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Designing and testing of renewable energy based electric vehicle with GSM technology

AIP Conference Proceedings 2023年第1期2690卷

作者： B. Senthil Kumaran J. P. Sridhar J. Kamalakannan K. V. Malini S. Monesh A. Venkata Narayana 1Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthaka R&D Institute of Science and Technology Avadi Chennai–600 062Tamil Nadu India 2Department of Electrical and Electronics Engineering SJB Institute of Technology Bangalore - 560060 Karnataka India 3Department of Mechanical Engineering GKM College of Engineering and Technology G.K.M. Nagar Perungalathur Chennai Tamil Nadu 600063 India 4Department Electrical and Electronics Engineering Sri Sairam College of Engineering Anekal Bangalore 562106 Karnataka India 5Department of Computer Science and Engineering Jerusalem College of Engineering Chennai 600100 India 6Department of Biotechnology Vignan’s Foundation for Science Technology & Research (Deemed to be University) Vadlamudi Guntur-522213 Andhra Pradesh India

The ability to drive a car is a significant step toward independence for individuals with impairments, however, the standard driving system placed in a car does not provide the functionality for the challenged driver to operate the vehicle. Hence, in this project, we focused on designing a prototype of a car that works with the help of renewable energy like solar for people who have disabilities related to their legs or arms. It will be very helpful for those people who have physical disabilities to drive from one place to another without counting on anybody. The research shows that the issues about sustainable mobility are gaining increasing attention both in public opinion and specialists because of the major impact of automotive systems on carbon Dioxide production, climate change (global warming), and fuel exhaustion. So, by using renewable energy such as solar energy as source power it helps pollution-free, sustainable, and causes no greenhouse gases which will save the environment in the future. Probably the best development in the clinical field that helped both the old and the impeded is the portability vehicle. The expense of the vehicle may not be reasonable for an average person. In this case, an endeavor is made to manufacture a Solar Electric vehicle for disabled people at an ideal cost that can be used easily. It ensures the physically challenged people to be comfortable in travel and life. As solar energy is the main source on which we are focusing nowadays, because of many reasons like pollution, cost of fuel and also due to unavailability of the fuels. In the future solar energy will be the major source. The features have made in this solar electric vehicle are intelligent ones and are very useful for physically disabled people who want to be independent. In addition to that, the GSM is attached to the vehicle for monitoring disabled people. If the vehicle got any damage or the people is in out of control or any other irregular activities are found

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Design of full state feedback controller for controlling depth of underwater robot

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AIP Conference Proceedings 2021年第1期2334卷

作者： Bashir Abdullahi Baba Parvaneh Esmaılı 1Department of Computer Science Sule Lamido University Kafin Hausa Jigawa State Nigeria 2Department of Electrical and Electronics Engineering Near East University North Cyprus Turkey

Underwater robots have the ability to go down the sea up to several meters of height without any fear of loss of human lives. These robots need autonomous control systems and guidance to carry out their tasks. One of the main objectives of any underwater robot is to reach a given depth under the water and also be able to maintain that depth throughout the operation period. In this paper a simple full state feedback controller was designed to control the underwater robot's depth, despite all the external forces and disturbances during a given mission.

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control design considering magnetic flux characteristic uncertainty for magnetic levitation system with magnetic flux and current feedback

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2019年第10期139卷 1159-1166页

作者： Urasaki, Shinpachiro Kobayashi, Yoshimitsu Kami, Yasushi Mitani, Yuichiroh Nobuyama, Eitaku Department of Electronic Control Engineering National Institute of Technology Gifu College 2236-2. Kamimakuwa. Motosu. Gifu 501-0495 Japan Department of Electrical and Computer Engineering National Institute of Technology Akashi College 679-3. Nishioka. Uozumi Akashi. Hyogo674-8501 Japan Department of Mechanical Engineering National Institute of Technology Numazu College 3600. Ooka. Numazu Shizuoka410-8501 Japan Department of Systems Innovation and Informatics Faculty of Computer Science and System Engineering Kyushu Institute of Technology 680-4.Kawazu. Iizuka Fukuoka820-8502 Japan

This paper describes control design considering magnetic flux characteristic uncertainty for magnetic levitation system with magnetic flux and current feedback. The position of the levitated object is calculated from the hall voltage and current of the electromagnet. We show the uncertainty for magnetic flux characteristic and design the stabilizing controller by proportional feedback with the hall voltage and current. Moreover, we tried to design servo controller by two-degree-of-freedom control by using a finite number of frequency response (FNFR) model including the uncertainty and confirmed the validity of the proposed method by experiment results. © 2019 The Institute of Eleclrical Engineers of Japan.

