2021 3rd International Conference on Signal Processing and Communication (ICPSC)最新文献_第5页

Solar Photo Voltaic Based Water Pumping Using BLDC Motor 基于无刷直流电机的太阳能光伏水泵

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451679

Loganathan N, N. C, Nivashini K, Nivin B, Pavurnaa S

引用次数: 0

A Review on Localization Problems in Wireless Sensor Network: Algorithmic and Performance Analysis 无线传感器网络定位问题综述:算法与性能分析

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451770

Sathya Prakash Racharla, J. Kalaivani

引用次数: 1

Embodying Current division transconductance reduction in M-CDTA and its application as low frequency filter 介绍了M-CDTA的分电流跨导降低及其在低频滤波器中的应用

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451677

Mohit Bansal, Pranav Semwal, Navneet Sagar, N. Pandey

引用次数: 0

Electricity Monitoring And Auto Bill Generation Using IOT 使用物联网的电力监控和自动账单生成

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451738

J. Deny, A. Narasimha, R. G. Vardhan Reddy, S. Sathish

引用次数: 1

A comparative study for Fault Location detection in bipolar HVDC Transmission Systems using Wavelet transform and Artificial Neural Networks 小波变换与人工神经网络在双极直流输电系统故障定位检测中的比较研究

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451746

Ankit Sourashtriya, Minal Tomar

{"title":"A comparative study for Fault Location detection in bipolar HVDC Transmission Systems using Wavelet transform and Artificial Neural Networks","authors":"Ankit Sourashtriya, Minal Tomar","doi":"10.1109/ICSPC51351.2021.9451746","DOIUrl":"https://doi.org/10.1109/ICSPC51351.2021.9451746","url":null,"abstract":"The present work proposes a WT-ANN-based model for fault location estimation of HVDC transmission line, for providing faster response time of estimation. HVDC has many advantages over its counterpart for long-distance transmission of power like it has fewer transmission losses and better power quality. But it lacks technological development in the field of fault location detection and clearance as compared to HVAC.The work is aimed to develop a model based on wavelet transform and self-learning technique i.e ANN algorithm to estimate the fault location of any HVDC transmission line. Wavelet transform is performed on the data obtained from the prepared model on PSCAD/EMTDC software for different fault locations at a difference of 1KM. Data from both rectifier and inverter end has been collected. Wavelet transform will help in extracting features from data for better learning of the ANN-based model. Both wavelet transform and ANN implementation are done using Matlab software.Four features obtained post wavelet transform (3 detailed coefficients and 1 approx. coefficient) will be used to train four different ANN models based on LM & BR model. The final prediction of fault location is done by adding the result obtained from the above 4 models. The results obtained are proved to be very reliable with an error of near 1- 1.5 KM for the WTANN combination.","PeriodicalId":182885,"journal":{"name":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","volume":"751 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117002767","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

Computer Vision-based Survey on Human Activity Recognition System, Challenges and Applications 基于计算机视觉的人体活动识别系统研究、挑战与应用

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451736

A. F., Sukhwinder Singh

{"title":"Computer Vision-based Survey on Human Activity Recognition System, Challenges and Applications","authors":"A. F., Sukhwinder Singh","doi":"10.1109/ICSPC51351.2021.9451736","DOIUrl":"https://doi.org/10.1109/ICSPC51351.2021.9451736","url":null,"abstract":"For surveillance purpose, lots of method were used by the researchers but computer vision based Human Activity Recognition (HAR) technologies/systems received the most interest because they automatically distinguish human behaviour and movements from video data utilizing recorded details from cameras. But the extraction of accurate and opportune information from video of human’s activities and behaviours is most important and difficult task in pervasive computing environment. Due to lots of applications of HAR systems like in medical field, security, visual monitoring, video recovery, entertainment and irregular behaviour detection, the accuracy of system is most important factors for researchers. This review article presents a brief survey of the existing video or vision-based HAR system to find out their challenges and applications in three aspects such as recognition of activities, activity analysis, and decision from visual content representation. In many applications, system recognition time and accuracy is most important factor and it is affected due to an increase in the usage of simple or low quality type cameras for automated systems. So, to obtain a better accuracy and fast responses, the usage of demanding and computationally intelligent classification techniques such as deep learning and machine learning is a better option for researchers. In this survey, we addressed numerous computationally intelligent classification techniques-based research for HAR from 2010 to 2020 for a better analysis of the benefits and drawbacks of systems, the challenges faced and applications with future directions for HAR. We also present some accessible problems and ideas that should be discussed in future research for the HAR system utilizing machine learning and deep learning principles due to their strong relevance.","PeriodicalId":182885,"journal":{"name":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133051852","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: 9

