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Simulation and implementation of a reconfigurable dual-function pixel

Optoelectronics Letters 2024年第8期20卷 454-459页

作者： Shaher dwik Gurusamy Sasikala Department of Electronics&Communication Engineering School of Electrical&CommunicationVel Tech Rangarajan Dr Sagunthala R&D Institute of Science and TechnologyChennai 600062India

This paper presents the simulation and implementation of a reconfigurable pixel that serves both data acquisition and energy harvesting *** main topic focuses on switching between the two operating modes of the photodiode:photoconductive and photovoltaic *** proposed model can be used to design novel optical sensors with energy harvesting capability,such as position sensitive device(PSd)and complementary metal oxide semiconductor(CMOS)image sensors,which can extend the battery lifetime of the whole optical ***,we can overcome power supply problems like wiring and changing batteries frequently,especially in hard-to-reach places like space(cube satellites)or even underwater wireless optical communication(UWOC).The proposed pixel architecture offers the advantage of a minimalistic design with only four ***,it does come with a drawback in the form of higher noise *** simulation was achieved using MATLAB,and the implementation was performed using the programmable system-on-chip(PSoC)*** results showed that the functionality of the dual-function pixel is correct,and the scheduling of both energy harvesting and signal sensing functions was successfully achieved.

关键词： implementation harvesting function

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Automated Breast Cancer diagnosis Using deep Learning CNN Models 2

Automated Breast Cancer Diagnosis Using Deep Learning CNN Mo...

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2nd IEEE International Conference on Emerging research in Computational science, ICErCS 2024

作者： Saravanan, G. Jeevanantham Prabin, S.M. Parthasarathy, r. VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Vellore India VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Design Chennai India

ISBN: (纸本)9798331534950

The study introduces a deep learning model, CCNN, developed to identify and classify eight types of breast cancer: normal adenosis, normal fibroadenoma, normal phyllodes tumor, normal tubular adenoma, malignant ductal carcinoma, malignant lobular carcinoma, malignant mucinous carcinoma, and malignant papillary carcinoma. This model was integrated with five pre-existing models - Xception, InceptionV3, VGG19, MobileNetV2, and resNet101 - all trained for image classification using the ImageNet database, to categorize breast cancer MrI images. The dataset, sourced from Kaggle's repository, was further augmented using the Generative Adversarial Network (GAN) technique. For 30 experiments carried out to evaluate the introduced model and the transfer learning of five and proposed CCNN models, the F1-score values accuracy yielded were respectively: 98.04%, 96.13%, 98.54%, 97.11%, 94.20% and 98.98%. This study emphasizes the importance of improving the accuracy of early breast cancer detection to enhance the survival rates of patients. © 2024 IEEE.

关键词： Generative adversarial networks

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CSPS- Cyber Security Physical System with a Gaming and defence Strategic Approach to detect the Malicious Attack for Vehicle to Everything Network

CSPS- Cyber Security Physical System with a Gaming and Defen...

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

作者： Sofia, r. Yazhinian, S. Sambathkumar, r. Saranya, r. Jeyakumar, M. Manakula Vinayagar Institute of Technology Department of Ece India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology India

ISBN: (纸本)9798331510022

Cyber is the word that relates to computer, network and virtual reality. And providing security for these types of system is called cyber security. And this paper discusses about cyber security physical system which is the integration of both hardware and software as there is a possibility of malicious attacks on hardware too because of intervention of IoT devices, where because of these malicious attacks can consume energy of the system or changes the commands for the malfunctioning and everything need to be tracked. The major difference between Cyber security and cyber security physical system is that cyber security is meant for restricting unauthorized access of electronic data and cyber physical security system aims in securing both data as well as IoT devices and other hardware devices from malicious attacks. Cyber security physical system (CSPS) together provides a network, Application, Infrastructure, and IoT security as well as surveillance, access control and testing. The proposed method finds the expected time of failure, malicious attacks on both hardware and software and based on the training. The CSPS system the system able to differentiate the normal command and the command from the attackers, so whenever the doubt arises the CSPS makes those command to wait and if it is secured the command will be executed with a delay or else it will be discarded which protects the system from any types of attackers. And also, the system aims in achieving the higher efficiency through a smaller number of IoTs devices, and also it aims to combinedly use gaming approach, defence strategy with a security supervisor approach to differentiate between the defender and attacker which proves its own efficiency. © 2024 IEEE.

