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10th International Conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Madhumithaa, S. Masoodhu Banu, N.M. Jehosheba Margaret, M. Sarma, A. Padmanabha VelTech Rangarajan Dr Sagunthala R&D institute of science and Technology Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350350951

Age-related macular degeneration (AMd) and diabetic macular edema (dME) affect the macula of the retina for the person above 50 years. Accurate diagnosis of eye diseases in the initial stages prevents blindness. Manual detection needs the use of trained human experts. Hence, automated models are necessary. In this research paper, a novel approach for detecting retinal conditions is proposed. This involves the progress of three deep convolutional neural network (CNNs) models viz., AlexNet, resNet50, and InceptionV3. These models are trained to classify Optical Coherence Tomography (OCT) retina images into three macular diseases viz., Choroidal neovascularization (CNV), dME, drUSEN, and Normal. The publicly available Kermany dataset is apply to test the accuracy of each model. The outcomes show that the AlexNet model achieves an accuracy of 97.2% followed by the InceptionV3 model (95%) and the resNet50 model (79.8%). This finding can help the Ophthalmologists for easy and fast diagnosis to ensure quality eye care for individuals who are at the risk of vision loss. © 2024 IEEE.

关键词： Optical tomography

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Ultralow-Vertical-Current Magnetization Switching Effect in an All Van der Waals 2d Heterostructure

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Chinese Physics Letters 2025年第2期42卷 239-248页

作者： Hao Wu Li Yang Gaojie Zhang Wen Jin Jie Yu Bichen Xiao Ahmed Annas Wenfeng Zhang Haixin Chang Center for Joining and Electronic Packaging State Key Laboratory of Material Processing and Die&Mold TechnologySchool of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China Wuhan National High Magnetic Field Center and Institute for Quantum Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Shenzhen R&D Center of Huazhong University of Science and Technology Shenzhen 518000China

The manipulation of magnetization and spin polarization using electrical currents represents a fundamental breakthrough in *** has formed the foundation for data storage and next-generation computing ***-transfer torque(STT)and spin-orbit torque(SOT)have emerged as prominent mechanisms in current-driven magnetization ***,these approaches typically require critical current densities in the range of 10^(6) to 10^(9) A·cm^(-2),resulting in significant heat generation during data writing ***,we report the discovery of an ultralow-vertical-current magnetization switching effect in a van der Waals ferromagnetic/ferroelectric heterostructure based on the modulation of the critical magnetic field(H_(C))using small vertical currents,with a critical current density as low as 1.81A·cm^(-2) and an average effective field(H_(eff)/J_(C))as high as 150.3mT·A^(-1)·cm^(2).This unique magnetization switching effect with ultralow-critical-vertical-current densities typically six to nine orders of magnitude lower than those of the STT and SOT provides a new transformative and viable pathway for developing next-generation spintronic and quantum technologies.

关键词： magnetization critical typically

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Efficient Architectures of FIr Filters using distributed Arithmetic 3

Efficient Architectures of FIR Filters using Distributed Ari...

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3rd International Conference on Automation, Computing and renewable Systems, ICACrS 2024

作者： Kumar, G. Charan Shiyamala, S. Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology India

ISBN: (纸本)9798331532420

This research presents an overview of the Finite impulse response (FIr) filter architectures that utilize distributed arithmetic design (dAd). This paper reviews non-reconfigurable as well as reconfigurable FIr filter architectures using dA. General Multiply Accumulator (MAC) based FIr filter architectures require large chip area, consume more power and enforce a limitation on the order of filters. dAd technique is a bit serial operation which has high throughput processing capability, cost effective, area and power efficient. This paper presents different realizations of FIr filters using different dAd techniques namely LUT based dAd, LUT-Less dAd, shared LUT based dAd. This paper presents a comparative analysis of different dA based FIr filters and can form a basis for further work on dA based reconfigurable FIr filters. © 2024 IEEE.

关键词： FIr filters

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deep Cryogenic Temperature CMOS Circuit and System design for Quantum Computing Applications

EAI Endorsed Transactions on Energy Web

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EAI Endorsed Transactions on Energy Web 2024年 11卷 1-8页

作者： rubia, Jency J. Shibi, Sherin C. rosi, A. Lincy, Babitha r. Nithila, Ezhil E. Vel Tech Rangarajan Sagunthala R&D Institute of Science and Technology Avadi India SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Sri Eshwar College of Engineering Coimbatore India

