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International Conference on Edge Computing and Applications (ICECAA)

作者： Nimitha N Saroj Bala V Satheeswaran M Janani S. Selvanayaki S. Ramasami Electronics and Communication Engineering RMK College of Engineering and Technology Chennai Department of MCA Ajay Kumar Garg Engineering College Ghaziabad Department of ECE Nehru Institute of Technology Coimbatore Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore Department of AI & DS Saveetha Engineering College Chennai Department of Computer Science and Engineering Bannari Amman Institute of Technology

Sentiment analysis is a powerful tool that has been gaining popularity among businesses in recent years. It involves analyzing text, speech, or images to understand the emotions or opinions conveyed by them. This process can provide valuable insights into customer preferences, behavior, and satisfaction levels. By leveraging sentiment analysis, businesses can gather customer feedback on their products and services, which can help them identify areas for improvement and develop stronger customer relationships. Furthermore, sentiment analysis can also be used to support emotional marketing campaigns, allowing businesses to create more targeted and personalized messaging that resonates with their audience. For example, by analyzing social media posts and comments, businesses can gain a better understanding of how their brand is perceived and adjust their marketing strategies accordingly. One popular method for this is transfer learning, where pre-trained models are used to analyze new datasets. Deep learning algorithms, such as convolutional neural networks (CNNs), have been particularly successful in achieving accurate results in a variety of applications, including image sentiment analysis. However, analyzing emotions conveyed through images is a complex task, and there is still much room for improvement. The Inception-v3 technique is a notable development in this field, as it can easily identify key parts of the body, such as the face, which is essential for accurately detecting emotions. The results of this model were compared to those of various other machine learning approaches, and the suggested model showed superior accuracy levels of up to 99.5%. This research demonstrates the potential of using deep learning algorithms and transfer learning methods to improve image sentiment analysis. For example, in the field of Healthcare, image sentiment analysis can be used to detect emotional expressions of patients, which can be valuable for assessing their mental and e

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Assessing the Efficacy of Distributed Ledger Technology for Immutable Data Logging and Fraud Prevention in IoT Retail Applications

Assessing the Efficacy of Distributed Ledger Technology for ...

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Advances in Computing Research on Science engineering and Technology (ACROSET), International Conference on

作者： M. Ponnrajakumari V. Elanangai S.R. Ramprasad Vijaya Kumar Velpula L. Bhagyalakshmi Prabha A G Dept. of ECE Velammal Engineering College Chennai India Department of Electrical and Electronics Engineering St. Peter's Institute of Higher Education and Research. AVADI Chennai India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Dept of ECE MLR Institute of Technology Hyderabad India Dept. of ECE Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798350388800

ISBN: (纸本)9798350388817

This paper presents a comprehensive framework for assessing the efficacy of Distributed Ledger Technology (DLT) in IoT retail applications. The framework integrates five key algorithms: Data Validation Algorithm (DVA), Consensus Mechanism Algorithm (CMA), Fraud Detection Algorithm (FDA), Privacy-Preserving Algorithm (PPA), and Dynamic Smart Contract Algorithm (DSCA). Each algorithm addresses specific challenges, ensuring data integrity, achieving consensus, preventing fraud, preserving privacy, and enhancing smart contract adaptability. The ablation study evaluates the individual contributions of each algorithm, highlighting their significance in the overall framework. Comparative performance evaluations demonstrate the proposed framework's superiority, with higher scores across key parameters compared to existing assessment methods. The framework offers a robust solution for enhancing the security, integrity, and efficiency of DLT in IoT retail applications, addressing multifaceted challenges and requirements.

关键词： Data privacy Distributed ledger Heuristic algorithms Prevention and mitigation Smart contracts Key performance indicator Reliability engineering Particle measurements Fraud Internet of Things

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Enhancing Kidney Stone Detection in CT scans with Image Processing and the DCNN-RELM Model

Enhancing Kidney Stone Detection in CT scans with Image Proc...

