Electronics最新文献_第9页

Efficient Human Activity Recognition on Wearable Devices Using Knowledge Distillation Techniques 利用知识提炼技术在可穿戴设备上高效识别人类活动

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-11 DOI: 10.3390/electronics13183612

Paulo H. N. Gonçalves, Hendrio Bragança, Eduardo Souto

{"title":"Efficient Human Activity Recognition on Wearable Devices Using Knowledge Distillation Techniques","authors":"Paulo H. N. Gonçalves, Hendrio Bragança, Eduardo Souto","doi":"10.3390/electronics13183612","DOIUrl":"https://doi.org/10.3390/electronics13183612","url":null,"abstract":"Mobile and wearable devices have revolutionized the field of continuous user activity monitoring. However, analyzing the vast and intricate data captured by the sensors of these devices poses significant challenges. Deep neural networks have shown remarkable accuracy in Human Activity Recognition (HAR), but their application on mobile and wearable devices is constrained by limited computational resources. To address this limitation, we propose a novel method called Knowledge Distillation for Human Activity Recognition (KD-HAR) that leverages the knowledge distillation technique to compress deep neural network models for HAR using inertial sensor data. Our approach transfers the acquired knowledge from high-complexity teacher models (state-of-the-art models) to student models with reduced complexity. This compression strategy allows us to maintain performance while keeping computational costs low. To assess the compression capabilities of our approach, we evaluate it using two popular databases (UCI-HAR and WISDM) comprising inertial sensor data from smartphones. Our results demonstrate that our method achieves competitive accuracy, even at compression rates ranging from 18 to 42 times the number of parameters compared to the original teacher model.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Twin for Modern Distribution Networks by Improved State Estimation with Consideration of Bad Date Identification 通过考虑坏日期识别的改进状态估计实现现代配电网络的数字孪生

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-11 DOI: 10.3390/electronics13183613

Huiqiang Zhi, Rui Mao, Longfei Hao, Xiao Chang, Xiangyu Guo, Liang Ji

{"title":"Digital Twin for Modern Distribution Networks by Improved State Estimation with Consideration of Bad Date Identification","authors":"Huiqiang Zhi, Rui Mao, Longfei Hao, Xiao Chang, Xiangyu Guo, Liang Ji","doi":"10.3390/electronics13183613","DOIUrl":"https://doi.org/10.3390/electronics13183613","url":null,"abstract":"With the rapid development of modern power systems, the structure and operation of distribution networks are becoming increasingly complex, demanding higher levels of intelligence and digitization. Digital twin, as a virtual cutting-edge technique, can effectively reflect the operational status of distribution networks, offering new possibilities for real-time monitoring, optimization and other functions for distribution networks. Building efficient and accurate models is the foundation of enabling a digital twin of distribution networks. This paper proposes a digital twin operating system for distribution networks with renewable energy based on robust state estimation and deep learning-based renewable energy prediction. Furthermore, the identification and correction of possible bad or missing data based on deep learning are also included to purify the input data for the digital twin system. A digital twin test platform is also proposed in the paper. A case study and evaluations based on a real-time digital simulator are carried out to verify the accuracy and real-time performance of the established digital twin system. In general, the proposed method can provide the basis and foundation for distribution network management and operation, as well as intelligent power system operation.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced Transformer for Remote-Sensing Image Captioning with Positional-Channel Semantic Fusion 利用位置-信道语义融合为遥感图像添加字幕的增强变换器

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-11 DOI: 10.3390/electronics13183605

An Zhao, Wenzhong Yang, Danny Chen, Fuyuan Wei

引用次数: 0

Challenges in Information Systems Curricula: Effectiveness of Systems Application Products in Data Processing Learning in Higher Education through a Technological, Organizational and Environmental Framework 信息系统课程的挑战：从技术、组织和环境框架看高等教育数据处理学习中系统应用产品的有效性

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-11 DOI: 10.3390/electronics13183616

Viorel-Costin Banța, Ștefan Bunea, Daniela Țuțui, Raluca Florentina Crețu

{"title":"Challenges in Information Systems Curricula: Effectiveness of Systems Application Products in Data Processing Learning in Higher Education through a Technological, Organizational and Environmental Framework","authors":"Viorel-Costin Banța, Ștefan Bunea, Daniela Țuțui, Raluca Florentina Crețu","doi":"10.3390/electronics13183616","DOIUrl":"https://doi.org/10.3390/electronics13183616","url":null,"abstract":"Higher education institutions are increasingly concerned with providing students with sustainable education by developing the necessary competencies for various roles in the business environment. To be more effective, courses must develop technological, organizational and environmental (TOE) competencies in an integrated manner. SAP is a tool that yields this possibility through the diversity of IT solutions by ensuring a significant increase in employability rates. Learning SAP is a competitive advantage because it helps with all aspects of digital transformation within the concept of Industry 4.0. Our research aims to investigate to what extent students perceive that they have acquired the knowledge and competencies specific to the three dimensions of the TOE framework within the SAP course. We have added a fourth dimension to the TOE framework: the learning context (L) considering the impact of the educational environment on perceived learning outcomes. Data collection was based on a questionnaire distributed to students enrolled in the SAP course in the academic year 2023–2024 at Bucharest University of Economic Studies (BUES). The data were processed using correlation and regression analysis. Reconfiguring the content elements of SAP courses based on the TOE framework would ensure greater effectiveness in the learning process.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning-Based Intrusion Detection Methods in IoT Systems: A Comprehensive Review 物联网系统中基于机器学习的入侵检测方法：全面回顾

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-11 DOI: 10.3390/electronics13183601