关键词： Cyber attacks

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Virtual Instrumentation under Supervisory Control for Safe Water Level Monitoring 5

Virtual Instrumentation under Supervisory Control for Safe W...

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5th International Conference on Circuits, Control, Communication and Computing, I4C 2024

作者： Ezilarasan, M.r. Gnanaprakash, V. Sreelakshmy, r. Preethi, d. rajesh, G. rahul, S.G. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science Engineering Chennai India

ISBN: (纸本)9798331528539

Water supplies are essential to farming and agriculture productivity as well as to our standard of living. Traditional water supply and quality monitoring systems need a large workforce in addition to complicated infrastructure. Agriculture depends heavily on the ability to control the level of water of a water supply, such as a water tank, bore well, etc It is difficult to monitor water tanks in real time using traditional water distribution methods. We can adjust to the newest technology in order to remove the complexity and streamline the system. For the water level monitoring system, a PId Control scheme that is solely software-oriented is thus created using *** Internet of Things (IoT) concept is used for continuous monitoring. In addition to tracking usage and gathering data via Wi-Fi and LAN, the server also keeps an eye on how much water is wasted at each outlet due to overuse. An alert is mailed to the user to let them know when water usage exceeds a predetermined level. With the help of this, customers can utilise a laptop or mobile device with an internet connection to continuously monitor water levels To prevent hacking, it additionally offers verified user access to this system. The government and authorities may monitor and manage the water supply with the help of this suggested water level monitoring system, which also enables individuals, schools, hospitals, businesses, department stores, malls, and agricultural areas to keep track of how much water they waste. © 2024 IEEE.

关键词： Water tanks

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Early Prediction of Heart disease using Modified Optuna-CNN Model: Performance Analysis

IAENG International Journal of Computer Science

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IAENG International Journal of Computer science 2025年第2期52卷 464-473页

作者： r, Jeen retna Kumar J, Shajeena S, Saumiya P, Bini Palas M, Anushia r Stanley, Berakhah F Department of ECE Vel Tech Rangarajan Sagunthala R&D Institute of Science and Technology Chennai India Department of CSE SRM Institute of Science and Technology Tiruchirapalli India Department of ECE Chennai Institute of Technology Chennai India Department of ECE SRM Easwari Engineering College Chennai India Department of CSE DMI College of Engineering Chennai India

Heart disease is currently a major cause of death in the world. Primitive detection of heart disease is important for improving patient results and reducing the burden of cardiovascular disease on society. In recent years, deep CNN (convolutional neural networks) have shown promising results for detecting heart disease using patient parameters such as age, sex, blood pressure, cholesterol levels, BMI, and family history of heart disease. Also, choosing an appropriate hyperparameter is crucial for the success of model performance and obtaining optimum results. Optuna is a hyperparameter optimization algorithm that helps in finding the optimal set of hyperparameters. This paper presents a modified optuna-CNN model for early detection of heart disease by patient parameters. The procedure includes gathering information, preparing the data, choosing a suitable model, training the model, assessing its performance, and implementing it in a healthcare environment. The paper also discusses the potential benefits of using deep CNN for early detection of heart disease, including improved accuracy, sensitivity, and specificity, which can aid in early diagnosis and timely intervention. Overall, the application of deep convolutional neural networks (CNNs) to identify heart disease in its early stages based on patient characteristics is a hopeful field of study that could enhance patient results and minimize the consequences of heart disease on people and the community. © (2025), (International Association of Engineers). All rights reserved.

