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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Mishra, Ajit Kumar Sheril, S. Ranganayaki, S. Al-Attabi, Kassem Kaur, Jaspreet Akila, P.G. Ies College of Technology Department of Electrical & Electronics Engineering M.P. Bhopal India Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Sri Ramakrishna Engineering College Department of Mathematics Tamilnadu Coimbatore India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Jhanjeri Mohali140307 India Psna College Of Engineering And Technology Department of Ece Dindigul India

ISBN: (纸本)9798350390759

In this research study, the authors examine the use of the Ant Lion Optimizer (ALO) in building reliable communication models for the Underwater Wireless Sensor Networks (UWSNs). Citing some of the challenges unique to the UWSNs include high latencies, low bandwidth and constrained power. The ALO-based protocol proposed for implementation will support efficient selection of routing paths, utilization of energy resources and overall, network scalability, and robustness. Simulation results revealed that the ALO-based protocol has better performance compared to other methods by at least 15% in terms of routing energy, packet delivery, network lifetime, and latency. This research benefits the further advancement of UWSNs by suggesting the improvement of present technologies, and may be used in a number of underwater operations. © 2024 IEEE.

关键词： Energy efficiency

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Design and implementation of cost-effective flexible paper based Wi-Fi sensor for commercial applications

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Analog Integrated Circuits and Signal Processing 2025年第2期124卷 1-8页

作者： S, Nithya V, Sujatha K P, Rama Prabha V, Saravanan Department of ECE KPR Institute of Engineering and Technology Coimbatore India Department of Mathematics Vellore Institute of Technology Vellore India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Nano Electronics Materials and Sensors Saveetha School of Engineering Saveetha University Chennai India

In recent days, it has been mandatory to embed sensors in almost all electronic products to make the products as smart gadgets. RF systems play a key role in enhancing the sensing capability of those gadgets in easier and affordable way. RF sensors defined to be resonated at the designated frequency is considered accurate within the bandlimit. RF sensors manufactured are high in demand in sensing wi-fi signals, when moving in anonymous regions. The demand gives an idea of developing a flexible wi-fi sensor with microstrip-coplanar waveguide-microstrip configuration on a paper substrate, for affordable applications. The sensor utilizes band pass characteristics at 2.45 GHz band over a bandwidth of 320 MHz. The design of the proposed sensor utilizes 60.5 × 30 × 0.358 mm3 volume. The proposed chip-less passive prototype will be advantageous in many commercial applications and cheaper one if manufactured in bulk.

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Conventional arrayed waveguide grating (CAWG) devices for high stability and low insertion loss in near infrared wavelength band

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Journal of Optical Communications 2024年第0期45卷 s1549-s1563页

作者： Leon, Megalan Leo Samuel, Rosaline Ahammad, Shaik Hasane Meenakshisundaram, Ramkumar Prabhu Hossain, Md. Amzad Rashed, Ahmed Nabih Zaki Department of ECE Sathyabama Institute of Science and Technology Chennai India Department of ECE R.M.K. Engineering College Chennai India Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Department of ECE PERI Institute of Technology Chennai 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

This study has presented the different suggested compounds based (CAWG) like silicon dioxide (SiO2), lithium niobate (LiNbO3) and gallium aluminum arsenide (Ga(1-x)Al(x)As) taking into consideration their operating wavelength range, their operating temperature range, their physical properties, and also their ability to be used in the manufacture of optical devices. The optimum performance was given in case of using the following materials such as SiO2, LiNbO3 and Ga(1-x)Al(x)As materials, so these materials have been used as a proposed materials based CAWG devices, which have been investigated for high stability and low insertion loss in near infrared wavelength band. The comparison between these proposed materials are clarified through the design parameters of CAWG device such as the order of diffraction (m), path length adjacent waveguides difference (ΔL), focal length (L f ), free spectral range (FSR), max no. of I/O wavelength channels (N max), and arrayed waveguides (P) number. © 2023 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Silica

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CLASSIFICATION OF LAND PATTERNS FROM INDIAN PINES DATASET USING RESCNN

CLASSIFICATION OF LAND PATTERNS FROM INDIAN PINES DATASET US...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Gnanasekaran, T. Jaya Rama Krishnaiah, V.V. Shaik, Nazeer Preethi, S. Department of Electronics and Instrumentation Engineering R.M.K. Engineering College RSM Nagar Tamilnadu Kavaraipettai India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur AP Vaddeswaram India Andhra Pradesh Anantapur India Department of ECE Dr. N.G.P Institute of Technology Tamil Nadu Coimbatore India

ISBN: (纸本)9798350305708

By utilising ResCNN, we were able to successfully classify the topographic attributes that were contained inside the Indian Pines dataset. The research also demonstrated how difficult it is to design the optimal configuration for a CNN, and it offered some recommendations for the parameter settings based on the findings of a grid search experiment. The recommendations were based on the findings of the experiment. The effect of patch sizes retrieved from images, the requirement of performing data augmentation, and the utilisation of regularisation techniques such as dropout and batch normalisation to avoid overfitting issues were also investigated in relation to the performance of the network. This was done to better understand how each of these factors affects the overall performance of the network. The primary finding of this work, which is that the convolutional neural network performed very well on minority classes in comparison to other approaches, is of the utmost importance. © 2023 IEEE.

