IEEE Latin America Transactions最新文献

{"title":"Short-Term Day-Ahead Hydrothermal Scheduling with Energy Renewables Variable, Storage, Load Shedding using Artificial Intelligence Techniques for Demand Forecasting","authors":"Alfonso Vazquez Mendoza;Héctor Francisco Ruiz Paredes","doi":"10.1109/TLA.2025.11072500","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072500","url":null,"abstract":"Short-Term Hydrothermal Scheduling (STHS) is a very complex, multimodal, nonlinear optimization problem that has primarily been addressed by conventional and, more recently, metaheuristic optimization algorithms. The objective of conventional STHS is to optimize the hourly energy production of hydroelectric power plants and other generation sources over a specific period of time, allowing for the determination of the optimal economic operation of the Power Electrical System (PES). The conventional STHS formulation is widely used in the planning, analysis and operation of PES. However, nowadays PES incorporate variable renewable generation such as wind and solar photovoltaic power, as well as Energy Storage Systems (ESS), transmission grid models and load shedding scenarios in case of possible operational contingencies. This paper presents a STHS formulated and simulated using nonlinear programming for a day ahead, using artificial neural networks (ANN) for demand forecasting. The integration of wind and solar photovoltaic generation, ESS and cascaded hydroelectric power plants is considered, along with the transmission grid and load shedding models, all within a single optimization problem. The objective is to minimize generation costs and optimize power usage, dispatching the units in the most efficient manner. The efficient assignment of thermal, hydro, solar, wind units and ESS allows for optimal use of available water without exceeding reservoir limits. The formulation is validated using the IEEE 30-node system, obtaining optimal solutions in all scenarios, without the need to relax system constraints for convergence.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"696-705"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072500","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of fruit number in coffee trees by maturity level, based on color space weighting, using a new segmentation algorithm","authors":"Mario Luiz Tronco;Ingrid Lorena Argote Pedrazza;Emerson Carlos Pedrino;Carlos Roberto Valencio","doi":"10.1109/TLA.2025.11072497","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072497","url":null,"abstract":"Computer vision systems are essential for automating agricultural tasks such as disease detection and fruit defect identification. However, their application in coffee farming faces significant challenges due to environmental variability and the complex structure of coffee trees, which complicate image acquisition. Thus, this study addresses two key questions: 1) Can low-cost, user-friendly equipment adapt to crop conditions while ensuring image quality 2) Can a computer vision algorithm accurately count and classify coffee beans with over 80% accuracy using data from low-cost cameras To answer these questions, an image acquisition system was developed based on the phenological characteristics of coffee plants, ensuring focused and consistent image capture. Additionally, a novel algorithm was created, utilizing statistical analysis of color spaces to effectively separate fruits from the background, segment images, and count fruits. The algorithm achieved accuracy rates, when compared with a traditional approach, within the desired range for each coffee fruit class: green (83%), green-olive (79%), cherry (86%), and raisin (80%). These results demonstrate the potential of this approach for accurate and efficient fruit processing in coffee farming, particularly when images are captured directly from tree branches.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"736-742"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072497","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bidirectional Step-Up Multi-Input Converter with Improved Voltage Gain for DC Microgrids","authors":"Mudadla Dhananjaya;Devendra Potnuru;Ramesh Devarapalli;Malleswara Rao K Durga;Thanikanti Sudhakar Babu","doi":"10.1109/TLA.2025.11072504","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072504","url":null,"abstract":"High-gain converters are well-established circuit designs that find practical use in industrial and commercial settings, particularly in applications demanding high power ratings, such as Fuel Cell Electric Vehicles (FCEV) and grid-connected Renewable Energy Sources (RES). High-gain topologies from a single source pose reliability issue in RES applications due to increased device count and stress. In the event of source failure, these topologies may lead to an energy supply gap for the loads. Addressing this challenge, integrating diverse energy sources with step-up voltage capability stands as a promising solution for both DC microgrid and Electric Vehicle (EV) applications. In this study, a Dual-Input Single-Output (DISO) converter is introduced to integrate various sources and achieve an increased output voltage gain by charging the inductors in parallel and discharging them in series. Moreover, if any sources fail, the converter can supply the energy to the load from the available source and it can be operated in bidirectional mode. This paper also extensively discusses theoretical analysis, considerations related to design and circuit modeling. Furthermore, include a comparison of this converter with several other topologies. It examined to validated with a 250 W laboratory prototype.