Improvement of the LoRaWAN Movement Tracking Framework LoRaWAN运动跟踪框架的改进

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451767

B. Perumal, J. Deny, B. Yaswanth, M. Sudheer, P. V. Charanreddy

{"title":"Improvement of the LoRaWAN Movement Tracking Framework","authors":"B. Perumal, J. Deny, B. Yaswanth, M. Sudheer, P. V. Charanreddy","doi":"10.1109/ICSPC51351.2021.9451767","DOIUrl":"https://doi.org/10.1109/ICSPC51351.2021.9451767","url":null,"abstract":"The Lora WAN (Long Range Wide Area Network) might be some other innovation in wireless machine. This lora wan test out seat undertaking contains of arduino microcontroller, dragino lora, and lora comfy to manipulate for the reason that the Lora gateway. Lora client wishes arduino microcontroller and lora/gps ensure. Imlora/gps might be steam-fueled with the resource of lora consumer, and it’s going to ship the gps place data to the lora phase any area the scenario got might be recorded in its information log inconsistently. The lora consumer can be flexible at the equal time as passage server could be at steady mode in the course of the take a look at. The checking out examination might be cleared out community and robust times. It completely changed into located that in an honestly community condition, the correspondence amongst two devices carries a better confirmed up diversely in connection than the metropolitan situation. Lora wan correspondence within the populated territory indicates that with better obstruction because of multiplied structures open, the correspondence can be less efficient. These issues are continuously settled via putting in lora wan zenith within the focal factor of the distance.","PeriodicalId":182885,"journal":{"name":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","volume":"389 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133466339","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

Hysteresis Controlled Single-Switch High Step-Up Coupled-Inductor Boost Converter 滞回控制单开关高升压耦合电感升压变换器

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451745

B. Balaji, B. Vengadesamani, M. Sarvajith

引用次数: 6

Leukocyte Classification based on Transfer Learning of VGG16 Features by K-Nearest Neighbor Classifier 基于迁移学习VGG16特征的k -最近邻分类器白细胞分类

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451707

Diana Baby, Sujitha Juliet Devaraj, Anishin Raj M. M

{"title":"Leukocyte Classification based on Transfer Learning of VGG16 Features by K-Nearest Neighbor Classifier","authors":"Diana Baby, Sujitha Juliet Devaraj, Anishin Raj M. M","doi":"10.1109/ICSPC51351.2021.9451707","DOIUrl":"https://doi.org/10.1109/ICSPC51351.2021.9451707","url":null,"abstract":"White blood cells (WBCs) are also called as leukocyte which is a significant component of blood that covers 1% of the total blood, protect us from numerous types of illness and other diseases. The automated classification of different types of leukocytes is very significant since each component have some designated functions in the human body and also the manual classification by skilled medical professionals is a tedious and erroneous task. In this work an automated approach based on transfer learning methodology is used for the detection and classification of leukocytes into four types such as Lymphocyte, Monocyte, Eosinophil and Neutrophil since there are limited numbers of images in the dataset. The methodology adopted in this work is a combination of deep learning and machine learning in which the features are extracted from the segmented nucleus of leukocyte by VGG16 deep learning model which is trained and evaluated using K-Nearest Neighbor (KNN) machine learning algorithm which provided an accuracy of 82.35% which is better when compared to Naive Bayes Classifier.","PeriodicalId":182885,"journal":{"name":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121324765","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: 5

An Approach for Detecting and Identifying Suspected Weapons Using YOLO Algorithm 一种基于YOLO算法的可疑武器检测与识别方法

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI: 10.1109/ICSPC51351.2021.9451686

M. A. Vinith, G. Pradeep, B. Priya

引用次数: 0