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检索条件"任意字段=3rd IEEE International Conference on Distributed Computing in Sensor Systems"

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3rd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

3rd IEEE International Conference on Distributed Computing a...

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3rd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

ISBN: (纸本)9798350318609

The proceedings contain 299 papers. The topics discussed include: time series modelling approach for predictive analytics;research on the recognition of accounting information distortion by random forest algorithm;reconstruction and update of 3D model of mechanical products based on 3D point cloud data;prediction of soil organic carbon content using machine learning based fuzzy C-means clustering;fault detection and classification in power transmission lines using discrete wavelet transform-based swish recurrent neural network;immersive dramatic space 3D layout using panoramic image reconstruction algorithm;multi-objective optimization of noise in a high-speed railway by a hybrid algorithm;new energy vehicle customer mining model based on machine learning algorithm;and robotization of agriculture using image processing techniques.

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3rd ieee 2022 international conference on computing, Communication, and Intelligent systems, ICCCIS 2022

3rd IEEE 2022 International Conference on Computing, Communi...

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3rd ieee international conference on computing, Communication, and Intelligent systems, ICCCIS 2022

ISBN: (纸本)9781665462006

The proceedings contain 168 papers. The topics discussed include: communication induced checkpointing based fault tolerance mechanism – a review and CIAC-FTM framework in IoT environment;a semantic review on challenges, trends towards defensive ids in Internet of things;semantic segmentation in medical image based on hybrid Dlinknet and UNet;smart car - one stop for all automobile needs;hybrid cryptography algorithm for the internet of things based plant information security;5G network: architecture, protocols, challenges and opportunities;fiber Bragg grating temperature sensor and calibration scheme in high magnetic field environment : an application for aluminum electrolysis cell in potline;federated learning with blockchain: a study of the latest decentralized couple;an enhanced copy-deterrence scheme for secure image outsourcing in cloud;decentralized data privacy protection and cloud auditing security management;land registry and title management using blockchain and smart contracts;breast cancer modeling and prediction combining machine learning and artificial neural network approaches;and confluence of artificial intelligence and blockchain powered smart contract in finance system.

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Enhancing Energy Efficiency of Underwater sensor Network Routing Aiming to Achieve Reliability 3

Enhancing Energy Efficiency of Underwater Sensor Network Rou...

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3rd international conference on distributed computing and High Performance computing, DCHPC 2024

作者： Tarif, Mehran Effatparvar, Mehdi Moghadam, Babak Nouri Islamic Azad University Ardabil Branch Department of Computer Engineering Ardabil Iran

ISBN: (纸本)9798350381580

In response to the demands and harsh conditions of underwater environments, developing sensor networks and underwater Internet of Things (IoT) has paved the way for wireless communication, ocean exploration, and various research applications. However, challenges such as increasing failure rates and decreasing network efficiency remain open issues, hindering the achievement of quality of service (QoS) in underwater sensor networks. Addressing resource constraints, including processing power, memory, bandwidth, and energy resources, adds to the complexity of supporting network service quality. This study aims to investigate the service quality requirements in protocols and highlight the weaknesses of ongoing research in this field. Finally, a routing solution based on fuzzy logic is proposed, which provides better results than recent methods in tests of energy consumption rate, Jain's fairness index, efficiency, and reliability. © 2024 ieee.

关键词： Quality of service

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Demo: SenShaMart - A sensor Sharing Marketplace for IoT 43

Demo: SenShaMart - A Sensor Sharing Marketplace for IoT

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43rd ieee international conference on distributed computing systems (ICDCS)

作者： Dawod, Anas Georgakopoulos, Dimitrios Jayaraman, Prem Prakash Milovac, Josip Karabotic Liao, Kewen Chrysanthis, Panos K. Swinburne Univ Technol Melbourne Australia Australian Catholic Univ Peter Faber Business Sch HilstLab Sydney Australia Univ Pittsburgh Pittsburgh PA USA

ISBN: (纸本)9798350339864

The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services that implement that FAIR (Findable, Accessible, Interoperable, Reusable) principles of IoT, SenShaMart incorporates a specialized blockchain that manages all the information its services need to allow different parties in IoT to describe, query, integrate, pay for, and use IoT sensors and their data. The paper presents the SenShaMart's architecture, implementation, evaluation, and demonstration.

