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26th International conference on Electrical Machines and systems, ICEMS 2023

作者： Yang, Ming Wang, Qunjing Zhou, Rui Li, Guoli Wen, Yan Anhui University School of Electrical Engineering and Automation Hefei China Quality Control Anhui University Collaborative Innovation Center of Industrial Energy-Saving and Power Hefei China Anhui University National Engineering Laboratory of Energy-Saving Motor and Control Technology Hefei China Anhui University School of Internet Hefei China

ISBN: (纸本)9798350317589

In order to analyze and optimize the structure of existing permanent magnet spherical motors, a method for 3D motion singularity analysis of permanent magnet spherical motors is presented in this paper. This calculation model of the motion singularity is established on the basis of the spherical motor's torque model by judging that the torque value is too small. Using this model to calculate the distribution of motion singularities, we can judge whether the structure of the spherical motor is reasonable or not. For this model, a singularity representation method is presented to visually represent the specific distribution of singularities. This method can be used to compare different optimization schemes, and select the optimal structure with better motion performance. © 2023 IEEE.

关键词： Structural optimization

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Optimal Packet Transmission Rates for Platooning under Random Access C-V2X 96

Optimal Packet Transmission Rates for Platooning under Rando...

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IEEE 96th Vehicular Technology conference (VTC-Fall)

作者： Villamil, Andres Gonzalez, Arturo Fettweis, Gerhard Tech Univ Dresden Vodafone Chair Mobile Commun Syst Dresden Germany Tech Univ Dresden Ctr Tactile Internet Human Loop CeTI Dresden Germany Vodafone Tech Innovat Ctr Dresden Dresden Germany

ISBN: (纸本)9781665454681

The usage of wireless networks for networked controlled systems (NCS) impose constraints on the required radio resources to ensure the desired quality-of-control (QoC). Usually, control systems are designed regardless of the wireless system and could misuse current wireless technologies capabilities by utilizing more resources than required and limiting the number of users accessing the network. However, the goal of Communications-control Co-Design (CoCoCo) is to enable better usage of the communications resources by exploiting the knowledge of the degrees of freedom of the control system. This paper proposes a methodology to find optimal rates for a random access scheme to ensure string stability in a platoon of vehicles.

关键词： platooning CACC string stability communications-control co-design 5G-V2X networked control PHY layer

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Peer to Peer Information Inter-Change and network Coding to Improve Transmission Efficiency in Wireless Mesh network 2

Peer to Peer Information Inter-Change and Network Coding to ...

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2nd International conference on Augmented Intelligence and Sustainable systems, ICAISS 2023

作者： Vanakamamidi, Rama Krishna Chandu, P.M.S.S. Ponkumar, D. David Neels Senkamalavalli, R. Senior Soultion Architect Hcl Technology Ltd Andhra Pradesh Vijayawada India Department of Computer Science and Engineering Andhra Pradesh Puttur India VelTech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India East Point College of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India

ISBN: (纸本)9798350325799

Wireless Mesh networks (WMNs) have been widely used in various industries, including industrial control, environmental monitoring, and military operations. The performance of WMNs may be improved with the help of an exciting new technique called network coding (NC). In particular, NC is appropriate for WMN since the energy supply to the fixed backbone of WMNs is often limitless. However, coding collision is a serious issue that negatively impacts the performance of the network. To solve these issues, Peer to Peer (P2P) Information inter-change and network Coding (PINC) to improve transmission efficiency in WMN is proposed. The objective of this paper is to enhance transmission efficiency and minimize delay. This method P2P information interchange is a method for increasing data availability by leveraging data already existent among network peers. This mechanism uses the NC algorithm can make the most of the transmit channel quality and make the most of the cooperative P2P information sharing that is possible. Experimental results demonstrate that using the PINC mechanism enhances the throughput and reduces the computational overhead in the WMN. © 2023 IEEE.

关键词： network coding

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Managing IoT Cyber-Security Using Programmable Telemetry and Machine Learning

Managing IoT Cyber-Security Using Programmable Telemetry and...

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2023 International conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Sutariya, Kamal Pramanik, Kundan Kumar Parul University Piet Department of Cse India Arka Jain University Department of Engg. & It India

