2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)最新文献_第2页

Arduino Based PI Control for a Nonlinear TITO System Using LabVIEW 基于Arduino的非线性TITO系统的PI控制

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668366

M. Chakravarthi, Y. V. Pavan Kumar, D. J. Pradeep, C. P. Reddy, Anumola Vaishnavi, N. S. Greeshma Reddy

引用次数: 0

Fall Detection System Using Novel Median Deviated Ternary Patterns and SVM 基于新颖中值偏差三元模式和支持向量机的跌倒检测系统

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668520

Babar Younis, A. Javed, Farman Hassan

{"title":"Fall Detection System Using Novel Median Deviated Ternary Patterns and SVM","authors":"Babar Younis, A. Javed, Farman Hassan","doi":"10.1109/ISAECT53699.2021.9668520","DOIUrl":"https://doi.org/10.1109/ISAECT53699.2021.9668520","url":null,"abstract":"In recent years, we have noticed exponential growth in the elderly population of the world due to the advancement in the medical field that necessitates proper care and more attention of elderly people. Accidental falls can be life threatening and can cause severe head trauma, bone fractures, and internal bleedings. Moreover, the most devasting problem of accidental fall incident is that the person remains on the floor for a long time without getting any immediate assistance and response. Research community proposed various fall detection systems but still there exist certain limitations of the existing methods i.e., computational complexity, expensive sensors, unable to wear wearable sensors, and associated privacy issues. To address these issues, we proposed a novel feature descriptor median deviated ternary patterns (MDTP) for audio representation to effectively capture the discriminatory traits of fall and non-fall events. We used the proposed MDTP features to train the support vector machine (SVM) to classify the fall and non-fall incidents. Our proposed method is evaluated against two datasets i.e. A3 fall 2.0 dataset and the MSP-UET fall detection dataset. Our proposed method achieved remarkable accuracy of 98% and 97%, precision of 100% and 96%, recall of 97% and 96%, and F1-score of 98% and 96% on the A3 fall 2.0 and MSP-UET fall detection datasets respectively. Experimental results signify the effectiveness of the proposed system for reliable monitoring of elderly people for fall detection.","PeriodicalId":137636,"journal":{"name":"2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)","volume":"25 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134036804","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 Fuzzy-Based Multisource Power Management control of Isolated Mini-Grid 基于模糊的隔离型微电网多源电源管理控制

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668497

M. B. Messaoud, Naoui Mohamed, F. Aymen

引用次数: 1

Evaluation of Transfer Learning based Deep Learning architectures for Waste Classification 基于迁移学习的垃圾分类深度学习体系结构评价

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668454

S. Singh, J. Gautam, SurSingh Rawat, Vimal Gupta, Gynendra Kumar, Lal Pratap Verma

{"title":"Evaluation of Transfer Learning based Deep Learning architectures for Waste Classification","authors":"S. Singh, J. Gautam, SurSingh Rawat, Vimal Gupta, Gynendra Kumar, Lal Pratap Verma","doi":"10.1109/ISAECT53699.2021.9668454","DOIUrl":"https://doi.org/10.1109/ISAECT53699.2021.9668454","url":null,"abstract":"Today, the development and modernization have led to the generation of waste, which has become a problem for all the living beings and the environment, whether it is medical waste, of which 25% is hazardous, or household waste, which contains harmful plastic. In this work, a deep learning solution has been provided towards the classification of a few classes of wastes such as plastic, paper, metal, glass, cardboard, etc. In this work, transfer learning has been used and applied. This helps deep learning models to accomplish the classification task in the most accurate way. The models such as EfficientNet, ResNet34, Densenet121, ResNeXt-50 32x4d, Wide ResNet50_2, Densenet169 are used here in this work. Extensive experimentation was done with the different optimizers. The training such as Adam optimizer, RMSprop optimizer, and Adadelta was performed and the experimental results demonstrate that the Adam optimizer produced the best results over the other competing methods. The proposed work has achieved a test accuracy of 98.02% using ResNeXt-50 32x4d and 95.8% using Wide ResNet50_2 architecture.","PeriodicalId":137636,"journal":{"name":"2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124746317","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: 2

Hybrid Storage System for Controlling Wind Uncertainty 控制风力不确定性的混合储能系统

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668334

Ibrahim M. Alotaibi, I. Elamin, M. A. Abido, M. Khalid

{"title":"Hybrid Storage System for Controlling Wind Uncertainty","authors":"Ibrahim M. Alotaibi, I. Elamin, M. A. Abido, M. Khalid","doi":"10.1109/ISAECT53699.2021.9668334","DOIUrl":"https://doi.org/10.1109/ISAECT53699.2021.9668334","url":null,"abstract":"The uncertainty and ramping behavior of Renewable Energy Resources (RESs) are the main barriers when it comes to the deployment of such resources. The Battery Energy Storage System (BESS) has been widely deployed to sustain the above shortcomings. However, excessive utilization of BESS is not advisable since it leads to bank deterioration and replacement. This paper shows that the hybridization of a high-energy-density storage device represented by BESS and a high-power density storage device represented by Superconducting Magnetic Energy Storage (SMES) would fulfill the exact requirements at a much lesser cost and better performance. A multi-stage optimization model is developed and solved using Particle Swarm Optimization (PSO) to allocate the optimal storage capacity and to operate the hybrid system considering load demand and ramp rates. Battery Health Index (BHI) and Rainflow counting algorithms are used to assess the impact of the hybridization. The study shows that the hybrid storage system remains preferable over the Stand-alone storage system in terms of cost and operation.","PeriodicalId":137636,"journal":{"name":"2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129754947","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

Application of 5G Technology in Orchestration of Virtual Power Plants and Demand Response 5G技术在虚拟电厂编排和需求响应中的应用