关键词： Frequency response

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ML-based intelligent management and prediction of heart disease

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AIP Conference Proceedings 2023年第1期2690卷

作者： Gnanaprakasam C. N. N. Arockia Rosy Vaishali Gajendra Shende N. B. Prakash P. V. Pramila S. Ramesh 1Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Chennai - 600 119 Tamil Nadu India 2Department of Information Technology R.M.D. Engineering College Kavaraipettai Thiruvallurdistrict Tamil Nadu 601206 India 3Department of Information Science and Engineering East Point College of Engineering and Technology Avalahalli Bengaluru Karnataka 560049 India 4Department of Electrical and Electronics Engineering National Engineering College K.R.Nagar Thoothukudi District Kovilpatti-628503 Tamil Nadu India 5Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamilnadu - 600077 India 6Department of Electronics and Communication Engineering St. Mother Theresa Engineering College Vagaikulam Thoothukudi Dist. – 628102 Tamil Nadu India

Heart disease or Coronary illness, leads to many kinds of disease and deaths beyond a couple of many years. Dataset cleaning is simply an incorporated method for tackling gigantic data in the health care space. This examination paper presents different traits identified with coronary illness and the model on-premise of administered learning calculations as K-closest neighbour (KNN) and Support Vector Machine. The results depict that the most elevated exactness score is accomplished with SVM. Utilizing a profound learning approach, 96.07 % exactness was gotten. computerized reasoning strategies have been generally utilized in clinical choice emotionally supportive networks for expectation and finding of different infections with great exactness. These characterizing strategies are extremely successful in planning clinical emotionally supportive networks because of their capacity to get covered up examples and connections in clinical information given by clinical experts. Perhaps the main utilization of such a system is in the analysis of heart sicknesses since it is one of the main sources of passings from one side of the planet to the other. A framework dependent on such danger variables would assist clinical experts with welling it would give patients an admonition about the plausible presence of coronary illness even before the patient visits an emergency clinic or goes for exorbitant clinical check-ups. Thus, this paper presents a procedure for the expectation of coronary illness utilizing significant danger factors with the assistance of various Classifying Algorithms. In this paper, the accuracy of ML Algorithms like SVM and K-Nearest Neighbour is been compared and the results are depicted.

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Design and development of digital e-library

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AIP Conference Proceedings 2021年第1期2387卷

作者： Vani Rajasekar Premalatha J. Sathya K. Janani Varthini R. Ishwarya S. 1Department of Computer Science Engineering Kongu Engineering College Perundurai-638060 Tamil Nadu India 2Department of Information Technology Kongu Engineering College Perundurai-638060 Tamil Nadu India 3Department of Computer Technology (UG) Kongu Engineering College Perundurai-638060 Tamil Nadu India

Digital libraries are platforms that allow users to access structured information in a knowledge-based repository of data and access. In the end, the availability of good content and easy accessibility and use will drive the production and growth of digital libraries. Significant advancements in IT and the rapid development of online data have generated an intense interest in tools to help users find desired data. This paper describes how, particularly in college libraries, a digital library can be built and enforced in an academic library. The specifications for hardware, software, processing and recovery technologies are addressed. An elegant user interface, combined with better browsing, insertion and reporting capabilities, functionality that anyone can access from anywhere. The library’s automatic update facility helps to get a clear idea of which books are accessed by the members, allows users to create a ’hard copy’ report. The Digital library system stores information such as name, address, ID number, date of birth of library members. The information of books such as book name, book number, topic to which it refers, author, edition, edition, year of publication, total number of publications, total number of books in the library can also be stored and accessed digitally.

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Risk and effective analysis of COVID-19 vaccine using mathematical models in the pandemic situation

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AIP Conference Proceedings 2022年第1期2516卷

作者： N. Balaji N. B. Sanjana E. P. Siva R. Lokesh A. J. Catherina 1Department of Mathematics College of Engineering SRM Institute of Science & Technology Kattankulathur 603 203 Chennai India 2Department of Computer science(software) College of Engineering SRM Institute of Science & Technology Kattankulathur 603 203 Chennai India 3College of Management SRM Institute of Science & Technology Kattankulathur 603 203 Chennai India

In the present situation COVID-19 global pandemic, an overall world got embrace with covid-19 virus. Moreover every country went under quarantine and firm mitigation measures by temporary shutdown in people crowded place like schools, restaurants, theatres and domestic and international transport facilities[1]. So government made these measures to be effective to support and compliance of public[2]. Advanced medical technology put up with new vaccines to control infection of virus. Vaccination is one of the most effective step to control the virus from affecting the entire population. This paper aims to explore the optimal effectiveness of Vaccination for novel COVID-19 non clinical approach. We need smart solutions and decisions to mitigate the coronavirus`s impact. We formulate the mathematical model to Analyse the vaccination effectiveness[3]. The objective function is designed to reduce both awareness of vaccination and effectiveness of vaccination using WHO data/ Indian dashboard data[4]. The degree of protection As a part we can analyse the risk factors of immunization using multivariate models using statistical analysis.