Quantum computing is a fascinating and rapidly evolving field of technology that promises to revolutionize many areas of science, engineering, and society. The fundamental unit of quantum computing is the quantum bit that can exist in two or more states concurrently, as opposed to a classical bit that can only be either 0 or 1. Any subatomic element, including atoms, electrons, and photons, can be used to implement qubits. The chosen sub-atomic elements should have quantum mechanical properties. Most commonly, photons have been used to implement qubits. Qubits can be manipulated and read by applying external fields or pulses, such as lasers, magnets, or microwaves. Quantum computers are currently suffering from various complications such as size, operating temperature, coherence problems, entanglement, etc. The realization of quantum computing, a novel paradigm that uses quantum mechanical phenomena to do computations that are not possible with classical computers, is made possible, most crucially, by the need for a quantum processor and a quantum SOC. As a result, Cryo-CMOS technology can make it possible to integrate a Quantum system on a chip. Cryo-CMOS devices are electronic circuits that operate at cryogenic temperatures, usually below 77 K (−196 °C). Copyright © 2024 Jency rubia J et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

关键词： Integrated circuit design

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Innovative Smart Network Enabled Charging Station for Future Electric Vehicle

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Journal of The Institution of Engineers (India): Series B 2024年第1期105卷 147-156页

作者： Paramasivam, Alagumariyappan Vijayalakshmi, Sankaran Swamynathan, Kudiyarasan Mahalingam, N. Gughan, N.M. Department of Biomedical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Electrical Group Bharatiya Nabhikiya Vidyut Nigam Limited Tamilnadu Kalpakkam603102 India School of Mathematics University of Leeds Leeds United Kingdom

renewable energy has become a major resource in the twenty-first century due to the excess usage of oil. The world is being transitioned to develop technology which uses renewable energy as its core element. The common renewable energy includes solar, wind, wave, geothermal. As technology develops, the Electric Vehicle became a demanding factor in the automobile sector. Increase in Electric vehicle production leads to the creation of the charging station. In this paper, a charging station is designed by utilizing the solar energy as a primary source. The primary focus of the charging station is the dC–dC converter which extracts energy from the PV Array. Further, the charging station detects the vehicle using YOLO v3 model and charge its battery. Additionally, the battery energy information in the charging station can be shared between other charging stations. © 2023, The Institution of Engineers (India).

关键词： Electric vehicles

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Virtual Car Showroom 15

Virtual Car Showroom

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Malarvizhi, N. Karthikeyan, V. Kumar, Abhay raj, Nirmal Kumar, Abhishek VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of CSE Chennai India

ISBN: (纸本)9798331300579

A virtual showroom is a digital representation of a physical showroom or store, where customers can browse and interact with products in a virtual environment. This can include features such as product information, 360-degree views, and the ability to zoom in on products for closer inspection. The showroom will allow users to explore and interact with different car models in a 3d environment, providing a realistic and immersive experience. Some examples of companies that use virtual showrooms include BMW and ralph. The comfort of real-world experience at their fingertips without the need of travel. The virtual showroom will include interactive features that allow users to interact with the car models. This will require programming using C# scripting in Unity, including animations, physics simulations, and user input handling. The car models will also be programmed with interactive features, such as opening doors, adjusting seats, and turning on headlights. © Grenze Scientific Society, 2024.

关键词： Helmet mounted displays

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Heart disease Prediction and diagnostic Analysis 15

Heart Disease Prediction and Diagnostic Analysis

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Malarvizhi, N. Kumari, Sakshi Nayan, Kunal Jupudi, Vamsi Kalyan VelTech Rangarajan Dr. Sagunthala R&D Institue of Science and Technology Department of CSE Chennai India

ISBN: (纸本)9798331300579

A heart disease is a significant health concern worldwide and is responsible for a considerable number of deaths every year. Early detection of heart disease can significantly reduce the risk of morbidity and mortality associated with it. This has led to the development of various machine learning techniques for predicting and analyzing heart disease. This study investigates the pertinence of machine learning techniques to predict long term outcomes in heart disease patient. The study aims to evaluate the performance of different machine learning algorithms such as decision tree, KNN, and SVM for predicting the occurrence of heart disease in patients. The data used in this project is collected from Kaggle Platform. The performance of each algorithm is evaluated using metrics which is accuracy and the results of this study will provide valuable insights into the effectiveness of different Machine learning algorithms for heart disease prediction and analysis, which can be used for early detection and management of heart disease. Varieties of data points that could lead to heart disease are examined. The diagnostic analysis additionally demonstrates how some factors, like Age, Sex, Cholestrol, CP, restbps etc. used in data-sheet are likely to cause heart disease. Tableau has been used for data Visualization. django has been used as web framework. User have to enter required input value and then prediction analysis will result whether patient having heart disease or not. © Grenze Scientific Society, 2024.

