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Research on Ultra-wideband Location of Mine Based on Clustering and TDOA

Research on Ultra-wideband Location of Mine Based on Cluster...

引用

2022 international conference on computing, Communication, Perception and Quantum technology, CCPQT 2022

作者： Dong, Jun Xia, Tianwen Computer & Information Engineering Institude Heilongjiang University of Science and Technology Harbin China

ISBN: (数字)9781665470209

ISBN: (纸本)9781665470209

To further improve the accuracy of underground positioning, a method of underground Ultra-Wide Band positioning based on clustering and TDOA is proposed. First, the TDOA method is used to measure, Chan algorithm is selected to solve, then the iterative solution is brought into the Taylor algorithm to establish the data collection in the iteration process, and remove the large error iteration values. Then, the data collection is aggregated through the K-means algorithm. Class iteration, filtering data processing and final accurate location *** non convergence problem caused by inaccurate initial value selection of Taylor algorithm can be well solved. Through simulation experiments, the performance of this algorithm is compared with Chan algorithm and Chan Taylor algorithm. The test results of this algorithm have higher accuracy and better stability, although positioning takes longer, the overall performance is obtained. Upgrading can cope with complex underground environment and achieve accurate positioning. © 2022 IEEE.

关键词： Time difference of arrival

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Meta-Reinforcement Learning for Adaptation in Dynamic Cyber Security Environment

Meta-Reinforcement Learning for Adaptation in Dynamic Cyber ...

引用

international conference on computing and Networking technology (ICCNT)

作者： Sambhavi Tiwari Aadharsh Roshan Ayush Baranwal Sahil Sharma Manas Gogoi Shekhar Verma Information Technology Indian Institute of Information Technology Allahabad Prayagraj India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This article investigates the application of meta-learning in training reinforcement learning agents for fast adaptation in rapidly changing dynamic environments. The proposed meta-learning approach demonstrates promising results in multi-agent environments, outperforming baseline algorithms and achieving stable convergence. However, in single-agent settings, the meta-algorithms exhibit similar or inferior performance compared to baseline algorithms, potentially due to overfitting. Nevertheless, the meta-learning algorithms perform well in non-dynamic single-agent environments, showcasing their ability to adapt effectively. The findings highlight the potential of incorporating meta-learning approaches in multi-agent systems to enhance adaptive behaviours and optimize performance in dynamic environments.

关键词： Metalearning Training Adaptation models Heuristic algorithms Reinforcement learning Security Computer crime Multi-agent systems convergence

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A Secure Federated Learning Framework using Blockchain and Differential Privacy 9

A Secure Federated Learning Framework using Blockchain and D...

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9th IEEE international conference on Cyber Security and Cloud computing and 8th IEEE international conference on Edge computing and Scalable Cloud, CSCloud-EdgeCom 2022

作者： Firdaus, Muhammad Larasati, Harashta Tatimma Rhee, Kyung-Hyune Pukyong National University Department of Artificial Intelligence Convergence Korea Republic of Pusan National University Department of Computer Engineering Korea Republic of Institut Teknologi Bandung School of Electrical Engineering and Informatics Indonesia

ISBN: (数字)9781665480666

ISBN: (纸本)9781665480666

Federated learning (FL) has considerably emerged as a promising solution to enhance user privacy and data security by enabling collaboratively multi-party model learning without exchanging confidential data. Nevertheless, most existing FL approaches still rely on a central server to obtain a global model by collecting all uploaded models from participants, which may lead to several threats from malicious participants and even expose participant privacy. Therefore, to tackle these problems, we proposed a secure FL framework by empowering blockchain to replace the centralized aggregator sever and utilize Differential Privacy (DP) to address various attacks, e.g., membership inference attacks, during the collaborative FL model training process. The proposed framework has been implemented through two scenarios, i.e., blockchain-based FL to form a decentralized system and DP-based FL to construct the randomized privacy protection using the IBM DP Library. © 2022 IEEE.

关键词： Blockchain

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Real-Time Environment Monitoring and Response Through IoT and Retrieval-Augmented Generation

Real-Time Environment Monitoring and Response Through IoT an...

