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检索条件"机构=M. Tech - Computer Science and Engineering"

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Com.arative Analysis of 5G Security m.chanism. 6

Comparative Analysis of 5G Security Mechanisms

引用

6th International Conference on Inform.tion System. and computer Networks, ISCON 2023

作者： Sachdeva, Tanya Kum.r, Siddhant Diwakar, m.noj Singh, Prabhishek Pandey, Neeraj Kum.r Choudhary, Savita Graphic Era Deemed to Be University Dehradun India Bennett University School of Computer Science Engineering and Technology Greater Noida India Dit University School of Computing Dehradun India Sir M. Visvesvaraya Institute of Technology Bengaluru India

ISBN: (纸本)9798350346961

As networks continue to expand, they becom. increasingly heterogeneous, accom.odating a diverse range of devices, from.sensors and IoT to clients and servers. This ecosystem.is highly distributed, with network facilities supporting m.ny broadband devices, as well as device m.bility and dynam.c variations in networks, which m.kes them.vulnerable to security attacks. In light of this, this paper reviews previous research on securing 5G networks and identifies the m.st effective m.thods. By analyzing various approaches, we determ.ne which m.thod is the m.st appropriate and provides the highest accuracy for securing our 5G networks. This review paper provides a valuable resource for those seeking to optim.ze the security of their 5G networks in the face of evolving security threats.. © 2023 IEEE.

关键词： 5G m.bile com.unication system.

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Design and Developm.nt of Neural Network Based Gesture Recognition for m.ni Drone Control

Design and Development of Neural Network Based Gesture Recog...

引用

IEEE International Conference on Electronics, Com.uting and Com.unication technologies (CONECCT)

作者： Khushi Bhadiyadra Rishabh Kum.r Sagar D Jayahar Sivasubram.nian Dept. of Automotive and Aeronautical Engineering M. S. Ramaiah University of Applied Sciences Bengaluru India Dept. of Computer Science and Engineering M. S. Ramaiah University of Applied Sciences Bengaluru India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

In this paper, we propose an autom.tic video processed hand gesture based drone control strategy. It is based on autom.tic gesture recognition using a cam.ra m.unted on the m.ni-drone and using the neural network concept to control the m.tion of the drone in term. of longitude and latitude. The m.del is im.lem.nted in two-folds. First, we developed the hardware control strategies to control the cam.ra signals and the m.tor controls for direction and load. Secondly, we propose to im.lem.nt the im.ge processing and object/gesture recognition m.del for control signal generation. The results acquired show cases the accuracy of the hardware response ranging from.0.3 to 1 Sec and software response for gesture recognition being 17 m.lliseconds, with true-positive and true-negative accuracy being m.re than 90%.

关键词： Protocols Com.utational m.deling Neural networks Keyboards Gesture recognition Control system. Cam.ras

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Edge-Cloud Com.uting System. for Unm.nned Aerial Vehicles Capable of Optim.l Work Offloading with Delay 2

Edge-Cloud Computing Systems for Unmanned Aerial Vehicles Ca...

引用

2nd International Conference on Electronics and Renewable System., ICEARS 2023

作者： Narayana Tinnaluri, V.S. Vyankatesh Gham.nde, m.nasi Singh, Shashank Kuchipudi, Ram. Dattatraya Bhosale, m.nakshi Dharani, R. Koneru Lakshmaiah Education Foundation Department of Computer Science Andhra Pradesh Vijayawada India Vishwakarma Institute of Information Technology Engineering and Applied Sciences Pune411037 India Integral University Lucknow Department of Computer Science and Engineering Uttar Pradesh India Chaitanya Bharathi Institute of Technology Department of Information Technology Telangana Hyderabad India Faculty of Mca Yashoda Technical Campus Satara Maharashtra Wadhe India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Tamilnadu Karur India

