IEEE Latin America Transactions最新文献_第9页

Real-time Object Detection Performance Analysis Using YOLOv7 on Edge Devices 在边缘设备上使用 YOLOv7 进行实时物体检测性能分析

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705971

Ricardo C. Camara de M. Santos;Mateus Coelho;Ricardo Oliveira

{"title":"Real-time Object Detection Performance Analysis Using YOLOv7 on Edge Devices","authors":"Ricardo C. Camara de M. Santos;Mateus Coelho;Ricardo Oliveira","doi":"10.1109/TLA.2024.10705971","DOIUrl":"https://doi.org/10.1109/TLA.2024.10705971","url":null,"abstract":"Real-time object detection in images is one of the most important areas in computer vision and finds applications in several fields, such as security systems, protection, independent vehicles, and robotics. Many of these applications need to use edge hardware platforms, and it is vital to know the performance of the object detector on these hardware platforms before developing the system. Therefore, in this work, we executed performance benchmark tests of the YOLOv7-tiny model for real-time object detection using a camera and three embedded hardware platforms: Raspberry Pi 4B, Jetson Nano, and Jetson Xavier NX. We tested and analyzed the NVIDIA platforms and their different power modes. The Raspberry Pi 4B achieved an average of 0.9 FPS. The Jetson Xavier NX achieved 30 FPS, the maximum possible FPS rate, in three power modes. In the tests, it was possible to notice that the maximum CPU clock of the Jetson Xavier NX impacts the FPS rate more than the GPU clock itself. The Jetson Nano achieved 7.4 and 5.2 FPS in its two power consumption modes.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 10","pages":"799-805"},"PeriodicalIF":1.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705971","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376789","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}

引用次数: 0

Transmission Network Expansion Planning Considering Uncertainty in Demand with Global and Nodal Approach 考虑需求不确定性的输电网络扩建规划与全局和节点方法

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705973

Nestor Gonzalez-Cabrera;Daniel Ernesto Hernandez Reyes;Vicente Torres García

{"title":"Transmission Network Expansion Planning Considering Uncertainty in Demand with Global and Nodal Approach","authors":"Nestor Gonzalez-Cabrera;Daniel Ernesto Hernandez Reyes;Vicente Torres García","doi":"10.1109/TLA.2024.10705973","DOIUrl":"https://doi.org/10.1109/TLA.2024.10705973","url":null,"abstract":"Transmission expansion planning aims to establish when and where to install new infrastructure such as transmission lines, cables, generators and transformers in the electrical power system. The planning must be motivated mainly to satisfy the increase in demand, consequently increase the reliability of the system and provide non-discriminatory access for generators and consumers to the electrical grid. In this sense, this work aims to propose a methodology to handle demand uncertainty by reducing scenarios through the K-means clustering algorithm, which is used to construct representative demand curves that allow using a static model of stochastic linear optimization with less computational effort, which seeks to minimize the investment and operating costs of the electrical system, meeting the total demand of the system. The global demand and nodal demand approach of the system is compared, observing the behaviour of investment and operating costs, as well as their advantages. The results demonstrate that the formulation can be estimate the number of scenarios through mathematical metrics and the global demand approach has the advantage of only needing data on the behavior of the total demand of the system.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 10","pages":"864-870"},"PeriodicalIF":1.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705973","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376970","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}

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Table of Contents October 2024 目录 2024 年 10 月

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705968

引用次数: 0

Addressing Class Imbalance in Healthcare Data: Machine Learning Solutions for Age-Related Macular Degeneration and Preeclampsia 解决医疗保健数据中的类别失衡问题：针对年龄相关性黄斑变性和先兆子痫的机器学习解决方案

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705995

Antonieta Martinez-Velasco;Lourdes Martínez -Villaseñor;Luis Miralles-Pechuán

{"title":"Addressing Class Imbalance in Healthcare Data: Machine Learning Solutions for Age-Related Macular Degeneration and Preeclampsia","authors":"Antonieta Martinez-Velasco;Lourdes Martínez -Villaseñor;Luis Miralles-Pechuán","doi":"10.1109/TLA.2024.10705995","DOIUrl":"https://doi.org/10.1109/TLA.2024.10705995","url":null,"abstract":"The use of machine learning in healthcare has transformed the way diseases are diagnosed and treatments are optimized. However, medical databases often lack balanced data due to challenges in data collection caused by privacy regulations. Certain health conditions are under represented, which hampers machine learning performance. To address this problem, a hybrid approach has been proposed that combines the Synthetic Minority Oversampling Technique (SMOTE) with under sampling and uses two specific techniques tailored for imbalanced datasets. Comparative evaluations were conducted using various thresholds to reduce one class and employingBalanced Accuracy to mitigate bias toward the majority class, with popular machine learning methods. The results showed that Balanced Bagging and Balanced Random Forest consistently outperformed other methods, performing the best with an average ranking of 1.42 and 3.58 out of 32 configurations in the two datasets, respectively. Tree-based approaches such as Random Forest and Gradient Boosting demonstrated similar effectiveness, emphasizing the power of aggregating predictions from multiple trees to reduce bias. Notably, under sampling andSMOTE proved advantageous for non-tree-based models likeKNN, SVM, and Logistic Regression showcasing their usefulness across different algorithms. This study provides a robust solution for handling imbalanced datasets in healthcare, which could potentially optimize healthcare interventions and improve patient outcomes and care.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 10","pages":"806-820"},"PeriodicalIF":1.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705995","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376985","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}