ISBN: (纸本)9798350322309

internet of Things (IoT) devices that are purchased from a variety of suppliers & installed in significant amounts are subject to increasing cybersecurity vulnerabilities. Consequently, it has become more crucial for telecom companies to control such devices. Current monitoring systems for communication analyze data through specialized speed on networking devices or thorough protocol analysis in programs, but these methods can be difficult, costly, rigid, and unable to scale. Using the SDN architecture together with ML, we harness the advantages of configurable motion-relied telemetry with adaptable information driven designs to control IoT gadgets depending on their system behavior in this article. Our 3 results are as follows: (1) Over the course of a half year period, we examine the network traffic patterns of 17 individual customer IoT devices in the laboratory as well as recognize a collection of traffic patterns (for every device) for whom the period characteristics tabulated at numerous timeframes (from a minute to an hour) characterize the connectivity behavior of different IoT gadget kinds, as well as their functioning stages (such as bootup, engaging with the subscriber effectively, or becoming inactive);(2) We create a multiple-level model of inferences which autonomously detect Iot systems from those which aren't IoTs, categories specific IoT device categories, & determine their operational statuses. (3) Then calculate the trade-off among expense & performance of our method and show the manner in which our tracking strategy can be utilized in practice for identifying behavioral changes. We teach the designs & test its effectiveness employing actual traffic patterns (firmware updates or cyberattacks). © 2023 IEEE.

关键词： internet of things

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Power System Transient Stability Assessment Based on Graph Neural network with Interpretable Attribution Analysis 4

Power System Transient Stability Assessment Based on Graph N...

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4th International conference on Smart Power and internet Energy systems (SPIES)

作者： Gu, Sili Qiao, Ji Zhao, Zixuan Zhu, Qiongfeng Han, Fujia China Elect Power Res Inst Dept Artificial Intelligence Applicat Beijing Peoples R China

ISBN: (纸本)9781665489577

The power transient stability analysis is one of the basis for determining the control strategy of power system security and stability. Considering the influence of power grid topology on the transient stability of power system, the transient stability evaluation model is constructed based on the graph attention neural network. The electrical components and their transient operation data are mapped to the graph data with the spatial topology characteristics of power system for model training, so as to improve the topological generalization performance of the model. The marginal contribution of input characteristics to the output of transient power angle stability evaluation model is quantitatively calculated based on Shapley additive explanation (SHAP), so as to improve the interpretability of data-driven method for transient power angle stability evaluation. The effectiveness of the proposed method is verified by the IEEE 39-bus system.

关键词： transient stability assessment graph neural network Shapley additive explanation

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Data-driven roughness estimation of additively manufactured samples using build angles

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MANUFACTURING LETTERS 2024年 41卷 1092-1099页

作者： Galarza, Jose Barron, Jorge, Jr. Ahmed, Farid Li, Jianzhi Univ Texas Rio Grande Valley 1201 W Univ Dr Edinburg TX 78539 USA

Achieving control of Laser Powder Bed Fusion ( L-PBF) over the quality of the print is the main motivation for finding an optimum set of parameters in the process. Surface roughness is one of the characteristics of the print that impacts the performance of the desired functionality. This research focus is to relate the build angle with the surface roughness on the L-PBF printed specimens and utilize machine learning methods for roughness estimation of geometric features with varying build angles. The EOS M290 L-PBF printer was used to print Inconel-718 coupons using standard process parameters while varying build angles from 20 to 90 degrees at fixed 5-degree intervals. The specimens' surface was analyzed using metrology tools and the data obtained was used for training the machine learning models. Machine learning methods are used to create regression models for estimating the roughness of the specimens using the build angle and location of the sample on the substrate. The findings of this study provide build angle-based predictive estimation of surface roughness of printed L-PBF parts. The machine learning model will help to make reliable decisions on choosing the build angle of a complex part based on the desired surface roughness of its geometric features.

关键词： Additive manufacturing laser powder bed fusion surface roughness machine learning neural network

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Multi-agent Reinforcement Learning for Energy Saving in Multi-Cell Massive MIMO systems 1

Multi-agent Reinforcement Learning for Energy Saving in Mult...

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1st IEEE International conference on Machine Learning for Communication and networking (IEEE ICMLCN)

作者： Cai, Tianzhang Wang, Qichen Zhang, Shuai Demir, Ozlem Tugfe Cavdar, Cicek KTH Royal Inst Technol Dept Comp Sci Stockholm Sweden TOBB ETU Dept Elect Engn Ankara Turkiye

ISBN: (纸本)9798350343205;9798350343199

We develop a multi-agent reinforcement learning (MARL) algorithm to minimize the total energy consumption of multiple massive MIMO (multiple-input multiple-output) base stations (BSs) in a multi-cell network while preserving the overall quality-of-service (QoS) by making decisions on the multi-level advanced sleep modes (ASMs) and antenna switching of these BSs. The problem is modeled as a decentralized partially observable Markov decision process (DEC-POMDP) to enable collaboration between individual BSs, which is necessary to tackle inter-cell interference. A multi-agent proximal policy optimization (MAPPO) algorithm is designed to learn a collaborative BS control policy. To enhance its scalability, a modified version called MAPPO-neighbor policy is further proposed. Simulation results demonstrate that the trained MAPPO agent achieves better performance compared to baseline policies. Specifically, compared to the auto sleep mode 1 (symbol-level sleeping) algorithm, the MAPPO-neighbor policy reduces power consumption by approximately 8.7% during low-traffic hours and improves energy efficiency by approximately 19% during high-traffic hours, respectively.

