2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)最新文献_第8页

Design & development of transmitted & encrypted datas using SDN and energy self-healing concepts used in RF energy harvesting wireless sensor nets 在射频能量收集无线传感器网络中使用SDN和能量自愈概念设计和开发传输和加密数据

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917923

S. S, T. Manjunath

引用次数: 2

Entropy based Detection approach for Micro-UAV and Classification using Machine Learning 基于熵的微型无人机检测方法及机器学习分类

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917577

Srihasam Mahesh Kaushik, Vuddagiri Chaitanya, Parasuramuni Kiran Kumar, Mohd Musaddiq Ahmed, Swetha Namburu

{"title":"Entropy based Detection approach for Micro-UAV and Classification using Machine Learning","authors":"Srihasam Mahesh Kaushik, Vuddagiri Chaitanya, Parasuramuni Kiran Kumar, Mohd Musaddiq Ahmed, Swetha Namburu","doi":"10.1109/ICICICT54557.2022.9917577","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917577","url":null,"abstract":"In this paper, we explore the techniques for detection and classification of Unmanned Aerial Vehicles (UAVs) using statistical features of the remote controller Radio Frequency (RF) signals in the presence of environmental noise. In the detection mechanism, the RF signal is transformed into Wavelet domain to filter out noise as well as to reduce computational cost. A kernel entropy based approach is used to partition the RF signal into bins and detect the presence of UAV. Unlike Conventional approaches, we compute the energy transient of signal from the Short Time Fourier Transform (STFT) coefficients obtained from Spectrogram of RF signal. Further, the higher order statistical features of energy transient signal are derived and ranked using Neighborhood Component Analysis (NCA)to select notable features for reducing the computational overhead. Finally, the significant features are used to train machine learning algorithm for classification. The algorithms are trained and tested using MPACT DroneRC Dataset containing 50 RF signals from each of the 15 different micro-UAV controllers. The dataset is partitioned with train to test ratio of 4:1 i.e., 80% of dataset is used for training and 20% for testing the algorithm. The k- Nearest Neighbor (kNN) algorithm with NCA classifies all micro-UAVs with an accuracy of 96.66%. The detection technique is also simulated for different Signal to Noise Ratio (SNR) levels and outcomes are reported.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116972151","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

Machine Learning Models based Mental Health Detection 基于机器学习模型的心理健康检测

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917622

Manivannan Karunakaran, Jeevanantham Balusamy, Krishnakumar Selvaraj

{"title":"Machine Learning Models based Mental Health Detection","authors":"Manivannan Karunakaran, Jeevanantham Balusamy, Krishnakumar Selvaraj","doi":"10.1109/ICICICT54557.2022.9917622","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917622","url":null,"abstract":"This century will be the fastest ever, putting a heavy burden on future generations, especially students. Future generations will face enormous stress, competition, social issues, and constant pressure. Their lives will become a race. That leaves students with mental health issues that lead to disorders. Five of the most common types of disorders that young people especially face are bipolar disorder (mood disorders), anxiety disorders, depression, eating disorders, and sleep issues. As machine learning plays a vital role in the easiness of human life, this paper also uses Machine Learning (ML) algorithms to screen Mental Health by using a Mental Disorder Questionnaire (MDQ). In this research, there are two types of Questionnaires employed. The first Self Reporting Questionnaire-15 (SRQ-15) has 15 general mental disorder questions with the option of Yes/No. The second Self Reporting Questionnaire-25 (SRQ-25) has 25 questions, five questions for each of the five different mental health disorders mentioned. Within each section, the user fills the questionnaire according to the instructions. We labeled the train data set using Supervised Machine Learning. So we use different algorithms to compare results with manual testing.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115522327","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 Characterization for Ladder like Chemical Structures 阶梯状化学结构的表征

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917942

A. D, Annammal Arputhamary I, Revathi R, Girija Bai H

引用次数: 0

Effects of Electric Vehicles Charging on the distribution system 电动汽车充电对配电系统的影响

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917958

Ameya K. Saonerkar, A. Kadu, Nivedita Padole, O. Mohamed, Walid N. Alnabulsi, Purva P. Khot, B. Bagde, P. Fulzele

引用次数: 0

Computational Fluid Analysis of Stented Cerebral Aneurysm in Smokers 吸烟者支架状脑动脉瘤的计算流体分析

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917803

S. M, T. Poojalakshmi, A. Riyavarshini, S. Begum, G. S. V. Vijayalakshmi, N. Vigneshwari, M. Moorthi

{"title":"Computational Fluid Analysis of Stented Cerebral Aneurysm in Smokers","authors":"S. M, T. Poojalakshmi, A. Riyavarshini, S. Begum, G. S. V. Vijayalakshmi, N. Vigneshwari, M. Moorthi","doi":"10.1109/ICICICT54557.2022.9917803","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917803","url":null,"abstract":"Recent studies say that 6.5 million people have unruptured cerebral aneurysms. Modern treatment for unruptured cerebral aneurysms uses newly devised flow diverters like pCONus, pulse rider, eCLIPs, etc.. Among these, eCLIPs has been the subject for many studies and has been proved to be more effective than others. CFD analysis is used to investigate blood flow post the placement of flow diverters. There is no detailed CFD study for smokers with aneurysms post endovascular treatment with flow diverters. In our study, we considered both smokers and non-smokers and analysed blood flow post-treatment with eCLIP using CFD. The properties of blood vessels and blood flow vary for smokers due to the presence of chemicals like nicotine. Here the blood vessel with eCLIP is modelled and visualised using Blender software. The blood vessel with and without aneurysm is modelled for various conditions using COMSOL software for CFD analysis. The velocity and pressure variation are analysed for different areas in the blood vessel.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123303477","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

IoMT Enabled Prototype Edge Computing Healthcare System for Isolated Patients 支持IoMT的隔离患者原型边缘计算医疗保健系统

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917973

Shamna P.A, Priyanka C Mohan

{"title":"IoMT Enabled Prototype Edge Computing Healthcare System for Isolated Patients","authors":"Shamna P.A, Priyanka C Mohan","doi":"10.1109/ICICICT54557.2022.9917973","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917973","url":null,"abstract":"Continuous patient care and the use of multiple medical machines are two challenges facing today's healthcare sector in terms of patient’s healthcare. During the pandemic situation, many people isolated in their home, such as covid-19 positive patients, elderly people living away from their families, bedridden patients, etc., need regular health checks and controls, but during this pandemic is lacking. Recent advances in the Internet of Medical Things (IoMT) has been able to give good results in collecting health data of patients at home environment. Deep learning (DL) applications can able to run on edge nodes, it locally processes, computes and analyzes data from IOMT devices to make inferences on patient health information. This ensures the privacy and security of the patient's physiological information and also and allows patient health information to remain at the patient's side. Send all this information to healthcare professionals and relatives of patients. This framework will provide safety for isolated patients and a health support systemas a whole.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121678935","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

Encryption with Automatic key Generation and Compression 加密与自动密钥生成和压缩

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917718

M. G.C, V. Perumal

引用次数: 0

Design of Synchronous NoC for High Speed Multiprocessor Environment 高速多处理器环境下的同步NoC设计

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917721

A. K, Mohammed Sadiq, Srivani Dommati

引用次数: 0

COVID-19 Detection from Chest X-Rays Using Deep Learning Techniques 利用深度学习技术从胸部x光片中检测COVID-19

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917612

T. A. Suresh, Viji Rajendran V

引用次数: 0