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Breadcrumbs for your Deep Learning Model: Following Provenance Traces with DLProv 你的深度学习模型的面包屑：用dlproof跟踪来源痕迹
IF 1.3
Software Impacts Pub Date : 2025-03-01 Epub Date: 2024-12-13 DOI: 10.1016/j.simpa.2024.100730
Débora Pina , Liliane Kunstmann , Daniel de Oliveira , Marta Mattoso
{"title":"Breadcrumbs for your Deep Learning Model: Following Provenance Traces with DLProv","authors":"Débora Pina ,&nbsp;Liliane Kunstmann ,&nbsp;Daniel de Oliveira ,&nbsp;Marta Mattoso","doi":"10.1016/j.simpa.2024.100730","DOIUrl":"10.1016/j.simpa.2024.100730","url":null,"abstract":"<div><div>To train a Deep Learning (DL) model, a workflow must be executed with four well-defined activities: (i) Acquiring data, (ii) Preprocessing, (iii) Splitting and balancing the dataset, and (iv) Building and training the model. After generating several DL models, they undergo a process called model selection. After being selected, the DL model is put into a production environment to make predictions on new data. One of the challenges in supporting these analyses is related to providing relationships between candidate models, their datasets for train, test, and validation, input data, and other derivations paths. These relationships are also essential for trust, reproducibility, and evolution of the selected model. While existing solutions allow monitoring and analyzing the artifacts generated throughout the DL workflow, they often fail to establish relationships for supporting data derivation within the DL workflow. DLProv is a provenance-centric service to support DL workflow analyses and reproducibility. DLProv captures provenance data and exports provenance graphs for DL model reproducibility. DLProv is W3C PROV compliant, ensuring standardized prospective and retrospective provenance, and enables provenance capture in arbitrary execution frameworks.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100730"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143139895","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
SpatialzOSM: A Python package for supporting the explicit spatialization in the population synthesis process SpatialzOSM：一个Python包，用于支持人口综合过程中的显式空间化
IF 1.3
Software Impacts Pub Date : 2025-03-01 Epub Date: 2024-12-05 DOI: 10.1016/j.simpa.2024.100724
Bladimir Toaza, Domokos Esztergár-Kiss
{"title":"SpatialzOSM: A Python package for supporting the explicit spatialization in the population synthesis process","authors":"Bladimir Toaza,&nbsp;Domokos Esztergár-Kiss","doi":"10.1016/j.simpa.2024.100724","DOIUrl":"10.1016/j.simpa.2024.100724","url":null,"abstract":"<div><div>SpatialzOSM, a package to spatialize aggregated locations into coordinates, thereby supporting population synthesis processes. This paper addresses the need for high-resolution data while ensuring data privacy. SpatialzOSM features include the generation of coordinates using three random distribution techniques: across zones, along road networks, and within buildings for residential locations. For non-residential locations, the package extracts points of interest from open sources. By leveraging open-source data, SpatialzOSM minimizes the risks of reidentification associated with census and survey datasets, ensuring privacy protection. This package is valuable for researchers and modelers engaged in synthetic population generation for models requiring explicit geographic location data.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100724"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143139894","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
pff-oc: A space–time phase-field fracture optimal control framework pff-oc：时空相场断裂最优控制框架
IF 1.3
Software Impacts Pub Date : 2025-03-01 Epub Date: 2025-01-02 DOI: 10.1016/j.simpa.2024.100734
Denis Khimin, Marc Christian Steinbach, Thomas Wick
{"title":"pff-oc: A space–time phase-field fracture optimal control framework","authors":"Denis Khimin,&nbsp;Marc Christian Steinbach,&nbsp;Thomas Wick","doi":"10.1016/j.simpa.2024.100734","DOIUrl":"10.1016/j.simpa.2024.100734","url":null,"abstract":"<div><div>This codebase is developed to address optimal control problems in phase-field fracture, aiming to achieve a desired fracture pattern in brittle materials through the application of external forces. Built alongside our recent work (Khimin et al., 2022), this framework provides an efficient and precise approach for simulating space–time phase-field optimal control problems. In this setup, the fracture is controlled via Neumann boundary conditions, with the cost functional designed to minimize the difference between the actual and desired fracture states. The implementation relies on the open-source libraries DOpElib (Goll et al., 2017) and deal.II (Arndt et al. <span><span>[1]</span></span>, <span><span>[2]</span></span>)</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100734"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143139898","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
dexisensitivity: An R package to perform sensitivity analyses of DEXi models 灵敏度：一个R包执行灵敏度分析的DEXi模型
IF 1.3
Software Impacts Pub Date : 2025-03-01 Epub Date: 2024-12-13 DOI: 10.1016/j.simpa.2024.100729
Roland Allart , Aude Alaphilippe , Marta Carpani , Nicolas Cavan , Hervé Monod , Jacques-Eric Bergez
