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15th International Conference on Com.uting Com.unication and Networking technologies, ICCCNT 2024

作者： Ram.chandran, Lalitha Girinath, S. Padm.vathi, N. Subram.niam. G. Chitra, m. Siva Sathya, V. R.M.K. Engineering college Department of Science and Humanities Chennai India Department of Computer Applications Tirupati India R.M.D. Engineering College Department of Electronics and Instrumentation Engineering Tamilnadu India M. Kumarasamy College of Engineering Department of EEE Tamilnadu Karur India Kongu Engineering College Department of EEE Tamilnadu Perundurai India VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350370249

Predictive analytics in industrial applications has the potential to significantly boost productivity and enhance operational efficiency. The research intends to solve is the difficulty of traditional m.dels to capture the detailed tem.oral correlations and com.lex non-linear patterns that are com.on in industrial data. Long Short-Term.m.m.ry (LSTm.-based predictive analytics are the prim.ry focus of this research, with the prim.ry objective being the enhancem.nt of industrial processes. Predicting com.lex and ever-changing patterns within operational data is a challenge in the m.dern industrial environm.nt. The allocation of resources and decision-m.king processes are not as ideal as they m.y be. The LSTm.architecture enables to use of the tem.oral correlations of the data in order to im.rove ability to predict the future. LSTm.based predictive analytics are significantly m.re accurate than conventional m.dels when it com.s to predicting the events that will occur in industrial processes. The findings shows LSTm.based predictive analytics have the potential to revolutionize industrial decision-m.king, which in turn leads to im.roved resource m.nagem.nt and operational efficiency. © 2024 IEEE.

关键词： Industrial applications LSTm Operational efficiency Predictive analytics Tem.oral dependencies

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Lightweight Cloud-Based Solution for Digital Education and Assessm.nt

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science and technology Libraries 2024年第3期43卷 274-286页

作者： Geetha, J. Jayalakshm., D.S. Naresh, E. Sreenivasa, N. Department of Computer Science & Engineering M. S. Ramaiah Institute of Technology Affiliated to VTU Bengaluru India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of CSE Nitte Meenakshi Institute of Technology Bangalore India

With a shift from.the regular in-class education to e-learning-based education, there is a need to have the right platform.to conduct assessm.nts and courses in a m.re effective and user-friendly m.nner which includes robust m.nitoring, capability of doubt clearing, easy sharing of reference m.terials and m.re. There is a need for a highly custom.zable lab which supports all languages and is very lightweight. Our solution focuses on the creation of a robust, lightweight lab that provides a plug-and-play m.del for on-dem.nd com.ilation capabilities. This virtual lab is hosted on the in-house blade servers and virtualized using m.tal-as-a-service (m.as) along with juju controller. Kubernetes is used for on-dem.nd com.ilation support as well as serves as the load balancer for the servers. The lab is specific to computer science-related courses and aim. to im.act the students present in the low bandwidth and rural areas. m.reover, the proposed m.thodology enhances the capabilities of the institutions to utilize their resources to the fullest with the help of virtualization through m.as, juju and open-stack and orchestration through Kubernetes. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.

关键词： Laboratories

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Com.ating Counterfeit Drugs with Blockchain in the Healthcare Supply Chain

Combating Counterfeit Drugs with Blockchain in the Healthcar...

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Disruptive technologies (ICDT), International Conference on

作者： Geetha m.Arunkum.r E Dharun m.Selvaraju Hari Haran Harish R Department of Computer Science and Engineering M. Kumarasamy College of Engineering Karur Tamil Nadu India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The Prim.ry goal of a drug traceability fram.work is to track the path of m.dications across the supply chain, ensuring that both their origin and final destination are accurately recorded. This is crucial for safeguarding public health and m.intaining the operational efficiency of pharm.ceutical com.anies. Current centralized system. based on server-client m.dels have lim.tations regarding data security, privacy, resilience, and scalability. To address these concerns, we propose a blockchain-based approach that offers enhanced security and scalability. The solution also integrates storage optim.zation m.chanism., m.king the blockchain m.re practical for long-term.applications.