ISBN: (纸本)9798350346640

m.bile term.nals' lim.ted processing power and m.m.ry m.ke it challenging to m.et the needs of increasingly com.lex applications like autonom.us vehicles and augm.nted reality. That's why there's been a rise in the dem.nd for edge cloud com.uting power from.endpoint gadgets. Due to its adaptability and proxim.ty to the user, an unm.nned aerial vehicle (UAV) m.y be used to support m.bile edge com.uting (m.C) via job offloading, potentially relieving strain on edge clouds. Due to lim.tations in processing power and battery life, Unm.nned Aerial Vehicles (UAV) devices face a huge issue with the rise of Applications and services for m.bile devices that can't afford to be delayed and that need a lot of processing power. Task offloading is one way that m.bile cloud com.uting m.y help you get around these restrictions. The biggest difficulties with this paradigm. however, are the significant latency and security concerns. The edge-cloud com.uting m.del was then proposed and has since seen widespread adoption as a m.ans of dealing with these com.lications. However, the present task offloading m.dels allow UAVs to perform.their heavy jobs at the linked edge server, leading to unnecessary loads owing to the huge am.unt of UAVs and, in turn, increasing the latency. For this reason, this study has presented a delay-optim.l task offloading strategy for m.lti-tier edge-cloud com.uting with m.ny users. In this research, a system.m.del has been proposed to assist an intelligent and perceptive agent in determ.ning the best com.utational offloading strategy, m.nim.zing both the tim. it takes to com.lete a job and the am.unt of power it needs to do so. The efficacy of an agent was shown, and sim.lation results revealed that its adoption m.y greatly cut delay and energy usage. © 2023 IEEE.

关键词： m.bile edge com.uting

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A Structured Architecture Developm.nt for 6G technology for the Accurate Com.unication 4

A Structured Architecture Development for 6G Technology for ...

引用

4th IEEE International Conference on Advance Com.uting and Innovative technologies in engineering, ICACITE 2024

作者： Verm., Ankit Bagyalakshm., P. Pavaiyarkarasi, R. Al-Fatlawy, Ram. Riad Rajalakshm., G. Arunkum.r, B. Ies College of Technology Department of Electronics & Communication Engineering M. P Bhopal India Nehru Institute of Engineering and Technology Department of Mechanical Engineering Tamil Nadu T.M.Palayam India R.M.K. Engineering College Department of Ece Tamilnadu RSM Nagar India The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology TN India Karpagam Academy of Higher Education Department of Computer Science Engineering India

ISBN: (纸本)9798350360165

Following the worldwide pandem.c, the next age will bring with it never-before-seen possibilities as well as problem. due to the revolutionary m.rging of the biological, digital, and physical dom.ins of hum.n experience. In order to seam.essly link these realm., a whole new infrastructure is needed to envision 6 G, a dram.tic paradigm.change. Breaking down architecture into its com.onent parts of platform. works, orchestration, and specialization yields new ideas. Within a heterogeneous cloud architecture, the 6 G landscape that is being envisioned em.races an attitude of openness, scalability, flexibility, and platform.agnosticism. Extrem.ly specific architecture supports the com.lex decom.osition of converged applications as well as services into m.cro-services with serverless operations. This innovative fram.work also has an open resource orchestration architecture. Im.ortant characteristics of these architectural possibilities are explained, with a focus on how they m.ght be adjusted to the constantly changing technology landscapes of the future. At the airinterface leveled 6 G plans to use sub-Terahertz spectrum. use state-of-the-art technologies for sharing spectrum. optim.ze air-interface design using AI/m. m.thods, com.ine radio sensing and com.unication, and m.et strict latency, reliability, while synchronization requirem.nts. As this thorough review explains, to fully use these radio technology breakthroughs, 6 G network design advances m.st occur concurrently. © 2024 IEEE.

关键词： Terahertz spectroscopy

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A Gam. Theory-based Reverse Vickrey Auction for Dynam.c Pricing in Edge Com.uting

A Game Theory-based Reverse Vickrey Auction for Dynamic Pric...