引用次数: 0

Deep Learning Based Hybrid Beamforming for mmWave Dual-Functional Radar-Communication 基于深度学习的毫米波双功能雷达-通信混合波束成形

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705967

Xiaoyou Yu;Tianchu Li;Ziyun Tian;Miao Yu

引用次数: 0

IoT-based Environmental Monitoring and Prediction of Banana Moisture Content in a Solar Greenhouse Dryer 基于物联网的环境监测以及太阳能温室干燥机中香蕉水分含量的预测

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705969

Baltazar López-Velasco;Agustin Ruiz-Garcia;José Guillermo Cebada-Reyes;Carlos Alberto Villaseñor-Perea

{"title":"IoT-based Environmental Monitoring and Prediction of Banana Moisture Content in a Solar Greenhouse Dryer","authors":"Baltazar López-Velasco;Agustin Ruiz-Garcia;José Guillermo Cebada-Reyes;Carlos Alberto Villaseñor-Perea","doi":"10.1109/TLA.2024.10705969","DOIUrl":"https://doi.org/10.1109/TLA.2024.10705969","url":null,"abstract":"Modernizing the drying process will reduce agricultural product waste and environmental pollution. The aim of this study was to design a monitoring system based on the internet of things (IoT), temperature and relative humidity for a solar dryer. This system consists of a data collection module that gathers data regarding temperature (Ta), external relative humidity (RH) and on/off time of the solar dryer exhaust fans; a communication module that transmits Ta and RH information via LoRa and Wifi to ThingSpeak for monitoring on a mobile device; and a power module providing electrical power for system operation by solar energy. The operation of the IoT monitoring system was evaluated in three drying experiments of Dominican bananas (Musa paradisiaca var sapientum), in which system performance was satisfactory, allowing the user to visualize graphically in a web and mobile interface the behavior of Ta and RH inside the dryer. The data measured by the system were used to predict banana moisture content with an autoregressive model with exogenous variables (ARX) identified online. The mathematical model found predicted the behavior of moisture content with a good goodness of fit, with values of R2 = 0.99, MSE = 1.2910-5 and MAE = -5.0310-6. The solar dryer allowed reducing the moisture content of bananas up to 19.84 % wet basis (w.b.) in a period of 4 days and by 20.03% w.b. for 5 days in the presence of rainfall.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 10","pages":"881-890"},"PeriodicalIF":1.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376618","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}

引用次数: 0

Learnable Query Contrast and Spatio-temporal Prediction on Point Cloud Video Pre-training 点云视频预培训的可学习查询对比度和时空预测

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10705970

Xiaoxiao Sheng;Zhiqiang Shen;Longguang Wang;Gang Xiao

{"title":"Learnable Query Contrast and Spatio-temporal Prediction on Point Cloud Video Pre-training","authors":"Xiaoxiao Sheng;Zhiqiang Shen;Longguang Wang;Gang Xiao","doi":"10.1109/TLA.2024.10705970","DOIUrl":"https://doi.org/10.1109/TLA.2024.10705970","url":null,"abstract":"Point cloud videos capture the time-varying environment and are widely used for dynamic scene understanding. Existing methods develop effective networks for point cloud videos but do not fully utilize the prior information uncovered during pre-training. Furthermore, relying on a single supervised task with a large amount of manually labeled data may be insufficient to capture the foundational structures in point cloud videos. In this paper, we propose a pre-training framework Query-CP to learn the representations of point cloud videos through multiple self-supervised pretext tasks. First, tokenlevel contrast is developed to predict future features under the guidance of historical information. Using a position-guided autoregressor with learnable queries, the predictions are directly contrasted with corresponding targets in the high-level feature space to capture fine-grained semantics. Second, performing only contrastive learning fails to fully explore the complementary structures and dynamics information. To alleviate this, a decoupled spatio-temporal prediction task is designed, where we use a spatial branch to predict low-level features and a temporal branch to predict timestamps of the target sequence explicitly. By combining the above self-supervised tasks, multi-level information is captured during the pre-training stage. Finally, the encoder is fine-tuned and evaluated for action recognition and dynamic semantic segmentation on three datasets. The results demonstrate the effectiveness of our Query-CP. Especially, compared with the state-of-the-art methods, the fine-tuning accuracy on action recognition improves by 3.23% for 24-frame point cloud videos, and the mean accuracy increases by 4.21%.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 10","pages":"821-828"},"PeriodicalIF":1.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705970","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376682","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}