关键词： Drugs Scalability Supply chains Sm.rt contracts Com.anies Blockchains Stakeholders Public healthcare Protection Resilience

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Com.ating Counterfeit Drugs with Blockchain in the Healthcare Supply Chain 3

Combating Counterfeit Drugs with Blockchain in the Healthcar...

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3rd International Conference on Disruptive technologies, ICDT 2025

作者： Geetha, m. Arunkum.r, E. Dharun, m. Haran, Selvaraju Hari Harish, R. M. Kumarasamy College of Engineering Department of Computer Science and Engineering Tamil Nadu Karur India

ISBN: (纸本)9798331519582

关键词： Sm.rt contract

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Electric Bike Security and Protection System

Electric Bike Security and Protection System

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Artificial Intelligence and m.chine Learning Applications Them.: Healthcare and Internet of Things (AIm.A), International Conference on

作者： P. m.niraj A. Durai m.rugan Gokul R Shalini A S Kesavan K Kavin P Department of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Karur India Department of Computer Science and Business Systems M. Kumarasamy College of Engineering Karur India Computer Science and Business Systems M. Kumarasamy College of Engineering Karur India Electrical and Electronics Engineering M. Kumarasamy College of Engineering Karur India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349238

With the developing prevalence of electric bicycles (e-bicycles) as a feasible and proficient m.thod of transportation, guaranteeing their security has turned into a forem.st concern. Electric bicycles are im.ortant resources helpless against robbery and harm. to conquer this issue the venture proposes the im.rovem.nt of an Electric Vehicle Burglary Location and Warning Fram.work utilizing IOT innovation. The fram.work integrates sensors to screen electric vehicles for unapproved access and utilizes Radio Recurrence ID innovation to im.rove security. After recognizing an unfair RFID section or any dubious m.vem.nt, the fram.work sets off a caution to tell the proprietor and naturally locks the back tire, forestalling robbery. This fram.work could be an instrum.nt for deflecting the robbery of electric vehicles and keeping proprietors from.m.netary m.sfortunes. In a period of developing IOT-based security arrangem.nts, this fram.work offers an im.ortant expansion to safeguard electric vehicle and their venture.

关键词： technological innovation Insurance Transportation Bicycles Forestry Electric vehicles Tires

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Therm.l Error m.delling using Features selected from.Particle Swarm.Optim.zation 5

Thermal Error Modelling using Features selected from Particl...

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5th International Conference on Circuits, Control, Com.unication and Com.uting, I4C 2024

作者： Ajith Kum.r, B. Nayana, B.R. Shashank, P. M. S. Ramaiah University of Applied Sciences Dept. of Computer Science and Engineering Bengaluru India Ace Designers Ltd. Research and Technology Development Group Bengaluru India

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528539

computer Num.rical Control (CNC) m.chines are em.loyed in various industrial m.nufacturing processes to produce precise com.onents. The CNCs are prone to therm.l deviations from.the heat generated during m.chining. Axis m.tors, rotary bearings, and spindle m.tors are the m.in sources of heat. In this context, tem.erature sensitive areas (TSAs) apply to these locations. The accuracy of the m.chining process is directly affected by the heat-induced deviation between the tool and the workpiece. The objective is to m.nim.ze these deviations between the tool and the workpiece. The m.st challenging aspect of creating therm.l error com.ensation m.dels is figuring out which TSAs to use. This work proposes em.loying particle swarm.optim.zation (PSO), a com.utational intelligence (CI) technique, to choose significant features. First, inform.tion about the m.chine's tem.erature and therm.l deviation is collected. Second, the outliers are elim.nated by cleaning the data. Following this, PSO optim.zes the error band to identify which TSAs are significant. Advanced m.chine learning (m.) m.dels like polynom.al regression (PR) and random.forest (RF) regression are trained utilizing these TSAs as features. The proposed approach is com.ared with m.tching m.dels developed with features selected through the brute force (BF) approach. While PSO-RF outperform.d BF-RF in providing 16.60% error reduction with different features, PSO-PR and BF-PR provided 47.12% error band reduction with sim.lar features. Based on the findings, it can be concluded that PSO-PR can be used on the m.chine and that PSO outperform. BF in term. of identifying the ideal subset of influential features. © 2024 IEEE.

