2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)最新文献

Joint Optimization of Clustering and Resource Allocation based on Game Theory for Ultra-Dense Networks 基于博弈论的超密集网络聚类与资源配置联合优化

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852056

Bui Thanh Tinh, L. Nguyen, H. H. Kha, T. Duong

引用次数: 1

Design of PCB Litz Coils for Improved Skin and Proximity Effects 改善趋肤和接近效应的PCB Litz线圈设计

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852073

Thi Duyen Nguyen, G. Byun

{"title":"Design of PCB Litz Coils for Improved Skin and Proximity Effects","authors":"Thi Duyen Nguyen, G. Byun","doi":"10.1109/ICCE55644.2022.9852073","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852073","url":null,"abstract":"Using a higher operating frequency range (from 20 kHz-150 kHz), the penetrating depth of the vessel is smaller, which is beneficial for both heating time and required power. However, the challenge of this trend compromises the coil’s efficiency due to higher conduction loss. Conventional inductors for domestic induction heating applications are made of multi-stranded litz wires, which reduce considerable losses. Therefore, developing a litz wire structure for printed circuit board (PCB) windings is interesting. Developing a technique to implement litz wire in a standard PCB is a priority objective of this work. This research analysis on two main factors was causing the losses heating based on the comparison between three types of PCB coils: solid, stranded, litz wires, and then comparing the factor to the power of the heating system. Three-dimensional finite element modeling (FEM) was performed for a straightforward method of designing and analyzing PCB litz coil with electromagnetic, transient, and thermal simulation. Finally, a prototype of the PCB is fabricated and measured to verify the manufacturing and modeling process.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116906646","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

Performance Analysis of Uplink MISO Systems with RIS Selections and MRC/SC Configurations 具有RIS选择和MRC/SC配置的上行MISO系统性能分析

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852037

K. Nguyen, Thai-Hoc Vu, Thi-Huong Khuat, Hai-Chau Le, Sunghwan Kim

引用次数: 3

Space Vector Pulse Width Modulation for Asymmetric Flying Capacitor Three-level Inverter 非对称飞电容三电平逆变器的空间矢量脉宽调制

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852088

N. X. Doan, Nho-Van Nguyen

引用次数: 0

A Compact Codesign of Antenna-LNA Sub-System for 60GHz Communication 60GHz通信天线- lna子系统的紧凑协同设计

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852058

Muhammad S. Alam

引用次数: 0

Application of Artificial Intelligence in Detecting and Classifying Faults of Solar Panels 人工智能在太阳能电池板故障检测与分类中的应用

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852089

Nguyen Thi Ngoc Trinh, Do Tran Hung, Nguyen Ho Trong Dat, P. Q. Dung

{"title":"Application of Artificial Intelligence in Detecting and Classifying Faults of Solar Panels","authors":"Nguyen Thi Ngoc Trinh, Do Tran Hung, Nguyen Ho Trong Dat, P. Q. Dung","doi":"10.1109/ICCE55644.2022.9852089","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852089","url":null,"abstract":"Solar energy has always been an important field, which has received a lot of attention and research in the world. One of those problems is the methods of diagnosing, detecting, and classifying faults in the solar panel system. Indeed, such methods are being widely studied with the aim of improving power quality, reliability and as well as ensuring safety when operating solar PV systems. Solar panels are one of the most important elements of a solar power system and by itself there are always problems that can be mentioned such as short circuit fault, open circuit fault, aging condition, discolor, cracks on the surface, … This paper will focus on researching a new method combining I-V curve analysis of solar cells and artificial intelligence algorithms in solar cell fault detection and classification. The failures that can be detected and classified in this study include short circuit, partial shading and hybrid fault. In order to recognize certain faults, the data are firstly simulated and analyzed on the change of I-V characteristics. Then, Principal Components Analysis (PCA) algorithm is introduced to reduce the dimensionality of the data sets and by comparing the changes of parameters with the SVM model, the system will predict the number of solar panels with which type of fault in a solar cell branch. Overall, the research has gathered 680 samples in total and the result shows positive outcomes since the accuracy of recognizing exceeds 90%.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121776279","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

Edge-Case Integration into Established NAT Traversal Techniques 边缘情况集成到已建立的NAT穿越技术

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852092

Simon Keller, T. Hossfeld, S. von Mammen

引用次数: 0

Integrated Modified Three-level Buck Converter With Flying Capacitor-Voltage Self-Balance 飞行电容电压自平衡集成改进型三电平降压变换器

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852097

Quyet Nguyen, Quynh-Trang Nguyen, Huy-Dung Han, L. Pham-Nguyen, Hanh-Phuc Le

引用次数: 1

An Efficient Masking Method for AES Using Tower Fields 利用塔场的有效AES掩蔽方法

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852062

Khac-Hoan Pham, Thai-Ha Tran, T. Nguyen, C. Pham

引用次数: 0

Data-Driven Network Performance Prediction for B5G Networks: A Graph Neural Network Approach 基于数据驱动的B5G网络性能预测:一种图神经网络方法

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852048

Mahnoor Yaqoob, R. Trestian, H. Nguyen

{"title":"Data-Driven Network Performance Prediction for B5G Networks: A Graph Neural Network Approach","authors":"Mahnoor Yaqoob, R. Trestian, H. Nguyen","doi":"10.1109/ICCE55644.2022.9852048","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852048","url":null,"abstract":"Extreme connectivity, dynamic resource provisioning and demand of quality assurance in 5G and Beyond 5G(B5G) networks calls for advance network modeling solutions. We need functional network models that are able to produce accurate prediction of Key Performance Indicators (KPI) such as latency, overall delay, jitter or packet loss at low cost. Graph Neural Networks (GNN) have already shown great potential for network performance prediction, because of their ability to understand the network configurations. In this paper, we focus on improving the generalization capabilities of GNN in relatively complex IP transport network scenarios of future generation networks. We take RouteNet GNN as a reference model and present an alternative GNN. We train both models with relatively smaller network scenarios while for evaluation we use complex and large network configurations. After hyper-parameter tuning for RouteNet and proposed GNN, the results show that our model outperforms baseline architecture in evaluation phase. The validation losses for scenarios not seen during training phase, are significantly lower than the RouteNet.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116827337","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