关键词： BS control for energy saving antenna switching massive MIMO multi-agent reinforcement learning

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Rural Micro-energy network Economic Coordination control Method Based on rural internet of Things

Rural Micro-energy Network Economic Coordination Control Met...

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IEEE Asia Power and Energy Engineering conference (APEEC)

作者： Shengduo Shi Tianjun Jing Hailong Zhang Zhen Niu Jinming Zhang Yongxian Wang College of Information and Electrical Engineering China Agricultural University Beijing China State Grid Gansu Electric Power Company State Grid Corporation of China Lanzhou China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

In China, there are still a lot of small and medium capacity users of distributed heating in addition to the central heating mode. Starting from the goal of carbon peaking and carbon neutrality, distributed clean energy should be used to achieve local heating, while distributed photovoltaic heating has uncertainties caused by meteorological factors. Light storage composite method can improve the performance and combined with heating control. It is expected to achieve comprehensive energy efficiency and green energy supply. Based on the rural internet of Things and optical heat storage internet of Things control system, this paper proposes a decentralized and coordinated control method suitable for small and medium capacity optical heat storage network, mainly considering economy, considering heating quality and green and low-carbon benefits. This method uses fuzzy control method and determines membership function according to expert experience and cloud model. The selling and purchasing electric power sequence of the micro-energy network in different periods is regulated to improve the operation economy of the photovoltaic thermal storage micro-energy network.

关键词： Heating systems Photovoltaic systems Uncertainty Electricity Heat engines Microgrids Optical fiber networks

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A Secure Deep Q-Reinforcement Learning Framework for network Intrusion Detection in IoT-Fog systems

A Secure Deep Q-Reinforcement Learning Framework for Network...

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2024 OPJU International Technology conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Bebortta, Sujit Tripathy, Subhranshu Sekhar Sharma, Vandana Behera, Jnana Ranjan Nayak, Aishwarya Ravenshaw University Department of Computer Science Cuttack753003 India Kiit Deemed to Be University School of Computer Engineering Bhubaneswar751024 India Department of Computational Sciences Delhi NCR Campus India Kiit Deemed to Be University School of Electronics Bhubaneswar751024 India Driems University Department of Computer Sceince & Engineering Cuttack74022 India

ISBN: (纸本)9798350373783

IoT-Fog system security depends on intrusion detection system (IDS) since the growing number of internet-of-Things (IoT) devices has increased the attack surface for cyber threats. The dynamic nature of cyberattacks often makes it difficult for traditional IDS techniques to stay up to date. Because it can adapt to changing threat landscapes, deep Q-reinforcement learning (DQRL) has become a potential technique for ID in IoT-Fog situations. In this paper, an IDS system for IoT-Fog networks based on DQRL is proposed. The suggested solution makes use of fog nodes' distributed computing power to provide real-time IDS with excellent accuracy and minimal latency. With feedback from the network environment, the DQRL agent learns to recognize and categorize network traffic patterns as either normal or intrusive. Adaptive exploration techniques, effective reward functions, and deep neural networks for feature extraction are adopted by the system to improve predictive performance. The evaluation findings show that, in terms of detection accuracy, precision, recall and f-measure, the proposed DQRL provides flexibility to changing threat patterns as compared to conventional IDS techniques. A vast array of cyberattacks, such as malware infections, denial-of-service (DoS) attacks, and command-and-control communications, are successfully recognized and categorized by the system. It is possible that the suggested solution will be crucial in safeguarding IoT-Fog networks and preventing cyberattacks © 2024 IEEE.

关键词： network intrusion

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DASH rate control using game theory to consider user video preference 36

DASH rate control using game theory to consider user video p...

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36th International conference on Information networking (ICOIN)

作者： Yanagisawa, Takumi Miyata, Sumiko Shibaura Inst Technol Koto Ku Toyosu 3-7-5 Tokyo 1350061 Japan

ISBN: (纸本)9781665413329

Dynamic adaptive streaming over HTTP (DASH) is the most widespread internet video delivery service system. In DASH, a bitrate is selected dynamically to appropriately share the bandwidth of the server among multiple users. While most of the existing rate-selection methods have been based on improving quality of service (QoS), quality of experience (QoE) methods that express user satisfaction with the quality of video content have been attracting the attention of service providers and network providers. In addition, some studies show that user preference affects QoE. Therefore, we both propose and demonstrate the effectiveness of a rate-selection method based on game theory that considers user preference for video streaming.

关键词： Adaptive systems Bit rate quality of service Bandwidth Streaming media quality of experience Servers

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