2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)最新文献_第10页

Home TechCare using IoT 使用物联网的家庭技术护理

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791664

Mrunal U. Patil, Siddhika Patil, Vaishnavi Wagh, Sudarshan Pillai, Sadhna Pai, Prasad Kulkarni

引用次数: 0

Flexible MIMO Antennas for 5G Applications 5G应用的灵活MIMO天线

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791704

N. Kulkarni, N. Bahadure, P. D. Patil, S. Karve, J. Kulkarni, S. Kadam

{"title":"Flexible MIMO Antennas for 5G Applications","authors":"N. Kulkarni, N. Bahadure, P. D. Patil, S. Karve, J. Kulkarni, S. Kadam","doi":"10.1109/ICETET-SIP-2254415.2022.9791704","DOIUrl":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791704","url":null,"abstract":"5G is emerging as a next-generation technology that enhances capacity, provides very low latency, very high data rates, and good quality of service. For any 5G device to operate successfully, the design and development of an antenna play a very important role. An antenna should be compact in size, cost-effective, and should cover the desired 5G band with enhanced bandwidth, gain, and negligible radiation losses. The shrinking size of the futuristic and next-generation wireless devices will need miniaturized and tightly assembled antennas without affecting the performance. With the number of antennas increased in the MIMO system it will be difficult to meet the space constraint of next-generation devices. Also, with the innovation and ever-increasing demand for flexible electronic devices, there will be a need to design flexible antennas for such devices. Flexible antennas are having tremendous applications in Gateways and Routers, Wireless Access Points, High-speed HD streaming, Handheld Devices, High-capacity MIMO networks for Public Transportation. This review paper explains the concept of flexible antennas and the various types of substrates used for antenna fabrication with its comparison. It also covers the various types of flexible MIMO antennas for 5G applications.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127441313","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

Design and Implementation of Multipurpose Robot for Covid-19 Ward 新型冠状病毒病区多用途机器人的设计与实现

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791549

Chetan Kale, M. Khanapurkar, Umesh Kubde

{"title":"Design and Implementation of Multipurpose Robot for Covid-19 Ward","authors":"Chetan Kale, M. Khanapurkar, Umesh Kubde","doi":"10.1109/ICETET-SIP-2254415.2022.9791549","DOIUrl":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791549","url":null,"abstract":"A multipurpose robot is a system for the covid-19 ward to provide support for serving food, medication, perform temperature check etc., for the covid positive patients without making more efforts by the medical or frontline workers towards the care of patients. As everyone there is a high risk getting infected by the virus. So, to avoid visiting rooms by the staff, multipurpose robot can minimize the contacts of patients and frontline workers or medical staff. The robot is controlled by the user using a transmitter section / remote. The main purpose of the robot is to move around, serve the food, check patient vital parameters like temperature, heart rate, SpO2 level wirelessly without making any contact with the patient and can transmit live video of patient using an IP web camera which will be placed on the robot. It will also help to navigate the directions in the hospital so that anyone can easily handle the robot. For the movement of robot from one place to other, authors have used 4 motors with dedicated wheels attached to them, which can be controlled by microcontroller using RF wireless communication module. The robot will be robust enough that it can sustain approximately 5 to 10 kg weight on it. Also, the patients can have a discussion with their families because everyone know family member are not allowed in the covid ward to visit the patient. The transmitter section plays a role of master and the robot plays the role of slave in this system. The multipurpose robot has many advantages with it as it is a low-cost system which requires low maintenance, easy to use, easy to deploy and can-do surveillance as well.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115482696","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

Chronic kidney disease prediction using different machine learning models 使用不同的机器学习模型预测慢性肾脏疾病

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791838

Apoorva Pravin Datir, Snehal Shivaji Funde, Nikita Tanaii Bhore, S. Gawande, Pallavi Dhade

{"title":"Chronic kidney disease prediction using different machine learning models","authors":"Apoorva Pravin Datir, Snehal Shivaji Funde, Nikita Tanaii Bhore, S. Gawande, Pallavi Dhade","doi":"10.1109/ICETET-SIP-2254415.2022.9791838","DOIUrl":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791838","url":null,"abstract":"A kidney's major purpose is to eliminate waste materials and excess fluids from the body through urine, which helps to maintain a stable chemical equilibrium in the body. Chronic kidney disease (CKD) is a serious global concern that is defined by a steady decline of kidney function over time. CKD affects over 14% of the world's population and is difficult to identify in its early stages. This disease is usually detected at the final or most critical stage in the human body, posing a significant risk to the human body and often resulting in the person's death. If the condition is identified early on, the patient's kidney function may be saved, allowing him or her to live a longer life. Machine learning has progressed to the point that we can now examine the medical records of individuals and detect chronic kidney disease in its early stages. On the CKD dataset from the UCI machine learning repository, this research examines the occurrence of CKD by creating ML models with 6 distinct classification algorithms. Before we can use machine learning techniques on the raw dataset, we must first process it and remove any duplicated or null variables before sending it to the models. After running the data through all of the models, it was observed that Random Forest and Extra Trees Classifier proved the highest accuracy of 98.33. The literature survey conducted before execution offered valuable insights and helped to shorten the execution time because we only chose algorithms with good accuracy.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129868422","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

Effective Breast Cancer Classification Using SDNN Based E-Health Care Services Framework 基于SDNN的电子医疗保健服务框架的有效乳腺癌分类