引用

international conference on Information and Communication technology convergence (ICTC)

作者： Seungtaek Oh Seungwoo Kum Jaewon Moon Information Media Research Center Korea Electronics Technology Institute Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper introduces an architecture that combines IoT-driven data collection with Retrieval-Augmented Generation (RAG) for real-time environmental monitoring, analysis, and prediction. Using edge computing for local processing and centralized LLMs for complex analysis, the system delivers scalable and timely insights into environmental issues like climate change and disaster prevention. Data from IoT sensors is preprocessed at edge devices and sent to a central server, where embeddings are generated, stored in a vector database, and analyzed by the LLM for fast query handling. This system provides real-time feedback through dashboards, focusing on overcoming challenges such as network delays, scalability, and security to deliver reliable environmental monitoring for non-expert users.

关键词： Accuracy Scalability Retrieval augmented generation Computer architecture Data collection Real-time systems Vectors Environmental monitoring Servers Edge computing

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Security Enhancement in MANET using Modified Crow Search Optimization Algorithm for IoT Applications 7

Security Enhancement in MANET using Modified Crow Search Opt...

引用

7th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2025

作者： Swathi, R. Perumalla, Subhadra Arun, M. Bharathi, D.V.N. Srinivas, E. Krishnan, V. Gokula Department of EEE P.V.P. Siddhartha Institute of Technology Vijayawada India Department of CSE Vignana Bharathi Institute of Technology Ghatkesar Hyderabad India Department of ECE Panimalar Engineering College Tamil Nadu Chennai India Department of ECE S.R.K.R. Engineering College A.P Bhimavaram India Department of ECE Anurag University Ghatkesar Hyderabad India Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Tamil Nadu Chennai India

ISBN: (纸本)9798331515683

Mobile Ad hoc Networks (MANETs) are the integral part of advanced IoT applications, offering flexibility as well as scalability in dynamic network conditions. However, their distributed nature and reliance on wireless communication become them extremely vulnerable to security threats. This paper suggested a Modified Crow Search Optimization (MCSO) algorithm to improve the security of MANETs for IoT based applications. The recommended approach explores the intelligent foraging behavior of crows to provide secure transmission from malicious attacks. The MCSO algorithm is assessed against established methods in terms of convergence analysis. The performance of MCSO is assessed through latency as well as throughput analysis, signifying its greater efficiency over standing procedures such as SASFO, CHHSO and CSA. The latency examination discloses that MCSO reliably attains the lowest latency, fluctuating from 0.01 to 0.15, compared to larger latencies identified in CHHSO (0.03-0.16), CSA (0.03-0.19) as well as SASFO (0.05-0.20). Furthermore, the throughput analysis shows that MCSO preserves the maximum throughput, begining at 96.7% and dropping minimally to 90.4% by the 200^th round. These outcomes authenticate MCSO's effectiveness in dropping latency and preserving higher throughput, thus making it a robust as well as reliable result for improving performance of a network in MANETs, mainly in IoT applications. © 2025 IEEE.

关键词： Internet of Things Mobile Ad hoc Networks Modified Crow Search Optimization Security

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An Improved Chemical Reaction Optimization Approach for Solving Multiple Sequence Alignment Problem 8

An Improved Chemical Reaction Optimization Approach for Solv...

引用

8th international conference on Advanced computing and Communication Systems, ICACCS 2022

作者： Paruchuri, Tirumala Kancharla, Gangadhara Rao Dara, Suresh College of Business Administration Jazan University Faculty of Mis Saudi Arabia Acharya Nagarjuna University Department of Computer Science and Engineering Andhra Pradesh Guntur India B V Raju Institute of Technology Department of Computer Science and Engineering Telangana Narsapur India

ISBN: (纸本)9781665408165

Multi-Sequence Alignment (MSA) is considered an NP problem in bioinformatics. Compared to traditional techniques, nature-inspired techniques produce accurate results. In this article, Improved Chemical Reaction Optimization (ICRO) addresses the problem of MSA. However, the CRO has a low population diversity and slow convergence, it is one of the problem with CRO. To overcome this problem, a pairwise alignment procedure is used to improve the initialization process to maintain diversity. Benchmark data set was assigned to the base version of Bali 2.0 in the performance analysis. Thus, the proposed method has made comparisons with three existing approaches such as GAPWA GSAMSA and IBBOMSA to show the betterment of the proposed ICRO. Thus, the proposed approach has achieved better results with the existing approaches. © 2022 IEEE.

