.2024.100716","url":null,"abstract":"<div><div>Time series forecasting faces challenges due to the non-stationarity, nonlinearity, and chaotic nature of the data. Traditional deep learning models like RNNs, LSTMs, and GRUs process data sequentially but are inefficient for long sequences. To overcome the limitations of these models, we proposed a transformer-based deep learning architecture utilizing an attention mechanism for parallel processing, enhancing prediction accuracy and efficiency. This paper presents user-friendly code for the implementation of the proposed transformer-based deep learning architecture utilizing an attention mechanism for parallel processing.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100716"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743490","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}
引用次数: 0
A real-time cyberbully checker 实时网络欺凌检查器
IF 1.3
Software Impacts Pub Date : 2024-10-19 DOI: 10.1016/j.simpa.2024.100710
Johnny Chan, Shohil Kishore, Xin Yang
{"title":"A real-time cyberbully checker","authors":"Johnny Chan,&nbsp;Shohil Kishore,&nbsp;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}
引用次数: 0
ShpStreetGraph: From spatial relations of streets to graph representations ShpStreetGraph：从街道空间关系到图形表示法
IF 1.3
Software Impacts Pub Date : 2024-10-18 DOI: 10.1016/j.simpa.2024.100711
Pablo V.R. Silva , Aurelienne A.S. Jorge , Leonardo B.L. Santos , Vander L.S. Freitas
{"title":"ShpStreetGraph: From spatial relations of streets to graph representations","authors":"Pablo V.R. Silva ,&nbsp;Aurelienne A.S. Jorge ,&nbsp;Leonardo B.L. Santos ,&nbsp;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}
引用次数: 0
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