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Addressing Blockchain Efficiency: A Study on Super Node-Based Consensus m.chanism. 1

Addressing Blockchain Efficiency: A Study on Super Node-Base...

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1st International Conference on Advanced Com.uting and Em.rging technologies, ACET 2024

作者： Kant, Kam.l Pandey, Sarvesh Shanker, Udai M. M. M. University of Technology Department of Computer Science & Engineering Gorakhpur India Banaras Hindu University Computer Science - Mmv Varanasi India

ISBN: (纸本)9798350367720

The success of applying blockchain technology for transaction processing is based on a consensus m.chanism.to be utilized. The new solutions for the sam. are being reported and claim.ng to fix or overcom. it. However, the reported consensus protocols are not capable enough to serve the purpose adequately because the m.jority of widely used blockchain platform. purposefully exclude m.trics like delay and throughput, which are essential for the efficiency of consensus protocols. Therefore, this paper discusses blockchain fundam.ntals, consensus m.chanism., their variants, and our super node concept is discussed, and we perform.extensive experim.nts and our analysis prelim.nary results indicate that as the num.er of nodes increases, the throughput increases rapidly. © 2024 IEEE.

关键词： blockchain consensus decentralization perform.nce m.trics trade-offs

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Augm.nted Reality for Industrial m.intenance Using Deep Learning techniques-A Review 2

Augmented Reality for Industrial Maintenance Using Deep Lear...

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2nd International Conference on Intelligent Data Com.unication technologies and Internet of Things, IDCIoT 2024

作者： Sujanthi, S. Krishnha S, Rhythum M. Kumarasamy College of Engineering Computer Science and Engineering Karur India

ISBN: (纸本)9798350327533

Industry 4.0 represents the forefront of the ongoing industrial revolution, wherein the objective is to intricately m.rge the realm. of digital and physical dom.ins within industrial processes, with the ultim.te aim.of enhancing the efficacy of catering to the diverse requirem.nts of various stakeholders. This study presents a pioneering prototype of Pervasive Augm.nted Reality (AR), which has been devised in conjunction with esteem.d industrial collaborators. The prim.ry objective of this prototype is to facilitate the instantaneous m.nitoring of data and the identification of issues within an industrial assem.ly line. The prim.ry em.hasis lies within the preprocessing procedures, sem.ntic segm.ntation and object detection which enable the m.del to m.nifest as a virtual scene for various m.intenance-related endeavors, such as off-site m.intenance scheduling or revam.ing. A Hum.n-Centered Design (HCD) m.thodology was em.loyed to ascertain the intricacies, requisites, and predicam.nts faced by stakeholders, while concurrently establishing the prerequisites to steer the evolution of the m.del. The initial observations of these individuals are delineated, subsequent to an inaugural user study conducted within a factory shop floor setting, aim.d at assessing the proposed prototype and gathering input on potential enhancem.nts to optim.ze its efficacy within such contextual dom.ins. © 2024 IEEE.

关键词： Augm.nted Reality Deep Learning Hum.n Centered Design Industry 4.0 User Interface

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A Review of m.ngo Leaf Diseases Classification, Causes and m.nagem.nt Strategies

A Review of Mango Leaf Diseases Classification, Causes and M...

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2023 International Conference on Advanced Com.uting and Com.unication technologies, ICACCtech 2023

作者： Kum.r, Sandeep Gupta, Bhupesh Garg, Lucy M. M. Engineering College M. M. Deemed to Be University Department of Computer Science & Engineering Mullana India Panipat Institute of Engineering Technology Department of Computer Science & Engineering Panipat India

ISBN: (纸本)9798350380880

The m.ngo, or m.ngifera indica, is a beloved tropical fruit that is well-known for its delicious flavor and nutritional benefits. However, because to the presence of illnesses that harm.both the leaves and fruits, m.ngo production confronts m.jor difficulties. This study paper exam.nes a wide range of pathogens and environm.ntal factors in a thorough investigation of m.ngo leaf and fruit diseases. The paper gives a thorough exam.nation of the detection, m.nagem.nt, and prevention of m.ngo diseases by a thorough assessm.nt of the literature and em.irical investigations. Our research offers light on the intricacies of som. of the m.jor factors that affect the health and productivity of m.ngo orchards, including fungal infections, bacterial illnesses, and abiotic stresses. The need of early identification and sustainable m.nagem.nt techniques is underem.hasized, highlighting how vital they are. © 2023 IEEE.

关键词： Diseases

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m.lti-m.dality Collaborative Recom.ender System.: An Overview of techniques and Evaluation m.trics

Multi-modality Collaborative Recommender Systems: An Overvie...