关键词： Classification HSI Land Pattern Remote Sensing

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An Effective Customer Segmentation Approach to Improve E-Commerce Platform Quality Based on Intensive Learning Methodology

An Effective Customer Segmentation Approach to Improve E-Com...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Suresh, G.R. Vinoparkavi, D. Govindasamy, Suresh Rohini, S. Giri, Jayant Sabri, M. Omar Dhanalakshmi Srinivasan College of Engineering and Technology Department of Ece Mamallapuram Chennai India Nandha Engineering College Department of Cse Erode India Sona College of Technology Department of Electrical and Electronics Engineering Salem India R.M.K Engineering College Department of Computer Science Engineering Kavaraipettai Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University Faculty of Economic Department of Business Information Technology Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

To accomplish company goals and reap advantages while satisfying and meeting consumer expectations, segmentation is an essential facilitator. Identifying subgroups of the target market that share common traits, requirements, and priorities is customer segmentation's primary goal. Various dataset dimensionalities are also considered, as are changes across time. In this study, we use time-based segmentation and clustering approaches to the e-commerce industry to conduct predictive neural network analysis using factors such as product reviews, goods, buying trend, watching pattern, and more. In this research, Intensive Neural Classification Learning (INCL) is presented as a novel deep learning technique. To assess its efficacy, it is cross-validated with the traditional Neural Network (NN) learning algorithm. We have evaluated unigrams, bigrams, and trigrams as part of the feature extraction process and identified the unique brands per consumer. In addition, the customer's chosen brands may be determined using a neural network, and the projected data can then be utilized for statistical analysis. We all know that sentiment analysis and categorization are huge help when trying to guess how customers feel about certain companies and items. Lastly, using the provided set of input data, we will choose the top brands by assessing the accuracy of the forecasts. © 2024 IEEE.

关键词： Sales

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Hybrid Optimization Based Long Short-Term Memory for Android Malware Detection

Hybrid Optimization Based Long Short-Term Memory for Android...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Lande, Jayapal Maheswari, M. Kamali, S.M. Dineshkumar, R. Priyanka, M.S. Sr University School of Computer Science & Artificial Intelligence Warangal India Srm Institue of Science and Technology School of Computing Department of Computational Intelligence Chennai India Annapoorana Engineering College Department of Electrical and Electronics Engineering Salem India Saveetha School of Engineering Department of Ece Sriperumbudur Thandalam India Nitte Meenakshi Institute of Technology Department of Ai and Ml Yelahanka Bengaluru India

ISBN: (纸本)9798350313413

Malware detection is process of detecting the suspicious files and activities, that can classify as benign and malicious depends on different characters like capability of infection, structure of malware and speed rate. In this paper, proposed a Particle Swarm Optimization and Ant Colony Optimization (HPSALO) based Long Short-Term Memory (LSTM) model for malware detection and classification. The combination of these two algorithms that leads to the balance between exploration and exploitation. The dataset utilized for the research is DREBIN dataset and process of data cleaning is performed by NumPy library. The feature selection is performed by combination of hybrid PSALO algorithms and selected features are given to Long Short-Term Memory (LSTM) classifier that classifies as benign and malware files. The performance of proposed method is estimated by performance metrics of accuracy, precision, recall and f1-score. The proposed method attained accuracy of 99.38%, precision of 99.30%, recall of 99.08% and f1-score of 99.42% which is comparatively higher than other existing methods like Whale Optimization Algorithm-LSTM (WOA-LSTM), Cat Swarm Optimization-LSTM (CSO-LSTM), Particle Swarm Optimization-LSTM and Ant Lion Optimization-LSTM. © 2023 IEEE.

关键词： Ant Lion Optimization Long Short-Term Memory Malware Detection NumPy and Particle Swarm Optimization

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Nano-scaled transistor reliability characterization at nano-second regime

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Science China(Information Sciences) 2021年第10期64卷 272-274页

作者： Ran CHENG Ying SUN Yiming QU Wei LIU Fanyu LIU Jianfeng GAO Nuo XU Bing CHEN School of Micro-Nano Electronics Zhejiang University College of Electronic Engineering and Information Science Zhejiang University Institute of Microelectronics Chinese Academy of Sciences Department of Electrical Engineering and Computer Sciences University of California

Dear editor,In recent years, novel MOSFET structures such as fullydepleted silicon-on-insulator(FDSOI) MOSFET and FinFET are adopted by the industry for their excellent electrostatic behavior and higher on-state current per ***, these novel structured transistors suffer from severe self-heating effects(SHE) owing to the more heat generation but lower thermal conductivity of the ultrathin Si channel [1].

