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2024 International Conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Yu, Penghui Li, Qiao Cai, Shichang Pan, Meisen College of Basic Medicine Hunan University of Medicine Huaihua418000 China College of Computer and Electrical Engineering Hunan University of Arts and Science Hunan Changde415000 China Huaihua Key Laboratory of Digital Anatomy 3D Printing for Clinical Translational Research Hunan Huaihua418000 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Currently, VR technology is constantly developing and widely applied in the field of medical education. Many experiments in medical courses have evolved from simple animated demonstrations to virtual simulation experiments. The current lack of intuitive clarity and ease of operation in teaching human anatomy experiments is a common problem. The 3D anatomical structure teaching model has the advantages of three-dimensional and highly simulated teaching, which can effectively reproduce the three-dimensional structure and three-dimensional entity information of tissues and organs. This article introduces the basic principles of VR technology and its application in anatomy experimental teaching. By comparing the traditional teaching methods and VR integrated teaching methods of 60 students in the anatomy course, the advantages of applying VR anatomical structure teaching mode to human anatomy experimental teaching were analyzed. As a result, the combination of VR anatomical structure teaching and traditional experimental entity specimen teaching solved many difficulties in the teaching process of this specialized course, and gave full play to their respective advantages, effectively overcame the shortcomings of traditional experimental teaching and VR anatomical structure teaching model, and greatly mobilized students' subjective initiative. Make it easier for students to master the complex knowledge of human anatomy. © 2025 SPIE.

关键词： digital elevation model

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Dynamic Scheduling of Mobile Energy Storage for Post-Disaster Power Recovery from Storm Tides: A Multi-Agent Reinforcement Learning Framework 7

Dynamic Scheduling of Mobile Energy Storage for Post-Disaste...

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7th IEEE Student Conference on Electric Machines and Systems, SCEMS 2024

作者： Liu, Fengrui Lao, Keng-Weng Guo, Haotian Zhang, Ziyao Kong, Weiming Hu, Xiaorui University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China King's College London Digital assets and media management London United Kingdom Institute of Energy Power Innovation North China Electric Power University Beijing China

ISBN: (纸本)9798350366945

Storm tide disasters may lead to extensive power outage in distribution networks. The usage of energy storage resources is necessary to ensure the power critical loads. Previous research has been designed to address typhoon disasters without considering the impact of storm tides, which reduces its effectiveness. This paper proposes a multi-agent deep reinforcement learning framework to address the issues, based on the integration of power and transportation networks, facing dynamic scheduling decisions of mobile energy storage for power supply recovery after storm tide. Firstly, to simulate the dynamic allocation of power demand and energy storage resources in various regions during storm tide disasters, a coupled transportation and power grid digital twin is constructed, ensuring that Mobile Energy Storage Systems (MESS) can efficiently transfer and distribute power resources between regions affected by storm tide. Then, the reinforcement learning method based on Multi-Agent Depth Q-Network (MADQN) is designed, and can optimize the real-time scheduling strategy of mobile energy storage resources, maximize power recovery efficiency, and minimize recovery time. Finally, a hazard assessment framework for storm tides in coastal cities is proposed. The experimental results show that this method has significantly improved recovery speed and power supply security after storm-tide disasters. © 2024 IEEE.

关键词： Reinforcement learning

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Interior Scene Intelligent Generated for Smart Homes Based on GAN-ID Algorithms

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第2期9卷 1046-1055页

作者： Zhang, Fu-Quan Ma, Lin-Juan Zhou, Jun-Xian Wang, Run-Hong Zhang, Guang-Zhen College of Computer and Control Engineering Minjiang University Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu China Fuzhou Technology Innovation Center of Intelligent Manufacturing Information System Minjiang University Fuzhou China Fujian Province University Fuzhou China School of Computer Science and Technology Beijing Institute of Technology Beijing China Minjiang University Fuzhou China Information Media School of Tianjin Technician Institute of Mechanical & Electrical Technology Tianjin China

The purpose of this paper is to present a new GAN-ID algorithm to gener-ate interior scene intelligently based on Artificial Intelligence of Things (AIoT). Although great progress has been made when GAN algorithm applied in smart homes and smart cities, the issue of the trade-off between the accuracy and the efficiency in interior scene has been overlooked. A number of experiments were performed to check the performance and it is indicated that the results of the proposed GAN-ID has great advantages in model sample generation than other common methods when generating interior scene intelligently, which is similar to state-of-the-art. It is meaningful when it can be applied in smart cities and smart homes filed based on AIoT in the future. © 2024, J. Network Intell. All rights reserved.