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791795

Anji Reddy Vaka, B. Soni, R. Murugan

{"title":"Effective Breast Cancer Classification Using SDNN Based E-Health Care Services Framework","authors":"Anji Reddy Vaka, B. Soni, R. Murugan","doi":"10.1109/ICETET-SIP-2254415.2022.9791795","DOIUrl":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791795","url":null,"abstract":"In the modern environment, many health care issues are raised day by day. Detecting the early stage of breast cancer may lead to prevention. In this paper, we proposed the breast cancer classification of the E-health care services framework with the Internet of Medical Things by utilizing the support value-based Deep Neural Network (SDNN) classification. Initially, the input cytology images are taken from the local health care center, and then attain the process of pre-processing and filtering technique is used the noise removed image goes to the feature extraction process includes entropy, Geometrical features, Textural features. After that segmentation is done using Histo-sigmoid fuzzy clustering. Finally, it attains the classification process of the proposed SDNN support value-based deep neural network. SDNN classifier classifies the breast cancer images as normal or abnormal compared with the existing approaches. The proposed method accuracy is 97.4 % which is better than other state - of - the art methods.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"39 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128438965","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

Vector Model Based Information Retrieval System With Word Embedding Transformation 基于向量模型的词嵌入信息检索系统

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791503

J. Brundha, K. Meera

引用次数: 2

Sensor Based Vibration Analysis of Motor Using MATLAB Software 基于传感器的电机振动分析

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791823

Vaishnavi Khandelwal, Pankaj Ramtekkar, Mohit Chauhan, Yashika Bhute, Rajratan Kouthekar

引用次数: 3

Transfer Learning-Assisted Prognosis of Alzheimer's Disease and Mild Cognitive Impairment Using Structural-MRI 结构磁共振成像对阿尔茨海默病和轻度认知障碍的迁移学习辅助预后

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791559

Yusera Farooq Khan, B. Kaushik, Bilal Ahmed Mir, Rahul Verma, Harsha Khandelwal

{"title":"Transfer Learning-Assisted Prognosis of Alzheimer's Disease and Mild Cognitive Impairment Using Structural-MRI","authors":"Yusera Farooq Khan, B. Kaushik, Bilal Ahmed Mir, Rahul Verma, Harsha Khandelwal","doi":"10.1109/ICETET-SIP-2254415.2022.9791559","DOIUrl":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791559","url":null,"abstract":"Alzheimer's is a neurodegenerative disease that damages human brain cells and causes dementia. When the brain cells gradually deteriorate, it leads to the inability to carry out everyday activities. While conventional machine learning (ML) has been shown to be efficient in assisting with AD diagnosis, relatively few research have examined the effectiveness of deep learning and transfer learning in this difficult challenge. We assessed the possibility of early recognition and prediction of Alzheimer's disease (AD) using pre-trained transfer-learning algorithms on structural brain MRI. Advances in artificial intelligence are assisting in the enhancement of early detection of Alzheimer's disease. Using open-source neuroimaging data, researchers have been able to construct programs that help in Alzheimer's diagnosis and prognosis. The presented study is based on an effective technique of applying transfer learning to classify the structural MRI (s-MRI) Axial brain scans by fine-tuning a pre-trained convolutional neural network (CNN), ResNet50, and VGG-16. We have taken s-MRI Axial data from an online available data repository Alzheimer's Disease Neuroimaging Initiative (ADNI). We implemented pre-trained model namely CNN, VGG-16 and ResNet50 trained on brain s-MRI axial scans to classify them into three classes: Cognitive Normal (CN), Mild cognitive impairment (MCI), and Alzheimer's disease (AD). Experiments show that ResNet50 outperformed CNN and VGG-60 with an accuracy of 95.30% on brain MRI axial scan for accurate and early prediction of AD and the onset of MCI.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123031823","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

Rayleigh Distribution-based Edge Detection in SAR Images 基于瑞利分布的SAR图像边缘检测

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791820

S. Paul, B. Saiteja, S. Rajasekharan, K. Pravallika, K. P. Reddy

引用次数: 0

Design of An IoT based Smart Plant Monitoring System 基于物联网的智能工厂监控系统设计

2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) Pub Date : 2022-04-29 DOI: 10.1109/ICETET-SIP-2254415.2022.9791690

Apeksha Rane, Bhushan Vidhale, Priyanka Hemant Kale, G. Khekare

{"title":"Design of An IoT based Smart Plant Monitoring System","authors":"Apeksha Rane, Bhushan Vidhale, Priyanka Hemant Kale, G. Khekare","doi":"10.1109/ICETET-SIP-2254415.2022.9791690","DOIUrl":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791690","url":null,"abstract":"In IoT plant monitoring system we can monitor and control with the help of IoT concepts. The gasses produced by the plant in Day time and nighttime will be monitored on IoT cloud. And according to the moisture of the soil the water pump supply to the plant will be controlled. If moisture is seen below the certain threshold value, then the pump will get turned on and when moisture reaches above the threshold level then the water pump will be turned off by the controller in the system. The Temperature and humidity will be sensed by smart sensors digitally. The hazardous gas will be sensed by the other sensor at that place. The controller which is integrated in the system will send all the monitored parameter and different gasses data on IoT Cloud with the help of Wi-Fi and IoT system. Other circuitry is used to control the relay and to provide power supply to the system. On the IoT cloud the data will be received on the google firebase Real-time database. From that it will be transferred to the AWS server and all the data will be visualized by different gauges and past data will be plotted.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132926167","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