2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)最新文献_第7页

A Review of Non Invasive Methods of Brain Activity Measurements via EEG Signals Analysis 基于脑电信号分析的无创脑活动测量方法综述

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10150607

Turkia Dabbabi, L. Bouafif, A. Cherif

{"title":"A Review of Non Invasive Methods of Brain Activity Measurements via EEG Signals Analysis","authors":"Turkia Dabbabi, L. Bouafif, A. Cherif","doi":"10.1109/IC_ASET58101.2023.10150607","DOIUrl":"https://doi.org/10.1109/IC_ASET58101.2023.10150607","url":null,"abstract":"In neuroscience, electroencephalography (EEG) is a non-invasive method of measuring and monitoring the brain electrical activity by recording the potentials of electrodes placed at standard positions on the scalp. The EEG has become an essential tool for diagnosing and monitoring neurological, cognitive, emotional and even psychological disorders (epilepsy, anesthesia, …). In this paper, we will present an overview of the several methods used for the analysis of EEG signals such as spectral analysis, techniques based on the response to electrical, acoustic or mechanical stimulation, such AEP (Acoustic Evoked Potential) and ERP (Event Related Potential) without forgetting the methods of separation based on independent components analysis (ICA) to identify the different cerebral sources and eliminate the artifacts. Finally, we give an overview on machine learning and artificial intelligence techniques applied to the analysis of EEG signals and Brain computer interface (BCI). To illustrate the results of the EEG analysis, we will present an example of simulation applied to real samples.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125697503","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

Humidity Control Inside Smart Greenhouse Using a Raspberry Pi Card by Applying FLC Technique 基于FLC技术的树莓派卡智能温室湿度控制

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10150959

A. Belkadi, Nizar Sghaier, Islem Ben Hassine, D. Mezghanni, A. Mami

引用次数: 0

Optimal Decision Making for Hybrid Power Systems Selection with Smart Grid and Local Generator Using Wireless Sensor Networks 基于无线传感器网络的智能电网和本地发电机混合动力系统选择优化决策

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10150557

Yousef E. M. Hamouda

{"title":"Optimal Decision Making for Hybrid Power Systems Selection with Smart Grid and Local Generator Using Wireless Sensor Networks","authors":"Yousef E. M. Hamouda","doi":"10.1109/IC_ASET58101.2023.10150557","DOIUrl":"https://doi.org/10.1109/IC_ASET58101.2023.10150557","url":null,"abstract":"Home Energy Management System (HEMS) at smart homes focuses on smart management and switching among different sources of energy supply and generations. Wireless Sensor Networks (WSNs) are employed in HEMS to sense, process, and communicate the different electrical parameters, such as electrical voltage, current, and frequency. The sources of electrical energy considered in this paper are the utility smart grid and the local power generator. In this paper, Hybrid Power Systems Selection (HPSS) is developed to ubiquitously distribute the demands of the electrical power between the utility smart grid and the local generator using WSNs, so that the energy cost and pollutant emission are reduced. Therefore, the main goal of HPSS is to get the optimal percentage of electrical power drifted from the smart grid utility, compared with the electrical power drifted from the local generator (UGR). At each time step, HPSS firstly measures the electrical parameters, such as the load power, and the grid frequency. After that, the cost function that combines the energy cost and emission pollution is solved to get the optimal solution. Simulated annealing optimization method is used to get the optimal/near-optimal solution of power distribution. Simulation results show that the proposed HPSS can optimally distribute the load power between the local generator and the utility smart grid with minimum energy cost and pollutant emission. In addition, the energy cost and emission pollution are controlled according to tuning of predefined weighting parameter.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127242556","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

Fuzzy T-S Model Based Fault Tolerant Control Using Immeasurable Decision Variables 基于模糊T-S模型的不可测决策变量容错控制

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10151245

Hassen Hichri, M. Ayadi

引用次数: 0

TeraHertz Path-Loss Prediction Indoor using Machine Learning 使用机器学习的室内太赫兹路径损耗预测

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10151166

Nagma Elburki, Affes Sofiene

引用次数: 0

A Comparative Study for the Detection of Stator Inter-Turn Faults in Induction Motors Using Shallow Neural Networks and Non-Neural Based Techniques 浅层神经网络与非神经网络检测异步电动机定子匝间故障的比较研究

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10150774

Priynka Sharma, G. Cirrincione, Rahul Kumar, Alireza Mohammadi, Maurizio Cirrincione

{"title":"A Comparative Study for the Detection of Stator Inter-Turn Faults in Induction Motors Using Shallow Neural Networks and Non-Neural Based Techniques","authors":"Priynka Sharma, G. Cirrincione, Rahul Kumar, Alireza Mohammadi, Maurizio Cirrincione","doi":"10.1109/IC_ASET58101.2023.10150774","DOIUrl":"https://doi.org/10.1109/IC_ASET58101.2023.10150774","url":null,"abstract":"Traditional Induction Motor (IM) Fault Diagnosis (FD) relies on extracting features from original signals, which directly impacts FD performance. However, high-quality features require expert knowledge and human interaction. Therefore, this paper presents a comparative analysis of the detection of stator inter-turn faults in IMs using state-of-art classifiers. Experimental data was acquired and the class was divided, into up to three levels of severity for the stator fault. Thereafter, using a non-parametric approach, features from the three-phase currents were engineered relative to the characteristic fault frequencies for stator faults. Various families of classifiers were trained on the developed feature-set, and for each family of classifiers, Bayesian Optimization was applied to train its own variants and derive the best hyperparameters. The best results were obtained for Tree, Ensembled and Shallow Neural-based techniques using a separate test set.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134038693","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