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electronics and Renewable Systems (ICEARS), International Conference on

作者： Manjula Prabakaran Jesmin Zakaria S Kannan Santhiya P Rajasekar P M V Rathnamma Department of CSE- (Data Science) Madanapalle Institute of Technology & Science Andhra Pradesh India Department of Electronics & Communication Engineering (ECE) NSHM Knowledge Campus Durgapur West Bengal India Department of Computer Science and Engineering School of Engineering and Technology Dhanalakshmi Srinivasan University Trichy Tamilnadu India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India Department of CSE KLM College of Engineering for Women Kadapa Andhra Pradesh India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

CT of the urinary system, abdomen, and kidneys appears to improve kidney stone screening and identification. Segmentation and categorization are essential for kidney stone identification and management. This work developed a semi-automatic kidney stone detection system using geometric concepts and image processing. The main steps include model training, feature extraction, segmentation, embossing, and preprocessing. Preprocessing involves trimming the input image to remove unnecessary kidney regions to focus on critical CT scan locations. Relief embossing enhanced image details. Segmentation accurately classified veins and blood arteries to define kidney stone boundaries. CNN-RELM was our training model. Compared to CNN and ELM models, the recommended system performed better. Its 93.87% kidney stone detection and localization accuracy prove its reliability. The semi-automatic system's reliable kidney stone detection and segmentation method may improve clinical decision-making. Combining CNN-RELM modeling and enhanced image processing could lead to medical imaging applications.

关键词： Training Image segmentation Accuracy Three-dimensional displays Computed tomography Embossing Data preprocessing Reliability Kidney Biomedical imaging

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Nano Functionalized Antenna Based IoT Enabled Devices for Health Care Applications

Nano Functionalized Antenna Based IoT Enabled Devices for He...

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electronics, Communication and Signal Processing (ICECSP), International Conference on

作者： J.Janish Blessy B. Jaison M. Daniel Nareshkumar Department of Electronics and Communication Engineering Velammal Institute of Technology Surappet Tamil Nadu India Department of Computer Science Engineering R.M.K. Engineering College Chennai Tamil Nadu India Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350364590

ISBN: (纸本)9798350375381

Continuous glucose monitoring (CGM) is crucial in diabetes management, necessitating the development of advanced sensing technologies. This study proposes a novel approach utilizing nano functionalized antenna-based IoT-enabled devices for CGM applications. The proposed method harnesses the unique properties of graphene, including high electrical conductivity, large surface area, and biocompatibility, to enhance glucose sensing capabilities. Evaluation of graphene-based materials involves assessing their electrical conductivity, surface area, and biocompatibility using techniques such as four-point probe measurements, BET analysis, and biocompatibility assays. A comparison with existing CGM models highlights the advantages of the proposed method, including high sensitivity, biocompatibility, miniaturization, and integration with IoT platforms. Numerical ratings on various parameters provide a quantitative assessment of the proposed method's performance relative to existing models. Overall, the proposed nano functionalized antenna-based IoT-enabled devices offer a promising solution for accurate and reliable CGM, with potential implications for improving diabetes management and patient outcomes.

关键词： Sensitivity Biological system modeling Medical services Conductivity Nanoscale devices Glucose Diabetes Sensors Antennas Monitoring

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Retraction Note: Reinforcement learning-based model for the prevention of beam-forming vector attacks on massive MIMO system

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Optical and Quantum electronics 2024年第1期57卷 1-2页

作者： Paranthaman, R. Nithya Sonker, Abhishek Varalakshmi, S. Madiajagan, M. Sagar, K. V. Daya Malathi, M. Department of NWC School of Computing College of E&T SRM Institute of Science and Technology Kattankulathur India Department of Electrical Engineering Samrat Ashok Technological Institute (SATI) Vidisha India Department of ECE Bharath Institute of Higher Education and Research Chennai India School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur India Department of Physics Kongu Engineering College Perundurai India

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Study and development of dual core photonic crystal fiber for the employment of guided waves polarization modes

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Journal of Optical Communications 2024年第0期45卷 s1539-s1548页

