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TechRxiv 2023年

作者： Du, Hongyang Wang, Jiacheng Niyato, Dusit Kang, Jiawen Xiong, Zehui In Kim, Dong The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

The next generation of Internet services, such as Metaverse, rely on mixed reality (MR) technology to provide immersive user experiences. However, limited computation power of MR headset-mounted devices (HMDs) hinders the deployment of such services. Therefore, we propose an efficient information-sharing scheme based on full-duplex device-to-device (D2D) semantic communications to address this issue. Our approach enables users to avoid heavy and repetitive computational tasks, such as artificial intelligence-generated content (AIGC) in the view images of all MR users. Specifically, a user can transmit the generated content and semantic information extracted from their view image to nearby users, who can then use this information to obtain the spatial matching of computation results under their view images. We analyze the performance of full-duplex D2D communications, including the achievable rate and bit error probability, by using generalized small-scale fading models. To facilitate semantic information sharing among users, we design a contract theoretic AI-generated incentive mechanism. The proposed diffusion model generates the optimal contract design, outperforming two deep reinforcement learning algorithms, i.e., proximal policy optimization and soft actor-critic algorithms. Our numerical analysis experiment proves the effectiveness of our proposed methods. © 2023, CC BY.

关键词： Reinforcement learning

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Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation

Anomaly Detection Based on Principle of Justifiable Granular...

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2023 China Automation Congress, CAC 2023

作者： Du, Sheng Ma, Xian Li, Xiang Wu, Min Cao, Weihua Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul Sariyer Turkey

ISBN: (纸本)9798350303759

Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.

关键词： Time series

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On the Generalization of Machine-Learning-aided QoT Estimation in Optical Networks 32

On the Generalization of Machine-Learning-aided QoT Estimati...

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32nd Wireless and Optical Communications Conference, WOCC 2023

作者： Gao, Hanyu Zhang, Liang Zhang, Bin Chen, Xiaoliang Li, Zhaohui School of Electronics and Information Technology Sun Yat-sen University Guangdong Provincial Key Labratory of Optoelectronic Information Processing Chips and Systems Guangzhou China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai China George Mason University Department of Electrical and Computer Engineering FairfaxVA22030 United States

ISBN: (纸本)9798350337150

This paper presents a composable machine learning method for generalizing the quality-of-transmission (QoT) metric estimation in optical networks. The composable machine learning approach characterizes this metric for lightpaths of arbitrary lengths by compositions of launch, propagation and readout modules. Results verify the feasibility of the design and show its successful application in facilitating autonomous lightpath provisioning. © 2023 IEEE.

关键词： Fiber optic networks

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A Generic Load Flow Solution for Droop-Controlled AC Microgrids Considering Electric Vehicle Loads

A Generic Load Flow Solution for Droop-Controlled AC Microgr...

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International Conference on Power Electronic Drives

作者： Ghanshyam Meena Akhilesh Mathur V. P. Singh Krishna Murari Sukumar Kamalasadan Department of Electrical Engineering Malaviya National Institute of Technology Jaipur Rajasthan India Electrical Engineering and Computer Science Department The University of Toledo Toledo Ohio USA Department of Electrical Engineering Power Energy and Intelligent Systems Laboratory EPIC University of North Carolina at Charlotte Charlotte NC USA

ISBN: (数字)9798350372472

ISBN: (纸本)9798350372489

Microgrids (MGs) have become more unpredictable due to integration of renewable generation sources. Several methods are used to solve load flow problems in MGs. Load flow analysis is a complex problem for islanded MGs due to the absence of slack bus and dependency of active power generation of droop-controlled DGs on frequency. In this paper, a Modified Newton Raphson (MNR) approach is used to perform load flow analysis of isolated MGs considering various types of electric vehicle (EV) loads. The presented method has been validated on 6-bus and 38-bus test systems of the islanded microgrid to give an accurate and simple approach for computing the load flow solutions.

关键词： Renewable energy sources Microgrids Drives Electric vehicles Software Power electronics Distributed power generation Planning MATLAB Load flow analysis

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AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharing

arXiv

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arXiv 2023年

作者： Du, Hongyang Wang, Jiacheng Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

关键词： Reinforcement learning

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Efficient Evaluation of Short-Circuit Faults in Active Distribution Networks

Efficient Evaluation of Short-Circuit Faults in Active Distr...

引用

International Conference on Power Electronic Drives

作者： Ghanshyam Meena Akhilesh Mathur V. P. Singh Krishna Murari Sukumar Kamalasadan Department of Electrical Engineering Malaviya National Institute of Technology Jaipur Rajasthan India Electrical Engineering and Computer Science Department The University of Toledo Toledo Ohio USA EPIC and Department of Electrical Engineering Power Energy and Intelligent Systems Laboratory University of North Carolina at Charlotte Charlotte NC USA

ISBN: (数字)9798350372472

ISBN: (纸本)9798350372489

Short-circuit problems in unbalanced radial distribution networks have become more common as a result of distributed generation connectivity and smart grid advancements. An accurate and effective strategy for assessing these faults due to short circuits is presented in this study. In contrast to traditional methods, this approach uses relationship matrices that are created expressly to take use of distribution network's radial characteristics. Through the examination of variations in bus voltages, bus current injections, and branch currents during fault conditions, the suggested method formulates the analysis of various fault types. The accuracy of developed method has been validated on IEEE-123 bus modified test network by comparing the obtained results with PSCAD/EMTDC simulation results.

