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3rd International Conference on Electrical, electronics, Information and communication Technologies, ICEEICT 2024

作者： Bhairavi, R. Thiruveni, M. Anita Christaline, J. Ashokkumar, N. Chandra, I. Nagarajan, P. Srm Institute of Science and Technology Department of Ece Chennai Vadapalani India Psna College of Engineering and Technology Department of Ece Dindigul India Vit Chennai School of Computer Science and Engineering India Department of Electronics and Communication Engineering Andhra Pradesh Tirupati India Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350369083

UWASN has various challenges such as minimal bandwidth availability, long propagation delay, increased energy exhaustion, increased deployment cost and security. The routing protocols should facilitate an enhanced data forwarding towards sink nodes. In this paper, an Improved Energy Balancing based Data Forwarding incorporating Whale optimization Technique (IEBDF-WO) is proposed to effectively elect optimal forwarders to participate in the routing process. The Whale optimization algorithm has three phases namely, scouring phase, encompassing phase and final bubble net raiding phase for facilitating enhanced data transmission towards sink node. The proposed technique determines a fitness function by using the weighted depth difference WD, Potential Relay Count (PRC), Residual energy of each potential relay node. The performance of the proposed IEBDF-WO technique is analyzed and is collated with the existing Energy-Efficient Probabilistic Depth-Based Routing (EEPDBR) technique. It is seen that, for a network comprising of 200 nodes, the proposed scheme has improved Packet Delivery Ratio of 96.04% while minimizing the end to end delay, energy tax and average number of hops. © 2024 IEEE.

关键词： encompassing phase fitness function potential relay count scouring phase whale optimization

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Automated 20-20-20 Timers Using Facial Detection and Facial Recognition 4

Automated 20-20-20 Timers Using Facial Detection and Facial ...

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4th IEEE Annual Flagship India Council International Subsections Conference, INDISCON 2023

作者： Das, Saumodip Pal, Geetanjali Manna, Somsubhra Dhara, Arnab Sen, Anindya Heritage Institute of Technology Department of Electronics and Communication Engineering Kolkata India Heritage Institute of Technology Department of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350333558

This paper proposes two automated 20-20-20 timers using facial detection and facial recognition respectively. computer Vision Syndrome (CVS) is a common phenomenon these days, resulting in eye irritation and headaches. A possible prevention of CVS is adopting the 20-20-20 rule. Two types of 20-20-20 timer exist in the market, but both have scopes of improvement. While one type of timer needs to be manually set by the user like a stopwatch, the other type of timer detects the ON -screen time of monitors as a parameter. Both these models fail to detect whether the user is actually looking at the screen, and interrupt the work schedule of the users. The authors have developed a smart automated 20-20-20 timer that uses haar-cascade classifiers for detecting the face and accordingly adapt to the situation. This timer is able to detect the facial features in real time, and alert the user after 20 minutes of screen time. Furthermore, the authors have developed another smart 20-20-20 timer using YOLOv5s. This timer can recognise multiple users looking at the screen and run the timer independently for each person. While the haar-cascade enabled timer is preferred for homes and personal laptops, desktops and PCs;the YOLOv5s enabled timer is suited for offices, schools, colleges and libraries. This paper proposes an automated smart 20-20-20 timer system. © 2023 IEEE.

关键词： Python

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Data sampling approach using heuristic Learning Vector Quantization (LVQ) classifier for software defect prediction

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Journal of Intelligent and Fuzzy Systems 2023年第3期44卷 3867-3876页

作者： Amanullah, M. Thanga Ramya, S. Sudha, M. Gladis Pushparathi, V.P. Haldorai, Anandakumar Pant, Bhaskar Department of Information Technology Aalim Muhammad Salegh College of Engineering Chennai India Department of Computer Science and Engineering R.M.K. Engineering College Kavaraipettai Chennai India Department of Electronics and Communication Srinivasa Ramanujan Centre Sastra Deemed to Be University Kumbakonam India Department of Computer Science and Engineering Velammal Institute of Technology Pancheeti Chennai India Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore India Department of Computer Science and Engineering Graphic Era Deemed to Be University Bell Road Clement Town Uttarakhand Dehradun India