关键词： Blockchain Internet of Things sensor Discovery sensor Sharing Data Marketplace

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Task Path Planning System for Autonomous Feeding Robots in Three-Dimensional Farms underYOLOV3 Algorithm 3

Task Path Planning System for Autonomous Feeding Robots in T...

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3rd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： He, Xinyi Guo, Wu Zhang, Jianlong Intelligent Manufacturing College Guangdong Lingnan Institute Of Technology Guangdong Qingyuan China

ISBN: (纸本)9798350318609

Traditional farm autonomous feeding robot path planning systems have low target detection accuracy, poor planning efficiency, and insufficient adaptability to environmental changes when facing complex farm environments. This article aims to solve the problems existing in traditional systems by introducing the YOLOv3 algorithm, in order to improve the performance and efficiency of robots in autonomous feeding tasks on farms. Firstly, this article utilizes the YOLOv3 algorithm to achieve target detection and localization in the system, and then uses sensor data fusion technology to perceive the environment and construct a map. It then integrates map information for path planning and optimization, achieving system adjustment and obstacle avoidance, and finally selects commonly used path planning algorithms for experimental comparison. The results show that the target detection accuracy of the task path planning system for autonomous feeding robots in three-dimensional farms based on the YOLOv3 algorithm is the highest, exceeding 99%. In addition, the operating efficiency of the system is also the highest, above 95%. In summary, the YOLOv3 algorithm is very suitable for the research of task path planning systems for autonomous feeding robots in three-dimensional farms. © 2024 ieee.

关键词： Feeding

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distributed Blockchain-SDN Models for Robust Data Security in Cloud-Integrated IoT Networks 3

Distributed Blockchain-SDN Models for Robust Data Security i...

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3rd international conference on Automation, computing and Renewable systems, ICACRS 2024

作者： Haritha, Koya Vellela, Sai Srinivas Roja, D. Vuyyuru, Lakshma Reddy Malathi, Nallapu Dalavai, Lavanya Dept. of CSE-Data Science Chalapathi Institute of Technology AP Guntur522016 India Dept. of CSE KoneruLakshmaiah Education Foundation AP Vaddeswaram India Dept. of CSE-DS KKR & KSR Institute of Technology and Sciences AP Guntur522017 India

ISBN: (纸本)9798331532420

Blockchain and SDN are combined in the "DistB-SD Cloud" architecture to secure and execute cloud-integrated IoT data. Cloud computing Management and Services, distributed Secure Blockchain Methodology, SDN Environment, and Data Extraction comprise the architecture. SDN-enabled devices safely gather and process sensor data in the data plane, while OpenFlow and OpenStack handle network component communication in the control plane. The application layer improves network administration with dynamic configuration and data analytics. distributed nodes and hash chains ensure system integrity in blockchain-based access control and ledger maintenance. Blockchain and SDN improve security, privacy, and scalability by resisting attacks. The architecture outperforms OpenFlow-based SDN models in throughput and bandwidth, proving its stability under different network conditions. The study shows that the suggested "DistB-SD Cloud" achieves increased throughput (22.1 KB/s) and bandwidth (1.9 GB/s) when nodes and packet arrival rates increase, making it a feasible solution for safe and scalable cloud computing in IoTbased systems. © 2024 ieee.

关键词： Cloud security

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Digital Test Platform of Train Control System Based on distributed Hybrid Cloud Platform 3

Digital Test Platform of Train Control System Based on Distr...