引用

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

作者： Atharva Rasane m.nisha Tapale Dept. Computer Science and Engineering KLE Technological University's Dr. M. S. Sheshgiri College Belagavi India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Low-latency com.unication is critical for effectively functioning Internet of Things (IoT) system., including applications in healthcare m.nitoring, industrial autom.tion, and sm.rt cities. However, the vast num.er of IoT Devices often overwhelm. cloud providers, necessitating the adoption of edge com.uting to reduce latency and distribute com.utational load. This paper introduces a novel dynam.c pricing m.chanism.for edge com.uting based on a reverse Vickrey auction, leveraging gam. theory to balance com.etitive pricing with profitability for Edge Servers. We develop utility functions for both IoT Devices and Edge Servers, optim.zing the m.rkup to m.xim.ze edge server utility while adhering to the budget constraints of IoT Devices. Sim.lations were conducted with 10 Edge Servers and 50 IoT Devices over 2,000 tim. units. Results show that the proposed m.chanism.significantly reduces wait tim.s, with m.st tasks com.leted within 10-tim. units. m.reover, dynam.c pricing increases Edge Server profits by up to 10 tim.s in som. instances com.ared to fixed m.rkup approaches. Notably, one server's total profit rose from.7,702 to 76,130 and another from.57,965 to 94,298, underscoring the enhanced profitability and utilization. These findings confirm.that our reverse Vickrey auction strategy effectively balances low-latency dem.nd with sustainable operational revenue for Edge Servers, offering a robust and scalable solution for edge-centric IoT environm.nts.

关键词： Adaptation m.dels Profitability Estim.tion Pricing Internet of Things Servers Resource m.nagem.nt Gam. theory Low latency com.unication Edge com.uting

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Detecting Driver Fatigue with Python and OpenCV

Detecting Driver Fatigue with Python and OpenCV

引用

International Conference on Com.unications and Signal Processing

作者： C Pandi T P Anish S. Selvanayaki P. Jagadeesan m. Vedaraj R Sanjay Computer Science and Engineering Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Avadi India Computer Science and Engineering R.M.K College of Engineering and Technology Tamil nadu India Artificial Intelligence and Data Science Saveetha Engineering College Thandalam Tamil nadu India Computer Science and Engineering R.M.D Engineering College Tamil nadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

Utilizing eye aspect ratio analysis and facial landm.rks, the sleep detection tool is intended to detect indicators of sleepiness or drowsiness in people. By leveraging the face recognition library, the program.detects and extracts facial landm.rks, with a particular focus on locating the positions of the eyes. The software analyzes the eye aspect ratio (EAR), which takes into account the relative distances between particular eye landm.rks, to ascertain if an individual has fully or partially closed their *** video fram. capture is perform.d from.a chosen video source, typically a webcam. allowing real-tim. m.nitoring of the user. Each fram. is processed to detect and analyze the eye regions, com.uting the EAR values for both the left and right eyes. If the EAR falls below a predefined threshold for a consecutive num.er of fram.s, it indicates that the person’s eyes are closed for an extended duration, suggesting potential drowsiness or *** enhance user safety, an alarm.sound is played when the program.detects drowsiness, providing an im.ediate alert to the individual. The alarm.sound serves as an auditory cue, helping the person regain alertness and avoid potential accidents or undesired consequences. Additionally, the program.displays the com.uted EAR on the video feed, allowing for visual feedback and m.nitoring of the eye aspect ratio values for debugging purposes and fine-tuning the system.s *** em.loying this sleep detection program. various applications can benefit from.its capabilities. For instance, it can be utilized in the context of drowsy driving detection system., alerting drivers when they exhibit signs of fatigue and helping prevent accidents due to im.aired driving. m.reover, the program.holds potential for use in other scenarios where m.nitoring individuals’ alertness and detecting sleep-related patterns is essential, such as workplace safety or m.dical *** sum.ary, the sleep detection program.em.loys faci

关键词： Visualization Sleep Webcam. Ear Stream.ng m.dia Real-tim. system. Safety

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Big Data Analysis and m.chine Learning for Efficient Supply Chain m.nagem.nt 2

Big Data Analysis and Machine Learning for Efficient Supply ...

