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检索条件"任意字段=Conference on Internet Quality and Performance and Control of Network Systems"

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7th International conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2023

7th International Conference on Artificial Intelligence in R...

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7th International conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2023

ISBN: (纸本)9783031606281

The proceedings contain 48 papers. The special focus in this conference is on Artificial Intelligence in Renewable Energetic systems. The topics include: Attacks and Countermeasures in Wireless Sensor networks;A System for Monitoring Hydroponic Plants in Greenhouse Using WSN, IoT and RnE;implementation of Smart Parking Using an IoT Based System;Dynamic Load Balancing in Cloud-IoT Based on Neural network Classification and GGA Optimization;blockchain-Based Identity Management;application of Machine Learning Forecasting Model for Renewable Generations of Adrar’s Power System;Using the PSO Algorithm to Optimize a Self-tuning PID-Type Fuzzy controller for Indoor Temperature;Kalman MPPT controller for Home Turbine Connected to the Utility Grid;Variation of the Speed of a DC Motor Powered by the Photovoltaic Generator Using MPPT control;MOTH-FLAME-MPPT Algorithms of PV Panels Under PSC;Improving Wind Turbine performance in Residential Grid-Connected System Operating at Variable Wind Conditions with WOA-MPPT Based Strategy;Improved Power quality with Active Shunt Power Filter Based on MPPT Firefly controller of a Wind Turbine;Optimal Design of an Off-Grid Photovoltaic-Battery System for UAV Charging in Wildlife Monitoring;Efficient Solar Energy Harvesting and Power Management for Electric Vehicles Using MPPT Under Partial Shading Conditions and Battery/Super-Capacitor Integration;New Hybrid Optimized MPPT Technique for PV systems Under Partial Shadow Conditions;frequency Characterization of Water Solutions Used in Electrolysis for Production of H2;the Traction Chain of an Electric Vehicle;A Comparative Study of Speed control Strategies for In-Wheel Direct Current Machines in Electric Vehicles: PI, Fuzzy Logic, and Artificial Neural networks.

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7th International conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2023

7th International Conference on Artificial Intelligence in R...

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7th International conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2023

ISBN: (纸本)9783031606311

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Research and implementation of network service quality monitoring and multi-authority message warning based on IPv6

Research and implementation of network service quality monit...

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2022 IEEE Asia-Pacific conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Zhao, Liuyin Ke, Li Wuhan University of Technology Network Information Center Wuhan China Zhongnan University of Economics and Law Information Management Department Wuhan China

ISBN: (纸本)9781665409025

The system mainly realizes the monitoring and early warning of the network layer and application layer in the ipv6 environment, provides comprehensive network monitoring services, can monitor network performance and potential faults in real time, and ensures the stable and efficient operation of business systems in the network environment. Real-time visual monitoring is realized, allowing users to obtain complete visibility into the entire network. Innovatively integrates the intelligent power environment monitoring system of the computer room based on the internet of Things to provide protection for the external environment in which the IPv6 network system can maximize its effect, fill the current market vacancy, and has forward-looking practical significance. The network early warning information can be notified to the corresponding manager in a timely and accurate manner. It supports SMS and email warning methods. Users can choose a single warning method or a combination of multiple media for warning, which improves the success rate of website content change alarms. © 2022 IEEE.

关键词： internet of things

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12th International conference on Recent Trends in Computing, ICRTC 2024

12th International Conference on Recent Trends in Computing,...

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12th International conference on Recent Trends in Computing, ICRTC 2024

ISBN: (纸本)9789819789450

The proceedings contain 34 papers. The special focus in this conference is on Recent Trends in Computing. The topics include: Deep Learning-Based Prediction of Human Ageing Related Proteins;the Insight of Clustering Algorithms for Emerging networking Paradigms;Revolutionizing Cardiovascular Health: Exploring the Potential of AI-Driven Approaches in Diagnosing Arrhythmia Disorders;humor Detection in Telugu Social Media Text Using Cost-Sensitive Learning and Indian Language Embeddings;empirical Comparison of Sleep Disorder Prediction Using Machine Learning Techniques;securing Smart Grids: Decentralized Anomaly Detection Using Federated Learning and Recurrent Neural networks;machine Learning-Powered Intrusion Detection for network Security;secure Chat System: Harnessing the Power of Hybrid Encryption for Enhanced Security and Confidentiality;deep Neural networks for Early Diabetes Mellitus Prediction;advancements in Image Deblurring and performance Metrics Using Deep Learning Technique;emotion-Levitating Music Recommendation System Through Real-Time Facial Recognition;smartVoice TrashMate: The Intelligent Voice-controlled Trash Bin;an Innovative Image Enhancement Algorithm for Color Filter Array Images: A Novel Approach;Enhancing Secure and Efficient Communication in Free-Space Optical networks Using Spectral Amplitude Coding - OCDMA Technology;enhancing Citrus Fruit Classification and quality Assessment Through Advanced Machine Learning Techniques;connecting Health for a Better Tomorrow Through internet of Medical Things;image Processing in Retail Marketing: Innovations for Customer Engagement, Sales, and Operational Efficiency;Leaf Checker: AI-Based Plant Diagnostic Tool Using Alexnet and Mobilenet;ioT-Supported Indoor Navigation System Using Machine Learning Technique;a Customizable Virtual Assistant Enhanced with Vision and Speech Capabilities;An Unequal Cluster-Based Routing Mechanism Using Lyrebird Optimization Algorithm to Achieve network Longevity in WSNs.