引用

3rd international conference on Cloud computing, Big Data Application and Software Engineering, CBASE 2024

作者： Qiu, Zhaoyang Zhang, Shuming Wen, Jiakun Institute Group Co Ltd Test & Verification Center China Railway Signal and Communication Research and Design Beijing China

ISBN: (纸本)9798331506582

With the continuous development of train operation control technology, the iteration of train operation control systems has been accelerated, leading to an increasing workload of system testing. Currently, most system tests rely on manual construction of test scenarios in semi-physical simulation testing environments, resulting in high workload for testers, low testing efficiency, and poor test coverage. To address these issues, this paper proposes the construction of a digital system testing platform for rail transit signaling systems based on a distributed hybrid cloud platform. First, the system framework of the distributed hybrid cloud platform is designed. Then, an automatic deployment scheme for the test environment based on templates is devised. Following that, a digital testing toolchain is developed. Ultimately, a digital testing platform for train control systems based on the distributed hybrid cloud platform is established, achieving automation, intelligence, and digitization of system testing. © 2024 ieee.

关键词： Cloud platforms

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Proceedings of the 3rd ieee international conference on Power Electronics, Intelligent Control and Energy systems, ICPEICES 2024

Proceedings of the 3rd IEEE International Conference on Powe...

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3rd ieee international conference on Power Electronics, Intelligent Control and Energy systems, ICPEICES 2024

ISBN: (纸本)9798350387193

The proceedings contain 216 papers. The topics discussed include: implementation of a wireless energy monitoring and databasing system using PLC;optimizing the integration of distributed generation, shunt capacitors, and electric vehicle charging stations into radial distribution systems;comparative analysis of TFET structures for low power sensor design;comparison of PID tuning methods for buck converter system;frequency control of power system under denial of service attack;GACNNXAI: employing genetic algorithm-enhanced convolutional neural networks and explainable artificial intelligence and its applications;and implementation of a non-invasive PCB embedded Rogowski coil current sensor for control of high frequency GaN LLC resonant converter with active rectification.

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2024 3rd international conference on distributed computing and High Performance computing, DCHPC 2024

2024 3rd International Conference on Distributed Computing a...

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3rd international conference on distributed computing and High Performance computing, DCHPC 2024

ISBN: (纸本)9798350381580

The proceedings contain 21 papers. The topics discussed include: enhancing the performance of photonic crystal and gates with machine learning optimization;bitcoin price prediction based on financial data, technical indicators, and news headlines sentiment analysis using CNN and GRU deep learning algorithms;promoting cybersecurity knowledge via gamification: an innovative intervention design;modeling and verification of the causal broadcast algorithm using colored Petri Nets;GPU-based parallel technique for solving n-similarity problem in textual data mining;a novel approach for specification and verification of symmetric distributed algorithms using spin;optimizing geophysical workloads in high-performance computing: leveraging machine learning and transformer models for enhanced parallelism and processor allocation;and rational Jacobi kernel functions: a novel massively parallelizable orthogonal kernel for support vector machines.

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distributed Classification by Divide and Conquer Approach 3

Distributed Classification by Divide and Conquer Approach

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3rd international conference on computing and Machine Intelligence (ICMI)

作者： Chen, Max Y. Wu, Qiang Illinois Math & Sci Acad 1500 Sullivan Rd Aurora IL 60506 USA Middle Tennessee State Univ Dept Math Sci Murfreesboro TN 37132 USA

ISBN: (纸本)9798350372977;9798350372984

In this paper, we investigate the efficacy of the divide and conquer approach for implementing distributed logistic regression and distributed support vector machine (SVM) algorithms for classification of large-scale datasets. This approach is designed to handle datasets that exceed the capacity of a single processor, necessitating the partitioning of data into multiple subsets. Logistic regression or SVM is then applied to each subset, yielding individual local classifiers. Subsequently, a global classifier is derived by aggregating these local classifiers to make the final decision. We propose three strategies for the aggregation stage: voting based on predicted labels, averaging of real-valued predictions, and averaging of posterior probabilities. Our analysis reveals that for distributed logistic regression, probability averaging is the most robust approach and is therefore recommended. Conversely, in the context of distributed SVM, probability averaging requires additional modeling but has a minimal impact on the performance. Therefore, functional averaging is recommended instead.

关键词： distributed machine learning logistic regression support vector machine divide and conquer

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