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2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024

作者： Kavitha, P. Teja, K. Pavan rahul, S.G. Charan, K. Sri reddy, K. rama Krishna reddy, V. Sai Charan Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350360660

Traffic congestion significantly impedes emergency vehicle response times in urban areas. This research introduces an IoT-based traffic control system designed to alleviate this issue by using rFId technology and Arduino microcontrollers. The system detects emergency vehicles via rFId tags and dynamically adjusts traffic signals to provide an uninterrupted path. Implemented with rFId receivers and Arduino controllers, the system ensures real-time management of traffic signals. results from preliminary tests indicate a substantial reduction in transit times for emergency vehicles. This study demonstrates the potential of IoT-based solutions in improving urban traffic management, enhancing both public safety and emergency response efficiency. © 2024 IEEE.

关键词： Traffic congestion

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Application Of Some Topological Indices In Nover Topologized Graphs

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Neutrosophic Sets and Systems 2023年 55卷 451-470页

作者： Muthumari, G. devi, r. Narmada Department of Mathematics Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai India

In this paper Nover top Z1 and Z2 index and Nover top H − index, rd − index, GA − index, CON − index are investigated and some of the related theorems are *** indices are also calculated for some specific types of Nov... 详细信息

关键词： Topology

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Condition Monitoring of Greenhouse Farming for Controlled Environment 3

Condition Monitoring of Greenhouse Farming for Controlled En...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： rahul, S.G. rajkumar, r. Abburi, rudrakonda Sai Kumar reddy, B. Trivikram raja, C.H. Teja, K. Pavan Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350354171

This paper presents the design, development, and implementation of a scalable Condition Monitoring System for controlled-environment greenhouse farming. To continuously monitor key environmental elements influencing crop growth, the system interfaces an ESP32 microprocessor with various sensors that measure temperature, water level, humidity, light intensity, and methane. The developed system prioritizes the selection of sturdy hardware parts that are specially made to endure the various circumstances found in a greenhouse. To guarantee ideal growing circumstances for crops, the gathered data can be displayed in the live IoT Blynk portal and possibly examined using the threshold values that have been established. The proposed technology provides real-time insights and data visualization into the greenhouse environment to improve agricultural productivity, yield, and resource efficiency. This project aids in outperforming conventional greenhouse systems in economic aspects by providing automation and real-time data insights for ideal plant growth. In terms of sustainable agriculture, this is a paradigm change that encourages resource optimization, decreased environmental impact, and maybe higher agricultural yields. © 2024 IEEE.

关键词： Environmental monitoring

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routing Selection and routing Scheme for IoT Beyond 5G (B5G) Network Using dispersed Path Selection for Communication and Multi-Criteria

Routing Selection and Routing Scheme for IoT Beyond 5G (B5G)...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Edwin Samraj, r. Coumar, Oudaya Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331510022

The inconsistency of mobile nodes within the network makes single-pass communication unsatisfactory. Should a different course be followed, the communication system would be unable to manage the increased workload. Packet loss is unpredictable when mobile nodes have poor connectivity. In this network, path linkages are not monitored. One of the most exciting developments in B5G (beyond fifth generation) wireless networks is device-to-device (d2d) communication. In addition, communication expenditures are concentrated on obtaining effective packet forwarding. This is a result of the increased communication costs associated with the long-distance networks selected for packet transmission. Both packet loss and energy usage rise. In order to achieve the best minimal distance routing path, the suggested path selection communication (dPAC) approach is set up to use queue modifications, which manage the maintenance of packets and slots that are above their allotted limitations. The message keeps waiting in an effort to increase message broadcasting efficiency. In order to detect packet overload, the multipath interference detection method is set up to offer a link-based routing packet overload detection system. To solve these significant issues, an MBMQA (Mobility, Battery and Queue Length Multipath Awareness) routing strategy based on d2d communication is also available for IoT B5G networks. Comprehensive simulation findings at different device speeds show that MBLCr outperforms traditional methods in terms of energy efficiency, latency, packet transfer rate, throughput, and latency. © 2024 IEEE.

