2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)最新文献_第10页

Improving the classification of propeller ships using LOFAR and triple loss variational auto encoder 利用LOFAR和三损耗变分自编码器改进螺旋桨船舶入级

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9873436

Nhat Hoang Bach, V. Nguyen, Le Ha Vu

引用次数: 2

Recognition of Butterfly strokes using different Machine Learning Models 使用不同的机器学习模型识别蝶泳动作

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9872896

Salma Tamer, Ayman Atia

{"title":"Recognition of Butterfly strokes using different Machine Learning Models","authors":"Salma Tamer, Ayman Atia","doi":"10.1109/ICECET55527.2022.9872896","DOIUrl":"https://doi.org/10.1109/ICECET55527.2022.9872896","url":null,"abstract":"Swimming is a lifelong beneficial activity. It is an excellent training since it requires you to move your entire body against the water’s resistance; however, by the time, these movements may not be in a right way. In addition, the wrong movements may lead to many pains such as shoulder pain, elbow pain and lower back pain especially in difficult strokes. The coach is the one who instructs the swimmers and tell them which is incorrect, and which is correct. However, he can’t recognize all the incorrect movements, so this needs an instructor who can see all the stroke’s mistakes. Hence our proposed system, which uses machine learning techniques, utilizes four different models which are Long short-term memory (LSTM), k-nearest neighbor (Knn), for time series 1-${$}$ recognizer and Dynamic time wrapping (DTW) to detect the incorrect butterfly stroke. The system uses an accelerometer and gyroscope sensors to detect and evaluate correct and Incorrect swimming patterns in butterfly stoke. In addition to attaching a mobile application to the swimmer’s wrist which gathers all data which allows the coach and the swimmer to know the incorrect strokes such as lifting the head too high, sweeping out after hand entry, and bending the arm. When an incorrect movement is recognized. DTW achieved the best accuracy among all classifiers which are 80.5%. The system helps in aiding the coaches to know all the swimmer’s performance and all his performance, and also aid the intermediate swimmers to know more about his performance to enhance it.","PeriodicalId":249012,"journal":{"name":"2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115725458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A self-healing cybersecurity mechanism for cyberattacks targeting artificial neural network-based human brain implants controlling smart homes 针对控制智能家居的基于人工神经网络的人脑植入物的网络攻击的自我修复网络安全机制

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9872885

S. Pazouki, Noorbakhsh Amiri Golilarz, S. M. Kazemi-Razi, Abdullah Aydeger

{"title":"A self-healing cybersecurity mechanism for cyberattacks targeting artificial neural network-based human brain implants controlling smart homes","authors":"S. Pazouki, Noorbakhsh Amiri Golilarz, S. M. Kazemi-Razi, Abdullah Aydeger","doi":"10.1109/ICECET55527.2022.9872885","DOIUrl":"https://doi.org/10.1109/ICECET55527.2022.9872885","url":null,"abstract":"Brain computer interfaces (BCIs) are considered cyber-physical systems (CPSs) capable of computation, communication, and decision-making progress. The cybernetic capabilities are implanted in the brain for the purpose of reading and writing on neurons of the brain. While current applications of the human brain implant are for neurogenetics disorders such as Alzheimer's, there are futuristic applications of the human brain implant for communication between the brains of humans and computer-based devices. Despite the outstanding advantages of cyber-physical technology, new techniques are required to control in/external devices, and the system is vulnerable to cyber threats. This paper presents 1) an artificial neural network (ANN) technique to control the smart home devices via the brain implants, 2) different cyberattacks (i.e., Flooding, Scanning, False Data Injection, and Jamming) on the human brain implant, 3) a recovery technique to mitigate the impact of the proposed cyberattacks on the human brain implant. The results demonstrate the effectiveness of the proposed cybersecurity/self-healing technique to mitigate the well-known cyberattacks imposing the brain implant.","PeriodicalId":249012,"journal":{"name":"2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115802172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Hybrid Linguistic Time Series Forecasting Model combined with Particle Swarm Optimization 结合粒子群优化的混合语言时间序列预测模型

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9873100

Phạm Đình Phong, N. D. Hieu, Mai Văn Linh

{"title":"A Hybrid Linguistic Time Series Forecasting Model combined with Particle Swarm Optimization","authors":"Phạm Đình Phong, N. D. Hieu, Mai Văn Linh","doi":"10.1109/ICECET55527.2022.9873100","DOIUrl":"https://doi.org/10.1109/ICECET55527.2022.9873100","url":null,"abstract":"Linguistic time series forecasting model (LTS-FM) which is proposed by Hieu et al. by utilizing hedge algebras theory is an efficient forecasting model. Instead of partitioning the universe of discourse (UD) of the linguistic variable into subintervals and assigning fuzzy sets to them, it establishes a formalism to convert historical numeric time series data into linguistic one based on numerical semantics of words which are transformed from the semantically quantifying mapping (SQM) values of the corresponding words. Therefore, a LTS-FM is established in such a way that it handles directly words of linguistic variable and their qualitative semantics. However, the fuzziness parameter values of the LTS-FM which determine the SQM values of words are currently specified by human experts, so the forecasted results may not be optimal. This paper proposes a hybrid LTS-FM in which particle swarm optimization is utilized to optimize the fuzziness parameter values. A new formula of computing crisp forecasted values is also proposed. The experimental studies carried out over two practical forecasting problems of the enrollments of University of Alabama and killed in car road accident in Belgium show that the proposed forecasting model obtains better forecasted results.","PeriodicalId":249012,"journal":{"name":"2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123134259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Two-Phase IPOS DC-DC Step-up Converter for PV Interface PV接口的两相IPOS DC-DC升压变换器