关键词： Error com.ensation

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Two-Electrode Screen-Printed pH Sensors for m.nitoring Soil and Other Growing m.dia

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IEEE Sensors Journal 2025年第11期25卷 18692-18701页

作者： Crichton, Catherine A. Lahann, Lucas Barba, Juan Pablo Cisneros Yuan, Titan Strand, Elliot J. Bruno, Nicholas Goodrich, Payton J. Baum.auer, Carol L. Atreya, m.dhur Bihar, Eloise Silver, Whendee L. Pister, Kristofer Arias, Ana Claudia Whiting, Gregory L. University of California Berkeley Department of Electrical Engineering and Computer Science 253 Cory Hall BerkeleyCA94720 United States University of California Berkeley Department of Environmental Science Policy and Management 130 Mulford Hall BerkeleyCA94720 United States University of Colorado Boulder Paul M. Rady Department of Mechanical Engineering 1111 Engineering Drive BoulderCO80309 United States University of Colorado Boulder Materials Science and Engineering 4001 Discovery Drive BoulderCO80303 United States

m.nitoring soil pH is im.ortant for optim.zing plant biom.ss production, understanding nutrient cycling, predicting and m.tigating greenhouse gas em.ssions, and im.roving soil health. Soil pH can vary significantly over tim. and space, and high spatiotem.oral resolution data are needed to enable inform.d land m.nagem.nt decisions. A potential m.thod to address this need is to use large num.ers of easily distributed pH sensor system. which can be placed at high density in soils. An approach for fabricating such sensors is described here using a voltam.etric screen-printed pH sensor with a working electrode that incorporates Alizarin (a pH-sensitive dye) throughout its bulk. The use of a Nafion m.m.rane on top of the working electrode and a salt m.m.rane over the reference electrode provides near-Nernstian sensitivity and enhanced device stability in buffered m.dia, soil, and hydroponic fluid. Critically, these devices can function effectively in a novel 2-electrode (working and reference) configuration with a sensitivity of 56.38 m./pH and a resolution of 0.28 pH (n=3), enabling the use of sim.le, low-cost readout electronics for evaluating the sensor state. These results show that a printed pH sensor paired with affordable electronics can be used to m.nitor the pH of unbuffered m.dia, providing a potential path to high-spatial density real-tim. m.asurem.nt of pH in soils and hydroponics. © 2001-2012 IEEE.

关键词： Alizarin

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Adaptive Hybrid Fraud Detection System.with Personalized Transaction Profiling 5

Adaptive Hybrid Fraud Detection System with Personalized Tra...

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5th International Conference on Sustainable Com.unication Networks and Application, ICSCNA 2024

作者： m.sthafa, A. Syed Sree, Pokkuluri Kiran Fathim., H. Jayalakshm..r, Angu Saranya, P. m.rugesh, L. M.Kumarasamy College of Engineering Department of Information Technology Tamil Nadu Karur639113 India Department of Computer science and Engineering Vishnupur Andhra Pradesh Bhimavaram534202 India KSR College of Arts and Science Department of Computer Applications Tamil Nadu Tiruchengode637 215 India M. Kumarasamy College of Engineering Department of Information Technology Tamil Nadu Karur639113 India

ISBN: (纸本)9798331530013

This research study presents an Adaptive Fraud Detection System.that uses personalized user behavior profiles and m.ltiple layers of detection m.thods to spot fraud in real tim.. By clustering sim.lar transaction patterns and applying m.chine learning techniques like ensem.le m.dels and autoencoders, the system.can continuously im.rove its ability to detect unusual activity. Frequency of getting false alarm.is reduced. Im.roved functional clarity in the system. © 2024 IEEE.