关键词： Cardiology

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Improvement of mechanical properties and investigation of strengthening mechanisms on the Ti_(3)AlC_(2) ceramic with nanosized WC addition

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Journal of Advanced Ceramics 2024年第6期13卷 861-876页

作者： Yi Zhong Ying Liu Qinkai Jiang Na Jin Zifeng Lin Jinwen Ye School of Materials Science&Engineering Sichuan UniversityChengdu 610065China Yibin R&D Park Yibin Industrial Technology Research InstituteSichuan UniversityYibin 644005China

Ti_(3)AlC_(2) (TAC) has great potential for use as an ablation material in aerospace applications due to its great oxidation/ablation resistance, but its high-temperature strength and thermal shock resistance still have much room for simultaneous improvement under fast temperature variation conditions. Herein, we used Ti_(3)AlC_(2) and WC powders as raw materials and successfully fabricated textured (Ti,W)_(3)AlC_(2) ceramic with small amounts of TiC and Al_(2)O_(3), and room temperature mechanical properties such as flexural strength (1146±46.9 MPa), fracture toughness (11.78±0.44 MPa·m^(1/2)), and hardness (5.81±0.11 GPa) at 5 wt% WC addition were achieved. The high-temperature strength of the ceramic was significantly improved, and better thermal shock resistance from 298 to 1173 K was simultaneously acquired together with the regulation of the elastic modulus, thermal conductivity, and thermal expansion coefficient, providing (Ti,W)_(3)AlC_(2) with more possibilities for fast-temperature variation applications. Strengthening and toughening mechanisms were proposed. Scanning transmission electron microscopy high-angle annular dark-field imaging (STEM-HAddF) showed that W randomly replaced the Ti1 and Ti2 sites of Ti_(3)AlC_(2), providing a good reference for establishing crystal models, and further density functional theory (dFT) calculations based on these models indicated a higher fracture energy of (Ti,W)_(3)AlC_(2) along different crystal planes, providing superior resistance to transgranular fracture;a lower mismatch degree of (Ti,W)_(3)AlC_(2)/Al_(2)O_(3) resulted in stronger interface bonding, resulting in greater resistance to intergranular fracture as well as more balanced stress distributions at different interfaces.

关键词： mechanical properties solid solution MAX phase transmission electron microscopy(TEM) ceramic atomic structure

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Cyber Threat detection in UrLs using Machine Learning 15

Cyber Threat Detection in URLs using Machine Learning

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Malarvizhi, N. Krishna, C.H. Sai Kumar, J. Kranthi Kumar, P. Venkata Sai Department of CSE VelTech Rangarajan Dr. Sagunthala R&D Institue of Science and Technology Chennai India

ISBN: (纸本)9798331300579

In the modern digital era cyber-attacks are the major concern. The major mode of these cyber-attacks is in the form of the online threats that are embedded in the UrL's. The main reason for these attacks is to gain the information illegally. To overcome this problem, we have developed an interactive platform for the people where they can check their UrL's about whether they are safe to use or not. The main purpose of the proposed digital platform is to help the people in order to find the threats that are hidden inside the UrL's. The platform requires the UrL from the user as input and displays its nature whether it is good or bad. We have trained our system using Machine-Learning (ML) algorithms in order to study the input UrL and compares it with the previous patterns of threats that are used while training the algorithm. The ML algorithms that we used is Support Vector Machines (SVM). This paper outlines a precise approach to threat detection and ensuring cyber safety through an interactive digital platform. This facilitates to mitigate the cyber-attacks and develops a healthy cyber space. © Grenze Scientific Society, 2024.

关键词： Cyber attacks

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Predictive Finance decision Support System using Machine Learning 15

Predictive Finance Decision Support System using Machine Lea...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Malarvizhi, N. reddy, Y. Shiva Yasaswi, Y. Mohith Harshitha, K. Department of CSE VelTech Rangarajan Dr. Sagunthala R&D Institue of Science and Technology Chennai India

ISBN: (纸本)9798331300579

Predictive Finance decision Support System is a key task for banks. Although the banking system offers a wide range of things for sale, its credit system is its main source of revenue. due to the fact that the credit system can profit from the interest on the loans it credits. Banking system always need accurate modelling system for large number of issues. The loan approval prediction system helps in predicting whether the applicant is eligible for loan or not in no time. The main objective of this paper is to predict whether assigning the loan to particular person will be safe or not. Finding out to whom the loan may be issued which will be a safer alternative for the bank is a usual process because of the growth in the banking industry, many people are seeking for bank loans, but the bank has limited assets that it has to grant to limited people only. It's no more a tedious task by using known machine learning algorithms. The performance of system is evaluated using Kaggle datasets. In this work, we split the data into training and testing data set and the testing can be done by using decision Tree and Naive Bayes algorithms. These algorithms predicts whether the applicant is eligible for loan or not. The performance of system shows that decision Tree and Naive Bayes achieves an accuracy of 70.73% and 82.92%. When comparing the performance of the algorithms, the Naive Bayes algorithm has more accuracy than decision Tree algorithm. Using Naïve Bayes helps banking sector to predict easier for processing the loan. © Grenze Scientific Society, 2024.

关键词： Predictive analytics

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