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2022 IEEE International Conference on Current Development in engineering and technology, CCET 2022

作者： Kanna, R. Kishore Devi, K. Yamuna Dhivy, A. Josephi Arocki Amutha, Priya. M Diana Gomalavalli, R. Ambikapathy, A. Vels Institute of Science Technology Advanced Studies Department of Biomedical Engineering Chennai India Srm Easwari Engineering College Department of Biomedical Engineering Chennai India Siddharth Institute of Engineering and Technology Department of Electronics and Communication Engineering Andhra Pradesh India Galgotias College of Engineering and Technology Department of Electrical and Electronics Engineering Uttar Pradesh India

ISBN: (纸本)9781665454155

The most difficult task in medicine is making a diagnosis of heart illness. Since the decision is dependent on a huge number of clinical and pathological information, the diagnosis of heart illness is challenging. This is such as resulted in a significant increase in interest among academics and medical professionals in accurate and efficient cardiac disease prediction. Since time is of the essence in cases of heart sickness, getting the appropriate diagnosis quickly is essential. Since heart disease is the leading cause of death globally, early detection of heart disease is crucial. With the proper case of training and testing, machine learning has recently emerged as one of the most advanced, trust worthy, and helpful technologies in the medical industry, offering the most assistance for sickness prediction. The main goal of this endeavor is to examine various heart disease prediction models and choose pertinent heart disease variables using a genetic approach. Genetically optimized prediction models outperform conventional prediction models in terms of performance. Analyzing heart disease using UCI datasets. The Cleveland database is the only one that ML researchers have used thus far. The patient's heart condition is indicated in the 'target' field. It is positioned in the target column and has an integer value between 0 (no presence) and 1 (presence). The goal is the dependent variable, while the other factors are the independent variables. © 2022 IEEE.

关键词： Heart

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Study of mechanical properties on Nano metal matrix Composites: Duralcan process

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Materials Today: Proceedings 2022年 62卷 1282-1287页

作者： Balajikrishnabharathi, A. Suyamburajan, Vijayananth Kaliappan, S. Patil, Pravin P Jayabalakrishnan, D. Sathya Prakash, M. Sivabalan, T. Department of Mechanical Engineering R.M.K. College of Engineering and Technology Tamil Nadu Chennai 601206 India Department of Mechanical engineering Vels Institute of Science Technology and Advanced Studies Tamil Nadu Chennai 600117 India Department of Mechanical Engineering Velammal Institute of Technology Tamil Nadu Chennai 601204 India Department of Mechanical Engineering Graphic Era Deemed to be University Uttarakhand 248002 India Department of Mechanical Engineering Chennai Institute of Technology Kundrathur Chennai 600069 India Department of Mechanical engineering Prathyusha Engineering College Tamil Nadu Chennai 602025 India Department of Mechanical Engineering Dr.M.G.R. Educational and Research Institute Maduravoyal Chennai 600095 India

Aluminium metal matrix nanocomposites with aluminium nanoparticles were created using the durolcan process. It is a stir casting process in which metals and ceramics are layered one on top of the other and composites are formed through heating and stirring. The nano Al2O3 was used in the composite in weight percentages of 1,1.5 and 2.5. The hardness and tensile strength of composite properties with and without heat treatment were investigated. According to the results of the tests, increasing the percentage of nanoparticles increases the hardness of the composite materials. © 2022

关键词： Hardness

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Nonlinear asymmetric thermomechanical buckling of shallow nanoscale arches having dissimilar end conditions embracing nonlocality and strain gradient size dependencies

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Defence technology 2025年 47卷 67-82页

作者： Sahmani, Saeid Kotrasova, Kamila Zareichian, Mona Sun, Jian Safaei, Babak Department of Civil Engineering School of Science and Technology The University of Georgia Tbilisi0171 Georgia Center for Advanced Materials and Structures School of Science and Technology The University of Georgia Tbilisi0171 Georgia Department of Mechanical Engineering College of Engineering 145 Anam-ro Seongbuk-gu Seoul 02841 Korea Republic of Department of Structural Mechanics Institute of Structural Engineering and Transportation Structures Faculty of Civil Engineering Technical University of Kosice Vysokoskolska 4 Kosice04200 Slovakia Yangzhou Polytechnic Institute Jiangsu Yangzhou225127 China Department of Mechanical Engineering Eastern Mediterranean University North Cyprus via Mersin 10 Famagusta Turkey UNESCO-UNISA Africa Chair in Nanosciences and Nanotechnology College of Graduate Studies University of South Africa Muckleneuk Ridge PO Box 392 Pretoria South Africa