LMI-Based Design of an Affine PD Controller for the Robust Stabilization of the Knee Joint of a Lower-Limb Rehabilitation Exoskeleton 基于lmi的下肢康复外骨骼膝关节鲁棒稳定仿射PD控制器设计

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10151346

Sahar Jenhani, H. Gritli

引用次数: 1

Design and Implementation of Real-Time Monitoring System for Building-integrated Photovoltaic System 建筑一体化光伏系统实时监控系统的设计与实现

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10151167

Atef Ftirich, B. Bouaziz, F. Bacha

{"title":"Design and Implementation of Real-Time Monitoring System for Building-integrated Photovoltaic System","authors":"Atef Ftirich, B. Bouaziz, F. Bacha","doi":"10.1109/IC_ASET58101.2023.10151167","DOIUrl":"https://doi.org/10.1109/IC_ASET58101.2023.10151167","url":null,"abstract":"Photovoltaic systems are used to provide electricity to people who are difficult to reach by the grid due to their location in inaccessible places or who consume very little energy. The need to provide all of the users' energy demands characterizes an independent installation. Photovoltaic modules, a charge controller, a storage system (rechargeable batteries), and a voltage inverter are among its components. In recent years, the Building integrated photovoltaic (BIPV) systems have the most used in home electrification. To make a easy BIPV system, there is a need to adopt digital technologies such as the internet of things (IoT), artificial intelligence (AI) and edge computing. In this study, we present the design and implementation of a real-time monitoring solution applicable to photovoltaic self-consumption or the BIPV system using the IoT technology. A detailed description of the proposed system at the hardware level is provided, and extended information on the communication characteristics and sensors data is also included. We will present a low-cost system to monitor solar energy production and the battery energy. This method based on open source internet of things solution that could collect in intelligent manner and monitor in real-time the produced power and environmental conditions via a mobile application and local web server for remote user. The solution is designed as a prototype test bench that could be extended to monitor large scale photovoltaic stations.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"84 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127982247","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

Early Detection of Alzheimer's Disease Using VOT Mean Measure in New Tunisian Arabic Database 新突尼斯阿拉伯语数据库VOT均值法早期检测阿尔茨海默病

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10150580

Karim Dabbabi, A. Kehili, A. Cherif

{"title":"Early Detection of Alzheimer's Disease Using VOT Mean Measure in New Tunisian Arabic Database","authors":"Karim Dabbabi, A. Kehili, A. Cherif","doi":"10.1109/IC_ASET58101.2023.10150580","DOIUrl":"https://doi.org/10.1109/IC_ASET58101.2023.10150580","url":null,"abstract":"Alzheimer”s disease (AD) is one of the neurodegenerative diseases, which first affects the function of speech in addition to a few other functions. This brings speech back to the top of promising biomarkers for the early detection of this disease before the appearance of the first preclinical symptoms. Despite the fact that there are many methods explored for early detection of Alzheimer's disease (AD), however the Voice Onset Time (VOT) values of stop consonants can be a good indicator of this disease by containing clues about the speaker's voice disorder in a language. In this study, we have proposed VOT_Mean measures to detect these deficiencies for the task of early detection of Alzheimer's disease (AD) in Arabic language using /pa/., /ta/., /ka/, and /pata/ syllables. An Arabic speech database of healthy control individuals (HC) and other with AD has been developed in association with the Alzheimer Family Assistance (AFA) center. Experimental tests were performed on this database for the didochakokinetik (DDK) task and showed that there is high significance for VOT_Mean with repect to syllables, while no significance with respect to gender. Additionnally, there is no statistical significance for the duration of words or for the duration of words in relation to sex. For the best results of the performances assessed using the VOT_Mean measurement, they were achieved with the XGBoost algorithm compared to those obtained by other machine learning algorithms for the AD and HC groups.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"4 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114026853","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

Predictive Direct Power Control Strategy for Grid-Connected VSI 并网VSI预测直接功率控制策略

2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2023-04-29 DOI: 10.1109/IC_ASET58101.2023.10151024

Zouhaira Ben Mahmoud, A. Khedher

{"title":"Predictive Direct Power Control Strategy for Grid-Connected VSI","authors":"Zouhaira Ben Mahmoud, A. Khedher","doi":"10.1109/IC_ASET58101.2023.10151024","DOIUrl":"https://doi.org/10.1109/IC_ASET58101.2023.10151024","url":null,"abstract":"A key limitation of the lookup table-based direct power control strategy is that the switching frequency varies with the distinct active and reactive powers combinations, resulting in an undesirable broadband harmonic spectrum range. The current study introduces a direct power control that is based on predictive approach (P-DPC) for grid-tied VSI. This approach is established through the fusion of the DPC technique and the predictive one, providing high dynamic performance and constant switching frequency. Rather than applying one voltage vector in the DPC scheme, the recommended P-DPC makes use the sequence of voltage vectors throughout a switching period. The strategy's principle involves two essential steps. The first one consists to determine the adequate sequence of vectors which contains zero and non-zero vectors and then to arrange them so that switching losses are kept to a minimal while still supervising the exchanged powers with the grid. Secondly, the power errors are eliminated by the prediction of the duration times. A grid-connected inverter model is used for numerical testing to validate the feasibility of the suggested P-DPC algorithm. The obtained results show high steady state and dynamic performances.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114711931","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