2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)最新文献_第3页

Discernment of Potential Buyers Based on Purchasing Behaviour Via Machine Learning Techniques 基于机器学习技术的购买行为识别潜在买家

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368935

Shivam Sharma, Hemant Kumar Soni

{"title":"Discernment of Potential Buyers Based on Purchasing Behaviour Via Machine Learning Techniques","authors":"Shivam Sharma, Hemant Kumar Soni","doi":"10.1109/ICADEE51157.2020.9368935","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368935","url":null,"abstract":"Artificial Intelligence (AI) is a fascinating technology that will rule the roost on various dimensions of life in time to come. Artificial Intelligence capacitates the machines to simulate human intelligence. Machine Learning is one of the momentous subsets of Artificial Intelligence. The phrase Machine Learning (ML) is self-explanatory meaning the machines that will learn on their own using their prior experience. The machines are not requisite to be programmed explicitly for learning new interactions. Today companies invest a great time and resource in mining the data of customers. As customer's data has concealed patterns and trends which are lucrative for the companies. Companies implement AI techniques onto the customer data to classify the potential clients for their products and services. In the proposed work, authors have implemented supervised machine learning algorithms i.e. Support Vector Machine (SVM), Random Forest, Logistic Regression, k-Nearest Neighbour on online customer shopping dataset for classifying whether the customer ended up purchasing the product or not. The authors have also made a critical comparison among the classification accuracies of these ML Algorithms. The paper brings to light that Random Forest performs better with the classification of categorical response variable.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130513836","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

Smart Grid - Meters and Communications - Design, Challlanges, Issues,Oppurtunities and Applications 智能电网-仪表和通信-设计，挑战，问题，机会和应用

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368903

V. Ganesh, S. Senthilmurugan, Ajay Krishna V.M, Ajit Ram R.R, A. Prabhu

{"title":"Smart Grid - Meters and Communications - Design, Challlanges, Issues,Oppurtunities and Applications","authors":"V. Ganesh, S. Senthilmurugan, Ajay Krishna V.M, Ajit Ram R.R, A. Prabhu","doi":"10.1109/ICADEE51157.2020.9368903","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368903","url":null,"abstract":"Our near-term strategy is strengthened by the complexity of regional threats such as climate change and stability of global power grids. The Indian economy is definitely one of the world's tallest economies. Increasingly, economic power networks have also grown exponentially with a significant increase in renewable energy installations. Given all this, the allocation of energy here isn't standardized. It poses several problems and finds a quicker and fresher way of addressing these issues. So, we will live an electrifying life everywhere in a remote section of our country, from a metro city, until then This paper is therefore a summary of the clean energy projects in our energy system and development in the introduction of smart grids. Any connectivity network is an important part of smart grid growth. Scalable and robust connectivity infrastructure is essential both for smart grid construction and operation. In this paper we discuss the context and inspiration of the smart grid networks communication infrastructure. As part of a complex smart grid network, we are addressing the problems for the communication infrastructure. Smart meters are fitted with electronic devices that secretly connect with utilities to save energy and ensure customers are using power properly. This cycle helps to reduce pollution from the commodity and waste electricity. This paper describes Smart Meter's architecture, obstacles, difficulties, chances and applications.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123170849","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

Reconfigure 5G sub 6 GHz and Wi-Fi bands Micro-strip Antenna using hybrid slotting and mix substrate material techniques 使用混合开槽和混合衬底材料技术重新配置5G sub - 6ghz和Wi-Fi频段微带天线

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368925

Nusrat Praween, S. Singh, Saima Khan

{"title":"Reconfigure 5G sub 6 GHz and Wi-Fi bands Micro-strip Antenna using hybrid slotting and mix substrate material techniques","authors":"Nusrat Praween, S. Singh, Saima Khan","doi":"10.1109/ICADEE51157.2020.9368925","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368925","url":null,"abstract":"In this paper Dual Band Multilayer Micro-strip antenna using LTCC (Low Temperature Ceramic co-efficient) and FR-4 materials for C-X- Band applications has been designed. The Proposed antenna is designed using two C type Slot inserted in top layer patch and five vertical slots design on middle patch. The properties of two materials LTCC and FR-4 substrates have been mixed to improve the radiation characteristics and return loss of design antenna from 4 to 6GHz. This antenna is used to improve the return loss and operating impedance bandwidth. The impedance bandwidth S11 • - 10dB achieves 34% of C-Band from 4.1 to 5.8 GHz and can be used in Wi-Fi bands and 5G sub 6 GHz. The Axial ratio bandwidth achieved • 1dB, so that design antenna included circular polarization characteristics from 4 to 6GHz. This proposed design provided return losses from - 10dB, to -52 dB. In this work has been simultaneously improved impedance bandwidth and axial ratio bandwidth. The linear and circular directivity has been improved simultaneously.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125717360","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