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"675-686"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072504","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmentative and Alternative Communication Using Eye Tracking and Word Recommendation Using Language Models","authors":"Bruno Waideman;Plínio Thomaz Aquino","doi":"10.1109/TLA.2025.11072932","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072932","url":null,"abstract":"The production, storage, and dissemination of information have evolved from ancient communication methods to modern digital technologies, with digital media playing a key role in connecting individuals. While keyboards are common tools for interaction, they present challenges for individuals with motor impairments. Augmentative and Alternative Communication (AAC) techniques, including gesture input, voice commands, and sensor-based systems, have emerged to address these limitations. Eye tracking, used in accessibility systems, offers both opportunities and challenges, such as visual fatigue and inaccuracies that lead to slower typing. To address these challenges, this study proposes an interaction approach integrating eye movement tracking with a virtual keyboard, utilizing an artificial neural network to interpret gaze data and translate intentions within the interface at a low cost for the user. Additionally, a Language Model (LM) aids in predicting next-word suggestions. This research will assess the impact of these technologies on typing speed, error rate, and linguistic predictability, contributing both scientifically and societally to the advancement of accessible communication systems.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"637-645"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072932","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Table of Contents August 2025","authors":"","doi":"10.1109/TLA.2025.11072502","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072502","url":null,"abstract":"","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"636-636"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072502","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attention Blocks Improve White Matter Hyperintensity Semantic Segmentation using U-Nets","authors":"Kauê Tartarotti Nepomuceno Duarte;Murilo Costa de Barros;Abhijot Singh Sidhu;David Gobbi;Cheryl McCreary;Feryal Saad;Richard Camicioli;Eric Smith;Marco Carvalho;Richard Frayne","doi":"10.1109/TLA.2025.11072499","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072499","url":null,"abstract":"White matter hyperintensities (WMHs) are a common finding on magnetic resonance (MR) images in older individuals, appearing as high-signal intensity regions on fluid-attenuated inversion recovery (FLAIR) imaging. People with high WMH volume are at increased risk for dementia and stroke, controlling for vascular risk factors, but WMH burden is not reliably assessed in clinical practice. Manual segmentation of WMHs is accepted as the gold standard (or ground truth), however, it is a laborious and time-consuming method. Newer machine learning (ML)-based approaches are being proposed as alternatives to manual segmentation. Among these approaches, U-Net convolutional neural networks have demonstrated good WMH segmentation performance. However, even state-of-the-art ML models sometimes fail to correctly identify WMHs and their boundaries with sufficient accuracy. Attention blocks have emerged as a potential solution for improving the performance of U-Net models by enhancing the ability of the model to focus on relevant features in the data. We investigated the effectiveness of attention blocks in U-Net models for WMH segmentation compared to three other models (U-Net++, U-Net3+, and a standard U-Net). Attention blocks significantly improved the F-measure score for WMH segmentation (0.811 vs 0.789 for next best model, p=0.04) in a diverse brain imaging dataset. This study demonstrates that attention blocks enhance U-Net models used for WMH identification and classification.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"646-661"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072499","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Welfare Optimization in Energy Communities with P2P Markets","authors":"Sofía Chacón;Katerine Guerrero;Germán Obando;Andrés Pantoja","doi":"10.1109/TLA.2025.11072495","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072495","url":null,"abstract":"We address the requirement for Energy Communities (ECs) to integrate efficient Energy Management Systems (EMSs) that optimize resource operation and maximize the benefits for participants. In this work, we implement an EMS that considers the supply and demand profiles of agents, fostering their engagement and ensuring their continued involvement within the community. We establish a mathematical model of an EC composed of prosumers with different types of distributed energy resources and pure consumers. The EMS integrates game theory and optimization techniques to coordinate and schedule energy transactions using welfare functions. Through the developed algorithm, the maximization of community welfare is ensured. This method is compared with the traditional Interior-Point Method (IPM). The results indicate a normalized error average of 0.23%. We simulate a community with six agents and analyze two case studies. The results show that the EMS promotes agent participation by optimizing their resources and achieving more competitive buy and sell prices compared to the main grid. Furthermore, the EMS prioritizes energy dispatch within the EC over transactions with the main grid and accounts for generation costs. The implementation of the EMS improves community welfare, thus contributing to the sustainability of the EC.