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检索条件"任意字段=IEEE International Conference on Distributed Computing Systems"

共 149810 条记录，以下是4701-4710 订阅

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5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

5th International Conference on Advances in Distributed Comp...

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5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

ISBN: (纸本)9789819718405

The proceedings contain 35 papers. The special focus in this conference is on Advances in distributed computing and Machine Learning. The topics include: Computer-Aided Bundle Branch Block Detection Using Symbolic Features of ECG Signal;block-Chain and Cloud-Based Tender Allocation System;reliability Assessment of IoT-Enabled systems Using Fault Trees and Bayesian Networks;resnet-50 Integrated with Attention Mechanism for Remote Sensing Classification;revolutionizing Data Annotation with Convergence of Deep Learning and Active Learning to Enhance Credibility on Twitter Datasets;statistical and Deep-Learning Approaches for Individual Carbon Footprint Calculation in India;intelligent Healthcare System Using Emerging Technologies: A Comprehensive Survey;Efficient Energy Management by Using SJF Scheduling in Wireless Sensor Network;cost Effective and Energy Efficient Drip Irrigation System for IoT Enabled Smart Agriculture;facial Detection and Recognition in Drone Imagery Using FaceNet;valluvan: Processing Name Board Images to Enhance Communication for Native Tamil Speakers;Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud computing;A Study on the Mental Health Among Indian Population in the Post COVID-19 Pandemic Using Computational Intelligence;Cloud-Based Anomaly Detection for Broken Rail Track Using LSTM Autoencoders and Cross-modal Audio Analysis;Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients;a Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-colour Space Feature Fusion and Quantum–Classical Stack Ensemble Method;comparative Analysis of Deep Learning-Based Hybrid Algorithms for Liver Disease Prediction;preface;performance Improvements of Covert Timing Channel Detection in the Era of Artificial Intelligence;sign Detection Using an N-Gram Language Model and MobileNet.

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Competitive Co-Evolution with Spiking Neural Networks

Competitive Co-Evolution with Spiking Neural Networks

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2024 international conference on Neuromorphic systems, ICONS 2024

作者： Mccombs, Luke Friend, Drew Whatley, Luke Schuman, Catherine D. University of Tennessee Department of EECS KnoxvilleTN United States

ISBN: (纸本)9798350368659

Spiking neural networks are a natural fit as controllers agents in control task. In this work, we investigate the use of competitive co-evolution to evolve two sets of agents (defenders and attackers) in a competitive environment. We show how the competitive co-evolution approach produces two relatively simple networks that are still capable of complex behaviors. © 2024 ieee.

关键词： competitive co-evolution neuromorphic computing spiking neural networks

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Evolution of Neuromorphic computing 4

Evolution of Neuromorphic Computing

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4th international conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Sai Sree Vaishnavi, Vakada G. Bhowmik, Biswajit National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Department of Computer Science and Engineering Surathkal Mangalore575025 India

ISBN: (纸本)9798350343670

With the advancement of artificial intelligence (AI) technologies, novel and inventive approaches for addressing complex problems are coming to the forefront. Neuromorphic computing based on AI technologies stands as an exemplar, endeavoring to mimic the human brain's intricate neural architecture and computational principles within electronic devices. Contrary to conventional Von Neumann architecture, neuromorphic computing architecture offers a promising solution for building intelligent and efficient computational systems that excel in tasks requiring low power consumption, real-time processing, and adaptability. Subsequently, it is employed in various applications such as robotics, sensory processing, neuromorphic vision, edge computing, etc. This paper explores the conventional Von Neumann architecture and outlines its shortcomings. Next, neuromorphic architecture as an alternative and its evolution are described. Next, the characteristics of neuromorphic computing and its diverse applications are illustrated. The paper also addresses the key challenges hindering neuromorphic computing development. © 2024 ieee.

关键词： Neuromorphic computing Neuromorphic computing Architecture Neuromorphic computing Challenges SpiNNaker Von Neumann Architecture

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Hypothyroid Disease Prediction Using Machine Learning & Ensemble Methods

Hypothyroid Disease Prediction Using Machine Learning & Ense...

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2024 ieee international conference on computing, Applications and systems, COMPAS 2024

作者： Haque Prantik, Md. Zihadul Mustary Abeda, Maliha Alam, Mohammad Jahangir Daffodil International University Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Thyroid illness is spreading more and more nowadays and it has become the most common disease that can lead to various health disorders. The main reason behind this disease is thyroid hormone disorder which can lead to problems like Hypothyroidism or Hyperthyroidism. As the problem is often underestimated, it is necessary but challenging to predict it efficiently. To diagnose Hypothyroidism, the traditional way is to perform thyroid tests based on various elements to diagnose the behavior of thyroid hormone. Machine learning algorithms play an important in detecting and predicting diseases at their early stages. Many analyses and models can be developed using machine learning classifiers to find the most effective and accurate predictions. Our study aims to use different machine-learning classification techniques and develop a model to predict hypothyroidism. We also compare machine learning methods to determine which classifier is optimal for constructing a classification model. We also aim to use ensemble learning techniques for optimal results and amplify accuracies. We have achieved 97.23% with gradient boosting and the AdaBoost classifier and gradient boosting are the best-performing models combined with the Boosting method giving the highest accuracy of 97.57% and 97.51% respectively. © 2024 ieee.