The undercurrent research survey explores the roles of nonlocality and strain gradient size dependencies in nonlinear asymmetric buckling of shallow nanoscale arches having dissimilar end conditions through a numerical analysis. The arches, made from a functionally graded graphene nanofiller reinforced composite (FG-GNRC), are subjected to discretional radial concentrated loads along with converting of temperature. To account for the size dependencies, the exploration is carried out stemming from the nonlocal strain gradient theory (NSGT) in the sense of a quasi-2D parabolic shear flexible concept of curved beam. The material properties of the contemplated FG-GNRC sandwich are determined using the modified Halpin-Tsai micromechanics model. Subsequently, an extended isogeometric analysis (XIGA) is manipulated comprising insertion plus multiplication of knots to achieve the demanded lower continuity allocated to the integration between flexural and tangential reflexes. It is perceived that the both softening and stiffening concomitants assigned to the salient concentrated radial loads obtained by the developed NSGT-based XIGA diminish from the first upper limit to the second one, and then likewise from the first lower limit to the second one. Although, by becoming the upsurge in temperature higher, these softening and stiffening concomitants get more remarkable. © 2025 China Ordnance Society

关键词： Arches

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An Analysis on the Power Consumption of Nodes in Ad hoc IEEE 802.11 Networks 3

An Analysis on the Power Consumption of Nodes in Ad hoc IEEE...

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3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Moyeenudin, H.M. Narender, M. Mukunthan, M.A. Raman, Kanimozhi Balasubramanian, D. Vels Institute of Science Technology and Advanced Studies Tamilnadu Chennai600117 India Tkr College of Engineering &technology Hyderabad India School of Computing Veltech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Chennai600062 India Kcg College of Technology Department of Mathematics Karapakkam Chennai600 097 India Jaya Engineering College Tamilnadu Thiruninravur602024 India

ISBN: (纸本)9798350322842

This article analyzes the power consumption of nodes in ad hoc IEEE 802.11 networks. The main objective of this analysis is to discover theoretic restrictions for the gains obtained in node lifetime through different energy conservation techniques found in the literature. The evaluation of energy consumption considers the characteristics of the medium access method and the interaction of the nodes in the packet forwarding process. The basic idea is to regulate the lifetime of a node based on its average consumption. Consumption is estimated based on the amount of time the node remnants transmitting, receiving or idle. The potential gains obtained by different techniques for saving or balancing energy consumption are then analysed. It is shown that the flow balancing technique can achieve a maximum gain for the node lifetime between 11% and 30%, depending on the network configuration. © 2023 IEEE.

关键词： Electric power utilization

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Machine Learning Based Cooperative Spectrum Sensing Using Regression Methods

Machine Learning Based Cooperative Spectrum Sensing Using Re...

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Advancement in Electronics & Communication engineering (AECE), International Conference on

作者： Somula Lakshmikantha Reddy Meena M Electronics & Communication Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai India

New cooperative spectrum sensing (CSS), it encounters better spectrum efficiency, has come into existence as a new strategy. In this study, techniques based on machine learning (ML) work together with CSS to improve user understanding; this is only possible when ML algorithms predict channel states. Additionally, many popular regressions machine learning models such as linear regression, nonlinear regression, generalized linear model, regression tree, and support vector machine regression (SVM) ensembles are discussed along with statistical analysis. This article assumes that 20 main users have different power, controls the maximum power of 20 units, and fixes the threshold of 4 units for all four cases, and analyses the results. In this respect, we came to the conclusion that a best fit line should be used for obtaining characteristics such that linear regression could be used. To further enhance regression and achieve the best results, other changes were also employed.

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Design of AED Based Drone to Deliver the Medical Kit on an Emergency Basis 3

Design of AED Based Drone to Deliver the Medical Kit on an E...

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3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Nagarani, P. Ahmad, Mohd Wazih Shalini, R. Singh, Pavitar Parkash Cvr College of Engineering Department of Emerging Technologies Hyderabad India Shri Ram Murti Smarak College of Engineering and Technology Department of Computer Science and Engineering Bareilly India Vels Institute of Science Technology and Advanced Studies Department of Bca & It School of Computing Sciences Chennai India Lovely Professional University Department of Management Phagwara India

ISBN: (纸本)9798350330724

Access to reliable modes of transportation is essential. Postal delivery to multi-million-dollar freight transports, practically everything is linked to its connections. Wheeled motor vehicles and manned aeroplanes are now the only options for transporting medical supplies at times of urgent need, which may be expensive, time-consuming, and often impossible if the emergency site is far. Drones are a game-changer in the medical industry because they can transfer vital supplies like blood and medical equipment. Unfortunately, given the state of the art, the drone's battery life is a constraint that may slow down the delivery process. This article details the research into the mechanisms designed for drones to increase their battery life and efficiently deliver first aid supplies. The drone's system safely delivers and drops medical supplies, reducing the drone's takeoffs and landings. The primary goal of this research is to develop a device that can safely transport medical equipment to its destination and then carefully unload it there. Results showed the system could safely transport and deploy first aid supplies during flight and landing. © 2023 IEEE.

关键词： Drones

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Hybrid Cuk-Zeta Converter with Neuro Fuzzy Approach for EV Applications

Hybrid Cuk-Zeta Converter with Neuro Fuzzy Approach for EV A...