关键词： Accuracy Simulation Distribution networks Drives Power electronics Distributed power generation Smart grids Circuit faults Active distribution networks

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Bilateral Teleoperation Control Using Unified Interactive Model for Manipulation in Contact Environment

Bilateral Teleoperation Control Using Unified Interactive Mo...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Yang, Xiao Huang, Fanghao Gu, Jason Chen, Zheng Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China Zhejiang University Ocean College Zhoushan316021 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada Zhejiang Laboratory Hangzhou311100 China

ISBN: (纸本)9798350325706

In this paper, a novel bilateral teleoperation control is designed specifically for manipulation in contact environment. Firstly, serval interaction conditions (e.g., free motion and rigid interaction) are defined and unified into one equation as the designed unified interactive model, which can also be utilized as a control objective. Based on this model, a remote hybrid motion/force controller is designed for remote robot, which achieves the good position and force tracking, and ensures the precise and safe contact force that helps reduce the workload of operator. Subsequently, the contact force is reconstructed in the local side by estimating and transmitting the non-power environment coefficient from remote side, which provides the operator with accurate force feedback. Since the coefficient replaces the direct transmission of force signal in the communication channel, the traditional power-cycle problem is essentially avoided, which guarantees the stability of teleoperation system under communication time delays. Comparative experiments are implemented to verify the effectiveness of proposed method for teleoperated manipulation. © 2023 IEEE.

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Annapoorna – Food, Water and Medicine Delivery Teleoperated Robot with Telemedicine Facility

Annapoorna – Food, Water and Medicine Delivery Teleoperated...

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E-mobility, Power Control and Smart systems (ICEMPS), International Conference on

作者： Rajesh Kannan Megalingam Sakthiprasad Kuttankulangara Manoharan Avinash Hegde Kota Department of Electronics and Communication Engineering Humanitarian Technology (HuT) Labs Amrita Vishwa Vidyapeetham Amritapuri India Electrical and Computer Engineering Department Digital Design Environment Laboratory (DDEL) University of Cincinnati Cincinnati OH USA

ISBN: (数字)9798350394399

ISBN: (纸本)9798350394405

Annapoorna is a tele-operated robot to deliver food, water, and medicines to COVID patients in isolation wards. It is equipped with a telemedicine facility for doctors and nurses to interact with patients remotely. This greatly reduces direct contact of doctors, nurses, and food service staff with patients during COVID or other pandemic times, thereby reducing infection risk. The battery powered robot reaches each bedside to serve food and medicines to the patients in isolation wards. The robot can be controlled by smartphone app or wireless joystick controller. The tablet attached at the top of the robot serves dual purpose. The doctors and nurses can interact with the patient with any online meeting portals like Skype, Google Hangout, Zoom etc. In addition, the operator can control the robot using the tablet camera there by saving additional cost for the camera.

关键词： COVID-19 Wireless communication Navigation Tuberculosis Telemedicine Robot vision systems Cameras

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Dynamic Decoding of Intention via EEG 55

Dynamic Decoding of Intention via EEG

引用

55th Asilomar Conference on Signals, systems and computers, ACSSC 2021

作者： Haddad, Ali Najafizadeh, Laleh University of Basrah Qarmat Ali Department of Computer Engineering Basrah61004 Iraq Rutgers University Integrated Systems and NeuroImaging Laboratory Department of Electrical and Computer Engineering PiscatawayNJ08854 United States

ISBN: (纸本)9781665458283

We consider the problem of dynamically decoding human intention via electroencephalography (EEG). We present two hierarchical frameworks to approach this problem. One framework processes the activities recorded in the sensor space, i.e., scalp, directly, while the other considers these activities in the source space, i.e., cortex. In both frameworks, the source-informed segmentation algorithm is used to identify the time intervals during which the spatial distribution of active cortical functional networks remains quasi-stationary, and a recurrent neural network (RNN) is employed as the dynamic classifier. The frameworks are applied to experimental motor execution vs. imagery data, and the results are discussed. © 2021 IEEE.

关键词： Electroencephalography

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Semantic Communications for Artificial Intelligence Generated Content (AIGC) Toward Effective Content Creation

arXiv

引用

arXiv 2023年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In Shen, Xuemin The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada

Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potential, especially when integrating with semantic communication (SemCom). In this paper, a novel comprehensive conceptual model for the integration of AIGC and SemCom is developed. Particularly, a content generation level is introduced on top of the semantic level that provides a clear outline of how AIGC and SemCom interact with each other to produce meaningful and effective content. Moreover, a novel framework that employs AIGC technology is proposed as an encoder and decoder for semantic information, considering the joint optimization of semantic extraction and evaluation metrics tailored to AIGC services. The framework can adapt to different types of content generated, the required quality and the semantic information utilized. By employing a Deep Q Network (DQN), a case study is presented that provides useful insights into the feasibility of the optimization problem and its convergence characteristics. © 2023, CC BY.

关键词： Wireless networks

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