引用次数: 0

Comparative Study of Tire Models Applied to Electronic Stability Control in Automotive Simulator 汽车模拟器中电子稳定性控制应用的轮胎模型比较研究

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-10-04 DOI: 10.1109/TLA.2024.10706024

Walter Paschoal;Igor Souza;Lucas Torres;Andre Murilo Pinto;Renan Ozelo

引用次数: 0

Comparison of sequential test strategies based on Monte Carlo simulations in the detection of auditory steady-state responses 基于蒙特卡罗模拟的顺序测试策略在听觉稳态反应检测中的比较

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-09-10 DOI: 10.1109/TLA.2024.10669254

Victor Hugo de Souza Ragazzi;Alexandre Gomes Caldeira;Patrícia Nogueira Vaz;Felipe Antunes;Leonardo Bonato Felix

{"title":"Comparison of sequential test strategies based on Monte Carlo simulations in the detection of auditory steady-state responses","authors":"Victor Hugo de Souza Ragazzi;Alexandre Gomes Caldeira;Patrícia Nogueira Vaz;Felipe Antunes;Leonardo Bonato Felix","doi":"10.1109/TLA.2024.10669254","DOIUrl":"https://doi.org/10.1109/TLA.2024.10669254","url":null,"abstract":"It is common to use sequential testing strategies to help reduce the time of automated detection of an auditory steady-state response (ASSR). However, the application of repeated tests leads to an increase of false positive rate. Monte Carlo-based strategies are used to overcome this obstacle. Despite several paper could be found describing such strategies, no comprehensive comparison was found in the literature. The chosen strategies are based on Monte Carlo simulations to calculate critical values and were faithfully replicated for comparison purposes, and then the test application parameters were varied to suggest an optimization. The detection rate and/or the detection speed improved with each implemented strategy, except for the one related to the year 2013, which increased the false positive rate to 15.3%. The other strategies kept the false positive rate under control. The Pareto curves compared the optimizations of the strategies and revealed that the modified 2015 strategy had the performance achieving 5.6% higher than the original parameters. The automated detection of ASSR improved with each implemented strategy, but not all of them kept a controlled false positive rate (2013 and 2015). The 2015 modified strategy had the highest detection rate in the shortest time.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 9","pages":"733-738"},"PeriodicalIF":1.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165019","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}

引用次数: 0

A prediction model for heat exchanger fouling factor based on stacking model 基于堆叠模型的换热器污垢系数预测模型

IF 1.3 4区工程技术

IEEE Latin America Transactions Pub Date : 2024-09-10 DOI: 10.1109/TLA.2024.10670205

Zhiping Chen;Yongle Meng;Haoshan Yu;Ruiqi Wang;Wenwu Zhou

{"title":"A prediction model for heat exchanger fouling factor based on stacking model","authors":"Zhiping Chen;Yongle Meng;Haoshan Yu;Ruiqi Wang;Wenwu Zhou","doi":"10.1109/TLA.2024.10670205","DOIUrl":"https://doi.org/10.1109/TLA.2024.10670205","url":null,"abstract":"Given the pressing demand for energy conservation, the petrochemical sector faces increasingly stringent energy-saving mandates. Heat exchangers, essential to this sector, suffer efficiency losses and increased energy consumption due to fouling. To ensure optimal operation of heat exchange systems, regular assessment of solid deposits and the implementation of cleaning schedules are imperative. However, the multitude of influencing factors renders traditional estimation methods unreliable. Consequently, we developed a stacking model to predict the fouling factor of heat exchangers. Specifically, we first constructed fouling factor prediction models using various machine learning techniques, then selected the best-performing models random forest, extreme gradient boosting , and light gradient boosting machine for integration. Finally, the predictions from these three models were fed into a linear regression layer to form the final stacking model. The results indicate that the constructed stacking model significantly enhances the accuracy of fouling factor prediction. This model not only surpasses traditional multilayer perceptron neural network methods but also outperforms the well-performing gaussian process regression. This achievement not only validates the effectiveness of our model but also provides robust support for future research and applications in related fields.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 9","pages":"746-754"},"PeriodicalIF":1.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10670205","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165018","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}

引用次数: 0