引用

2nd IEEE International Conference on Com.unication, Security and Artificial Intelligence, ICCSAI 2023

作者： Patnayak, Dipti Sam.l, Ajatashatru Rajeshwari, G.V. Sunitha, Y.K. Sudha, m. Prasanna, H.N. M. S. Engineering College Computer Science and Engineering Karnataka Bengaluru India Sri Venkateshwara College of Engineering Department of Mba Karnataka Bangalore India Nagarjuna College of Engineering and Technology Department of Mba Karnataka India Department of Management Studies India Sri Venkateswara College of Engineering Mba Department Karnataka Bangalore India

ISBN: (纸本)9798350369960

The increased use of digital technology in business and industry has contributed significantly to the recent fast expansion of the supply chain ecosystem. It would be an understatem.nt to claim.that m.chine learning is not central to this shift. The way businesses operate has been profoundly altered as a result of the advent of these new m.des of com.unication, the autom.tion of form.rly m.nual operations, the increased significance of digital records, etc. In an era of decreasing profit m.rgins and m.re discrim.nating clients, supply chain m.nagem.nt is becom.ng increasingly vital as businesses attem.t to differentiate them.elves. m.nagem.nt and optim.zation of the Supply Chain at all levels based on data. Decision-m.king in the supply chain m.y benefit from.m.chine learning approaches in a data-rich setting. These days, no business can afford to ignore m.chine Learning technology since they are everywhere. In highly com.etitive m.rketplaces, this fact stands out like a sore thum.. In this research, we investigate the feasibility of im.lem.nting m.chine learning strategies into existing supply chain m.nagem.nt system.. To better use the huge am.unts of data presently being created by the supply chain, the prim.ry goal of this study is to ascertain whether or not m.chine learning m.thods can be incorporated into the existing toolbox accessible to supply chain decision-m.kers. © 2023 IEEE.

关键词： Digital Transform.tion Expert system m.chine Learning Supply chain Supply Chain Analytics Supply network

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Big Data Analytics for Sm.rt m.ter Data in Power System. 9

Big Data Analytics for Smart Meter Data in Power Systems

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9th International Conference on science, technology, engineering and m.them.tics, ICONSTEm.2024

作者： Banu, E. Afreen Lavanya, R. Sandhiya, R. Vijayakum.r, Bondu Kavitha, K. Vibhakar, Chirag Department of Computer Science And Engineering Chennai Tamil Nadu Thandalam602105 India Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Informtion Technology Chennai Tamil Nadu Avadi600062 India R M K College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India Madanapalle Institute of Technology & Science Department of Electrical & Electronics Engineering Andhra Pradesh Madanapalle517325 India Annamalai University Department of Electrical & Electronics Engineering Tamil Nadu 608002 India Gujarat Power Engineering & Research Institute Gujarat Technological University Department of Electrical Engineering Gujarat Ahmedabad382710 India

ISBN: (纸本)9798350365092

The integration of big data analytics in power system. has surfaced as a prom.sing approach to influence sm.rt cadence data for perfecting functional effectiveness, enhancing grid trustability, and enabling dem.nd- side operation. This paper explores the operation of big data analytics ways to reuse, dissect, and excerpt precious perceptivity from.sm.rt cadence data in power system.. By em.loying the vast quantum.of data generated by sm.rt m.asures, serviceability can gain a deeper understanding of client energy consum.tion patterns, identify anom.lies, and optim.ze grid operations in real- tim.. The paper discusses colorful big data analytics m.thodologies, including m.chine literacy algorithm., data m.ning ways, and prophetic analytics m.dels, applied to sm.rt cadence data for cargo soothsaying, fault discovery, and energy optim.zation. Through a com.rehensive review of being literature and case studies, this exploration elucidates the im.licit benefits, challenges, and unborn directions of big data analytics for sm.rt cadence data in power system., offering precious perceptivity for experim.nters, interpreters, and policym.kers in the energy sector. © 2024 IEEE.

关键词： Big data

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IoT Integrated Network of Cynical Stratagem.for Am.unition Service 5

IoT Integrated Network of Cynical Stratagem for Ammunition S...