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International Conference on Smart Structures and Systems (ICSSS)

作者： Indirakumar. A N. Janaki Department of Electrical and Electronics Engineering Vels Institute of Science Technology & Advanced Studies Chennai India

The transportation sector is a key component of tackling global climate change, which facilitates sustainable development. An effective and environmentally friendly way to decarbonize the transportation industry is through electric vehicles (EVs). This paper proposes EV charging station, using hybrid converter technique along with Maximum Power Point Tracking (MPPT) approach. In this work charging of EV is accomplished by Photovoltaic (PV) system. The voltage from PV system is boosted with the support of Cuk-Zeta converter. Furthermore, Adaptive Neuro Fuzzy Inference System (ANFIS) based MPPT approach is established to control the converter along with maximum extraction of PV voltage. Finally, the voltage across DC link is transferred to EV battery from where, it is offered for Vehicles for charging. The exhaustive construction is examined and validated using MATLAB, proving that the proposed setup results in improved performance with 95.32% converter efficiency respectively.

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A Novel Spectrum Handoff Technique for Long Range Applications using Adaptive Beam Selection with Machine Learning Algorithms

A Novel Spectrum Handoff Technique for Long Range Applicatio...

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Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), International Conference on

作者： Patan Babjan V. Rajendran Department of Electronics and Communication Engineering VELS Institute of Science Technology and Advanced Studies Chennai India

A cognitive radio network is an intelligent system that can detect the presence of unused spectrum space without affecting the primary user. The CRN is responsible for managing the allocation of channels, which leads to the scarcity of spectrum. This issue should be addressed in order to ensure that the network can continue to provide long-term and profitable service to its users. The issue of spectrum handoff is considered a major issue that needs to be resolved in order to improve the efficiency of the network. One of the most common factors that can affect the network's performance is the power consumption and communication delay. This paper proposes a method that can detect the availability of channels during the handover. The accuracy and network latency of various ML algorithms are evaluated through resampling techniques. The Nave Bayes Classifier and KNN algorithms performed better than their benchmarks. For a total of 500 and 100 users, respectively, the networks experienced a network latency of 10.91 and 13.08 seconds.

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UGVs for Agri Spray with AI assisted Paddy Crop disease Identification 3

UGVs for Agri Spray with AI assisted Paddy Crop disease Iden...

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3rd International Conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Sujatha, K. Reddy, T. Kalpalatha Bhavani, N.P.G. Ponmagal, R.S. Srividhya, V. Janaki, N. EEE\ECE Department Dr. MGR Educational and Research Institute Chennai600095 India ECE Department Saveetha Institute of Medical Sciences Chennai India CSE Department SRM Institute of Science and Technology Kattankolathur India EEE Department Meenakshi College of Engineering Chennai India Vels Institute of Science Technology and Advanced Studies Chennai India

This research work involves data access and control of Unmanned Ground Vehicles (UGVs) which is designed for health monitoring of paddy crops as an exception from traditional monitoring system. The proposed scheme of autonomous navigation of drones is planned to be carried out as per the six milestones for disease detection and control in paddy crops. Drones serve as Unmanned Robotic Vehicles (URV) capable of performing desired tasks in unstructured, uncertain and potentially hostile environments and are remotely-operated without human intervention. URVs function completely as autonomous entities in diversified environments. Current UGVs adhere to different levels of automaticity. Typically the vehicle follows high level waypoints spaced for few hundred meters of distance to provide monitoring of agricultural fields and early detection of the various diseases that may occur in the paddy fields in a polyhouse. To increase the vehicle's abilities, tracking efficiency, obstacle avoidance, path planning or lead and follow up augmented control with Fuzzy Logic Controller (FLC) is incorporated. The distributed autonomous system for information gathering related to the paddy crops in polyhouse is enabled using different sensors, which is a data-intensive task. To increase the robustness of the system, fuzzy controllers are proposed to control the navigation of the proposed UGV in "All terrain conditions". They are needed to offer problem specific heuristic control knowledge for the Inference Engine Design which occurs due to imprecision and uncertainty of the sensor readings. It also requires low computation time which favours the polyhouse situations. The navigation of UGV and the FLC action will in turn depend on "All terrain traversability" and "dead zone" monitoring. The proposed UGV model is capable of measuring the parameters associated with the paddy crops inside a polyhouse. The various diseases in paddy crops are False Smut (FS), Sheath Blight (SB), Rice Blast (RB

关键词： Controllers

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Named Entity Recognition for Protecting Sensitive Data using Hybrid CNN

Named Entity Recognition for Protecting Sensitive Data using...

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International Conference on Smart Systems and Inventive technology (ICSSIT)

作者： Sheela Gowr. P Kumar. N Department of Computer science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

Named entity recognition is a natural language processing technique that effectively recognizes and categorizes named entities in a document. The named entity recognition helps to bring out dynamic information about a document or gather critical data to store in a database. Deep learning helps to develop over time, while NLP examines the structure and standards of language and produces an automated system that can discern meaning from text. Mining the essential entities in a text helps identify related data, which is vital when functioning with enormous datasets. The proposed system has a feature that can retrieve and identify sensitive data such as PAN numbers, bank account numbers, and Aadhar numbers from unstructured text data.. The proposed model is designed using Hybrid CNN and it attains 95% F1-Score, 97.5% precision, and 98.3% recall.

关键词： Deep learning Training Radio frequency Databases Data security Forestry Predictive models

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