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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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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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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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Selective peripheral nerve recordings from nerve cuff electrodes using convolutional neural networks

Selective peripheral nerve recordings from nerve cuff electr...

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作者： Koh, Ryan G. L. Balas, Michael Nachman, Adrian I. Zariffa, José Institute of Biomaterials and Biomedical Engineering University of Toronto TorontoONM5S 3G4 Canada KITE Toronto Rehabilitation Institute University Health Network TorontoONM5G 2A2 Canada Faculty of Health Sciences McMaster University HamiltonONL8S 4L8 Canada Edward S Rogers Sr Department of Electrical and Computer Engineering University of Toronto TorontoONM4G 3V9 Canada Department of Mathematics University of Toronto TorontoONM5S 2E4 Canada Rehabilitation Sciences Institute University of Toronto TorontoONM5G 1V7 Canada

Objective. Recording and stimulating from the peripheral nervous system are becoming important components in a new generation of bioelectronics systems. Although neurostimulation has seen a history of successful chronic applications in humans, peripheral nerve recording in humans chronically remains a challenge. Multi-contact nerve cuff electrode configurations have the potential to improve recording selectivity. We introduce the idea of using a convolutional neural network (CNN) to associate recordings of individual naturally evoked compound action potentials (CAPs) with neural pathways of interest, by exploiting the spatiotemporal patterns in multi-contact nerve cuff recordings. Approach. Nine Long-Evan rats were implanted with a 56-channel nerve cuff electrode on the sciatic nerve and afferent activity was selectively evoked in different fascicles (tibial, peroneal, sural) using mechanical stimuli. A recurrent neural network was then used to predict joint angles based on the predicted firing patterns from the CNN. Performance was measured based on the classification accuracy, F 1-score and the ability to track the ankle joint angle. Main results. Classification accuracy and F 1-score of the best CNN configuration were 0.808 ± 0.104 and 0.747 ± 0.114, respectively. The mean Pearson correlation coefficient between the manually measured ankle angle and the angle predicted from the estimated firing rate was 0.812 ± 0.177. Significance. The proposed method demonstrates that CAP-based classification can be achieved with high accuracy and can be used to track a physiological meaningful measure (e.g. joint angle). These results provide a promising direction for realizing more effective and intuitive neuroprosthetic systems. © 2020 IOP Publishing Ltd.

关键词： Recurrent neural networks

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An application of the frequency-based matrix converter used in a wind energy conversion system using a synchronous generator with synchronous variable-speed, pulse width modulation technique

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AIP Conference Proceedings 2022年第1期2519卷

作者： V. Senthil Nayagam E. Fantin Irudaya Raj A. Sasireka M. Kumarasamy S. K. Dinesh Kumar Ram Subbiah G. Pavithra 1Department of Electrical and Electronics Engineering College Sathyabama Institute of Science and Technology Tamilnadu India 2Department of Electrical and Electronics Engineering Dr. Sivanthi Aditanar College of Engineering Tamilnadu India 3Department of Mathematics PSNA College of Engineering and Technology Dindigul Tamilnadu India 4Department of Computer Science College of Engineering and Technology Wollega University Nekemte Ethopia 5Department of Mechanical Engineering Sri Sairam Engineering Chennai Tamilnadu India 6Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India 7Department of Electronics & Communication Engineering Dayananda Sagar College of Engineering (DSCE) Bangalore India

An alternative source is growing in popularity with increasing global energy use and perceivable environmental degradation everywhere in the universe. The growth of wind farms necessitates system stability analysis, which incorporates dynamical distributed generation models. Doubly fed induction machines are widely used in the context of turbines of power higher than 1MW. However, direct-drive wind turbines that use synchronous generator principles have gained significant market penetration. This investigation implements a synchronous generator model using a frequency-based matrix converter with the assistance of an SVPWM method, which measures stator as grid voltage/current and analyses total THD. Converting the fluctuating voltages to something like a stable value using a frequency-based method is done with a matrix converter.