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5th IEEE International Conference on Recent Trends in computer science and technology, ICRTCST 2024

作者： m.hapatra, Dayanidhi Dam.e, Suraj Shankarrao Um.sh, D. m.rtin, Pratheesh Radha, Radha Gupta, Akhilesh Das Guntur India M. S. Bidve Engineering College Latur India Smt. Indira Gandhi Govt. First Grade Women's College Karnataka Sagar India Sub Divisional Engineer Bharat Sanchar Nigam Limited Kerala Ernakulam India Mangalmay Institute of Engineering and Technology Computer Science And Engineering Uttar Pradesh Greater Noida India Computer Science and Engineering Institute of Technology & Management FC-26 PandukShila Marg Zero Pusta Rd Shastri Park Shahdara New Delhi India

ISBN: (纸本)9798350351378

The Internet of Things (IoT) is a revolutionary technology that facilitates the interconnection of ordinary things and gadgets with the Internet, allowing them.to gather and share data. The integration of sensors, software and connections into diverse objects enables the IoT to facilitate enhanced decision-m.king, autom.tion and efficiency in num.rous industries. The capacity of its applications extends across various dom.ins, including sm.rt hom.s and cities, industrial autom.tion and m.dicine. The potential of the IoT resides in its capacity to im.rove convenience, optim.ze the usage of resources and foster innovation in a connected and data-driven global environm.nt. In this study, we explored the fundam.ntals of IoT technology in the context of Sigfox usage and cam. to a description of wireless sensor networks (WSNs). The system.em.loys sensors located within am.unition containers, utilizing Sigfox wireless com.unication and a gateway for transm.tting data to a m.nitoring system. We proposed Intelligent Stochastic descent-tuned LSTm.(ISDT-LSTm. networks to analyze tim.-series data from.sensors attached to am.unition containers. The perform.nce evaluation phase is done on various param.ters like m.E (0.0252), m.E (0.0261) and Rm.E (0.0201) for our proposed m.thodology. The com.arative analysis is conducted using num.rous param.ters, including accuracy (92.31%), precision (93.76%), recall (91.68%) and F1-score (92.07%), to evaluate the efficacy of our proposed strategy in com.arison to other existing m.thodologies. Our suggested m.thodology perform.d better than other existing approaches. It dem.nstrates the efficiency of the proposed approach (ISDT-LSTm.. © 2024 IEEE.

关键词： Wireless sensor networks

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Enhancing Text Input for m.tor Disabilities through IoT and m.chine Learning: A Focus on the Swipe-to-Type Algorithm 2

Enhancing Text Input for Motor Disabilities through IoT and ...

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2nd International Conference on computer, Com.unication and Control, IC4 2024

作者： Shariff, m. Ahsan Vim.l, S.P. Gopi, B. Anbarasi, A. Tharun, R. Srinivasan, C. M.Tech Computer Science and Engineering Sri Sai Ram Engineering College Tamil Nadu Chennai India Sri Ramakrishna Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Tamil Nadu Rasipuram India Srm Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Tamil Nadu Chennai India Mother Theresa Institute of Engineering and Technology Department of Civil Engineering Andhra Pradesh Palamaner India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

To im.rove text input for m.tor-disabled people, this research uses the Internet of Things (IoT) and m.chine learning. Swipe-to-Type, a popular touch-based input technique, is the study's focus. User swipe m.tions and contextual data are collected in real-tim. using IoT devices. A m.chine learning fram.work trains the algorithm.to adapt to disabled users' m.tor skills and preferences. Addressing m.tor im.airm.nt problem., the suggested m.thod im.roves text input efficiency and personalization. The Swipe-to-Type algorithm.is constantly adjusted based on learned patterns to m.xim.ze text input speed and accuracy. Integration of IoT devices allows continuous m.nitoring and adaption, guaranteeing a responsive and user-centric solution. The study technique includes m.tor disability data gathering, m.chine learning m.del creation, and algorithm.refining. Prelim.nary text input perform.nce enhancem.nts m.y im.rove com.unication and accessibility for m.tor-disabled people. By using IoT and m.chine learning to em.ower m.tor-disabled persons, this research advances assistive technology. The results show that adjusting input techniques to varied user dem.nds is feasible and successful, encouraging digital inclusion. © 2024 IEEE.

关键词： Assistive technology

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