关键词： Contrastive Learning

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Accessing the Edge: Delay Evaluation to distributed Edge Services in a City-Level 5G Network 12

Accessing the Edge: Delay Evaluation to Distributed Edge Ser...

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12th international conference on Cloud Engineering

作者： Frei, Matthias Karbownik, Piotr German, Reinhard Djanatliev, Anatoli Fraunhofer Inst Integrated Circuits IIS Erlangen Germany Univ Erlangen Nurnberg Dept Comp Sci Comp Networks & Commun Syst Erlangen Germany

ISBN: (纸本)9798331528690;9798331528706

Cloud combined with Multi-Access Edge computing (MEC) empowers service creators and application developers with promising architectural design and communication performance improvements. In fifth generation (5G) and in 6G cellular networks, MEC gains more importance as a service platform to enable new applications. However, as of today, the availability of MEC resources in public networks is still low, thus not much communication performance measurement data exists. In this work, we use our private, city-level 5G test bed, to evaluate the end-to-end communication performance to different edge and cloud endpoints through realistic outdoor field tests. Multiple topological locations of the edge service are evaluated, the network is operated in stand-alone (SA) and non-stand-alone (NSA) modes, and two-way as well as one-way latency measurements with multiple traffic patterns are performed. The measurements are executed in different environmental settings: fixed position and drive tests, including 5G cell hand-overs. The results not only demonstrate the performance benefits gained from MEC resources, but also show the impact of the communication system and user mobility to Quality of Service (QoS) parameters. Especially for different traffic patterns and for the performance during our drive tests, our results show the time overhead required for exchanging data, which may be challenging for service lookups or delay-constrained applications.

关键词： edge computing cloud MEC 5G QoS latency RTT OWD PDV performance field test

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Quantum Secure Key Management & Delivery Protocol in the QKD framework 5

Quantum Secure Key Management & Delivery Protocol in the QKD...

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5th ieee India Council international Subsections conference, INDISCON 2024

作者： Harmalkar, Manjiri Jain, Kurunandan Aneesh Kumar, K.B. Krishnan, Prabhakar Amrita Vishwa Vidyapeetham Amritapuri Amrita Center for Cybersecurity Systems and Networks India Center for Development of Advanced Computing Cyber Security Group Kerala Thiruvanathapuram India

ISBN: (纸本)9798350376753

The current Quantum Key Distribution (QKD) key delivery API relies on HTTPS for secure communication. It is vulnerable to quantum computer threats due to its use of public key cryptography. To mitigate insider attacks, leveraging quantum computing threats within the security boundary and encrypting communication between the application and the KMS is essential. This paper focuses on simulating a 2-node QKD topology using the DARPAN Application. Additionally, we conduct tests on QKD KMS APIs with the Postman tool to ensure consistent retrieval of shared keys at both communication endpoints. Through our simulations and tests, we aim to validate the effectiveness and reliability of the proposed approach in securely managing cryptographic keys within the QKD-network. © 2024 ieee.

关键词： Quantum communication

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PROOF: Decentralized Platform for Verifiable Outsourced Computation 6

PROOF: Decentralized Platform for Verifiable Outsourced Comp...

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6th ieee international conference on Blockchain and Cryptocurrency, ICBC 2024

作者： Grigoratos, Spiros Doka, Katerina Koziris, Nectarios National Technical University of Athens Computing Systems Laboratory Greece

ISBN: (纸本)9798350316742

Decentralization is reshaping our digital landscape, promising improved control, security, and accessibility. This demo paper explores the potential of decentralization in Cloud computing, presenting PROOF, a platform designed to enable task outsourcing to any - potentially untrusted - computational resource without compromising the credibility of the produced output. Implemented as an Ethereum dApp, PROOF handles task allocation, execution, and verification, leveraging Blockchain technology for transparent and secure transactions. It utilizes an auction mechanism to match outsourcing requests to resource providers, the IPFS peer-to-peer file system to serve as storage, and Docker containers to facilitate secure and standardized task execution across a network of individual providers. During the demonstration, the attendees will have the chance to interact with PROOF (a) as clients, requesting resources, delegating task processing to remote infrastructures and verifying the validity of results and (b) as resource providers engaging in auctions, performing computations either in an honest or in a malicious way and automatically receiving payments. © 2024 ieee.