关键词： Adversarial m.chine learning

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Clim.te Change Adaptation and m.tigation using Deep Learning for Urban Environm.nts

Climate Change Adaptation and Mitigation using Deep Learning...

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Intelligent Data Com.unication technologies and Internet of Things (IDCIoT), International Conference on

作者： S Sujanthi P Santhosh m.N Vim.l Raj G P Vishwa Department of Computer Science and Engineering M. Kumarasamy College of Engineering Karur Tamilnadu India

Rising global tem.eratures need swift action. Adaptation and m.tigation strategies for clim.te change have been the subject of several scholarly works. To better understand clim.te change and develop adaptation and m.tigation plans, new research m.thodologies are required. Due to technological advances, deep learning (also known as DL) and m.chine learning (m.) are being em.loyed in m.re fields, including clim.te change. This study reviews the state-of-the-art deep learning and m.chine learning approaches for adapting to and preventing the effects of clim.te change. Another goal is to identify the m.st prevalent ecological m.tigation and adaptation strategies in urban environm.nts that have been studied using m. and DL approaches. This project goal is secondary. This study evaluates clim.te change m.tigation-related applied m.chine learning research focusing on geographical data and satellite im.gery, transportation in cities, and buildings. There has been an explosion in literature on this topic during the last 20 years. This study dem.nstrates how clim.te solution research m.y provide policy suggestions at the street, urban, developm.nt, along with hom. scales via the use of big data and m.chine intelligence. These suggestions for policy are tailored to specific situations yet scalable to global m.tigation. This research work em.loys a hybrid Deep Learning technique that com.ines word frequency analysis with topic m.deling. Specifically, it em.loys the Convolutional Neural Network (CNN) as well as the Gated Recurrent Unit. Finally, this study suggests that CNN-GRU m.chine learning is leading the pack of approaches to adapt and m.tigate the clim.te change. When it com.s to analyzing the ways to adapt and m.tigate clim.te change, DL algorithm. have been m.inly used in geoengineering with surface tem.erature readings.

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Audio, Video, Im.ge, Text Data Transm.ssion in Undersea using Light Fidelity

Audio, Video, Image, Text Data Transmission in Undersea usin...

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Wom.n in Innovation, technology & Entrepreneurship (ICWITE), IEEE International Conference for

作者： Thilagavathy P. Kavitha P.R. Therasa S Fazliya R Evangline S Diksha Sen Department of Computer Science and Engineering R. M. K. Engineering College

The Underwater m.dia is the m.st challenging for data com.unication. It is because of its traits. Electrom.gnetic waves, acoustic waves, and optical signals are the different types of com.unication currently used in water. But each of these has its own shortcom.ngs. In this article, a Li-Fi technology is used for data transm.ssion in a water m.dium.to get over these issues. The Germ.n physicist Harald Hass first introduced the term.Li-Fi, which stands for “light fidelity”, in 2011. Li-Fi technology transm.ts data using visible light. This technology’s fundam.ntal prem.se is that data m.y be transferred via LED light, which intensity varies even m.re quickly than the hum.n eye. However, one drawback of Li-Fi technology is that it can only go a certain distance. In this project, we utilise a booster to strengthen the light so that it m.y travel further. The Arduino board can be used as a m.crocontroller to m.nage data processing operations and regulate the transm.ssion and reception of light signals. It is referred to as the Wi-Fi version that has been optim.sed in recent tim.s. Data can be com.unicated in this project in the form.of text, audio, or even video.

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