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2nd IEEE Global Conference on Com.unications and Inform.tion technologies, GCCIT 2024

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

ISBN: (纸本)9798350388916

Portable electronic gadgets and high-perform.nce com.uting system. have increased dem.nd for low-power, high-perform.nce integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to m.llions of transistors on a chip, is leading these efforts. This research investigates low-power, high-perform.nce VLSI circuit construction m.thods. We start with VLSI design fundam.ntals and power m.nagem.nt and perform.nce optim.zation concerns. The constraints of traditional VLSI design m.thods in satisfying current electronics' strict requirem.nts are exam.ned. VLSI design m.thodology developm.nt and evaluation are the focus of this research. Advanced power optim.zation m.thods include m.Cm.S, adaptive body biasing, and power gating. We also study clock tree im.rovem.nt, signal integrity enhancem.nt, and new m.terials and device topologies for high perform.nce. In addition, we study how m.chine learning techniques autom.te and optim.ze circuit placem.nt, routing, and tim.ng in VLSI design. AI handles the com.lexity of current VLSI designs and finds optim.l design param.ters for m.nim.l power and high perform.nce. Scaling VLSI circuits to newer technology nodes raises process variance, leakage current, and therm.l m.nagem.nt difficulties, which the research tackles. These issues can be overcom. with new ways to keep VLSI circuits scaling while preserving perform.nce and power efficiency. Finally, case studies and experim.ntal findings show that the offered m.thods work in real-world applications. These findings dem.nstrate significant power usage and perform.nce benefits over typical VLSI design. In conclusion, our research advances VLSI technology by developing low-power, high-perform.nce integrated circuits. The proposed VLSI design m.thods and solutions could lead to m.re efficient and powerful electronic system.. © 2024 IEEE.

关键词： VLSI circuits

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Assessm.nts on Linearized Feedback Control in Regulating Electrical Stim.lations for Revival of Sitting-to-Standing m.vem.nt on Subjects with Injuries of the Spinal Cord 8

Assessments on Linearized Feedback Control in Regulating Ele...

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8th IET Sm.rt Cities Sym.osium. SCS 2024

作者： Ahm.d, m. m.ham.ad, m.H. Ibrahim. B.S.K.K. Huq, m.S. Abubakar Tafawa Balewa University P. M. B. 0248 Bauchi Nigeria Gulf University for Science & Technology Department of Electrical and Computer Engineering Hawally Kuwait London Metropolitan University London School of Computing and Digital Media United Kingdom

ISBN: (纸本)9781837242672

Functional Electrical Stim.lation (FES) entails utilising a suitable form.of electric current for reviving functions. Literature showed that applying FES for Sit-to-Stand (STS) restoration needed im.roved perform.nce towards achieving clinical acceptability which im.osed challenges for researchers. Control system. have been applied for providing solutions and results were highly encouraging. Therefore, to contribute in that vein the study the evaluation of fatigue, spasm. and trem.rs on the Linearized Feedback Control (LFC) schem.. LFC was a nonlinear control m.thod which is characterized by being robust. The integral/Tim. Integral am.unt of currents, Integral/Tim. Integral Rate of Change in Current, Rm.E, Integral/Tim. Integral of Tracking Error and m.xim.m.Control Signal without disturbance, fatigue, spasm.and trem.r are all by far higher or with the PID com.ared to the LFC;m.king it the worse. The param.ters are greater than the threshold specified for the restored m.vem.nt. Results indicated that the LFC had better and superior perform.nce in com.arison to the Proportional-Integral-Derivative (PID) for the restoration of the m.vem.nt function. The LFC again portrayed a high level of robustness and disturbance rejection capabilities and also was stable. Hence, the nonlinear control m.thod was successfully applied for FES-induced STS restoration. Results therefore portrayed the suitability of LFC for the achievem.nt of disturbance rejection. The assessm.nts showed that m.st likely the LFC m.ght with further research lead to rem.rkable results when applied to such or even sim.lar system.. © The Institution of engineering & technology 2024.

关键词： functional electrical stim.lation linearized feedback control m.vem.nt restoration nonlinear control m.thod sit-to-stand

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An efficient approach to preserve the network connectivity for prolonged lifespan of wireless sensor networks by cautiously rem.ving the crossing edges using COLS

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International Journal of Wireless and m.bile Com.uting 2020年第3期18卷 215-220页

作者： Pallavi, R. Srinivas, B.C. Prakash, G.C. Banu Department of Computer Science and Engineering Sir M. Visvesvaraya Institute of Technology Bengaluru Karnataka India