On the basis of quality estimate, early prediction and identification of software flaws is crucial in the software area. Prediction of Software Defects SDP is defined as the process of exposing software to flaws through the use of prediction models and defect datasets. This study recommended a method for dealing with the class imbalance problem based on Improved Random Synthetic Minority Oversampling Technique (SMOTE), followed by Linear Pearson Correlation Technique to perform feature selection to predict software failure. On the basis of the SMOTE data sampling approach, a strategy for software defect prediction is given in this paper. To address the class imbalance, the defect datasets were initially processed using the Improved Random-SMOTE Oversampling technique. Then, using the Linear Pearson Correlation approach, the features were chosen, and using the k-fold cross validation process, the samples were split into training and testing datasets. Finally, Heuristic Learning Vector Quantization is used to classify data in order to predict software problems. Based on measures like sensitivity, specificity, FPR, and accuracy rate for two separate datasets, the performance of the proposed strategy is contrasted with the approaches to classification that presently exist. © 2023 - IOS Press. All rights reserved.

关键词： Defects

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Millimeter-Wave GaAs Ultra-Wideband Medium Power Amplifier and Broadband High-Power Power Amplifier for 5G/6G Applications

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IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2024年第1期14卷 111-121页

作者： Fu, Zi-Hao Li, Ming-Xuan Ma, Tzyh-Ghuang Wu, Chan-Shin Lin, Kun-You National Taiwan University Graduate Institute of Communication Engineering Department of Electrical Engineering Taipei10617 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei10607 Taiwan ASUSTek Computer Inc. Taipei11259 Taiwan Ultraband Technologies Inc. Taipei11158 Taiwan

This paper presents an ultra-wideband (UWB) medium power amplifier (MPA) and a broadband high-power power amplifier (HPA) operating at the 5G/6G frequency bands. By using 0.15~\mu \text{m} GaAs pseudomorphic high electron mobility transistor (pHEMT) technology process, the proposed UWB MPA delivers an average small-signal gain of 16.5 dB, a saturation output power (\text{P}_{\mathrm {sat}} ) of 24 dBm, and a peak power-added efficiency (PAE) over 24% from 24 to 38 GHz with a chip area of 2\times1 mm2. The broadband HPA demonstrates a 17-dB average small-signal gain, 29-dBm \text{P}_{\mathrm {sat}} , and a PAE over 28% from 24 to 32 GHz with a 2.4\times1.1 mm2 chip size. The measurement results have demonstrated the great potential of the proposed PA for 5G/6G millimeter-wave applications. © 2011 IEEE.

关键词： Power amplifiers

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Design of Evolutionary Algorithm Based Energy Efficient Clustering Approach for Vehicular Adhoc Networks

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computer Systems Science & engineering 2023年第7期46卷 687-699页

作者： VDinesh SSrinivasan Gyanendra Prasad Joshi Woong Cho Department of Electronics and Communication Engineering Kongu Engineering CollegePerundurai638060India Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha University602105ChennaiIndia Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea

In a vehicular ad hoc network(VANET),a massive quantity of data needs to be transmitted on a large scale in shorter time *** the same time,vehicles exhibit high velocity,leading to more vehicle *** of these characteristics result in unreliable data communication in VANET.A vehicle clustering algorithm clusters the vehicles in groups employed in VANET to enhance network scalability and connection *** is considered one of the possible solutions for attaining effectual interaction in *** one such difficulty was reducing the cluster number under increasing transmitting *** article introduces an Evolutionary Hide Objects Game Optimization based Distance Aware Clustering(EHOGO-DAC)Scheme for *** major intention of the EHOGO-DAC technique is to portion the VANET into distinct sets of clusters by grouping *** addition,the DHOGO-EAC technique is mainly based on the HOGO algorithm,which is stimulated by old games,and the searching agent tries to identify hidden objects in a given *** DHOGO-EAC technique derives a fitness function for the clustering process,including the total number of clusters and Euclidean *** experimental assessment of the DHOGO-EAC technique was carried out under distinct *** comparison outcome stated the enhanced outcomes of the DHOGO-EAC technique compared to recent approaches.