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"687-695"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072495","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Satellite and Reanalysis Models for Solar Irradiance Estimation in Northwest Argentina","authors":"Rubén Ledesma;Rodrigo Alonso-Suárez;Germán Salazar;Fernando Nollas;Olga Vilela","doi":"10.1109/TLA.2025.11072498","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072498","url":null,"abstract":"Accurate solar resource assessment is critical for the development of solar energy projects, especially in regions with complex climatic and geographic conditions. This study evaluates the performance of various satellite-based and reanalysis models in estimating global horizontal irradiance (GHI) in Northwestern Argentina, focusing on two locations characterized by different environmental conditions: La Quiaca and Salta. Five satellite-based models (CAMS Heliosat-4, NREL NSRDB, GOES DSR, LSA-SAF MDSSFTD, and GOES G-CIM) and two reanalysis datasets (MERRA-2 and ERA-5) were analysed and compared with high-quality ground-based measurements recorded between 2020 and 2023. The results show that the G-CIM and NSRDB models provide the most accurate irradiance estimates, effectivelyminimising errors even in challenging environments with extreme altitude or variable terrain reflectivity. At the 10-minute time scale in Salta, the G-CIM model yields a root mean squared deviation (RMSD) of 23.4% and a mean bias of 4.8%, whereas the NSRDB model records an RMSD of 26.6% and a mean bias of 4.2%. In La Quiaca, both models achieve RMSD values below 20% and mean biases under 1%. At the 60-minute scale, in Salta, G-CIM and NSRDB exhibit RMSDs of 20.7% and 19.7%, with corresponding mean biases of 5.4% and 3.6%, respectively, while in La Quiaca they maintain mean biases below 1% and RMSDs of 13.2% for G-CIM and 12.6% for NSRDB. Conversely, the MERRA-2 and ERA-5 reanalysis models showed higher uncertainties, particularly in areas with significant microclimatic variations. The study highlights the importance of using locally validated satellite data for accurate solar resource assessment and emphasises the need for site-specific adjustments when applying global irradiance models. These findings contribute to improved planning and decision-making for solar energy projects in Northwest Argentina and provide valuable insights for researchers, policy makers and industry professionals.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"706-717"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redefining Human-Machine Collaboration: Industry 5.0 to Improve Safety and Efficiency","authors":"Francisco Antonio Lloret Abrisqueta;Antonio Guerrero González;Roberto Zapata Martinez","doi":"10.1109/TLA.2025.11072501","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072501","url":null,"abstract":"This study presents an innovative implementation of Industry 5.0 principles in a window production line, integrating advanced robotics and artificial intelligence technologies to improve operational efficiency and worker well-being. A robotic cell was designed to automate the handling of heavy components in the final production stage, resulting in a 35% reduction in cycle times and a significant decrease in ergonomic risks. Additionally, an interactive voice assistant based on generative AI was implemented, allowing operators to access system data and technical information in real-time through cognitive interaction. The results show a substantial improvement in job satisfaction, with a 278% increase in the perception of occupational health. This approach not only optimizes productivity but also redefines workers' roles, aligning with the human-centered vision of Industry 5.0. The study demonstrates how the integration of advanced technologies can create safer, more efficient, and adaptable work environments in modern manufacturing.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"729-735"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DeepRetinaNet: An Automated AI-Based Framework for Retinal Disease Diagnosis","authors":"Akshya Kumar Sahoo;Priyadarsan Parida;Manoj Kumar Panda;Chittaranjan Nayak;N. Mohankumar","doi":"10.1109/TLA.2025.11072496","DOIUrl":"https://doi.org/10.1109/TLA.2025.11072496","url":null,"abstract":"Automated retinal disease diagnosis leveraging cutting-edge computer vision methodologies supports clinicians in the early identification of pathological conditions. This investigation delivers a novel framework, DeepRetinaNet for automating retinal disease diagnosis. The developed DeepRetinaNet model has two stages of novelties, including vessel extraction followed by disease identification. In the vessel extraction stage, the green channel, known for its heightened sensitivity to retinal vascular structures, is extracted from the source images. Subsequently, the vessel extraction network: RetiSegNet, processes these green channel images to extract retinal vessels, generating binary vessel maps. During the fusion phase, the original fundus images are combined with the extracted vessel maps to produce fused representations, encapsulating enriched spatial details from both sources. In the identification stage, these fused images are utilized to train the proposed classification framework: STDeepNet, which incorporates Modified Identity (MI), Modified Convolution (MCONV) blocks, and Long Short-Term Memory (LSTM) layers to effectively identify the diseases. The efficacy of the developed technique is corroborated using visual illustration and objective analysis. Also, the efficiency of the designed framework is verified on six benchmark datasets. The proposed framework demonstrates superior performance compared to 49 state-of-the-art methods, achieving notable accuracy in retinal disease diagnosis.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 8","pages":"718-728"},"PeriodicalIF":1.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}