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9872986

Ahmad Alzahrani

引用次数: 0

A Secured Scheme for Optimal Navigation of a Berthing Ship 一种靠泊船舶最优航行安全方案

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9872741

Kailash Jamuda, Radhika Lama, Sandip Karmakar

{"title":"A Secured Scheme for Optimal Navigation of a Berthing Ship","authors":"Kailash Jamuda, Radhika Lama, Sandip Karmakar","doi":"10.1109/ICECET55527.2022.9872741","DOIUrl":"https://doi.org/10.1109/ICECET55527.2022.9872741","url":null,"abstract":"The immense growth of the marine industry has led to increased maritime commerce in recent years. This has resulted in a rise in maritime activities and challenges in the security of communication between entities involved in a ship’s port navigation. In response to the challenges, the suggested security strategy in this work can provide vital security features such as authentication between communicating entities and important security services while consuming fewer resources. This technique also calculates the ideal distance between the berthing ship and the available parking site using their geographic coordinates to provide optimal navigation for a berthing ship. An external entity known as the trusted third party is in charge of calculating the optimum path, which works as a middleman in the communication process. The suggested technique is resistant to a variety of security attacks, these are Man-in-the-Middle attack, Replay attack, information leakage, and impersonation attack. This scheme also assures unlinkability and anonymity. The Automated Validation of Internet Security Protocols and Applications (AVISPA) software is utilized to formally verify the proposed scheme’s safety.","PeriodicalId":249012,"journal":{"name":"2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124712922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Survival analysis for the identified cancer gene subtype from the co-clustering algorithm 通过共聚类算法对鉴定出的癌症基因亚型进行生存分析

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9872811

Logenthiran Machap, Kohbalan Moorthy

引用次数: 0

Blind Digital Watermarking Method Based on Quadtree Decomposition and Complex Wavelet Transform for Medical Application 基于四叉树分解和复小波变换的医学盲数字水印方法

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9873503

Nadhir Nouioua, A. Seddiki, Abdelkrim Ghaz

引用次数: 0

A Performance Analysis of Deep Neural Network Models on an Edge Tensor Processing Unit 边缘张量处理单元上深度神经网络模型的性能分析

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9873024

Christian DeLozier, Forte Rooney, Jennifer Jung, Justin A. Blanco, R. Rakvic, James Shey

引用次数: 0

Co-simulation framework for estimating the rotor bar currents of a cage induction motor using FEA and ANN 基于有限元分析和神经网络的笼型异步电动机转子棒电流联合仿真框架

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Pub Date : 2022-07-20 DOI: 10.1109/ICECET55527.2022.9872604

M. Barukčić, T. Varga, V. J. Štil, T. Benšić

{"title":"Co-simulation framework for estimating the rotor bar currents of a cage induction motor using FEA and ANN","authors":"M. Barukčić, T. Varga, V. J. Štil, T. Benšić","doi":"10.1109/ICECET55527.2022.9872604","DOIUrl":"https://doi.org/10.1109/ICECET55527.2022.9872604","url":null,"abstract":"The paper presents a research work on the estimation of rotor bar currents of a squirrel-cage induction motor (IM). The main objective of the research conducted is to investigate whether it is possible to estimate the values of IM rotor bar current with artificial neural network (ANN) with satisfactory accuracy. Another objective of the study is to investigate the generality of such bar current estimation for different operating conditions of the motor. For this purpose, different designs of ANN are also investigated. The method is based on the application of a finite element analysis simulation tool to determine rotor current values under transient and steady state conditions. The ANN based estimation method uses the standard measurable data of stator current and rotor speed. In the next step of the proposed method, the calculated rotor current values are used to train an artificial neural network. Based on this approach, the presented method represents a data-based estimation model. After the ANN is trained, ANN is tested on motor transients that are different from those used in learning the artificial neural network. Data from a real motor is used for the study. The three different ANN designs are examined in the study. The values of the loss function (mean square error, used in the ANN training process) are (for normalized data) 0.0013, 0.0013, and 0.0014 (during ANN training) and 0.0038, 0.0035 (ANN prediction for new input data) for the proposed designs ANN 1, ANN 2, and ANN 3.","PeriodicalId":249012,"journal":{"name":"2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122676533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1