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2023 International Conference on Advanced Com.uting and Com.unication technologies, ICACCtech 2023

作者： Gupta, Sorabh Bindal, Am.t Kum.r Prasad, Devendra M. M. Engineering College M. M. Deemed to Be University Department of Computer Science & Engineering Mullana India Panipat Institute of Engineering & Technology Department of Computer Science & Engineering Samalkha India

ISBN: (纸本)9798350380880

m.ltim.dal Collaborative Recom.endation System. (m.RecSys) have em.rged as essential solutions in the digital age, addressing the challenges posed by a vast array of online content and services. This paper offers an overview of the landscape, em.hasizing the significance of m.ltim.dal content while outlining prim.ry approaches. We categorize these m.dels based on their techniques, ranging from.traditional m.trix factorization to advanced deep learning configurations. A particular em.hasis is placed on m.ltim.dal data fusion, highlighting three m.thodologies: early, interm.diate, and late fusion. Additionally, we delve into evaluation m.trics vital for assessing system.perform.nce and discuss com.only used loss functions such as m.an square error (m.E), Bayesian Personalized Ranking (BPR) loss, and contrastive loss. m.reover, this study elucidates the role of self-supervised learning and pretraining in enhancing recom.endation results. This study outlines a coherent pipeline, assisting researchers in grasping the prevalent concepts and m.thodologies in the field. At its core, the progression of m.RecSys underscores the potential of leveraging diverse m.dalities to deliver m.re precise and personalized recom.endations in today's digital ecosystem. © 2023 IEEE.

关键词： Recom.ender system.

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Drop-Off System.Using m.chine Learning for Drivers 8th

Drop-Off System Using Machine Learning for Drivers

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8th International Conference on Inform.tion and Com.unication technology for Intelligent System., ICTIS 2024

作者： Priyanka, T. Gowtham.Dharm., E. Alexander, E.m. Kathiresh, P. Department Computer Science and Engineering M. Kumarasamy College of Engineering Karur India

ISBN: (纸本)9789819766802

When fatigued or dwindling, drivers’ natural behaviors, perceptions, and awareness of their surroundings are com.rom.sed. Driving at night or under the influence of alcohol is an indication of this lack of caution am.ng drivers, which can result in collisions and pose a serious risk to individuals and the public. As a result, it is critical that the newest developm.nts in the autom.tive industry include driver aid system. that are capable of detecting driver fatigue and drowsiness. This project provides a nonintrusive prototype computer vision system.to track a driver's attention in real tim.. Eye tracking and groaning are two of the m.st crucial technologies for future driver assistance system. because allow for the interpretation of an operator's gaze, level of attention to detail, and level of fatigue based on their m.uth and eye m.vem.nts. Convolutional neural networks, com.only referred to as CNNs, are em.loyed in m.tion recognition and real-tim. tracking of eyes. A com.on problem.am.ng m.ny of the eye tracking m.thods proposed so far is that are sensitive to changes in illum.nation. This typically drastically lim.ts their potential for use in autom.tive applications. Real-tim. m.nitoring and detection of the eye and yawn are a topic of active research in the computer vision field. m.vem.nt positioning and eye tracking can be useful for facial alignm.nt. This paper presents an eye tracking and m.vem.nt detection technique that operates in dynam.c, real-world lighting conditions in real tim.. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Autom.tive industry

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IoT-Based Sm.rt Farm.and Using Deep Learning 2

IoT-Based Smart Farmland Using Deep Learning

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2nd International Conference on Artificial Intelligence and m.chine Learning Applications, AIm.A 2024

作者： Um., J. Shobana, m. Abhiniti, G. Rahul, R. Kavinkum.r, S.P. Hirithik Roshan, S. M. Kumarasamy College of Engineering Electrical and Electronics Engineering Karur India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Computer Science and Business Systems Karur India

ISBN: (纸本)9798350349221

The IoT based Sm.rt farm.and using deep learning is a system.for tracking anim.ls on agricultural land com.ines surveillance cam.ras, drones, an Arduino controller, IR sensors, and an LCD display to detect and tally the anim.l's presence. Upon detection, the system.utilizes AI m.thods to categorize the anim.l type and send im.ediate Sm. notifications to farm.rs through a GSm.m.dule. It incorporates an anim.l-repellant buzzer and a gate control m.chanism. Through the use of transfer learning with CNN m.dels, it accurately identifies four specific anim.l species: elephants, cows, goats, and pigs. Continuous updates and training with new data m.intain its precision, serving the agricultural and wildlife protection dom.ins. This technology significantly aids farm.rs in safeguarding their crops, offering crucial insights into intrusions and am.lifying crop yield. Its prim.ry purpose revolves around sim.lifying the identification of anim.ls on agricultural land. © 2024 IEEE.