关键词： Benchmarking

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Robust Sliding Mode Control with Reaching Laws for a Pediatric Lower-Limb Exoskeleton System 2

Robust Sliding Mode Control with Reaching Laws for a Pediatr...

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2nd international conference on Power, Control and computing Technologies, ICPC2T 2022

作者： Narayan, Jyotindra Bharti, Rahul Ranjan Dwivedy, Santosha K. Indian Institute of Technology Guwahati Department of Mechanical Engineering Guwahati701039 India

ISBN: (纸本)9781665458580

The precise control of an exoskeleton, especially for pediatric subjects, is a challenging task due to the presence of parametric perturbations and external disturbances (PPED). The sliding mode control is a well-known robust control scheme to address such dynamic uncertainties. Therefore, in this work, a robust sliding mode control (RSMC) with is proposed for a pediatric lower-limb exoskeleton system during passive-Assist therapy mode. The performance of different reaching laws (constant, power, exponential, and general) used in proposed control are compared with each other. Lyapunov stability analysis is carried out to ensure the asymptotic convergence of the gait tracking error. It is noted from the simulation runs that the proposed RSMC with exponential reaching law outperforms the different controllers for the less tracking error in passive-Assist gait rehabilitation. However, chattering is found to be less with constant reaching law. © 2022 IEEE.

关键词： Robust control Visualization Uncertainty Trajectory tracking Computational modeling Exoskeletons Power control

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Self-Homodyne Coherent Transmission for Datacenter Interconnections 27

Self-Homodyne Coherent Transmission for Datacenter Interconn...

引用

27th OptoElectronics and Communications conference/international conference on Photonics in Switching and computing, OECC/PSC 2022

作者： Zhou, Xian Gao, Yuyuan Fang, Qianwen Liu, Fei Yuan, Jinhui Long, Keping No.30 Xue Yuan Road Haidian Beijing100083 China Shunde Graduate School of University of Science and Technology Foshan Beijing528300 China

We review recent research progress in the self-homodyne optical coherent system to address two key challenges in length mismatch induced phase noise and LO power fading induced by polarization rotation. © 2022 IE... 详细信息

ISBN: (数字)9784885523366

ISBN: (纸本)9784885523366

关键词： Phase noise

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Ice hockey game using Deep Reinforcement Learning

Ice hockey game using Deep Reinforcement Learning

引用

international conference for convergence of technology (I2CT)

作者： Y. Mounika Y. Lakshmi Prasanna Y. Tarakaram J. Amudha K. Aiswariya Milan Department of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

Modern deep Reinforcement Learning (RL) techniques are quite good at choosing the best possible rules to maximise rewards. By using rich visual information for policy selection, this method combined with Deep Learning methodologies shows promise for difficult tasks. In this work, we have used Double DQN and also three variants of Duelling DQN to implement the ice hockey environment. The Duelling DQN outperformed the Double DQN and gave better results.

关键词： Visualization Games Deep reinforcement learning Ice Task analysis Sports convergence

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Dynamic Optimization Framework for Multi-Hop Code Offloading in LEO Satellite Edge computing

Dynamic Optimization Framework for Multi-Hop Code Offloading...

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international conference on Information and Communication technology convergence (ICTC)

作者： Jeonghwan Kim Taewoo Lee Jeongho Kwak Electrical Engineering and Computer Science (EECS) Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea School of Undergraduate Studies Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea

In our swiftly digitizing world, the importance of low-earth-orbit satellite (LEO SAT) communication is escalating. Advancements in 5G, IoT, and AI underscore the need for a robust communication network. Research reveals that nearly 40% of the global population faces Internet service challenges due to limited high-performance access by 2022. This technology not only addresses coverage limitations but also mitigates latency issues. Multinational corporations like SpaceX and Amazon are already exploring its potential. As we approach the 6G era, users’ computational demands surge, prompting satellite edge computing with onboard processing. Our paper proposes a multi-hop code offloading model using LEO SAT, reducing energy consumption, and introduces a dynamic optimization algorithm for LEO SAT - mobile edge computing. The research aims to enhance satellite-based communication networks, with a focus on optimizing satellite edge computing efficiency.

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