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668601

Javad Jazaeri

引用次数: 2

Techno-Economic Assessment of Different Solar PV Configurations for a Typical House in Dhahran 达兰典型住宅不同太阳能光伏配置的技术经济评估

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668595

Jaafar Alboali, Abdullah Alsuwaid, Mustafa Aljafar, M. Khalid

{"title":"Techno-Economic Assessment of Different Solar PV Configurations for a Typical House in Dhahran","authors":"Jaafar Alboali, Abdullah Alsuwaid, Mustafa Aljafar, M. Khalid","doi":"10.1109/ISAECT53699.2021.9668595","DOIUrl":"https://doi.org/10.1109/ISAECT53699.2021.9668595","url":null,"abstract":"Solar PV market is expected to expand significantly as the residential sector investments in this market have started increasing recently. This creates a golden opportunity for Saudi Arabia which aims to achieve 50% renewable penetration by 2030. However, the public is not yet confident of the financial gains of rooftop solar PV, so this rises the need for detailed feasibility study that considers local metrological data, prices, and regulations. In this paper, two different designs of grid-connected and standalone PV are studied, starting by evaluating the average electricity consumption of 3 houses and the utilization of standard load profile (SLP) concept to achieve reasonable hourly data. Then, local metrological data and system components pricings are collected. After that, HOMER is used to simulate and analyze system performance, and determining the feasibility of the system using two variables as references, which are levelized cost of electricity (LCOE) and payback period. The study showed that grid-connected PV system could provide 28% reduction in LCOE compared to grid-only case with a payback period of 14 years, while for the standalone case the LCOE is still relatively high. Eventually, the study successfully proved the feasibility of grid-connected rooftop PV system, but with long payback period.","PeriodicalId":137636,"journal":{"name":"2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)","volume":"327 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116644481","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: 3

Adaptive Fine-tuning for Deep Transfer Learning Based Traffic Signs Classification 基于深度迁移学习的交通标志分类自适应微调

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668592

Ismail Nasri, A. Messaoudi, K. Kassmi, Mohammed Karrouchi, Hajar Snoussi

{"title":"Adaptive Fine-tuning for Deep Transfer Learning Based Traffic Signs Classification","authors":"Ismail Nasri, A. Messaoudi, K. Kassmi, Mohammed Karrouchi, Hajar Snoussi","doi":"10.1109/ISAECT53699.2021.9668592","DOIUrl":"https://doi.org/10.1109/ISAECT53699.2021.9668592","url":null,"abstract":"In recent years, traffic signs recognition represents an important issue in intelligent transportation systems. Several systems use traffic signs recognition including, driving assistance systems, road safety, autonomous driving. The traffic signs recognition aims to read and interpret road signs to inform the driver if he could not see them or when the vehicle is in self-driving mode. Each category of traffic sign has a special shape and color. This includes regulatory, warning, and guide signs. This paper proposes a practical solution for traffic signs classification based on convolutional neural networks technique to classify input images into 43 classes. Also, this paper provides a comparison between the Support Vector Machine (SVM) and the Softmax classifier. We have analyzed the impact of fine-tuning the pre-trained CNN model in the transfer learning algorithm. As a result, the SVM classifier in CNN achieves an accuracy of 96.60%, whereas the Softmax classifier accuracy is 97.84%. Experimental results demonstrate that fine-tuning in transfer learning can lead to significant performances in terms of accuracy of classification.","PeriodicalId":137636,"journal":{"name":"2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116700126","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

Predicting Nodes for Effectively Spreading Vaccine Awareness: An Influence Maximization Approach 有效传播疫苗意识的预测节点:影响最大化方法

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668587

Deboleena Bhattacharyya, Khavin Shankar G, P. Aaranan, K. Raja, Amira Alturki, Mithileysh Sathiyanarayanan

{"title":"Predicting Nodes for Effectively Spreading Vaccine Awareness: An Influence Maximization Approach","authors":"Deboleena Bhattacharyya, Khavin Shankar G, P. Aaranan, K. Raja, Amira Alturki, Mithileysh Sathiyanarayanan","doi":"10.1109/ISAECT53699.2021.9668587","DOIUrl":"https://doi.org/10.1109/ISAECT53699.2021.9668587","url":null,"abstract":"Many large pandemics have occurred throughout human history, and pandemic-related crises have had massive detrimental effects on global health, economics, and even national security. Aside from the potentially lethal spread of infections, one key problem is persuading people to get vaccines. For decades, problematic negative vaccine beliefs have been the largest predictor of opposition to vaccination efforts. In this research, we attempted to examine the probability of an individual to be vaccinated or not and offer a strategy for efficiently spreading awareness among people via a well-executed network. Finding a set of seed nodes that maximizes the spread of influence in a social network is known as influence maximization. The seed nodes are employed in viral marketing to maximize profit by leveraging effective word-of-mouth. By finding the most important seeds in the network, we want to use this strategy to raise vaccination awareness in communities. For prediction, we compared a few deep learning models and a random forest classifier. Then we examined the model with the best performance and conducted a basic study on employing influence maximization to raise awareness in distinct communities. The best model was roughly eighty four percent accurate and forecasted us those who are most likely to be vaccinated, which could be utilized as seeds for our Influence Maximization model, to spread vaccination awareness among the unvaccinated, which can also be discovered by our prediction model.","PeriodicalId":137636,"journal":{"name":"2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123037116","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 Four-Legged H-Bridge Inverter Topology for Cascaded Multilevel Inverter 用于级联多电平逆变器的四足h桥逆变器拓扑

2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) Pub Date : 2021-12-06 DOI: 10.1109/ISAECT53699.2021.9668423

Muhammad Munib, K. Qureshi, J. Gu, M. Asad, Naureen Butt, U. Farooq

引用次数: 0