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Infection detection in older person using artificial intelligence

AIP Conference Proceedings 2022年第1期2393卷

作者： Shiek Saidhbi AhmedAdem Endris S. Deepajothi R. Juliana Pravin R. Kshirsagar Anand Mohan 1Department of computer science Samara university Ethiopia 2Department of computer science Samara university Ethiopia 3CSE Guru Nanak institute of technology Hyderabad-501506 Telangana India 4Deptartment of information technology Loyola ICAM college of engineering and technology Chennai India 5ECE AVN Institute Of Engineering And Technology Hyderabad India 6LN Mithila University Darbhanga Bihar India

Artificial intelligence is programmed to copy the cognitive functions of human beings. It introduces a paradigm shift to health care, enabled by the growing availability of health data and rapid developments in analytical technology. Pneumonia is a disease that affects life due to bacterial or viral infections of the lungs. It can be life-threatening if not made at the correct time, and it is therefore important to diagnose early pneumonia. It is also one of the most dangerous babies and children’s diseases, for people older than 65 and people with health conditions or poor immune systems. The paper introduces a distinctive approach between healthy and patient pneumonia and distinguishes them by presenting signals that help picture-based approaches for diagnostic diseases among viral pneumonia and bacterial pneumonia.

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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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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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Introducing a mobility on demand system beyond COVID-19: Evidences from users’ perspective

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AIP Conference Proceedings 2021年第1期2343卷

作者： Vincenza Torrisi Giuseppe Inturri Matteo Ignaccolo 1Department of Civil Engineering and Architecture University of Catania Via S.Sofia 64 Catania 95125 Italy 2Department of Electric Electronic and Computer Engineering University of Catania Via S. Sofia 64 Catania 95125 Italy

The rapidly increasing transport in the last decades, characterized by high motorization rate especially in urban areas, constitutes a relevant contemporary issue addressed by scholars, planners and policy-makers, aiming to promote sustainable mobility. Nowadays, the COVID-19 crisis has influencing transport behaviour with a massive blow to public transport (PT) due to the social distancing. In this context, solutions represented by Demand Responsive Transport (DRT) can play a fundamental role not only in weak demand areas but also where the use of PT is relevant, as on-demand shuttles allow for more physical distancing and are cost-effective for more frequent *** essential point of the proposed study to be highlighted is the design of a structured multi-layered survey to identify the core attributes and the fundamental variables connected to the acceptance and potential use of a DRT service. The case study of a Mediterranean University has been analyzed, which is considering the opportunity to implement a public on-demand transport system, in order to enhance the efficiency of the current traditional public transport service and to discourage the use of the private *** results of an in-depth investigation are presented, which will serve to explore transport demand preferences towards flexible mobility and to identify the characteristics of the DRT service to be implemented. This work also lays the basis for further research with the aim of investigating the key aspects connected to innovative shared mobility solutions and thus supporting policy-makers and public and private transport companies to face new mobility issues.

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Robust copyright protection scheme for digital images using DCT and compressed sensing techniques

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AIP Conference Proceedings 2022年第1期2393卷

作者： Geetamma Tummalapalli D. Yuvaraj S. Jaganathan V. K. Sheela 1ECE GMR Institute of Technology Rajam Andhra Pradesh India 2Department of Computer Science Cihan University-Duhok Kurdistan region Iraq 3Dept. of Electrical and Electronics Engineering Dr.N.G.P. Institute of Technology Coimbatore India 4IT Viswajyothi College of Engineering and Technology Muvattupuzha Ernakulam Kerala India

The objective of this paper is to implement the robust image watermarking based on compressed sensing technique for copyright protection. This paper proposes an assimilation of watermarking technique into compressed sensing systems. Digital image watermarked signal is created by embedding the definite copyright data in host image signal. Compressive sensing is a recently developed topic in the arena of data compression. It is also called as compressed sampling in which the signals follow the Nyquist-Shannon sampling theorem. In this paper the watermark is extracted under compressive sensing attack with different number of available image coefficients. This paper compares the values of watermarking with compressed sensing and watermarking without compressed sensing.