NON-CONTACT PULSE RATE MEASUREMENT USING FACIAL VIDEOS 使用面部视频进行非接触式脉搏率测量

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368944

Ruba M, V. Jeyakumar, Gurucharan Marthi Krishna Kumar, Kousika V, V. S

{"title":"NON-CONTACT PULSE RATE MEASUREMENT USING FACIAL VIDEOS","authors":"Ruba M, V. Jeyakumar, Gurucharan Marthi Krishna Kumar, Kousika V, V. S","doi":"10.1109/ICADEE51157.2020.9368944","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368944","url":null,"abstract":"Pulse rate (PR) is one of the vital physiological parameters which indicates the physiological state of individuals thus proving to be an important parameter to be monitored. In the last decade, more emphasis is given to non-contact based systems that are low-cost and are easy to use. Despite these advancements, most of these systems are suitable for a lab environment in offline situations. This project presents an effective system for the estimation of a pulse rate from facial videos. A dataset of 160 videos with pulse rate has been introduced. The dataset is obtained from 20 subjects performing 4 activities in 2 lighting conditions. Each activity is captured by a smartphone camera placed on a tripod. This dataset with facial videos and pulse rate is trained on different Convolutional Neural Network (CNN) models to predict the pulse rate. Their performances were compared to obtain better results. Another method called Eulerian video magnification (EVM) was also implemented with the same dataset and the results were compared with the CNN results for better accuracy. This technology possesses a high potential in advancing personal health care and in the field of telemedicine. Additional improvements to the proposed system with regards to movement and illumination can prove to be useful in many real-time applications.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115830310","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

Automatic Vehicle Number Recognition System using Character Segmentation and Morphological algorithm 基于字符分割和形态学算法的车辆号码自动识别系统

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368901

N. Vijayalakshmi, S. Sindhu, S. Suriya

引用次数: 2

Comparison of Different Machine Learning Models for diabetes detection 不同机器学习模型在糖尿病检测中的比较

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368899

R. Katarya, Sajal Jain

{"title":"Comparison of Different Machine Learning Models for diabetes detection","authors":"R. Katarya, Sajal Jain","doi":"10.1109/ICADEE51157.2020.9368899","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368899","url":null,"abstract":"Diabetes metilus which is commonly known as diabetes is a major metabolic disorder which has a severe effect on a human being. Diabetes results in high blood sugar. In a human body, there is a hormone which is secreted by the pancreas called insulin which helps to move the glucose from the blood to the cells which are used for energy later. In diabetes, one's body doesn't produce insulin inadequate amount or is impotent to use insulin effectively. When diabetes is not treated properly the danger of heart attack, retinopathy or vision loss, skin conditions and some other disorders increases. There are more than a million people currently who are suffering from this disease. The detection of diabetes in early stages can help one to take appropriate measures. The rapid increase in the number of people suffering from diabetes is gaining everyone's attention. The subset of artificial intelligence is Machine learning(ML) in which the system learns from the experience without doing any explicit programming. In this research, we have applied the machine learning technique for the detection of patterns and risk factors in Pima Indian diabetes dataset using python data manipulation tool. For the categorization of the patient into diabetic or non-diabetic, we have applied six machine learning algorithms specifically support vector machine(SVM), k-nearest neighbour (KNN), Gradient boosting, Decision tree, Random forest and logistic regression.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128020687","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: 10

Gap Analysis of the Accuracy of Doctors versus Machine Learning Models for Pneumonia Detection from X-Rays 医生与机器学习模型对x射线肺炎检测准确性的差距分析

