2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)最新文献_第8页

Classification of heart disease from ECG signals using Machine Learning 利用机器学习从心电信号中分类心脏病

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573659

V. Rajendran, S. Jayalalitha, M. Thalaimalaichamy, Tinto Raj

引用次数: 0

A Hybrid Approach of ANN-GWO Technique for Intrusion Detection 一种基于ANN-GWO技术的混合入侵检测方法

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573800

Anushka Sharma, Utkarsh Tyagi

引用次数: 3

Subspace and Frequency Domain Speech Enhancement Techniques 子空间和频域语音增强技术

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573833

Ragipati Naga Sai Tejaswini, Ravikumar Kandagatla, Jahnavi Nandeti, Mamidi Krupakar, Paragati Haveela

{"title":"Subspace and Frequency Domain Speech Enhancement Techniques","authors":"Ragipati Naga Sai Tejaswini, Ravikumar Kandagatla, Jahnavi Nandeti, Mamidi Krupakar, Paragati Haveela","doi":"10.1109/RTEICT52294.2021.9573833","DOIUrl":"https://doi.org/10.1109/RTEICT52294.2021.9573833","url":null,"abstract":"Speech enhancement or noise reduction is used as front end processing for speech recognition application. Speech enhancement applications include mobile phones, hand free phones, hearing aids, personal assistants, home automation, robots and so on. Also the hearing aid plays important role for hearing impaired listeners for comfort listening. To understand the speech enhancement algorithms it is important to analyze the output/performance by varying the parameters involved in the technique / algorithm. The main objective of paper is to compare different frequency domain approaches and time domain approaches available for speech enhancement. Karhunen-Loeve transform (KLT) and the MMSE estimators for speech enhancement is discussed. It is observed that considering perceptually motivated techniques shows improved performance and thus results are compared for basic approach and perceptual motivated approaches. This work discusses the theory related to speech enhancement and gives the guidance on how to proceed for implementation of speech enhancement algorithms using MATLAB. The real time application of mathematical operations like Fourier transform, Averaging, variance, Minimum Mean Square and windowing is discussed. Sub space algorithms for speech enhancement are discussed and the performance is compared with frequency domain approaches. Simulations are performed using MATLAB and the performance is compared using objective performance measures Signal to Noise Ratio (SNR), Segmental SNR and PESQ.","PeriodicalId":191410,"journal":{"name":"2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130188960","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 Comparative Analysis of Extreme Gradient Boosting Technique with Long Short-Term Memory and Layered Recurrent Neural Network for Electricity Demand Forecas 基于长短期记忆的极值梯度增强技术与分层递归神经网络在电力需求预测中的比较分析

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573988

Surbhi Singh, M. M. Tripathi

{"title":"A Comparative Analysis of Extreme Gradient Boosting Technique with Long Short-Term Memory and Layered Recurrent Neural Network for Electricity Demand Forecas","authors":"Surbhi Singh, M. M. Tripathi","doi":"10.1109/RTEICT52294.2021.9573988","DOIUrl":"https://doi.org/10.1109/RTEICT52294.2021.9573988","url":null,"abstract":"In the energy sector, for an efficient electricity load management which includes viable utilization and allocation of energy assets, Electricity Load Forecasting plays a critical role. Precise long-term and short-term electricity demand forecast is significant as it enables complete utilization of produced electric power, preventing over-production and sometimes wastage of energy and resources. This paper presents a comparative proof of ensemble learning based algorithm Extreme Gradient Boosting Technique (XGBoost) with Deep Recurrent Neural Network (RNN) and Stacked Long Short-Term Memory Network (LSTM) for short term electricity demand forecast on the Dominion Energy Data taken from PJM energy market. The aim of this paper is to prove that stacked LSTM performs better as compared to an ensemble machine learning model XGBoost and deep RNN algorithms on PJM energy data, by using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2 score as evaluation metrics for performance validation. This work sheds light on the internal architecture of the models and the different values of hyper-parameters used while training the models to justify the observed day-ahead predictions.","PeriodicalId":191410,"journal":{"name":"2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132680332","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

Stabilizing Voltage Fluctuations in Wind Energy Conversion System using Arduino controlled Buck-Boost Converter 利用Arduino控制的Buck-Boost转换器稳定风能转换系统的电压波动

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573948

Sk. Vahid, V. Rafi, G. Nageshkumar, Y. Ganesh, R. Preethi, O. NandaKishore

{"title":"Stabilizing Voltage Fluctuations in Wind Energy Conversion System using Arduino controlled Buck-Boost Converter","authors":"Sk. Vahid, V. Rafi, G. Nageshkumar, Y. Ganesh, R. Preethi, O. NandaKishore","doi":"10.1109/RTEICT52294.2021.9573948","DOIUrl":"https://doi.org/10.1109/RTEICT52294.2021.9573948","url":null,"abstract":"In this paper, we proposed a prototype simulation model for stabilizing the voltage fluctuations in wind energy conversion system using Arduino controlled Buck boost converter. As there is an increase in energy demand, the use of non-conventional source of energy like wind energy, solar energy, tidal energy etc is also increasing from the last few decades. So there is need of changing the topology of these renewable energy conversion systems so as to make it simple, cost effective and efficient. This paper focuses on the wind energy conversion system. As wind speed fluctuates, there is a change in the magnitude and frequency of output voltage of the generator in WECS. So it is to be rectified to DC and then fed it to an inverter before giving it to a grid. But this DC also varies depending on wind speed. The input to the inverter is to be maintained constant DC so as to convert it to desired magnitude and frequency of output voltage with less control units for inverter. We are using a buck boost converter using Arduino and fly back converter in between rectifier and inverter in order to make the input of the inverter a constant DC. Thus we can reduce the number of control system units required for voltage control in WECS and hence cost can also be reduced","PeriodicalId":191410,"journal":{"name":"2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114567620","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

