2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)最新文献_第9页

Single-phase seven-level inverter with multilevel boost converter for solar photovoltaic systems 太阳能光伏系统用多电平升压变换器单相七电平逆变器

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776859

Narender Reddy Kedika, Laxman Bhukya, Srinivas Punna, R. Motamarri

引用次数: 1

Intersection over Union based analysis of Image detection/segmentation using CNN model 基于交集的CNN模型图像检测/分割分析

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776896

Amitkumar N Gajjar, Jignesh B. Jethva

引用次数: 3

Reliability Analysis of PFC Multilevel Rectifier Based LED Driver Circuit 基于PFC多电平整流器的LED驱动电路可靠性分析

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776846

Manish Kumar Barwar, L. Sahu, P. Bhatnagar

引用次数: 0

Author Index ICPC2T_2022 作者索引ICPC2T_2022

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/icpc2t53885.2022.9777002

引用次数: 0

An Effective Predictive Torque Control Technique for Open-end Winding Permanent Magnet Synchronous Motor Drives with Reduced Ripples for EVs 电动汽车开放式绕组永磁同步电机减波纹驱动的有效预测转矩控制技术

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776814

Kasoju Bharath Kumar, K. Kumar

{"title":"An Effective Predictive Torque Control Technique for Open-end Winding Permanent Magnet Synchronous Motor Drives with Reduced Ripples for EVs","authors":"Kasoju Bharath Kumar, K. Kumar","doi":"10.1109/ICPC2T53885.2022.9776814","DOIUrl":"https://doi.org/10.1109/ICPC2T53885.2022.9776814","url":null,"abstract":"Permanent Magnet Synchronous motors (PMSM) are commonly used in the applications of Electric Vehicles (EVs). Predictive torque control (PTC) is the method which is popularly used for the control of PMSM. Generally, a PMSM is fed with a two-level inverter for the above operation. But, PMSM fed with multi-level inverter will give better performance. To achieve this configuration, Open-End Winding PMSM (OEW-PMSM) is used which is fed by a dual inverter. OEW-PMSM with three level inversion will comparatively produce less torque ripples and flux ripples. In PTC, cost function is the absolute function of torque and flux errors. Since torque and flux are two different quantities, a weighting factor place an important role in the PTC. The proposed PTC reduces the torque ripples by introducing a new method of utilizing cost function to eliminate weighting factors. Simulation studies are performed with dual-inverter fed OEW-PMSM with conventional and proposed PTC with three level inversion. The effectiveness of the proposed method is verified by comparing conventional PTC with proposed PTC.","PeriodicalId":283298,"journal":{"name":"2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116310086","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

Intelligent Brain Tumor Detection System using Deep Learning Technique 基于深度学习技术的智能脑肿瘤检测系统

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9777073

Anil Kumar Mandle, S. Sahu, Govind P. Gupta

{"title":"Intelligent Brain Tumor Detection System using Deep Learning Technique","authors":"Anil Kumar Mandle, S. Sahu, Govind P. Gupta","doi":"10.1109/ICPC2T53885.2022.9777073","DOIUrl":"https://doi.org/10.1109/ICPC2T53885.2022.9777073","url":null,"abstract":"Brain tumors are dangerous and serious disorders affected by uncontrolled cell growth in the brain. Brain tumors are one of the most challenging diseases to cure among the different ailments encountered in medical study. Tumors are classified as either benign or malignant, with benign tumors being non-cancerous and malignant tumors being cancerous from the MRI (Magnetic Resonance Images). There are several tumor detection techniques available, but more study is needed in this field since numerical analysis, precisedisorder diagnosis, and brain tumor detection are all necessary for scientific confirmation. As a result, good planning can protect a person's life that has a brain tumor. Using the 2D Convolutional Neural Network (CNN) technique, this study proposes Computer-Aided Diagnosis (CAD) a deep learning-based intelligent brain tumor detection framework for categorization of brain MRI images with the dataset from Figshare, It is a combination of 3064 brain MRI images from 233 patients into two categories: benign and malignant. The performance of the proposed framework is calculated and compared with state-of-the-art methods in terms of accuracy, recall, and F1-Score.","PeriodicalId":283298,"journal":{"name":"2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122350426","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 Novel Indoor Human Comfort Control Technique 一种新的室内人体舒适控制技术