关键词： Vehicular networks clustering evolutionary algorithm fitness function distance metric

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Optimizing Power Flow with Hvdc Lines and Facts for Improved Power System Stability

Optimizing Power Flow with Hvdc Lines and Facts for Improved...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Karthikeyan, M.P. Nisha Garg, Raghav Department of Computer Bangalore India Noida Institute of Engineering and Technology Department of Electronics and Communication Engineering Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350357769

The increasing expenses incurred in the establishment of transmission networks, in conjunction with the essential function these networks serve in reorganized settings, highlight the need of using Flexible AC Transit System devices. The ideal placement and capacity distribution for Thyristor-Controlled State Capacitor in networks of transmission are important factors that are covered in this research. The suggested approach develops an objective function with the dual goals of reducing losses and increasing server capacity. Both technological and economic viewpoints are used in the inquiry, and the results are described appropriately. The results of the simulation demonstrated the effectiveness of the suggested approach in terms of both technical and financial factors. The infrastructure's load index significantly improved as a result of this compensation, rising by 23.02%. In addition, the economic method reduced power losses and improved network load ability by using the simulation to identify the best placement and capacity that produced the most profit. The thorough outcomes highlight how well the suggested methods worked in a variety of case studies. © 2023 IEEE.

关键词： economic analysis Flexible AC Transmission System (FACTS) HVDC lines multi-objective optimization and transmission networks Power flow optimization Thyristor-Controlled Series Capacitor (TCSC)

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Advanced Modulation Technique for Power electronic Converters in Grid-Tied Inverters

Advanced Modulation Technique for Power Electronic Converter...

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

作者： Jyothsna, Kalakonda Sundar, Y Shyam Sathyavani, B. Roy, Upendra B. P. Sapna Kumari, C. Vaageshwari College of Engineering Department of Electronics and Communication Engineering Karimnagar India Cmr Engineering College Department of Computer Science and Engineering Hyderabad India Sr University Department of Electrical and Electronics Engineering Warangal India Engineering Channabasaveshwara Institute of Technology Department of Electronics and Communication Tumkur India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350313413

In stationary reference frames for both single phase and three phase ac systems, proportional and resonant (PR) current controllers have been employed. Transforming PR controllers, which are suitable for controlling DC signals, produced the initial structure of the PR controller. In terms of ac signal, the PR controllers should theoretically attain zero stable error. For low frequency signal control, PR controllers often operate satisfactorily with a comparatively large cutoff frequency. However, the performance decreases and the transient become more dependent on system characteristics as the regulated as frequency and the cutoff frequency get closer. This behaviour is noticeable when controlling high frequency signals, like when dead time or grid harmonics compensation is involved. Thus, a modified PR controller (MPRC) with better performance of transient for controlling signals of high frequency is implemented in this study. Simulation is used to demonstrate the effectiveness of the implemented controller. © 2023 IEEE.

关键词： and Transient response Current controllers cutoff frequency Harmonics suppression PR controller

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AI-based Learning Techniques for Bladder Cancer Detection

AI-based Learning Techniques for Bladder Cancer Detection

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kumar, Sandeep Saurabh Aggarwal, Ankita Aryan Institute of Technology Ghaziabad India Chandigarh Group of Colleges Chandigarh College of Engineering Department of Computer Science & Engineering Mohali India Chandigarh Group of Colleges Chandigarh Engineering College Department of Electronics & Communication Engineering Mohali India

ISBN: (纸本)9798331508685

There is no doubt that the main issue to address in these patients is the early diagnosis of Bladder carcinoma. This work aims at initiating a new path in this research and undertakes advanced artificial intelligence (AI) and machine learning to enhance bladder cancer diagnosis. Bladder cancer is one of the more widespread malignant neoplasms, it is more prevalent in the male population and particularly in male gerontocracy. Conventional diagnostic approaches are hypertrophied and crippled by constraints that lead to diagnostic imperfections and unkind lateness. There stands a great opportunity to deal with these challenges through the implementation of Artificial Intelligence in healthcare. By incorporating the modern artificial intelligence models such as CNN and RNN along with other modern techniques, this research intends to improve the diagnostic outcomes and provide strong prognosis. It is through a comprehensive method of data preprocessing and feature engineering, an incorporation of ethical factors, and the use of complex algorithms that this research hopes to advance the future of precision medicine. In this context, the customized solutions based on the most effective data also expand the scope of the diagnosis of bladder cancer and bring positive changes to the treatment of patients. © 2025 IEEE.