{"title":"dexisensitivity: An R package to perform sensitivity analyses of DEXi models","authors":"Roland Allart ,&nbsp;Aude Alaphilippe ,&nbsp;Marta Carpani ,&nbsp;Nicolas Cavan ,&nbsp;Hervé Monod ,&nbsp;Jacques-Eric Bergez","doi":"10.1016/j.simpa.2024.100729","DOIUrl":"10.1016/j.simpa.2024.100729","url":null,"abstract":"<div><div>DEXi is a software for developing qualitative hierarchical models. Widely used in the French agriculture sector to analyze the sustainability of farming systems, the sensitivity analyses of the models are still missing. The <em>dexisensitivity</em> R package performs such sensitivity analyses. Written using R S4 Object programming, it performs basic functions (reads DEXi models, describes and draws the models, generates and simulates scenarios) and other functions to perform different types of sensitivity analyses: analysis of variance, One-At-A-Time, sensitivity indexes using the Shapiro-Shapley approach… The <em>dexisensitivity</em> R package is distributed under the GPL license and is accessible from CRAN and GitHub.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100729"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143139886","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
RTC-MR: A WebRTC-based framework for real-time communication in Mixed Reality RTC-MR：混合现实中基于web的实时通信框架
IF 1.3
Software Impacts Pub Date : 2025-03-01 Epub Date: 2024-12-05 DOI: 10.1016/j.simpa.2024.100727
Francisco M. García, Santiago Schez-Sobrino, Carlos Glez-Morcillo, José J. Castro-Schez, Javier A. Albusac, David Vallejo
{"title":"RTC-MR: A WebRTC-based framework for real-time communication in Mixed Reality","authors":"Francisco M. García,&nbsp;Santiago Schez-Sobrino,&nbsp;Carlos Glez-Morcillo,&nbsp;José J. Castro-Schez,&nbsp;Javier A. Albusac,&nbsp;David Vallejo","doi":"10.1016/j.simpa.2024.100727","DOIUrl":"10.1016/j.simpa.2024.100727","url":null,"abstract":"<div><div>This paper presents RTC-MR, a real-time communications framework designed for integrating WebRTC into Mixed Reality (MR) environments, particularly optimised for Microsoft HoloLens 2™. By reducing the complexity associated with WebRTC implementation, our proposal aims to simplify the creation of custom applications that demand real-time audiovisual interaction. Beyond facilitating the development of MR applications, RTC-MR provides a valuable resource for both developers and researchers interested in exploring the full potential of MR in remote support scenarios and various other applications.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100727"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143139892","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
HoughVG:Hough Transform Toolbox for Straight-Line Detection and Fingerprint Recognition HoughVG：用于直线检测和指纹识别的 Hough 变换工具箱
IF 1.3
Software Impacts Pub Date : 2024-11-01 Epub Date: 2024-10-11 DOI: 10.1016/j.simpa.2024.100709
Moïse Ouedraogo , Abdoulaye Sere , Cheick Amed Diloma Gabriel Traore
{"title":"HoughVG:Hough Transform Toolbox for Straight-Line Detection and Fingerprint Recognition","authors":"Moïse Ouedraogo ,&nbsp;Abdoulaye Sere ,&nbsp;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":"2024-11-01","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}
引用次数: 0
SlabCutOpt: A code for ornamental stone slab cut optimization SlabCutOpt：装饰石板切割优化代码
IF 1.3
Software Impacts Pub Date : 2024-11-01 Epub Date: 2024-10-18 DOI: 10.1016/j.simpa.2024.100704
S. Bonduà , S. Focaccia , M. Elkarmoty
{"title":"SlabCutOpt: A code for ornamental stone slab cut optimization","authors":"S. Bonduà ,&nbsp;S. Focaccia ,&nbsp;M. Elkarmoty","doi":"10.1016/j.simpa.2024.100704","DOIUrl":"10.1016/j.simpa.2024.100704","url":null,"abstract":"<div><div>Rock masses are naturally affected by discontinuities, joints and fractures that affect their exploitation. After block extraction, different cutting pattern can produce different recovery ratio of the block. The optimization of the cutting pattern can be computed if the discontinuities are mapped by the use of non-destructive methods. We propose a software code able to compute the number of intersected slabs by different cuttings scenarios. The algorithm adopts a brute force computation of several scenarios as specified by the user. The software uses the Open MP library in order to reduce computation time.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100704"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573305","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 : 2024-11-01 Epub 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":"2024-11-01","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
Enhanced leaf disease detection: UNet for segmentation and optimized EfficientNet for disease classification 增强叶片病害检测：用于分割的 UNet 和用于病害分类的优化 EfficientNet
IF 1.3
Software Impacts Pub Date : 2024-11-01 Epub Date: 2024-09-14 DOI: 10.1016/j.simpa.2024.100701
Jameer Kotwal , Ramgopal Kashyap , Pathan Mohd Shafi , Vinod Kimbahune
{"title":"Enhanced leaf disease detection: UNet for segmentation and optimized EfficientNet for disease classification","authors":"Jameer Kotwal ,&nbsp;Ramgopal Kashyap ,&nbsp;Pathan Mohd Shafi ,&nbsp;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":"2024-11-01","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}
引用次数: 0
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 Epub Date: 2024-11-20 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
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