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776797

Amrapali Deorao Nimsarkar, H. Naidu, P. Kokate

{"title":"A Novel Indoor Human Comfort Control Technique","authors":"Amrapali Deorao Nimsarkar, H. Naidu, P. Kokate","doi":"10.1109/ICPC2T53885.2022.9776797","DOIUrl":"https://doi.org/10.1109/ICPC2T53885.2022.9776797","url":null,"abstract":"According to the National Human Activity Pattern Survey (NHAPS), humans spend about 86.9% of their time indoors. Living, working etc. International Energy Agency (IEA) recently stated the cooling sectors demand at international level will be doubled up-to 2050. Hence, thermal comfort will be a challenging parameter for developing countries like India. Thermal comfort depends on a variety of factors such as temperature, humidity, airspeed, clothing, and resident activity. This paper discussed the systematic study of the thermal comfort during various indoor conditions. First, we collected data (temperature, relative humidity, air speed, energy consumption in KWh) from a closed room in the government building. Next, the Predictive Mean Vote (PMV), Predicted Percentage Dissatisfied (PPD), Standard Effective Temperature (SET), which are indices of thermal comfort are determined using Center for Built Environment (CBE). This tool complies with ASHRAE 552017, ISO 77300:2005 AND EN 167981:2019 standards. Finally, we obtained an average setting temperature for Air conditioners (AC) in various Indian cities that satisfies the human body's thermal comfort. This novel concept will be useful to decrease the consumption of AC load in major Indian cities and government offices.","PeriodicalId":283298,"journal":{"name":"2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121096745","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

SaDiTect: Dirt Detection in Salt Using YOLOv3 使用YOLOv3进行盐中的污垢检测

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776837

M. A. Malbog, Marte D. Nipas, Jennalyn N. Mindoro, Julie Ann B. Susa, Joshua S. Gulmatico, Aimee G. Acoba

{"title":"SaDiTect: Dirt Detection in Salt Using YOLOv3","authors":"M. A. Malbog, Marte D. Nipas, Jennalyn N. Mindoro, Julie Ann B. Susa, Joshua S. Gulmatico, Aimee G. Acoba","doi":"10.1109/ICPC2T53885.2022.9776837","DOIUrl":"https://doi.org/10.1109/ICPC2T53885.2022.9776837","url":null,"abstract":"Salt is essential for maintaining people's life. The presence of undesirable pieces such as dirt contributes to the overall quality of salt provided to customers. People's naked eyes seldom distinguish between salt and dirt; as a result, it would take time and effort to separate salt and dirt. Unseen dirt can also add to the total weight of manufacturing fine salt, and removing this dirt manually can be time-consuming. Artificial Intelligence (AI) algorithms employ object categorization systems to recognize certain items in a class as the topic of study. The systems aggregate things in pictures into categories where objects having similar qualities are grouped along, while others are ignored until specifically configured. The objective of the study is to develop a detection system for unwanted dirt that is mixed in salt. This system can be embedded into a dirt removal system for the salt manufacturing process. The study gathered 500 images of salt as the dataset and divided it into two (2) parts: training is set to 70% and for testing is 30%. creating the model using the dataset that has been gathered together with the Yolov3 pre-trained model for object detection was used in creating the model for the dirt detection system and the training has 50 epochs. The researchers conducted testing using ten (10) photos of dirt to assess the system's accuracy, and they reached a 70 percent accuracy. This study also evaluated the system by importing video clips to be detected and the system easily detected most of the dirt. This demonstrates that the system is trustworthy and effective in detecting dirt in the salt. This system can be improved in terms of accuracy by adding techniques like data augmentation, transfer learning, and model selection.","PeriodicalId":283298,"journal":{"name":"2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121164135","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

Implementation of Particle Swarm Optimization for Model Order Reduction 粒子群算法在模型降阶中的应用

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776988

Mitali Vijay Kondukwar, P. Dewangan

引用次数: 0

Exploration of Deep Convolutional Neural Networks(Via Transfer Learning) for Handwritten Character Recognition 探索深度卷积神经网络(通过迁移学习)用于手写字符识别

2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T) Pub Date : 2022-03-01 DOI: 10.1109/ICPC2T53885.2022.9776795

Naragoni Saidulu, K. A. Monsley, K. Yadav, R. Laskar

引用次数: 0