2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)最新文献_第9页

Direct Flux-Vector Oriented Control for Interior Permanent Magnet Synchronous Motor 内置式永磁同步电动机的直接磁通矢量定向控制

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852072

Thien-Phuoc Nguyen, M. Hsieh, Thanh Anh Huynh, Q. Doan

{"title":"Direct Flux-Vector Oriented Control for Interior Permanent Magnet Synchronous Motor","authors":"Thien-Phuoc Nguyen, M. Hsieh, Thanh Anh Huynh, Q. Doan","doi":"10.1109/ICCE55644.2022.9852072","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852072","url":null,"abstract":"Direct torque control or direct torque and flux control have significant advantages in operating motors in the field-weakening (FW) region. The flux can be controlled simply in the stator flux linkage frame, directly affecting back-EMF, torque, and speed. However, controlling the current limit under the stator flux frame has not been investigated extensively, especially for FW operation. This paper analyzes the trajectory of the flux regarding the fed current form inverters and the characteristic current. From the analysis, a novel Direct Flux Control is proposed as a promising controller for interior permanent magnet synchronous motor (IPMSM) functioning across an extensive speed range. Then, the performance of the proposed method is compared with the conventional direct torque control method. The analysis results reveal that the torque and flux ripples of the proposed method are reduced, the maximum speed is increased compared to the conventional controller. Finally, simulation results by using MATLAB/Simulink are provided, and the hardware-in-the-loop validates and demonstrates the feasibility and performance of the proposed method.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"2 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":"126749019","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

Comparative study on super resolution techniques for upper gastrointestinal endoscopic images 上消化道内镜超分辨率成像技术的比较研究

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852031

Long-Thuy Nguyen, Danh H. Vu, Ngoc Cuong Vu, V. Dao, Thanh-Hai Tran

{"title":"Comparative study on super resolution techniques for upper gastrointestinal endoscopic images","authors":"Long-Thuy Nguyen, Danh H. Vu, Ngoc Cuong Vu, V. Dao, Thanh-Hai Tran","doi":"10.1109/ICCE55644.2022.9852031","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852031","url":null,"abstract":"Endoscopy is considered the gold standard for diagnosis of gastrointestinal diseases. Image quality is an important creteria for a better accurate prediction of the diseases. Actually, in many current health facilities in developing countries as Vietnam, due to the endoscope limitation and environmental impacts, endoscopic images are of very low resolution. As a result, some textures and colors in lesion regions of the image could be ignored. This paper investigates different techniques for enchancement of image resolution. Spefically, we implement fundamental interpolation methods such as Nearest Neighbor Interpolation (NNI), Bilinear Interpolation (BLI) and Bicubic Interpolation (BCI) and advanced methods using deep learning such as Efficient Supixel Convolution Neuron Network (ESPCN), Residual Dense Network (RDN) and Super Resolution Dense Network All (SRDenseNet All). We then compare the performance of these techninques according to SSIM, PSNR and framerate metrics. The experimental results on dataset of upper gastrointestinal endoscopic images show that deep learning super-resolution method (RDN) provides the highest efficiency. This method produces sharper images, some of them look more intuitive and provide more information to doctors that can improve their diagnosis and treatment.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"5 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":"128548388","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

Aerial IRS-Aided Vertical Backhaul FSO Networks over Fisher-Snedecor F Turbulence Channels Fisher-Snedecor F湍流通道上的空中irs辅助垂直回程FSO网络

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852053

Hoang D. Le, T. V. Nguyen, A. Pham

{"title":"Aerial IRS-Aided Vertical Backhaul FSO Networks over Fisher-Snedecor F Turbulence Channels","authors":"Hoang D. Le, T. V. Nguyen, A. Pham","doi":"10.1109/ICCE55644.2022.9852053","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852053","url":null,"abstract":"Free-space optics (FSO)-based, high-altitude plat form (HAP)-assisted backhaul network has recently attracted research efforts worldwide. Nevertheless, one of the critical concerns on HAP-assisted FSO links is cloud coverage, which may block the FSO connections completely. This paper explores a novel solution that uses multiple unmanned aerial vehicles (UAVs) equipped with an intelligent reflecting surface (IRS) array. These UAVs are deployed to diverse the FSO link from HAP-to-ground base station (BS) to avoid cloud coverage. We assume the Fisher-Snedecor $mathcal{F}$ model for the atmospheric turbulence and use a selection combing (SC) receiver to obtain signals from multiple UAVs. We analytically derive the probability density function (PDF) of the received end-to-end signal-to-noise ratio (SNR) by employing the moment matching method, which can obtain an accurate approximation of PDF to the product of $mathcal{F}$ variables. Using the derived statistics, we investigate different system performance metrics, including outage probability, outage capacity, and average bit error rate (BER). Finally, Monte Carlo simulations are provided to validate analytical results.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"31 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":"127107992","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 method for automatic honey bees detection and counting from images with high density of bees 一种基于高密度蜜蜂图像的蜜蜂自动检测与计数方法

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852024

Hai Cong Nguyen, Dinh-Tu Nguyen, T. Phung, Thi-Lan-Anh Nguyen, Toi Nguyen, Pham Thai, Thu-Hong Phan, Thi-Lan Le, Xuan Dung Nguyen, Ngoc-Diem Tran Thi, Vu Hai

{"title":"A method for automatic honey bees detection and counting from images with high density of bees","authors":"Hai Cong Nguyen, Dinh-Tu Nguyen, T. Phung, Thi-Lan-Anh Nguyen, Toi Nguyen, Pham Thai, Thu-Hong Phan, Thi-Lan Le, Xuan Dung Nguyen, Ngoc-Diem Tran Thi, Vu Hai","doi":"10.1109/ICCE55644.2022.9852024","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852024","url":null,"abstract":"This paper presents a design and vision-based techniques for an automated bee counting system. Particularly, the proposed system aims to count bees with high density presences in front of beehive’s entrance. This is a common situation at a bee farm when beekeepers observe honey bee’s appearances to monitor their health. To this end, the proposed system is constructed with a Jetson Nano computer board and a high resolution camera. The bees are automatically and real-time counted from the collected video data. The counting techniques are deployed using recent advantaged deep learning techniques. First, we adapt a YOLO neural network to predict bee’s position on images. However, YOLO is not robust enough in case of occlusions due to a high density of bees’ presence. We then utilize a kernel-based density estimator for each local region. In case a high-density area is detected, we deploy the FAMNET, a neural network recently achieves the best performance for counting objects in high density scenarios. The FAMNET is fine-tuned and optimized parameters for the bee collected data. We measure the performances of the proposed method using a distance between ground-truth counted by beekeepers and the estimated results. The experimental results confirm that it is averagely 10% differences between beekeepers’ counting and the proposed technique. These results show a promising solution to further deploy an IoT system to automatically monitor bee’s health in a bee farm.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"57 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":"133234860","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