关键词： Packet loss

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detection and Classification of Bipolar disorder Syndrome using deep Learning 5

Detection and Classification of Bipolar Disorder Syndrome us...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Charaan, r.M. dilip Vimala Ithayan, J. Sankar, M. Chithambaramani, r. Sivaprakash, P. Marichamy, d. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala Institute of Science and Technology Department of Cse Chennai India Vel Tech Rangarajan Dr. Sagunthala Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798331504403

Neural networks that are inspired by the way a human brain is structured, are known as artificial neural networks represent a unique class of machine learning algorithms. These algorithms allow artificial neural networks to acquire from data, and make resolutions based on the outcome, just like humans do. Non-linear data models, which have a whole load of variables and inputs, can predict new patterns. Artificial neural networks are already leveraged in everything from medical diagnoses to speech recognition as well as the ever-growing field of machine translation. There are multiple processes involved in the deep learning methodology that the method suggests for classifying bipolar disease. First, clinical and demographic data such as the sample's age, gender, symptom severity, and medication history would be included in the dataset of bipolar disorder patient samples and control samples. The dataset would next undergo preprocessing to remove any outliers or missing values. In the meantime, standardization and normalization would be applied to the data to ensure that each variable is on a consistent scale. data scientists may also decide to use feature selection to determine which variables are most useful for overall optimization for classification goals. In this proposed system accuracy is better as compared to the remaining conventional models. This makes it easier for us to select the elements that are most crucial to making our part a real feature. The two models ANN are the final features. Findings demonstrate that deep learning models, like as artificial neural networks (ANNs), are effective in treating neuroinformatics illnesses since datasets are readily available. When it comes to public relations, moods, and the dataset, the deep learning model predicts the correct classes with more precision. A popular application of ANN involves approximating a random function, thereby providing an inexpensive way to get to various statistics characterizing its distrib

关键词： Contrastive Learning

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Experimental Tribological Investigation on EN39B in Aerospace Application 7

Experimental Tribological Investigation on EN39B in Aerospac...

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7th International Conference on Circuit Power and Computing technologies, ICCPCT 2024

作者： Subbiah Jeeva, G. darwin, J.d. Abhilash, V.M. Subin raj, M. Ferlin deva Shahila, d. Loyola Institute of Technology and Science TN Thovalai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of ECE Chennai India

ISBN: (纸本)9798350372816

In aerospace applications, it is imperative for materials to possess outstanding mechanical and tribological characteristics. The Aero Industry employs carburized steel of grade EN39B for manufacturing gears, particularly those utilized in transmission systems. These gears are thermal resistant, and while composites a recurrently used extensively in aeronautics due to their superior mechanical and tribological properties compared to alloys, there is an increasing interest in developing composites based on EN39B as the base matrix material. Therefore, understanding these properties is crucial. Our research aims to investigate the tribological properties of EN39B steel. Using a pin/ball on disc tribometer, we can determine the wear rate and coefficient of friction of carburized EN39B steel. Initially, the specimens will undergo testing for tribological properties under ambient conditions. Subsequently, the specimens will be reevaluated to discern tribological properties in relation to increased speed. The speed will be gradually raised to 1600 rpm, and the corresponding tribological properties will be assessed. © 2024 IEEE.

关键词： Aerospace industry

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IoT Based on Non-invasive Glucometer 7th

IoT Based on Non-invasive Glucometer

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7th International Conference on Smart Trends in Computing and Communications, SmartCom 2023