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Research on Real-time Monitoring System of Multi-scenario Health Data Based on internet of Things 3

Research on Real-time Monitoring System of Multi-scenario He...

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3rd International conference on Digital Society and Intelligent systems, DSInS 2023

作者： Wang, Hongyang Huo, Jiuyuan Hu, Jun Wang, Tingjuan School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China Gansu YiWangKeJi Network Technology Co. LTD Lanzhou730070 China

ISBN: (纸本)9798350331387

para>With the continuous development of society and people's growing concern for health, health monitoring technology has become an important part of our lives. For this reason, this study designs and implements a multi-scene real-time health data monitoring system based on the internet of Things. The system adopts innovative technologies such as smart bracelet, Bluetooth gateway and message queue telemetry transfer (MQTT) to collect and transmit health data in real time. In addition, users can adjust the parameters of the data collection terminal through the remote control function. Through the web interface, users are able to conveniently view their health data in real time. The experimental results show that the data collected by this monitoring system has high accuracy, multi-scene adaptability and real-time performance. Meanwhile, the system is easy to operate and understand, providing users with a convenient experience. This will bring important technological innovation and practical application value to the field of health monitoring, providing people with more convenient and efficient health monitoring services. Future research directions can include optimising system performance, expanding application scenarios, etc., which will help promote the further development of health monitoring technology and protect people's health. © 2023 IEEE.

关键词： internet of things

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Evaluation of Failure Analysis of IoT Applications Using Edge-Cloud Architecture 16

Evaluation of Failure Analysis of IoT Applications Using Edg...

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16th Annual IEEE International systems conference (SysCon)

作者： Jassas, Mohammad S. Mahmoud, Qusay H. Ontario Tech Univ Dept Elect Comp & Software Engn Oshawa ON L1G 0C5 Canada

ISBN: (纸本)9781665439923

The most important features of the internet of Things (IoT) application architecture are connectivity, detection, scalability, intelligence and integration. IoT devices should be designed and installed so that they can be scaled up or down based on business and application requirements. Cloud computing has faced various challenges due to its rapid expansion. Due to the growing number of IoT devices and the data they generate, cloud computing cannot meet quality-of-service requirements such as low latency due to its remote geographic location. Edge computing models are urgently needed to develop IoT applications. This paper investigates the impact of combining IoT, cloud, and edge computing for failure analysis and prediction. Furthermore, based on the Edge-Cloud architecture, we offer an architecture for a highly reliable and available IoT application that can support the new paradigm of cloud-IoT applications. The proposed model can reduce the number of failed tasks for cloud-IoT applications. We have also examined how many tasks fail when different architectures are used. The evaluation results show that failed tasks and CPU usage have decreased after applying the "Edge and Cloud" architecture. Using "Edge and Cloud" architecture can also control network traffic compared to other architecture.

关键词： Cloud computing Computational modeling Scalability Failure analysis Computer architecture Telecommunication traffic internet of Things

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Design and Development of an Integrated End of Line Testing Platform for Electronic control Units

Design and Development of an Integrated End of Line Testing ...

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2022 International conference on Communication, Computing and internet of Things, IC3IoT 2022

作者： Deepa, M. Askarali, N. Psg Department of Electronics and Communication Engineering Institute of Technology and Applied Research Coimbatore India

ISBN: (纸本)9781665479950

Electronics play an important role in today's home appliances. Many electronic control units (ECUs) are used to make everyday life and home activities more enjoyable. Fault detection and identification are the characteristics of high performance and quality production systems in checking and monitoring programs. These systems are designed in a way that allows real-time detection and error detection to realize these qualities. Errors are indicated by diagnosis, and the diagnosis identifies the root cause. ECU is a real-time microcontroller-based system equipped with multiple sensors and actuators for collection of data and control. The primary purpose of the test is to reliably detect non-functioning units;however, the ultimate goal is to reduce the rejection rate and increase output. More and more quality tests are being replaced by 100% automated testing by human operators. Accurate identification of the key characteristics and features of the device under test is required to identify the overall quality, perform quick measurements that provide useful data, and obtain the correct pass/fail result. Without separating the electronic and electrical systems, ECU firmware allows diagnostic and self-detection results to be read at the end of line testing station. This system is implemented by connecting the 'test tool' to the UART line provided by the ECU. The design of the PC-based integrated test platform is described in this article, ensuring that ECU development is not delayed by the absence of an actual tester at the end of the production line. © 2022 IEEE.