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Comparison of methods of prediction of compressive strength of concrete using multiple linear regression in microsoft excel and artificial neural networks in RStudio

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AIP Conference Proceedings 2021年第1期2358卷

作者： Mohammed Hussain G. Yedukondalu Y. Kamala Raju V. Kamakshi Prasad 1Department of Civil Engineering Gokaraju Rangaraju Institute of Engineering and Technology(GRIET) Hyderabad India 2Department of Computer Science and Enginering Vignan Institute of Technology and Science Hyderabad India 3Department of Computer Science and Engineering Jawaharlal Nehru Technological University Hyderabad(JNTUH) Hyderabad India

Compressive strength (CS) of concrete is a key quality factor that is being monitored continuously in all construction projects which use huge quantity of concrete throughout the world. Engineers need to be open minded with the attitude of lifelonglearning to upskill with the ever-evolving softwareand hardware technologies. Seven day and twenty-eight-day compressive strengths of concrete samples with varied amounts of cement, blast furnace slag, fly ash, water, super plasticizer, coarse aggregate, and fine aggregate are studied. Multiple Linear Regression (MLR) models are fitted for this data in Microsoft Excel. Artificial Neural Networks (ANNs) in RStudio are developed for this data. The performances of both methods are compared. This paper takes care of Goal 12 of United Nations Sustainable Development of ensuring sustainable consumption and production patterns as environmentally degrading materials (flyash and blast furnace slag) are used.

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Head shape variations based on a three-shell forward electroencephalographic spherical model

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AIP Conference Proceedings 2022年第1期2425卷

作者： A. Papargiri V. Kalantonis P. Vafeas M. Doschoris F. Kariotou G. Fragoyiannis 1Department of Electrical and Computer Engineering University of Patras 26504 Patras Greece 2Department of Chemical Engineering University of Patras 26504 Patras Greece 3Institute of Genetics and Biometry Leibniz Institute for Farm Animal Biology 18196 Dummerstorf Germany 4School of Science and Technology Hellenic Open University 26222 Patras Greece

The current research is focused on the study of the effect of head shape geometrical deformations to the solution of the forward electroencephalographic (EEG) problem and its sensitivity response. A novel and accurate analytical scheme has been developed by performing a perturbation analysis in the linear regime, where a homogenous three-shell spherical model, equipped with all the necessary mathematical tools, is introduced. The efficacy of the method is demonstrated by incorporating the numerical implementation of the obtained formulae in which both cases, with or without surface deviations, are presented and benchmarked. The suggested procedure provides us with a criterion, which recognizes whether surface perturbations will influence EEG recordings.

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Single-shot fringe projection profilometry based on deep learning and computer graphics

arXiv

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arXiv 2021年

作者： Wang, Fanzhou Wang, Chenxing Guan, Qingze School of Automation Southeast University 2# Sipailou Xuanwu Nanjing210096 China Key laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Computer Science University College London Gower St Bloomsbury LondonWC1E 6BT United Kingdom

Multiple works have applied deep learning to fringe projection profilometry (FPP) in recent years. However, to obtain a large amount of data from actual systems for training is still a tricky problem, and moreover, the network design and optimization still worth exploring. In this paper, we introduce computer graphics to build virtual FPP systems in order to generate the desired datasets conveniently and simply. The way of constructing a virtual FPP system is described in detail firstly, and then some key factors to set the virtual FPP system much close to the reality are analyzed. With the aim of accurately estimating the depth image from only one fringe image, we also design a new loss function to enhance the quality of the overall and detailed information restored. And two representative networks, U-Net and pix2pix, are compared in multiple aspects. The real experiments prove the good accuracy and generalization of the network trained by the data from our virtual systems and the designed loss, implying the potential of our method for applications. Copyright © 2021, The Authors. All rights reserved.

关键词： computer graphics

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Segmentation of breast cancer using fuzzy C means and classification by SVM based on LBP features

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AIP Conference Proceedings 2022年第1期2405卷

作者： M. Malathi P. Sinthia G. Aloy Anuja Mary M. Nalini Fareen Farzana Wahed 1Department of Electronics and Communication Rajalakshmi Institute of Technology Chennai 600 124 India 2Department of Biomedical Engineering Saveetha Engineering College Chennai 602105 India 3Department of Electronics and Communication Engineering Vel Tech RangarajanDrSagunthala R&D Institute of Science and Technology Chennai 600 062 India 4Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602105 India 5Department of Electronics and Communication Engineering Saveetha Engineering College Chennai 602105 India

Recent years many women are affected by breast cancer. Mammogram is one of the early breast cancer diagnosis techniques used to identify the abnormal regions of breast. The recommended research work uses Fuzzy C-means segmentation algorithm to locate the wound area of mammogram breast image. Further the features of abnormal regions were extracted using Local Binary pattern (LBP) techniques. The statistical features are Entropy, Mean, RMS (Root Mean Square), correlation helps to train the neural network. Finally SVM (Support Vector Machine) classifier is utilized to categorize the abnormal regions of mammogram images with the accuracy rates of 86%.

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