作者： Zuhayer, Asif Reddy, Mittamidi Madhusudhan Anwer, Twana Mohammed Kak Ahammad, Shaik Hasane Hossain, Md. Amzad Rashed, Ahmed Nabih Zaki Mahrous, Lenna Department of Electronics & Telecommunication Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh Department of Civil Engineering Institute of Aeronautical Engineering Dundigal Hyderabad500043 India Department of Physics College of Education Salahaddin University-Erbil Kurdistan Region Erbil44002 Iraq Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Institute of Theoretical Electrical Engineering Faculty of Electrical Engineering and Information Technology Ruhr University Bochum Bochum44801 Germany Department of Electrical and Electronic Engineering Jashore University of Science and Technology Jashore7408 Bangladesh Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt Department of VLSI Microelectronics Institute of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Tamilnadu Chennai602105 India

The properties of PCF have been emerged as an interesting field of research for sensing and detection of wavelengths of different refractive indices. These properties indicate that if analyte is used or not in the core of the PCF that does not influence on the sensor sensitivity. By reshaping the airhole's size, wavelength sensitivity can be improved. The vast detection limit of refractive indices (RI) is taken 1.33-1.41. In addition, high amount of linearity is obtained at the limit of 1.33-1.42. After simulation, it is obtained that this work proposes high sensitivity of 4250 and 6200 nm/RIU for x and y polarization modes. Because of high sensing capability in the range of various frequencies, this PCF can be applicable for other simultaneous wavelength detection. This PCF also offers its eligibility on the field of biomedical technologies. © 2023 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Finite element method

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Innovative Techniques in the Construction of Very Large Scale Integration Circuits for Low-Power and High-Performance Circuits

Innovative Techniques in the Construction of Very Large Scal...

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Communications and Information Technologies (GCCIT), Global Conference on

作者： V. Saravanan G. Sasikala P. Gomathi D. Kirubakaran A. Rajalingam Jubert R. Pagunuran Department of Nano Electronics Materials and Sensors Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamilnadu India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Department of ECE V.S.B. Engineering College Department of Computer Science and Engineering R.M.K Engineering College Engineering Department College of Engineering and Technology University of Technology and Applied Sciences Shinas Sultanate of Oman

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

Portable electronic gadgets and high-performance computing systems have increased demand for low-power, high-performance integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to millions of transistors on a chip, is leading these efforts. This research investigates low-power, high-performance VLSI circuit construction methods. We start with VLSI design fundamentals and power management and performance optimization concerns. The constraints of traditional VLSI design methods in satisfying current electronics' strict requirements are examined. VLSI design methodology development and evaluation are the focus of this research. Advanced power optimization methods include MTCMOS, adaptive body biasing, and power gating. We also study clock tree improvement, signal integrity enhancement, and new materials and device topologies for high performance. In addition, we study how machine learning techniques automate and optimize circuit placement, routing, and timing in VLSI design. AI handles the complexity of current VLSI designs and finds optimal design parameters for minimal power and high performance. Scaling VLSI circuits to newer technology nodes raises process variance, leakage current, and thermal management difficulties, which the research tackles. These issues can be overcome with new ways to keep VLSI circuits scaling while preserving performance and power efficiency. Finally, case studies and experimental findings show that the offered methods work in real-world applications. These findings demonstrate significant power usage and performance benefits over typical VLSI design. In conclusion, our research advances VLSI technology by developing low-power, high-performance integrated circuits. The proposed VLSI design methods and solutions could lead to more efficient and powerful electronic systems.