关键词： Decentralized control

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A Comprehensive Survey of Intrusion Detection System Using Machine Learning and Deep Learning Approaches 10

A Comprehensive Survey of Intrusion Detection System Using M...

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10th international conference on Advanced computing and Communication systems, ICACCS 2024

作者： Abhiram, Kotnur Muthusamy, Hariharan Ravindran, Sindhu Vijean, Vikneswaran Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India National Institute of Technology Uttarakhand Department of Electronis Engineering Uttarakhand Srinagar Garhwal246174 India Universiti Malaysia Perlis Faculty of Electronic Engineering & Technology Arau Pauh Putra Perlis02600 Malaysia

ISBN: (纸本)9798350384369

The necessity for Computer networks' use is expanding quickly, which raises problems with preserving network secrecy, availability, and integrity. Intrusion can be defined as an intentional breach of security rules within a secured network. Such intrusions can be identified by an Intrusion Detection system which searches for any malicious actions and recognized dangers within a secured network. Intrusion detection systems patrol the traffic passing through computer systems and give out notifications when they do. Recently, an immense upsurge in cyber-attack cases on computer networks has imposed the need for an effective Intrusion detection system than ever before. Nowadays, network administrators are utilizing multivarious kinds of Intrusion Detection systems (IDS), in order to monitor network traffic for malicious and unauthorized activities. This review paper focuses on various research works that has developed an approach for evaluating or identifying IDS using many kinds of Machine Learning (ML) and Deep Learning (DL) techniques. © 2024 ieee.

关键词： Network intrusion

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CYBERSECURITY FUNDAMENTALS - NOT JUST FOR INDUSTRIAL CONTROL systems WHEN GUIDANCE AND DIRECTION ARE AVAILABLE

CYBERSECURITY FUNDAMENTALS - NOT JUST FOR INDUSTRIAL CONTROL...

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ieee IAS Petroleum and Chemical Industry Technical conference (PCIC)

作者： Dunn, Donald G. Cosman, Eric OIT Concepts LLC Lakeway TX 78734 USA

ISBN: (纸本)9798350304534

Industrial Control systems (ICS) are important to supporting US critical infrastructure and maintaining national security. ICS owners and operators continue to face threats from a variety of adversaries whose intentions include gathering intelligence, stealing intellectual property, obtaining financial compensation through ransom, and disrupting national critical infrastructures. The ICS discussed do not just include control systems but often include electrical assets (microprocessorbased relays, trip units, etc.) which have been networked together using various communication protocols. Previous ieee PCIC papers have mentioned cybersecurity without providing details on howto secure an ICS. This paper describes the issues that ICS owners and operators face and introduces the international Society of Automation (ISA)/lnternational Electrotechnical Commission (IEC) 62443 [1-10] series of standards as the basis for an effective cybersecurity program. These standards have been developed by the ISA99 committee of the international Society of Automation and IEC Technical Committee 65 Working Group 10.

关键词： Cybersecurity Industrial Automation and Control systems (IACS) Supervisory Control and Data Acquisition (SCADA) systems distributed Control systems (DCS) Programmable Logic Controllers (PLC) operational technology (OT) enterprise information technology (IT) systems Internet of Things (loT) smart grid smart substations substation automation IEC-61850 [10] plant safety reliability communication configurations intelligent electronic devices and substation HMI

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An Optical Transceiver Reliability Study based on SFP Monitoring and OS-level Metric Data 23

An Optical Transceiver Reliability Study based on SFP Monito...

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23rd ieee/ACM international Symposium on Cluster, Cloud and Internet computing (CCGrid)

作者： Notaro, Paolo Yu, Qiao Haeri, Soroush Cardoso, Jorge Gerndt, Michael Huawei Technol Duesseldorf GmbH D-80992 Munich Germany Tech Univ Munich Chair Comp Architecture & Parallel Syst Munich Germany Tech Univ Berlin Chair Distributed & Operating Syst Berlin Germany Univ Coimbra Dept Informat Engn CISUC Coimbra Portugal

ISBN: (纸本)9798350301199

The increasing demand for cloud computing drives the expansion in scale of datacenters and their internal optical network, in a strive for increasing bandwidth, high reliability, and lower latency. Optical transceivers are essential elements of optical networks, whose reliability has not been well-studied compared to other hardware components. In this paper, we leverage high quantities of monitoring data from optical transceivers and OS-level metrics to provide statistical insights about the occurrence of optical transceiver failures. We estimate transceiver failure rates and normal operating ranges for monitored attributes, correlate early-observable patterns to known failure symptoms, and finally develop failure prediction models based on our analyses. Our results enable network administrators to deploy early-warning systems and enact predictive maintenance strategies, such as replacement or traffic re-routing, reducing the number of incidents and their associated costs.

关键词： hardware reliability optical network optical transceiver failure study datacenters cloud computing

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