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/icadee51157.2020.9368913

A. Rao

{"title":"Gap Analysis of the Accuracy of Doctors versus Machine Learning Models for Pneumonia Detection from X-Rays","authors":"A. Rao","doi":"10.1109/icadee51157.2020.9368913","DOIUrl":"https://doi.org/10.1109/icadee51157.2020.9368913","url":null,"abstract":"Machine learning (ML) can help in analyzing xray images to assist human doctors. ML algorithms are not perfect and when a ML algorithm makes a diagnostic error, it is often unclear why - were the features genuinely confusing or was it a badly trained algorithm. In this work, we first compare the accuracy of four well-known ML algorithms (KNN, Decision Tree, Logistic Regression and Convolutional Neural network) to detect pneumonia from chest X-rays of pediatric patients. We show that an algorithm based on Convolutional Neural Networks (CNN) gave the best accuracy of 90.7%. We then present a small test set of the X-rays which were wrongly diagnosed by the CNN algorithm to a panel of 14 doctors to investigate why the algorithm may have failed. We analyze the gap between ML algorithms and real doctors. The panel of doctors was able to diagnose 37% of the images correctly, while it was confused on the remaining 63% of images. This shows that better ML algorithms and training methods can improve the accuracy up to 94%. For the truly confusing images, the doctors identified the following additional features that could be included to help in the diagnosis: Oxygen saturation level (SPO2), Age, Respiratory Rate, and Body Temperature.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130191601","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

Predicting Mental health disorders using Machine Learning for employees in technical and non-technical companies 利用机器学习预测技术和非技术公司员工的心理健康障碍

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368923

R. Katarya, S. Maan

引用次数: 10

Enhanced Performance of Solar PV Array-Based Machine Drives Using Zeta Converter 利用Zeta变换器提高太阳能光伏阵列驱动性能

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368937

T. Kumar, M. R. Nayak, R. krishna, K. P. Rao

{"title":"Enhanced Performance of Solar PV Array-Based Machine Drives Using Zeta Converter","authors":"T. Kumar, M. R. Nayak, R. krishna, K. P. Rao","doi":"10.1109/ICADEE51157.2020.9368937","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368937","url":null,"abstract":"Application of renewable energy fed machine drives in various applications curtails the plant energy demand in day to day life. This suggests the design of renewable energy-based machine drives for medium to high rated applications is inveterate. Concentration on socio-economic type machine drives such as BLDC motor drives fed through solar PV array offers an efficient performance of the operation. This paper presents the design and performance of solar PV array fed brushless DC motor drive using the Zeta converter control technique. The Zeta converter technique extort the highest energy from solar PV array to obtain the effective performance of the BLDC motor. This technique avoids the additional detecting sensors and reading the fundamental switching frequency instead of the high switching frequency of voltage source inverter (VSI). This results in reduced switching power losses. Also, the proposed zeta converter control technique allows smooth starting and speed control of the BLDC motor. The design of solar PV array fed through BLDC motor is performed using the MATLAB/Simulink and simulation results are presented.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123369149","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: 13

Role of Artificial Intelligence in fighting against COVID -19 人工智能在抗疫中的作用

2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE) Pub Date : 2020-12-10 DOI: 10.1109/ICADEE51157.2020.9368956

A. P. Nirmala, S. More

{"title":"Role of Artificial Intelligence in fighting against COVID -19","authors":"A. P. Nirmala, S. More","doi":"10.1109/ICADEE51157.2020.9368956","DOIUrl":"https://doi.org/10.1109/ICADEE51157.2020.9368956","url":null,"abstract":"In today's world, AI has been contributed in variety of ways in our daily lives with numerous successful stories. Even during the outbreak of the corona virus disease (COVID-19) pandemic, AI has played a vital role in fighting against it. In this paper, we have represented a survey of AI applications that has been used in order to fight against the corona virus pandemic. From Internet of Things (IoT), text mining, medical image processing, biology and medicine, data analytics, AI has always played the important role. Motivated by the modern technology and Artificial Intelligence applications in wide areas, this paper mainly focus on importance of controlling the spread of COVID-19 pandemic and finding the solutions to prevent the severe effects of this corona virus disease. By using the methods of deep learning and artificial intelligence, a number of domains like agriculture, medical, electronics, retail, healthcare, etc. has achieved better results and benefits. This paper firstly represents the literature review and then the various applications of AI in fighting against the COVID-19. It is expected that this paper provides the organization and researchers with new insights in how helpful the AI has been to improve the situation of COVID-19 and in further stopping the spread of COVID-19 outbreak.","PeriodicalId":202026,"journal":{"name":"2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123594488","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: 12