关键词： Performance evaluation Design methodology Machine learning Very large scale integration Thermal management Routing Topology Timing Leakage currents Signal integrity

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Bipolar alternate mark inversion encoding (BAMI) scheme for performance signature of optical transceiver systems under thermal effects

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Journal of Optical Communications 2024年第0期45卷 s1511-s1524页

作者： Rashed, Ahmed Nabih Zaki Kumar, Manoharan Ranjith Pugazhenthi, Revathi Prabu, Ramachandran Thandaiah Ahammad, Shaik Hasane Hossain, Md. Amzad Electronics and Electrical Communications Engineering Department Menoufia University Faculty of Electronic Engineering Menouf32951 Egypt Department of Mathematics Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India Department of Computer Science and Engineering C. Abdul Hakeem College of Engineering and Technology Melvisharam Vellore India Department of ECE Saveetha School of Engineering SIMATS Chennai India Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Institute of Theoretical Electrical Engineering Faculty of Electrical Engineering and Information Technology Ruhr University Bochum Bochum44801 Germany Department of Electrical and Electronic Engineering Jashore University of Science and Technology Jashore7408 Bangladesh

This study has clarified the bipolar alternate mark inversion encoding scheme for performance signature of optical transceiver systems under thermal effects. The light power through optical fiber channel variations with spectral wavelength at various temperature variations are clarified. The total electrical power through PIN receiver at various temperature variations are demonstrated. The electrical power amplitude, max Q Factor and min BER through PIN receiver at different temperature variations are clarified in details. Electrical and optical signal per noise ratio with laser bias current at various ambient temperatures are demonstrated. The total optical/electrical power and maximum quality signal with laser bias current at various temperature variations. © 2023 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Single mode fibers

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Deep Learning-Based Approaches for Enhanced Image Compression in computer Vision Applications

Deep Learning-Based Approaches for Enhanced Image Compressio...

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Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Avinash Avinash Christian Rafael Quevedo Lezama Ramya Murugesan K Anitha C.R. Bharathi Abid Y Department of MBA St. Josephs College of Engineering Chennai India Department of Electrical and Electronics Engineer National University of San Marcos Lima Peru Department of Electronics and Communication Engineering Karpagam Academy of Higher Education Coimbatore India Department of ECE Saveetha Engineering College Thandalam Chennai India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of VLSI Microelectronics Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Image compression is required for many computer vision applications, but traditional methods like JPEG and PNG have trouble preserving image quality at high compression levels. The study suggests a deep learning-based method for efficiently compressing images while maintaining visual information, utilizing convolutional neural networks (CNNs). Preparing the dataset, choosing CNN architectures (such as autoencoders and GANs), training with loss functions like MSE, and assessing using PSNR and SSIM metrics are all part of the process. According to the results, the deep learning approach outperforms JPEG (18:1) and PNG (6:1) in terms of compression ratios for complicated textures, reaching up to 25:1. The deep learning approach's PSNR values are 35.2 dB, while its SSIM scores are 0.92 in contrast to JPEG's (0.87) and PNG's (0.84) values. The process preserves visual quality while offering increased storage and transmission efficiency.

关键词： Deep learning Training Measurement computer vision Visualization Image coding Computational modeling Transform coding Streaming media Convolutional neural networks

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Different modulation schemes for direct and external modulators based on various laser sources

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Journal of Optical Communications 2023年第s1期44卷 S697-S706页

作者： El-Hageen, Hazem M. Kuppusamy, P.G. Alatwi, Aadel M. Sivaram, M. Yasar, Z. Ahamed Rashed, Ahmed Nabih Zaki Department of ECE Sri Krishna College of Technology Coimbatore India Electrical Engineering Department Faculty o Engineering University of Tabuk Tabuk Saudi Arabia Egyptian Nuclear & Radiological Regulatory Authority Cairo Egypt Department of ECE Siddharth Institute of Engineering and Technology Puttur India Department of Computer Networking Lebanese French University Kurdistan Region Erbil Iraq Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt

Different types of laser source modulation techniques have been used in various applications depending on the objective. As optical systems extract the laws and the best solutions from experiments and simulations, the present study uses simulation software with different modulation types so the output signals can be compared. The modulators used are Mach-Zehnder, which is an external modulator, and electro-absorption modulator and laser rate equation modulator, which are direct modulators. All these types have an optical link multimode (MM) fiber with a photodiode in the receiver end that can be modeled. The input and output signals are analyzed using different types of modulations. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Photodiodes

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