关键词： FDSOI Self-heating effect Reliability PRBS Vth shift

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Enhancing Segmentation of Abdominal Aortic Aneurysms in CT Images

Enhancing Segmentation of Abdominal Aortic Aneurysms in CT I...

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2023 International Conference on Data Science and Network Security, ICDSNS 2023

作者： Saleem Javeed, Abdul Veeresh, K.M. Ganesh, V.N. Lavanya, Chunduri Parameshachari, B.D. Gst Gitam University Bengaluru Campus Dept. of Cse Bengaluru India Sjbit Dept. of Cse Bengaluru India Mangalore Institute of Technology and Engineering Department of Ece Moodabidri India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaadeswaram India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350301595

This study concentrates on a potential strategy for improving Abdominal aortic aneurysms (AAAs) segmentation in CT imaging. The study's dataset included 19 CT images of healthy AAAs acquired from different patients. Ground-truth segmentations that matched the training data were also included. For enhanced accuracy while segmenting AAA, the suggested technique integrates pre-processing, deep learning segmentation, and post-processing into a cohesive workflow. Convolutional neural networks (CNNs) are trained for deep learning segmentation using a U-Net architecture, and noise in input pictures is removed during pre-processing. This differs from the conventional habit of employing linear regression for image segmentation. The results were measured using the dice similarity coefficient, sensitivity, specificity, accuracy, recall, and F1 score. With a DSC of 0.81, sensitivity of 0.89, specificity of 0.97, accuracy of 0.86, recall of 0.89, and F1 score of 0.86, the suggested approach was proven to be successful in segmenting AAAs in CT images. The technique has shown potential in clinical settings for improving AAA diagnosis and treatment planning. © 2023 IEEE.

关键词： Image segmentation

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NFC Implementation Methods for ESP32 Based IoT Systems

NFC Implementation Methods for ESP32 Based IoT Systems

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International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Nikola Mitrović Antonio Pousibet-Garrido Sandra Veljković Isidoro Ruiz-Garcia Danijel Danković Alberto J. Palma Goran Ristić Miguel A. Carvajal Department of Microelectronics Faculty of Electronic Engineering University of Niš Serbia Department of Electronics and Computer Technology University of Granada Spain

This paper presents research on methods for implementation of NFC technology into ESP32 based IoT systems. Two main methods are proposed, first with the commercial modules that incorporate built-in antenna and module that is universal transceiver and decoder, and second method, where all of the integral parts of the system are designed separately. Methods are analyzed and compared in terms of feasibility, speed, resources and cost, using specially developed tests. Tests consist of multiple writing and reading tasks from the NFC tag, ESP32 and the smartphone. Tests also examine the compatibility with the ESP32 for IoT applications and with NFC enabled smartphones. Results point out that first implementation method offers higher performance rate in terms of the most of criteria, while the second method gives broader versatility and wider compatibility range.

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A Smart and Systematic Vehicle Headlight Operations Controlling System based on Light Dependent Resistor 2

A Smart and Systematic Vehicle Headlight Operations Controll...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and electronics, ICIITCEE 2024

作者： Sumithra, J. Sumalatha, A. Vanitha, A. Sivadharshini, B. Pandi, V. Samuthira Ravi, S. Rmd Engineering College Department of Ece Tamil Nadu Chennai India Kristu Jayanti College Department of Computer Science Bengaluru India Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Biomedical Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Tamil Nadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Simats Saveetha School of Engineering Department of Vlsi Microelectronics Tamil Nadu Chennai India

ISBN: (纸本)9798350306415

A knowledgeable management system based on a single integrated device is developed for the automobile lighting system in order to enhance the smart operation of vehicle headlamps and increase the security and dependability of vehicle driving in a wide range of weather conditions, particularly with dust, fog, and haze. When driving at night, the vast majority of drivers turn on their brightest beam. The inconvenience this provides to the individual coming from the opposite route is obvious. To prevent such occurrences, two vehicles are needed to demonstrate the proposed system, which uses a Light Dependent Resistor (LDR) sensor and related communication to help drivers avoid collisions by adjusting their high beams in response to oncoming traffic. To prevent this glare, engineers devised a prototype automated headlamp intensity adjustment system. People driving at night are temporarily rendered blind by this beam, increasing the risk of collisions. When it detects an oncoming vehicle, the high beam automatically changes to the low beam. The manual switching by the driver is unnecessary thanks to this model's philosophy. The primary objective of this technology is to use an Arduino to control the vehicle's headlights in a sophisticated manner, taking into account ambient light levels via a resistor that depends on light and the presence of oncoming traffic via an ultrasonic sensor. Consequently, the system automatically controls the strength of the car's headlights and establishes an appropriate intensity quality throughout the night, taking into account the ambient light level and the presence of a vehicle approaching from the opposite way. © 2024 IEEE.

关键词： Driver Assistance LDR Light Dependent Resistor Roadside Assistance Smart Vehicle Vehicle Headlight Control Vehicle Safety

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