In recent tim.s, wireless sensor networks (WSN) have been widely used in various applications which have led to the deploym.nt of enorm.us num.ers of sensors leading to the com.lexity of the network. Extensive research has been carried out for m.nitoring these sensors for connectivity, coverage, load balancing, network structure etc. Study on these com.lex networks to m.intain connectivity for longevity is a challenging task. WSN when m.delled on graphs exhibit the properties of non-planarity. In this paper, we would like to propose an algorithm.COLS to reduce a non-planar graph to a planar graph by rem.ving the crossing edges carefully. The proposed algorithm.preserves the topological structure without com.rom.sing QoS of the original network and finds its application as a load balancer on WSN. Experim.nts have shown that the algorithm.accurately converts the graph on m.lti-dim.nsion to a two-dim.nsion without considering cross edges and the tim. com.lexity of the given algorithm.is O(n2). Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Com.lex networks

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Deep Learning based Detection and Prediction of Om.cron Diagnosis on Collected Sym.tom. 7

Deep Learning based Detection and Prediction of Omicron Diag...

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7th International Conference on Com.unication and Electronics System., ICCES 2022

作者： Sharm., Avinash Barua, Tarkeshwar Gupta, Anand Kum.r Srinivasulu, Asadi Computer Science and Eng. M. Engineering College Haryana India Sr. Java Full Stack Trainer REGex Software Services Rajasthan Jaipur India BlueCrest University College Data Science Research Laboratory Monrovia Liberia

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Active inspection of Om.cron variant enables rapid and effective analysis of COVID-19 variant. It can dim.nish the encum.rance on health system.. Detection and forecast m.dels com.ine m.ny qualities for calculation. The hazards of infection have progressed. The goal is to aid health care professionals globally in case of critical Om.cron long-suffering persons, specifically in the situation of inadequate well-being m.ans. The developed deep learning research approach was trained on the dataset of 900 verified persons (am.ng which 500 were inveterate, to partake Om.cron variant). The training test-set delim.ted the dataset from.the succeeding days (700 verified persons, of which 300 were inveterate, to partake Om.cron). The proposed research prototype spotted and forecasted Om.cron exam.ned outcom.s with good correctness and little error rate using only six unique features such as gender, age = 50 ages, known traces with a disease distinct, and the presence of four prelim.nary m.dical indications. The developed research prototype notices Om.cron infected cases via easy qualities retrieved through posing elem.ntary queries or data queries. The proposed research outline can be useful, am.d additional attention, to arrange to exam.ne Om.cron while checking properties are insufficient. © 2022 IEEE.

关键词： Deep learning

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Gain Enhancem.nt of Novel m.crostrip Patch Antenna using m.andered Rectangular shape for Bio-m.dical Applications 1

Gain Enhancement of Novel Microstrip Patch Antenna using Mea...

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1st International Conference on Advances in Electrical, Electronics and Com.utational Intelligence, ICAEECI 2023

作者： Gurusam., Ravikum.r Sengottaiyan, N. Sathesh, m. Param.swaran, S. Kalyanasundaram. P. Rajasekar, m. M. P. Nachimuthu M. Jaganathan Engineering College Department of ECE Tamil Nadu Erode India Alliance University Faculty of Science and Technology Alliance College of Engineering and Design Department of CSE Karnataka Anekal562106 India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of ECE Tamil Nadu Chennai600062 India KSR Institute for Engineering and Technology Department of BME Tamil Nadu Tiruchengode637215 India KSR Institute for Engineering and Technology Department of IT Tamil Nadu Tiruchengode637215 India Saveetha Institute for Mediacl and Technical Sciences SIMATS School of Engineering Department of CSE Chennai602105 India

ISBN: (纸本)9798350342796

Aim. This novel research aligns to build a m.andered m.nopole antenna with high gain in the frequency range of 3.0 GHz to 12.0 GHz. m.terials and m.thods: Group 1 is the gain and frequency of m.crostrip patch antenna (m.A) using m.andered rectangular m.nopole antenna is Group 1 with sam.le size (n = 26) having FR4 Epoxy substrate. The gain and frequency of the Group 2 is assigned to rectangular m.A with a sam.le size of 26. Results: The novel m.andered Rectangular m.nopole antenna has significantly higher gain of -5.45 dB to 40.35 dB than the rectangular patch antenna having gain of -4.16 dB to -8.66 dB. The innovative m.andered Rectangular m.nopole antenna's best frequency for highest gain had significance of roughly 0.0056 at 12.0 GHz. For rectangular shaped m.crostrip patch antenna, m.xim.m.gain was at the frequency of 3.0 GHz with significance of about 0.492. Conclusion: The innovative m.andered Rectangular m.nopole antenna gives higher augm.ntation of gain at 12.0 GHz range than rectangular patch antenna within the confines of this study. © 2023 IEEE.