作者： Premalatha, P. Poonguzhali, E. rekha, r. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9789819908370

diabetes mellitus is named the most important developer source of any kind of major disease and if it’s not treated properly then the majority of it gives severe health-related issues and leads to death. This is considered one of the non-contagious diseases, and it occurs when the sugar level within the blood increases above an average value. Therefore, regular calculation of blood glucose levels could be the condition to take care of sugar patients. Existing techniques for the determination of blood glucose levels are invasive methods that carry small single-use needles that are directly pricked into a finger to collect blood samples out of the body so it's passed to the fresh test tube for further processing chemically to see the number of sugar molecules present there. However, tolerating and reducing the patient's pain and the use of strips of those techniques have led to the process of non-invasive techniques. The near-infrared LEd and photodetector determine the sugar and insulin concentration. The attentiveness of glycemia within the blood sample is estimated by the level of infrared emission in the blood. The total concentration level of sugar molecules is on the LCd in an appropriate unit. To start the process, insert the fingertip in between the NIr-LEd and NIr-Pd. The reflected signal is fetched by the NIr-Pd. The evaluation value obtained from it'll be filtered out and then amplified. The noise has been removed by FFT. The filtered signal and amplified to attach to an NPN transistor for getting the negative value and for early showing the evaluated value within the LCd. The signal has been connected to Arduino port A0. Finally, the output value is displayed on the LCd display. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Light emitting diodes

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Solving of assignment problem by Pythagorean octagonal neutrosophic fuzzy number

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International Journal of Information technology (Singapore) 2025年第2期17卷 1079-1085页

作者： Narmada devi, r. Sowmiya, S. Parthiban, Yamini Department of Mathematics Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology Vel Nagar Tamil Nadu Chennai 600062 India

The article introduces Pythagorean Octagonal Neutrosophic Fuzzy Numbers (PONFN) for addressing assignment problems amidst uncertainty. It employs diverse ranking procedures tailored for PONFNs, ensuring reliability and robustness. Through meticulous comparative analyses, the study demonstrates PONFNs’ flexibility in capturing real-world uncertainties and solving assignment problems practically. The framework’s stability is validated, enhancing credibility and applicability. Overall, the article advances understanding and application of PONFNs in decision-making contexts © Bharati Vidyapeeth's institute of Computer Applications and Management 2024.

关键词： Neutrosophic fuzzy set (NFS) Pythagorean fuzzy set (PFS) Pythagorean neutrosophic fuzzy set (PNFS) Pythagorean octagonal neutrosophic fuzzy number (PONFN)

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Alzheimer's disease recognition and detection using Machine Learning 5

Alzheimer's Disease Recognition and Detection using Machine ...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Bennet, M. Anto Jeyaraj, Josephine Pon Gloria Subha, K.J. Vidhya, Ch. Sri Yamini, K. Pasha, P. Laljan Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai Avadi600062 India

ISBN: (纸本)9798331504403

Alzheimer's disease is a neurological disorder marked by memory loss, diminished cognitive function, and difficulties with day-to-day activities. As the world's population ages, Alzheimer's disease has become a major public health concern. This review looks at what is now known about Alzheimer's disease, including its causes, diagnosis techniques, and therapies. Amyloid plaques and tau neurofibrillary tangles are examples of abnormal protein clumps that accumulate in Alzheimer's disease pathogenesis and cause synaptic dysfunction, neuronal death, and eventually cognitive impairment. Familial forms of Alzheimer's disease have been linked to genetic mutations, including those in the APP, PSEN1, and PSEN2 genes. © 2024 IEEE.

关键词： Machine learning

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Crop Yield Prediction: Leveraging Machine Learning for Sustainable Agriculture 2

Crop Yield Prediction: Leveraging Machine Learning for Susta...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Keerthi, K. Tejaswi, K. Shalini, S. Kishore Kumar, K. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Cse Chennai India

ISBN: (纸本)9798350368413

: Accurate crop yield prediction is essential for ensuring food security and optimizing agricultural practices. Traditional methods often rely on historical data and expert knowledge, which may not always be sufficient. This research explores the application of machine learning techniques to predict crop yield based on various factors such as soil properties, weather conditions, and crop management practices. By analyzing historical agricultural data, this research study aims to develop robust predictive models. The research utilizes random Forest, a abstract- powerful machine learning algorithm to extract patterns from the data and make accurate yield predictions. The results of this study can provide valuable insights to farmers, enabling them to make informed decisions about crop selection, resource allocation, and risk management. By integrating machine learning, this research contributes to the development of sustainable agriculture practices and improves food security. © 2024 IEEE.

关键词： Adversarial machine learning

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