关键词： Convolutional neural networks

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Implementation of a Balancing Controller for A Humanoid robot driving Scooter 5

Implementation of a Balancing Controller for A Humanoid Robo...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Srinivasan, r. Kavitha, M. rajeev Kumar, M. Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385649

A two-wheel self-balancing robot is a technological advancement in robotics. during the last few years, research has gained momentum on self-balancing robots, two-wheel inverted pendulums. Without external control, a self-balancing robot would roll around the wheels' rotation axis and eventually fall. When the robot is driven in the right direction at the right speed, it will return to the right position. despite this, the robot is naturally unstable. robots tend to fall off their axis if their base or platform is unstable or unbalanced. The gyro chip provides the change in angle of the robot, so the PId controller can check the error in the angular position of the self-balancing robot's base. A microcontroller and sensor system are used to stabilize an unstable system based on such a control system. After the Kalman filter recognizes an error in the angle or speed, the Proportionality Integrative derivative (PId) calculates the error and sends the corrected signal to the robot. An open-source robotic 3d platform is used for the virtual demonstration of the paper (GAZEBO) and robotics Operated System (rOS) for the pre-build robotic packages. It can be used for a variety of purposes, including surveillance, transportation, and reducing accidents and traffic jams. © 2024 IEEE.

关键词： Kalman filters

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rEAL-TIME GLUCOSE MONITOrING SYSTEM ANd dIETArY rECOMMENdATIONS FOr dIABETES MELLITUS USING FOG COMPUTING

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Telecommunications and radio Engineering (English translation of Elektrosvyaz and radiotekhnika) 2025年第5期84卷 55-67页

作者： Sathish, N. Elangovan, d. Nagalakshmi, r. Suresh, G. Chitra, devi d. Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Information Technology Saveetha Engineering College Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India Department of Artificial Intelligence and Data Science Kings Engineering College Sriperumbudur India Department of Computer Science And Engineering S.A. Engineering College Chennai India

This systematic review gave special attention to diabetes and the advancements in food and nutrition needed to prevent or manage diabetes in all its forms. There are two main forms of diabetes mellitus: Type 1 (T1d) and Type 2 (T2d). The loss of beta cells brought on by an autoimmune reaction causes the pancreas to be unable to produce enough insulin, which leads to Type 1 diabetes. A deficiency of insulin could arise as the illness worsens. The most frequent cause is a combination of excessive body weight and inadequate exercise. Currently, 90–95% of patients have Type 2 diabetes mellitus (T2dM). Age-specific normal blood sugar ranges exist and knowing them is crucial for determining a target blood sugar level that is both healthy and appropriate. The main takeaway is that diet regimens ought to be tailored to the patient’s requirements and should account for their capacity for change. Carbohydrates are the nutrients that have the biggest impact on the rise in blood glucose. In this paper, we have proposed a novel method for glucose monitoring and diet recommendations for diabetic patients using fog computing. A paradigm known as fog computing makes use of the benefits that come from using both cloud and edge devices to support modern computing systems by offering high-quality services, cutting latency, facilitating mobility, supporting multi-tenancy, and many other features. © 2025 by Begell House, Inc.

关键词： Fog computing

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design and analysis of Quad-Element MIMO Antenna for Bio-Medical Applications 3

Design and analysis of Quad-Element MIMO Antenna for Bio-Med...

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3rd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Pappa, C. Kanmani rajesh Kumar, d. Kavitha, T. Murugan, C. Vel Tech Rangarajan Dr Sagnuthala R&d Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350369083

This article introduces an innovative four-port CPW MIMO antenna with a doughnut-shaped design tailored for dual-band usage. Covering frequencies ranging from 2.4 to 2.5 GHz and 4.4 to 5 GHz, boasting a notable 10 dB impedance bandwidth, the antenna is crafted on an Fr4 substrate measuring 55 mm x 55 mm x 1.6 mm. By strategically placing the antenna elements orthogonally to achieve isolation exceeding 20 dB, it significantly enhances various MIMO performance metrics including Envelope Correlation Coefficient (ECC), Total Active reflection Coefficient (TArC), Channel Capacity Loss (CCL), diversity Gain (dG), and Mean Effective Gain (MEG). Its versatility extends to diverse applications within Industrial, Scientific, and Medical (ISM) bands, as well as the emerging radio band 78 (n78) pertinent to biomedical and 5G applications. Furthermore, Specific Absorption rate (SAr) calculations confirm the antenna's effectiveness for biomedical purposes. © 2024 IEEE.

关键词： Medical applications

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Comparison of dL model for retinal diseases classification using OCT images 10

Comparison of DL model for retinal diseases classification u...

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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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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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