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Design and development of mini electric bike

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AIP Conference Proceedings 2022年第1期2527卷

作者： Dhiyaneswaran Jaganathan Rajender Gogu Balakumar Subramanian Harikumar Pallathadka Nithya Sabtharishi 1Department of Mechanical Engineering Sri Krishna College of Engineering and Technology Coimbatore - 641008 Tamil Nadu India 2Department of EEE Kakatiya Institute of Technology and Science Warangal Telangana India 3Electrical and Computer Engineering Arba Minch University Arba Minch Ethiopia 4Manipur International University Imphal Manipur India 5Department of Information Technology P.S.N.A College of Engineering and Technology Dindigul Tamilnadu India

The Concept and idea behind our E-bike is that due to the increase in usage of automobiles in the world, in turn it increases global warming and heat in our world. On behalf of this, the Indian government took a mission that by 2030, the nation will be transformed to a 100 percent e-mobility country. To achieve this humongous mission, first we need to achieve the factors like customers acceptability and desirability and the major factor cost-efficiency. In 2021, 15.2 million units of engine-based bikes were sold in India and the previous year 21 million units were sold. So, these bike owners tend to use these bikes around 10 years from the purchase, this shatters India’s 2030 mission. To overcome this, we come up with an idea that if we can convert the conventional engine bikes to electric bikes then we can displace the engines into e-bikes, which can make stupendous improvement in e-mobility usage in our country. Our bike is totally built and designed using old bikes, which makes it cost efficient as well as it retains every grain feature of bikes.

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Efficient authenticated key establishment protocol for telecare medicine information systems

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AIP Conference Proceedings 2022年第1期2519卷

作者： Mahalakshmi R. Lokesh Kumar K. S. Ranjini S. Sindhu R. Udhayakumar 1Department of Mathematics School of Applied Sciences REVA University Bangalore Karnataka India 2Department of Analytics School of Computer Science and EngineeringVellore Institute of Technology Vellore -632014 Tamilnadu India 3Department of Computer Applications Dayanand Sagar college of Arts Science and Commerce Bangalore Karnataka India 4Department of Master of Computer Applications Cambridge Institute of Technology(VTU) Bengaluru India 5Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Vellore -632014 Tamilnadu India

Secure checked based three person affirmation plot for records trade telecare remedy facts structures permits two customers simply store their verifiers prepared from their certifiable thriller state in approval verifiers informational index. By then the confirmation professional can test the clients’ verifiers and help them to exchange electronic medical records or electronic prosperity statistics securely and favorably. In this work, we must suggested protocol based on SPSD.

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Deep learning enabled smart charging technology for electric vehicles

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AIP Conference Proceedings 2022年第1期2527卷

作者： T. Blesslin Sheeba C. Sharanya C. Nayanatara S. K. Indumathi K. Kalins G. Ignisha Rajathi 1Department of ECE R.M.K. Engineering College Chennai India 2Department of ECE Vels Institute of Science Technology and Advanced Studies Chennai India 3Department of EEE Sri Sairam Engineering College Chennai India 4Centre for Automation and Robotics Hindustan Institute of Technology and Science Chennai India 5Department of Science and Humanities Sri Krishna College of Engineering and Technology Coimbatore India 6Department of Computer Science and Business Systems Sri Krishna College of Engineering and Technology Coimbatore India

Reliability, efficiency, and cost-effectiveness of smart grids are enhanced with power demand softening by means of efficient load management in electric vehicles. In such initiatives, the involvement of EV users may reduce due to the lack of adaptable user-centric approaches. During the connection sessions, the EV charging time is determined using a deep learning algorithm-based smart charging strategy proposed in this paper. Here, the total energy cost of the vehicle is minimized by making charging decisions considering demand time series, pricing, environment, driving, and other auxiliary data. The memorization technique is used for the estimation of the optimal solution of the existing connection sessions in the initial stage. The deep learning models are trained with this existing data and optimal decisions to make suitable decisions in real-time scenarios where car usage or future energy price values are undetermined. A significant reduction in the charging cost is observed by training the neural network with the proposed model. The results obtained are compared to the optimal charging costs computed and are found to be closely similar.