关键词： Diseases

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Recent advances in breathable electronics

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Nano Research 2023年第3期16卷 4130-4142页

作者： Zhuocheng Yan Jian Xiong Bin Wang Min Gao Guangqiang Yin Tao Hu Taisong Pan Xinzhong Wang Yuan Lin Department of Electronic Communication and Technology Shenzhen Institute of Information TechnologyShenzhen 518172China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 610054China School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054China Engineering Cooperation on Applied Medicine Research Center University of Electronic Science and Technology of ChinaChengdu 610054China

The successful implementation of bioelectronic devices attached to living organism hinges on a number of material and device characteristics,including not only electrical and mechanical performances to gather physiological signals from living organism thus enabling status monitoring,but also permeability or breathability for gas/nutrient exchange between living organisms and surroundings to ensure minimum perturbation of the intrinsic biological ***,most bioelectronic devices built on planar polymeric substrates,such as polydimethylsiloxane(PDMS),polyurethane(PU),and polyimide(PI),lack efficient gas permeability,which may hinder the emission of volatile compounds from the surface of living organism,affecting the natural metabolism and reducing the comfort of ***,achieving permeability or breathability in bioelectronic devices is a significant ***,the devices made of gas-permeable materials with porous structures,that combine electronic components with daily garments,such as fibric and textile,offer exciting opportunities for breathable *** this review,several types of gas-permeable materials with their synthesis and processing routes are ***,two methods for measuring water vapor transmission rate of materials are discussed in ***,recent progress in the use of gaspermeable materials for the applications of plant-and skin-attached electronics is summarized systematically.

关键词： breathability gas permeability porous sponge foam nano materials plant electronics wearable electronics

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Brain Tumor Identification Using Data Augmentation and Transfer Learning Approach

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computer Systems Science & engineering 2023年第8期46卷 1845-1861页

作者： K.Kavin Kumar P.M.Dinesh P.Rayavel L.Vijayaraja R.Dhanasekar Rupa Kesavan Kannadasan Raju Arfat Ahmad Khan Chitapong Wechtaisong Mohd Anul Haq Zamil S.Alzamil Ahmed Alhussen Department of Electronics and Communication Engineering Kongu Engineering College638060Tamil NaduIndia Department of Electronics and Communication Engineering Sona College of Technology636005Tamil NaduIndia Department of Computer Science and Engineering Sri Sairam Institute of TechnologyChennai600044Tamil NaduIndia Department of Electrical and Electronics Engineering Sri Sairam Institute of TechnologyChennai600044Tamil NaduIndia Department of Computer Science and Engineering Sri Venkateswara College of EngineeringSriperumbudur602117Tamil NaduIndia Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117Tamil NaduIndia Department of Computer Science College of ComputingKhon Kaen UniversityKhonKaen40002Thailand School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

A brain tumor is a lethal neurological disease that affects the average performance of the brain and can be *** India,around 15 million cases are diagnosed *** mitigate the seriousness of the tumor it is essential to diagnose at the ***,the manual evaluation process utilizing Magnetic Resonance Imaging(MRI)causes a few worries,remarkably inefficient and inaccurate brain tumor ***,the examination process of brain tumors is intricate as they display high unbalance in nature like shape,size,appearance,and ***,a precise and expeditious prognosis of brain tumors is essential for implementing the of an implicit *** computer models adapted to diagnose the tumor,but the accuracy of the model needs to be *** all the above mentioned things,this work aims to identify the best classification system by considering the prediction accuracy out of Alex-Net,ResNet 50,and Inception *** augmentation is performed on the database and fed into the three convolutions neural network(CNN)models.A comparison line is drawn between the three models based on accuracy and *** accuracy of 96.2%is obtained for AlexNet with augmentation and performed better than ResNet 50 and Inception V3 for the 120th *** the suggested model with higher accuracy,it is highly reliable if brain tumors are diagnosed with available datasets.

关键词： AlexNet brain tumor data augmentation inception V3 ResNet 50

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