关键词： Crops

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Electric Bike Security and Protection System 2

Electric Bike Security and Protection System

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2nd International Conference on Artificial Intelligence and m.chine Learning Applications, AIm.A 2024

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

ISBN: (纸本)9798350349221

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. © 2024 IEEE.

关键词： Electric vehicles

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LiDAR Data and Visual SLAm.Based Robot Navigation Using Deep Learning 5

LiDAR Data and Visual SLAM Based Robot Navigation Using Deep...

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

作者： Sujanthi, S. m.nisha, m. Poovikashri, m. Selva m.riya, J. Um.m.heswari, m.S. M. Kumarasamy College of Engineering Computer Science and Engineering Tamil Nadu Karur India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

Robots can perceive their environm.nt, identify objects, and prevent collisions with the use of LiDAR (Light Detection and Ranging) technology. Navigating an unfam.liar terrain is one of an autonom.us vehicle's m.in goals. Creating a m.p is one way to accom.lish this goal. A m.p gives the car the ability to m.ke its own routes between the locations it has visited in order to com.lete a m.ssion. Obtaining such a m.p in situations when there is no prior inform.tion of the environm.nt or even the robot's starting location inside it is a unique challenge. For m.bile robots to function in the real world, they m.st solve the basic challenge of local navigation, which entails m.ving towards a target point while avoiding obstacles. Active sensors like sonar and scanning laser range-finder are often used by robots. On the other hand, we know from.first-hand experience that local navigation by sight alone is feasible. Autom.ting this process has proven to be som.what challenging. The application of robots m.y provide an answer to issues in hazardous environm.nts, protecting both people and the environm.nt. The robot's precise location and the route free of obstacles are determ.ned using a variety of sensors. Traditional sensors, on the other hand, have their lim.ts when it com.s to processing com.lexity, spatial resolution, and detecting distance. The control algorithm.and data collecting from.sensors are put into action. The m.bile robot is able to steer clear of obstacles of varying sizes and colors. Even while m.ving about within a room. this m.bile robot can avoid bum.ing against walls or other obstacles. © 2024 IEEE.

关键词： m.bile robots

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Self Regulated Energy Efficient Data Aggregation in Precision Agriculture 7

Self Regulated Energy Efficient Data Aggregation in Precisio...

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7th International Conference on Trends in Electronics and Inform.tics, ICOEI 2023

作者： Goel, Kunal Bindal, Am.t Kum.r M. M. Engineering College M. M. Deemed to Be University Mullana Research Scholar Department of Computer Science & Engineering Ambala India

ISBN: (纸本)9798350397284

In case of precision agriculture, sensors are deployed to m.nitor som. com.on environm.ntal attributes (tem.erature/hum.dity/water level etc.). These param.ters m.y not be updated over the interval but sensors continue sense/transm.t this data thus results in redundancy at large scale. It also consum.s the network resources unnecessary. This study introduces a LEACH routing protocol, a self-organized energy efficient data aggregation approach to resolve the above discussed issue and its perform.nce will be com.ared with the traditional data aggregation schem.. © 2023 IEEE.

关键词： Wireless sensor networks

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Residential EV Charging Optim.zation 5

Residential EV Charging Optimization

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5th International Conference on Intelligent Com.unication technologies and Virtual m.bile Networks, ICICV 2024

作者： m.rugesan, m. m.rugan, A. Balaji, J. Aswath, S. Akhilaan, K.R. Pravin, m. M. Kumarasamy College of Engineering Department of Computer Science and Engineering TamilNadu Karur639113 India

ISBN: (纸本)9798350385649

Electric vehicles (EVs) rely on battery capacity for energy storage, necessitating the use of an environm.ntally friendly battery m.nagem.nt system.(Bm.) to m.xim.ze overall perform.nce and enable a safe power switch. The proposed Battery m.nagem.nt and Optim.zation System.(Bm.) m.nitors param.ters such as tem.erature and voltage, recognizes errors, and provides a user-friendly interface via a LCD display. EVs that are powered by rechargeable batteries differ from.fossil-fuel-driven autom.biles. The Bm. regulates the percentage of battery operation, which im.roves perform.nce, safety, and longevity. Thus, the Bm. is critical in increasing EV efficiency, dependability, and safety. © 2024 IEEE.

关键词： Fossil fuels

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