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Variational autoencoder with CCA for audio-visual cross-modal retrieval

arXiv

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arXiv 2021年

作者： Zhang, Jiwei Yu, Yi Tang, Suhua Wu, Jianming Li, Wei Digital Content and Media Sciences Research Division National Institute of Informatics 2-1-2 Hitotsubashi Chiyoda-ku Tokyo101-8430 Japan Department of Computer and Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu-shi Tokyo182-8585 Japan KDDI Research Inc 2-1-15 Ohara Saitama Prefecture Fujimino356-8502 Japan School of Computer Science Fudan University 220 Handan Road Yangpu District Shanghai Shanghai356-8502 China

Cross-modal retrieval is to utilize one modality as a query to retrieve data from another modality, which has become a popular topic in information retrieval, machine learning, and database. How to effectively measure the similarity between different modality data is the major challenge of cross-modal retrieval. Although several reasearch works have calculated the correlation between different modality data via learning a common subspace representation, the encoder's ability to extract features from multi-modal information is not satisfactory. In this paper, we present a novel variational autoencoder (VAE) architecture for audiovisual cross-modal retrieval, by learning paired audio-visual correlation embedding and category correlation embedding as constraints to reinforce the mutuality of audio-visual information. On the one hand, audio encoder and visual encoder separately encode audio data and visual data into two different latent spaces. Further, two mutual latent spaces are respectively constructed by canonical correlation analysis (CCA). On the other hand, probabilistic modeling methods is used to deal with possible noise and missing information in the data. Additionally, in this way, the cross-modal discrepancy from intra-modal and inter-modal information are simultaneously eliminated in the joint embedding subspace. We conduct extensive experiments over two benchmark datasets. The experimental outcomes exhibit that the proposed architecture is effective in learning audio-visual correlation and is appreciably better than the existing cross-modal retrieval methods. © 2021, CC BY.

关键词： Signal encoding

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IoT based mobile app for continuous health monitoring of the person

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AIP Conference Proceedings 2023年第1期2690卷

作者： Indira Priyadarsini I. S. Chakrapani S. Manochitra B. Tejaswini S. Ramesh Kamal Alaskar 1Department of Botany SKR Govt. Degree College Nagari Andhra Pradesh-517590 India 2Department of Zoology PRR & VS Govt College Vidavalluru Nellore Andhra Pradesh-524318 India 3Department of Computer science & Information Technology Kalasalingam Academy of Research & Education Anand Nagar Krishnankoil-626126Tamil Nadu India 4Department of Information Science and Engineering East point college of engineering and Technology Avalahalli Bengaluru Karnataka 560049 India 5Department of Electronics and Communication Engineering St. Mother Theresa Engineering College Vagaikulam Mudivaithanenthal Post Thoothukudi District–628102 Tamil Nadu India 6Department of Computer Application Bharati Vidyapeeth (Deemed to be University) Institute of Management Kadamwadi Rd Laxminarayan Nagar Tarabai Park Kolhapur Maharashtra 416003India

In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in communicating with doctors and patients through the use of health monitoring equipment and lowering healthcare costs in the future years. The internet of things (IoT) is making the world a smarter and more efficient village by allowing a variety of sensors and smart gadgets to gather and analyse data for a variety of reasons. As a result of these smart things, the healthcare system is growing wiser. When basic health facilities lack comprehensive medical care infrastructure, emerging countries gain. However, there is currently no specialized architecture for smart health units that can allow for this gathering and transferring patient health information to headquarters hospitals where live patient assistance is offered. Here, a smart IoT-based healthcare system is proposed, which includes a smart medical kit linked to sensors and a server for frequent health tracking. This smart medical kit is associated with sensors to measure the health parameters like body temperature, blood pressure, and heart rate for the effective function of the body. The proposed idea can alert the patient and their relatives in case of any abnormalities in their health parameters and also get suggestions from the doctor without physical contact with the doctor.

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