关键词： Domestic appliances

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Resilient Robust Model Predictive control under Adaptive Event-Triggered Mechanism

Resilient Robust Model Predictive Control under Adaptive Eve...

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internet of Things, Automation and Artificial Intelligence (IoTAAI), International conference on

作者： Yanye Yu Huangju Li Jianhua Wang Min Zhou Jiawei Zuo School of Engineering Huzhou University Huzhou China Huzhou Key Laboratory of Intelligent Sensing and Optimal Control of Industrial Systems Huzhou China

ISBN: (数字)9798350386974

ISBN: (纸本)9798350386981

The problem of resilient robust model predictive control (RMPC) with hard constraints based on an adaptive event-triggered mechanism for a class of polytopic uncertain systems is investigated in this article. To reduce the burden of network communication, a novel adaptive event-triggering mechanism is introduced between the sensor and the controller (S/C) network. The objective of this paper is to design a resilient RMPC controller while considering the system performance degradation caused by the adaptive event-triggered mechanism, aiming to maintain high system performance while conserving communication resources. Moreover, by solving an online optimization problem, sufficient conditions are obtained to ensure that all states of the system are in the time-varying terminal constraint set. To conclusively validate the efficacy of the proposed resilient RMPC algorithm under the adaptive event-triggered mechanism, we adopt a specific distillation parameter example for illustration.

关键词： Uncertain systems Sufficient conditions Adaptive systems System performance systems architecture Prediction algorithms Stability analysis Resource management Time-varying systems Predictive control

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Research on industrial internet intrusion detection model based on optimized BI-GRU

Research on industrial internet intrusion detection model ba...

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2022 International conference on Signal Processing and Communication Technology, SPCT 2022

作者： Shi, Wenqiang Wang, Hao Gong, Yuanlin Xu, Hao School of automation Chongqing University of Posts and Telecommunications Chong Qing China

ISBN: (纸本)9781510664333

The intrusion detection model based on deep learning has become a research hotspot in the field of network security, aiming at the high FPR and low DR of current intrusion detection systems, this paper proposes an anomaly detection model based on deep learning. The system is first optimized by particle swarm optimization. Data feature extraction, and then through the fusion of MLP's bidirectional GRU model to better mine the information contained in the data set and its correlation, and improve the efficiency and quality of feature extraction. Finally, experiments show that the model has good performance, with a detection readiness rate of 98.74%, a false positive rate of 0.029, and a detection rate of 98.42%. The results show that the detection effect of PSO+BI-GRU+MLP is better than other algorithm models. © 2023 SPIE.

关键词： Feature extraction

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13th Computer Science Online conference, CSOC 2024

13th Computer Science Online Conference, CSOC 2024

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13th Computer Science Online conference, CSOC 2024

ISBN: (纸本)9783031705946

The proceedings contain 108 papers. The special focus in this conference is on Computer Science Online. The topics include: Methodology for Solving the Problem of Classification of Professional Orientation Using Encephalogram Data;Investigation of the Influence of External Conditions on the Process of Automated Landing of an UAV on a Seismic Sensor Using Technical Vision;methodology for a Business Intelligence Platform by Using Oracle 19C Database Engine and its Limitations;control of the State of Agrocenosis and Soil Environment According to Remote Sensing Data;design of a Web Platform for Smoke and Flood Monitoring in a Data Center Based on the internet of Things (IoT);enhancing quality of Experience in Omnidirectional Video: Strategies Overview;optimizing 360° Video Delivery: Advancements and Strategic Approaches;identification and Interpretation of Significant Factors Influencing Client Defaults in Microfinance Institutions Using Machine Learning Methods;a Study About Complexity of Social network;Limitations and Benefits of the ChatGPT for Python Programmers and Its Tools for Evaluation;Security Testing in IEEE 802.11 Wireless networks;technology Transfer in the Field of Additive Medical Technologies Based on Patent Informatics Research;personnel Privacy and Organisational Data: The Awareness and Policy Enforcement for Smartphone Security Among the Malaysian Armed Forces Personnel;Forensic Analysis of Cyber Attacks Using the Cyber Kill Chain Model to Enhance Antivirus Protection in an IT Solutions Company;integral Assessment of Cryptocurrency quality;proposed Model for the Detection of Diabetic Retinopathy Using Convolutional Neural networks;proposed Ransomware Detection Model Based on Machine Learning;unbiasing on the Fly: Explanation-Guided Human Oversight of Machine Learning Decisions;Analyzing Nonlinear Behavior Sequences Through ASM.

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