Brunel Rolack Kikissagbe, Meddi Adda

引用次数: 0

Multi-UAV Reconnaissance Task Assignment for Heterogeneous Targets with ACD-NSGA-II Algorithm 利用 ACD-NSGA-II 算法为异构目标分配多无人机侦察任务

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-11 DOI: 10.3390/electronics13183609

Hong Zhang, Kunzhong Miao, Huangzhi Yu, Yifeng Niu

引用次数: 0

Adaptive Knowledge Contrastive Learning with Dynamic Attention for Recommender Systems 针对推荐系统的动态关注自适应知识对比学习

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-10 DOI: 10.3390/electronics13183594

Hongchan Li, Jinming Zheng, Baohua Jin, Haodong Zhu

{"title":"Adaptive Knowledge Contrastive Learning with Dynamic Attention for Recommender Systems","authors":"Hongchan Li, Jinming Zheng, Baohua Jin, Haodong Zhu","doi":"10.3390/electronics13183594","DOIUrl":"https://doi.org/10.3390/electronics13183594","url":null,"abstract":"Knowledge graphs equipped with graph network networks (GNNs) have led to a successful step forward in alleviating cold start problems in recommender systems. However, the performance highly depends on precious high-quality knowledge graphs and supervised labels. This paper argues that existing knowledge-graph-based recommendation methods still suffer from insufficiently exploiting sparse information and the mismatch between personalized interests and general knowledge. This paper proposes a model named Adaptive Knowledge Contrastive Learning with Dynamic Attention (AKCL-DA) to address the above challenges. Specifically, instead of building contrastive views by randomly discarding information, in this study, an adaptive data augmentation method was designed to leverage sparse information effectively. Furthermore, a personalized dynamic attention network was proposed to capture knowledge-aware personalized behaviors by dynamically adjusting user attention, therefore alleviating the mismatch between personalized behavior and general knowledge. Extensive experiments on Yelp2018, LastFM, and MovieLens datasets show that AKCL-DA achieves a strong performance, improving the NDCG by 4.82%, 13.66%, and 4.41% compared to state-of-the-art models, respectively.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Objective Parameter Configuration Optimization of Hydrogen Fuel Cell Hybrid Power System for Locomotives 机车氢燃料电池混合动力系统的多目标参数配置优化

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-10 DOI: 10.3390/electronics13183599

Suyao Liu, Chunmei Xu, Yifei Zhang, Haoying Pei, Kan Dong, Ning Yang, Yingtao Ma

{"title":"Multi-Objective Parameter Configuration Optimization of Hydrogen Fuel Cell Hybrid Power System for Locomotives","authors":"Suyao Liu, Chunmei Xu, Yifei Zhang, Haoying Pei, Kan Dong, Ning Yang, Yingtao Ma","doi":"10.3390/electronics13183599","DOIUrl":"https://doi.org/10.3390/electronics13183599","url":null,"abstract":"Conventional methods of parameterizing fuel cell hybrid power systems (FCHPS) often rely on engineering experience, which leads to problems such as increased economic costs and excessive weight of the system. These shortcomings limit the performance of FCHPS in real-world applications. To address these issues, this paper proposes a novel method for optimizing the parameter configuration of FCHPS. First, the power and energy requirements of the vehicle are determined through traction calculations, and a real-time energy management strategy is used to ensure efficient power distribution. On this basis, a multi-objective parameter configuration optimization model is developed, which comprehensively considers economic cost and system weight, and uses a particle swarm optimization (PSO) algorithm to determine the optimal configuration of each power source. The optimization results show that the system economic cost is reduced by 8.76% and 18.05% and the weight is reduced by 11.47% and 9.13%, respectively, compared with the initial configuration. These results verify the effectiveness of the proposed optimization strategy and demonstrate its potential to improve the overall performance of the FCHPS.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Rail Surface Defect Detection Based on Improved CenterNet 基于改进型中心网的轨道表面缺陷检测研究

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-09 DOI: 10.3390/electronics13173580

Yizhou Mao, Shubin Zheng, Liming Li, Renjie Shi, Xiaoxue An

引用次数: 0

Improved Plasma Etch Endpoint Detection Using Attention-Based Long Short-Term Memory Machine Learning 利用基于注意力的长短期记忆机器学习改进等离子体蚀刻终点检测

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-09 DOI: 10.3390/electronics13173577

Ye Jin Kim, Jung Ho Song, Ki Hwan Cho, Jong Hyeon Shin, Jong Sik Kim, Jung Sik Yoon, Sang Jeen Hong

{"title":"Improved Plasma Etch Endpoint Detection Using Attention-Based Long Short-Term Memory Machine Learning","authors":"Ye Jin Kim, Jung Ho Song, Ki Hwan Cho, Jong Hyeon Shin, Jong Sik Kim, Jung Sik Yoon, Sang Jeen Hong","doi":"10.3390/electronics13173577","DOIUrl":"https://doi.org/10.3390/electronics13173577","url":null,"abstract":"Existing etch endpoint detection (EPD) methods, primarily based on single wavelengths, have limitations, such as low signal-to-noise ratios and the inability to consider the long-term dependencies of time series data. To address these issues, this study proposes a context of time series data using long short-term memory (LSTM), a kind of recurrent neural network (RNN). The proposed method is based on the time series data collected through optical emission spectroscopy (OES) data during the SiO2 etching process. After training the LSTM model, the proposed method demonstrated the ability to detect the etch endpoint more accurately than existing methods by considering the entire time series. The LSTM model achieved an accuracy of 97.1% in a given condition, which shows that considering the flow and context of time series data can significantly reduce the false detection rate. To improve the performance of the proposed LSTM model, we created an attention-based LSTM model and confirmed that the model accuracy is 98.2%, and the performance is improved compared to that of the existing LSTM model.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0