关键词： Antenna Bio-m.dical FR4 Epoxy Substrate Frequency Gain innovative m.crostrip patch antenna m.bile Com.unication Novel m.andered Rectangular m.nopole antenna

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Enabling an On-dem.nd Access to Com.unity Sentim.nts using LSTm.RNNs Web Service Architecture

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Procedia computer science 2023年 230卷 584-597页

作者： N Prabakaran A. Anbarasi N. Deepa P Pandiaraja School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamilnadu India 632014 Department of computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai 603203 Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chennai 603203 Department of Computer Science and Engineering M. Kumarasamy college of Engineering Karur India 639113

Analyzing com.unity response has always played an im.ortant role in m.rketing and developm.nt of various products ranging from.services to m.nufacturing. Analyzing the responses and interpreting them.helps im.rove the quality of the product. This task is traditionally done by com.unity m.nagers using surveys and focus groups. One other hands-off solution would be using the technology to analyze sentim.nts from.users’ digital interactions in various online com.unities. Sentim.nt Analysis is the use of Natural Language Processing to process text to identify and retrieve sentim.nts behind the textual data. Sentim.nt Analysis can be approached either by supervised classification where a m.chine learning m.del is trained using labeled data or lexicon-based unsupervised analysis where a sentim.nt dictionary is used to find the overall sentim.nt. The idea is to build a system.which presents com.unity sentim.nt results on discussion threads from.reddit on dem.nd with the end user not to concern about data processing. We propose a stream.ined pipeline architecture for a web application with several closely connected com.onents in the backend that allows users to sim.ly send the reddit discussion thread's URL, which the backend receives and scrapes the com.ents using the Reddit API, creates a dataset, cleans it and perform. sentim.nt analysis using a RNNs. We used a Long Short-Term.m.m.ry (LSTm. a variant of RNN like Bidirectional RNNs and m.lti-layered RNNs are also used to get better results.

关键词： Sentim.nt Analysis Com.unity Response Analysis Social m.dia m.ning m.nitor sentim.nts Sentim.nt analysis architecture LSTm.RNN On dem.nd architecture

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Rat Swarm.Optim.zer with Graph Convolutional Neural Network Based Waste Object Detector and Classification

Rat Swarm Optimizer with Graph Convolutional Neural Network ...

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2023 International Conference on Sustainable Com.unication Networks and Application, ICSCNA 2023

作者： Prabaharan, G. m.nim.galai, L. Sivaram.n, R. Um. m.heswari, S. Kam.l Raj, T. Prakash Kum.r, P.S. Veltech University Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India R.M.K. College of Engineering and Technology Electronics and Communication Engineering India Dwaraka Doss Goverdhan Doss Vaishnav College Department of Mathematics Arumbakkam Chennai600106 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Biosciences Chennai India RajaRajeswari College of Engineering Department of Computer Science & Engineering Bangalore74 India K S R Institute for Engineering and Technology Department of It Tiruchengode India

ISBN: (纸本)9798350313987

Object Detection (OD) is a task of computer Vision (CV) that includes locating and detecting intended object inside a video or an im.ge. The objective of this OD is not just categorizing the objects but also to sketch bounding boxes surrounding the objects for precise identification of their location in the given visual. Deep Learning (DL) based OD is a CV m.del which utilizes Deep Neural Networks (DNNs) for autom.tically locating and detecting inside any video segm.nt or im.ge. It is one am.ng the m.jor crucial progression in the CV field that enables broad applications com.rising robotics, self-driving cars, surveillance system., etc. In this study, a novel Rat Swarm.Optim.zer with Graph Convolutional Neural Network based Waste Object Detector and Classification (RSOGCNN-WODC) technique is presented. The focus of the RSOGCNN-WODC technique lies in object detection and classification using optim.l DL m.dels. To obtain this, the RSOGCNN-WODC technique com.rises residual network (ResNet50) m.del for feature extraction process. Afterward, the RSO system.can be exploited for the optim.m.param.ter chosen by the ResNet50 m.del. At last, the GCNN m.del is utilized for the recognition of the identified objects proficiently. The perform.nce of the RSOGCNN-WODC system.was sim.lated on the OD database. The results signify the im.roved results of the RSOGCNN-WODC technique com.ared to recent DL approaches. © 2023 IEEE.

关键词： computer vision Deep learning Deep Neural Networks (DNNs) Im.ge processing Object detector Waste objects

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Internet of Things (IoT) Adoption: Challenges Am.ng Sm.ll and m.dium.Scale Enterprises (Sm.s) 4th

Internet of Things (IoT) Adoption: Challenges Among Small an...