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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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Electric power supply of steel producing companies: Schematic design solutions to improve reliability of power grids

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AIP Conference Proceedings 2022年第1期2686卷

作者： Gennady P. Kornilov Ildar R. Abdulveleev Oxana S. Logunova Palvan I. Kalandarov Obid Tursunov Dilshod Kodirov Doniyor Abdurakhimov 1Department of Power Supply of Industrial Enterprises Nosov Mangnitogorsk State Technical University Magnitogorsk Russia 2Department of Computer Engineering and Programming Nosov Mangnitogorsk State Technical University Magnitogorsk Russia 3Department of Automation and Control of Technological Process and Production Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 100000 Tashkent Uzbekistan 4Department of Power Supply and Renewable Energy Sources Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 100000 Tashkent Uzbekistan 5Research Institute of Forestry 111104 Tashkent Uzbekistan 6Gulistan State University 120100 Gulistan Uzbekistan

This research is aimed at improving electric power supply reliability at major industrial plants by applying schematic design solutions. The authors analyzed the features of branch electric power distribution systems at a metallurgical plant; considered options of their revamping to improve reliability of electric power supply; carried out experimental research on splitting 110 kV meshed system at the integrated iron and steel works. When performing the research, mathematical simulation methods and full-scale experiment methods were used. Following the research, we proposed three options to revamp the power grid at the industrial plant applying schematic design solutions: Scheme A - separating substations, causing problems, in an individual block; Scheme B - separating independent 110 kV closed electric power grids; Scheme C – splitting the meshed system into two independent circuits. It is proved that the most efficient solution is Scheme C, which is characterized by a lower number of unscheduled downtimes of the facilities by mitigating the effects of faults in one of meshed systems on a continuous operation of shops powered from the neighboring grid; eliminated risks of simultaneous stops of all or the majority of metallurgical shops of the works during short circuits in 110 kV grids; and a considerable reduction in short circuit currents and active losses in 110 kV industrial grids. An aggregate benefit from the proposed measures aimed at revamping of the electrical grid of metallurgical units by applying schematic design solutions is over USD750,000/year.

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Leaf disease identification using machine learning models

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AIP Conference Proceedings 2022年第1期2519卷

作者： M. SivaramKrishnan A. R. Rajini K. Logu M. Kumarasamy S. Jayaprakash R. R. Rubia Gandhi M. Siva Ramkumar 1Department of EEE Karpagam College of engineering India 2Department of Electronics and Communication Engineering Sri Sairam Engineering College Chennai Tamilnadu India 3Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu India 4Department of Computer Science College of Engineering and Technology Wollega University Nekemte. Ethiopia 5School of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India 6Dept of EEE Sri Ramakrishnan Engineering College India 7Dept of EEE Karpagam Academy of Higher Education India

The field which encompasses predictive data analysis known as machine learning is quickly developing. Agricultural outcomes have been improved due to its suitability in automation, weather prediction, and share market applications. This article covers the latest on using machine learning to various fields in agriculture. The broad variety of machine learning methods applicable for said predictive modeling within important agricultural It is a great difficulty to be living in a densely populated nation, since one must meet the requirements of everyone. Agriculture ranks ahead of almost everything else when it comes to moving our nation forward. Machine learning makes the system adaptive to various environmental conditions by reducing human involvement. This article talks about the many algorithms for choosing the best for the application.

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Artificial intelligence based handwritten text recognition system

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AIP Conference Proceedings 2022年第1期2393卷

作者： B. Parvathi Sangeetha E. Kodhai M. Belsam Jeba Ananth R. Revathi Akkaraju Sailesh Chandra P. Vijayakumar 1Dept. of EEE AarupadaiVeedu Institute of Technology Chennai Tamilnadu India 2Department of CSE Sri ManakulaVinayagar Engineering College Pondicherry India. 3Department of Mechatronics engineering SRM Institute of Science and Technology Tamilnadu India 4Department of Computer Science Idhaya College of Arts and Science for Women Pondicherry India 5E-Cell Dhruva College of Management Hyderabad India 6School of Electronics Engineering Vellore Institute of Technology Chennai India.

Handwriting Detection is a computer's approach or ability to access and interpret understandable handwritten source inputs such as paper documents, touch screens, images, etc. Recognition of handwriting is characterized as the task of turning a language into its symbolic representation represented in its spatial form of graphical marks. The progress is base on artificial neural networks, which is an artificial intelligence area of study. To build a Handwriting character recognition system, similar techniques and methods are used. When the data is implemented and translated into digital form by an OCR (Optical Character Recognition) device, it can be edited, manipulated, and processed in a computer-understandable form. For extracting the characteristics of the handwritten alphabets, a method of feature extraction is implemented and then we use the data to train the artificial neural network. It contributes enormously to the development of an automation process and in various applications will enhance the interface between man and machine.

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User search keyword based image and video retrival

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AIP Conference Proceedings 2020年第1期2282卷

作者： K. Meenakshi S. Aruna 1Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India 2Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India

Retrieval of images and videos are based on user's keyword. Video ranking is based on the number of likes and the keyword entered. Then, it will be compared with the maximum matching keywords. A searching algorithm is used in order to rank the images. A search engine is created in which images are retrieved by the keyword entered and the images are ranked according to the keyword and description of an image. All keywords would be stored in the database so that any image could be retrieved. Next, videos are retrieved by the keyword and language, if language is mentioned. The videos are sorted in ascending order of likes.

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