Polynomial Based Linear Regression Model to Predict COVID-19 Cases 基于多项式的线性回归模型预测COVID-19病例

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9574032

Nikhil, Arushi Saini, Santu Panday, Neha Gupta

{"title":"Polynomial Based Linear Regression Model to Predict COVID-19 Cases","authors":"Nikhil, Arushi Saini, Santu Panday, Neha Gupta","doi":"10.1109/RTEICT52294.2021.9574032","DOIUrl":"https://doi.org/10.1109/RTEICT52294.2021.9574032","url":null,"abstract":"The epidemic COVID-19 has profoundly influenced people's wellness worldwide and the number of fatalities from diseases continues to increase world-wide. Despite technology's remarkable success in our daily lives, notably in ML and DL, AI also helped humanity fight the grueling COVID-19 war. DL is only one approach of ensuring that potential data-driven technologies can help humankind manage COVID-19. Big data and artificial intelligence are used to leverage exceptional efforts to combat the COVID-19 pandemic crisis. In some prior disease outbreaks, various AI offshoots were deployed. AI was applied in the identification of disease clusters, case monitoring, future outbreak predictions, mortality risk, and diagnosis of COVID-19, resource allocation illness management, training facilitation, record maintaining and design identification for the investigation of the trend towards the illness. AI & Machine learning can help to find out the strategies to prevent the Corona virus. This paper presents a polynomial based linear regression model to predict the future cases according to the current situation using data of last few months, showing the output on the graph. The paper also discusses the applications of AI & Machine learning in Corona virus pandemic like forecasting infection rate, diagnose with images comprehensively and will also discuss the role of Machine learning in facilitating the development of vaccine as well.","PeriodicalId":191410,"journal":{"name":"2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276390","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: 3

Brushless DC Motor Based E-Rickshaw Controller Design 基于无刷直流电动机的三轮车控制器设计

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573560

A. Goswami, M. Sreejeth, Radhakrishna Upadhyay, S. Indu

引用次数: 1

A Solar Powered Kiosk for Contactless Body Temperature Sensor and Hand Sanitizer Dispenser to Monitor and Control Covid-19 Disease 用于监测和控制Covid-19疾病的非接触式体温传感器和洗手液分配器的太阳能Kiosk

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573663

B. K. Kumar, N. Thanusha, Shwetha Hiremath, K. Soujanya, B. C. Vanishree, Ganesh U Navadeep

{"title":"A Solar Powered Kiosk for Contactless Body Temperature Sensor and Hand Sanitizer Dispenser to Monitor and Control Covid-19 Disease","authors":"B. K. Kumar, N. Thanusha, Shwetha Hiremath, K. Soujanya, B. C. Vanishree, Ganesh U Navadeep","doi":"10.1109/RTEICT52294.2021.9573663","DOIUrl":"https://doi.org/10.1109/RTEICT52294.2021.9573663","url":null,"abstract":"Covid-19 is a pandemic disease that is affecting people all over the world. The Novel Corona virus spreads mostly through human contact, which includes coughing, sneezing, and even coming into contact with materials used by an infected person. Hence this paper presents a solar powered kiosk for contactless temperature sensor for human and automatic hand sanitizer dispenser with flip gates to monitor and control the spread of covid-19 disease. The main aim is to aid in the prevention and control of corona virus infection, as well as to maintain and improve community health by lowering the infection's detrimental impact on the economy and society. The paper presents the design and development of a kiosk that helps in screening human body temperature and dispense the hand sanitizer with automatic opening of flip gates upon the temperature of human in kiosk is under limits. The temperature of human body is sensed automatically with the help of sensor placed in the kiosk and the dispenser will dispense the sanitizer when the person keeps his/her hand under the dispenser. Once, these two task completes, a flip gate will open automatically, which helps people to come out of the kiosk. A 10 Watt solar PV (Photovoltaic) placed on the roof of the kiosk is used to power up the kiosk. An Arduino Uno is used to control the operations of various actuators used in the system. The kiosk is portable and can be placed at the entrance of malls, offices, educational institute and etc.","PeriodicalId":191410,"journal":{"name":"2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134521436","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

SECURITY ENHANCEMENT OF IIOT WITH PERMISSIONED BLOCKCHAIN AND CLOUD COMPUTING 通过允许区块链和云计算增强工业物联网的安全性

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573678

M. Kavyashree, Zainab Mudassir

引用次数: 1

Podcast Hosting Using Spectral Gating And Speech Recognition Methodology 播客主机使用频谱门控和语音识别方法

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) Pub Date : 2021-08-27 DOI: 10.1109/RTEICT52294.2021.9573977

Shubham Lotliker, Gouri Bhatikar, Avina Almeida, Ugam Gaude, S. Naik, V. Jog

引用次数: 0