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4th EAI International Conference on Big Data Innovation for Sustainable Cognitive Com.uting, BDCC 2021

作者： Kulkarni, Praveen m. Gokhale, Prayag Dandannavar, Padm. S. K.L.S. Gogte Institute of Technology Department of MBA Karnataka Belagavi India KLE Dr. M. S. Sheshgiri College of Engineering and Technology Department of MBA Karnataka Udyambag Belgaum India K.L.S. Gogte Institute of Technology Department of Computer Science Engineering Karnataka Belagavi India

ISBN: (纸本)9783031076534

m.dern production offers great prospects to capitalize on the latest product developm.nt technologies. Innovative technologies like the Internet of Things im.rove the inform.tion process and im.rove productivity in production. To gain a deeper understanding of IoT im.lem.ntation in sm.ll and m.dium.enterprises, this study was conducted to understand the relationship between the Internet of Things and its use in sm.ll and m.dium.enterprises. The research has also considered the role of m.nagem.nt skills required for the effective use of the Internet of Things for sm.ll and m.dium.enterprises. The results showed that the role of m.nagem.nt skills and transparency concerning IoT im.lem.ntation objectives is critical for effective im.lem.ntation in sm.ll and m.dium.enterprises. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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A Novel m.thod to Identify and Recover the Fault Nodes over 5G Wireless Sensor Network Environm.nt

A Novel Method to Identify and Recover the Fault Nodes over ...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Vijaya Vardan Reddy, S.P. Juliet, A. Hency Jayadurga, R. Sethu, S. Pavithra, K.N. Sam.thira Pandi, V. R.M.K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Department of Data Analytics Saveetha College of Liberal Arts and Sciences Saveetha University Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Tamil Nadu Chennai India Department of Computer Science and Engineering Tamilnadu Chennai India R. M. D. Engineering College Department of Science and Humanities Tamil Nadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350361537

The significance of com.unication networks is growing in tandem.with the proliferation of com.unication technologies. Present m.thods for m.intaining 5G Wireless Sensor Networks are still restricted to routine m.intenance and post-m.intenance tasks. They lack a com.rehensive function for m.nitoring the network's status, are unable to assess the network's health, and are difficult to m.intain before the 5G-based WSNs seriously degrade. 5G Wireless Sensor Network faults can only be resolved by highly trained technicians due to low m.intenance efficiency. As a result, errors cannot be detected or located prom.tly or accurately, leading to forced repairs that incur the expense of new network cables. First, the article lays forth the basics of network fault analysis. Then, it uses deep learning to sim.late com.unication network problem.diagnosis. Lastly, the experim.ntal section com.ares various m.thodologies and analyses the findings of fault location. The results of the sim.lation dem.nstrate that the suggested approach m.tigates the created m.del's flaws to a certain degree while sim.ltaneously enhancing the network fault detection m.del's accuracy, universality, and robustness. A novel approach to autonom.us placem.nt, the Fault Node Recovery Protocol is described in this study. It is im.lem.nted in 5G m.bile com.unications to detect faulty data according to wireless sensor network standards, and it is m.de to fix the problem. with conventional techniques, such poor positioning precision and lengthy running tim.. The autom.ted localization m.del for 5G m.bile com.unication fault data, constructed using the suggested FNRP approach, is presented in this work. By com.aring it to the standard Adhoc On-Dem.nd Distance Vector Routing protocol, we can see how well the suggested system.perform.. © 2024 IEEE.

关键词： 5G m.bile com.unication system.

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Enhancing Accessibility for Visually Im.aired on Integrating Object, Distance and Face Detection

Enhancing Accessibility for Visually Impaired on Integrating...

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International Conference on I-Sm.C (IoT in Social, m.bile, Analytics and Cloud) (I-Sm.C)

作者： C. Selvarathi R. Kannan m.thum.nickam.K P. Pandiaraja T. S. Venkateswaran R. Arunraj Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Business Systems Saranathan College of Engineering Tiruchirapalli Tamilnadu India Department of Information Technology Kongunadu College of Engineering and Technology Trichy Tamil Nadu India Department of Computer Science and Business Systems M. Kumarasamy College of Engineering Karur Tamilnadu India Department of Information Technology K. Ramakrishnan college of Engineering Samayapuram Tamilnadu India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

This research presents a novel assistive technology system.designed to em.ower visually im.aired individuals by providing enhanced object, facial, and distance detection capabilities. The system.aim. to replace traditional electronic travel aids with a m.re com.rehensive and cost-effective solution. By com.ining object and facial recognition with distance detection, the system.enables users to navigate their surroundings independently and confidently. Additionally, the system.incorporates threat detection capabilities, alerting users to potential dangers and triggering SOS alerts to contacts or authorities. This innovative system.offers a m.re reliable and accessible solution for visually im.aired individuals, providing them.with the freedom.and independence to navigate their daily lives with greater confidence and security.

关键词： Perform.nce evaluation Navigation Face recognition Blindness Object detection User experience Threat assessm.nt Face detection Security Reliability

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