2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)最新文献_第5页

K Best Sphere Decoders for Massive MIMO Receivers 大规模MIMO接收机的最佳球面解码器

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029056

P. Mishra, G. Singh

引用次数: 0

Analysis of Diabetes mellitus using Machine Learning Techniques 用机器学习技术分析糖尿病

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029058

S. S. Bhat, V. Selvam, Gufran Ahmad Ansari, Mohd Dilshad Ansari

{"title":"Analysis of Diabetes mellitus using Machine Learning Techniques","authors":"S. S. Bhat, V. Selvam, Gufran Ahmad Ansari, Mohd Dilshad Ansari","doi":"10.1109/IMPACT55510.2022.10029058","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029058","url":null,"abstract":"Diabetes Mellitus (DM) often known as hyperglycemia is caused by high blood sugar levels. Although DM is a metabolic chronic disease. Treatment and early detection are essential to reducing the risk of serious outcomes. The World Health Organization (WHO) reports that diabetes has a significant mortality rate causing 1.5 million deaths worldwide. The disease can be identified early because to technology tremendous improvements. In order to build a model with a few variables based on the PIMA dataset this research focuses on evaluating diabetes patients as well as diabetes diagnosis using various Machine Learning Techniques (MLT). Exploratory data analysis is the first step in our process after which the information is transferred for data pre-processing and feature selection. The relevant features are chosen and the data is then training and testing using three different MLT such as Support Vector Machine (SVC), Random Forest (RF) and K-Nearest Neighbors (KNN). Amongst all of the classifiers Random Forest has the highest accuracy of 97.75% followed by Support Vector Machine (82.25%) and K-Nearest Neighbors (86.25%).","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"7 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132654211","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: 4

A Novel High performance D-latch using Gate Engineered Schottky device 一种采用门控肖特基器件的新型高性能d型锁存器

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029328

Mehak Ashraf Mir, S. Loan

引用次数: 0

On Banking Site Selection Decision Making Problem Utilizing Similarity Measures of Picture Fuzzy Soft Sets 基于图像模糊软集相似性测度的银行选址决策问题

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029288

S. Aggarwal, Himanshu Dhumras, R. Bajaj

引用次数: 0

Data Analytics in Farming: Rice price prediction in Andhra Pradesh 农业数据分析:安得拉邦大米价格预测

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029009

Pundru Chandra Shaker Reddy, G. Suryanarayana, L. K, Sucharitha Yadala

{"title":"Data Analytics in Farming: Rice price prediction in Andhra Pradesh","authors":"Pundru Chandra Shaker Reddy, G. Suryanarayana, L. K, Sucharitha Yadala","doi":"10.1109/IMPACT55510.2022.10029009","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029009","url":null,"abstract":"The variances regarding prices of horticultural commodities adversely affect the nations GDP. The ranchers are genuinely and monetarily influenced as their long stretches of difficult work go to no end. Forecast of the prices might help the farming production network in settling on vital choices in limiting and dealing with the danger in value variances. By the way of outcome of the diminution of crop yield making due to uneven atmosphere circumstances and global warming. Rice is a significant yield developed in India, with Andhra Pradesh (AP) state being second as far as creation. At present ranchers in AP are moving from rice development to different harvests on account of worth variances and environmental variation. In this research, the costs of rice in AP remain anticipated utilizing time-series using data analytics like Machine Learning (ML) models. The prototypes SARIMA, Holt-Winter's Periodic technique, and Long Short-Term Memory (LSTM) Neural Networks (NN)be situated and utilized, and their recital was assessed dependent on the RMSE esteem on the rice database whose costs from 2001 to 2020. The conclusions demonstrate that the recommended process, LSTM neural network method is actual expectant and finest method which is suitable for the data.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117308440","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: 15

Brain-Computer Interface Based Control for Disabled 基于脑机接口的残疾人控制

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029243

Manish Sharma, N. Rafiuddin, Mohammad Sarfaraz, Yusuf Uzzaman Khan

{"title":"Brain-Computer Interface Based Control for Disabled","authors":"Manish Sharma, N. Rafiuddin, Mohammad Sarfaraz, Yusuf Uzzaman Khan","doi":"10.1109/IMPACT55510.2022.10029243","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029243","url":null,"abstract":"Brain-computer interface (BCI) has gained popularity in recent years as an alternate communication mechanism between the human brain and technology for output. WHO accounts for 15% of the world’s population with disabilities, and there is a critical need for assistive systems to aid those persons in carrying out their everyday activities. This study can help disabled people to increase their independence and quality of life. Electrical impulses from the human scalp are detected and converted into control commands that may be utilized to control external equipment, computer screens, and virtual objects in real time. The present work uses the Deep Learning method to interpret motor imagery signals for Brain-Computer Interface applications. ERD patterns are also gathered that represent the activation and deactivation of the motor cortex. In addition, task-related band power changes are recorded in every trial, which can show stimulation of sensory-motor areas. Furthermore, the goal is to categorize EEG data derived from a Motor Imagery task into two classes, viz. left and right, using the convolutional neural networks. The time-frequency pictures of EEG data fed as input to the convolutional neural network were obtained using continuous wavelet transform. The three channels were separated using data segmentation to convert the raw data into images. To get over the issue of few trials in motor imagery tasks, transfer learning strategies are employed. Transfer learning is applied to three premade neural networks GoogLeNet, AlexNet, and ResNet50, to proceed with CNN classification. Upon analyzing results, AlexNet achieved the best accuracy among the others.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122879749","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

An Energy Efficient and Fast Hybrid Full Adder Circuit 一种高效、快速的混合全加法器电路

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029019

Md. Shahbaz Hussain, Jyoti Kandpal, Aiman Malik, M. Hasan

引用次数: 0

Comparison of SVM and Naïve Bayes for Sentiment Classification using BERT data 基于BERT数据的SVM与Naïve贝叶斯情感分类的比较

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029067

Shivani Rana, Rakesh Kanji, Shruti Jain

引用次数: 0

A New Circular Slot Based Dual Frequency Band Reconfigurable Antenna for 5G and Wi-Fi Applications 5G和Wi-Fi应用的新型圆槽双频可重构天线

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029085

Bashrat Ali, Umhara Rasool Khan, J. Sheikh, Asmat Ara, Sabreena Javeed

引用次数: 0

Hydrogen Cyanide Gas Sensor using Doped/Undoped Graphene Nanoribbon 使用掺杂/未掺杂石墨烯纳米带的氰化氢气体传感器

2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Pub Date : 2022-11-26 DOI: 10.1109/IMPACT55510.2022.10029158

K. Solanki, M. Majumder

引用次数: 0