关键词： Automation

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Large Scale Model Enabled Semantic Communications Based on Robust Knowledge Distillation

Large Scale Model Enabled Semantic Communications Based on R...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Ding, Kuiyuan Liu, Fangfang Yang, Yang Chen, Mingzhe Guo, Caili Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering The Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9798350351255

Large scale artificial intelligence (AI) models possess excellent capabilities in semantic representation and understanding, making them particularly well-suited for semantic encoding and decoding. However, the substantial scale of these AI models imposes unacceptable computational resources and communication delays. To address this issue, we propose a semantic communication scheme based on robust knowledge distillation (RKD-SC) for large scale model enabled semantic communications. In the considered system, a transmitter extracts the features of the source image for robust transmission and accurate image classification at the receiver. To effectively utilize the superior capability of large scale model while make the cost affordable, we first transfer knowledge from a large scale model to a smaller scale model to serve as the semantic encoder. Then, to enhance the robustness of the system against channel noise, we propose a channel-aware autoencoder (CAA) based on the Transformer architecture. Experimental results show that the encoder of proposed RKD-SC system can achieve over 93.3% of the performance of a large scale model while compressing 96.67% number of parameters. Code: https://***/echojayne/RKD-SC. © 2024 IEEE.

关键词： Channel coding

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Darly: Deep Reinforcement Learning for QoS-aware scheduling under resource heterogeneity Optimizing serverless video analytics

Darly: Deep Reinforcement Learning for QoS-aware scheduling ...

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IEEE International Conference on Cloud Computing, CLOUD

作者： Dimitrios Giagkos Achilleas Tzenetopoulos Dimosthenis Masouros Dimitrios Soudris Sotirios Xydis Microprocessors Laboratory and Digital Systems Lab (MicroLab) School of Electrical and Computer Engineering National Technical University of Athens

Today, video analytics are becoming extremely popular due to the increasing need for extracting valuable information from videos available in public sharing services through camera-driven streams. Typically, video analytics are organized as a set of separate tasks, each of which has different resource requirements (e.g., computational- vs. memory-intensive tasks). The serverless computing paradigm forms a very promising approach for mapping such types of applications, as it enables fine-grained deployment and management in a per-function manner. However, modern serverless frameworks suffer from performance variability issues, due to i) the interference introduced due to co-location of third-party workloads with the serverless funcations and ii) the increasing hardware heterogeneity introduced in public clouds. To this end, this work introduces Darly, a QoS- and heterogeneity-aware Deep Reinforcement Learning-based Scheduler for serverless video analytics deployments. The proposed framework incorporates a DRL agent which exploits low-level performance counters to identify the levels of interference and the degree of heterogeneity in the underlying infrastructure and combines this information along with user-defined QoS requirements to dynamically optimize resource allocations by deciding the placement, migration, or horizontal scaling of serverless functions. Promising results are produced withing our experiments, which are accompanied with the intent to further build upon this groundwork.

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ONLINE ML-BASED JOINT CHANNEL ESTIMATION AND MIMO DECODING FOR DYNAMIC CHANNELS

arXiv

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arXiv 2024年

作者： Fernando, Luiz Teixeira, Moreira Luiz, Vinicius Henrique Soares, Jonathan Aguiar Mayer, Kayol Soares Arantes, Dalton Soares Digital Communications Laboratory – ComLab Department of Communications School of Electrical and Computer Engineering University of Campinas – Unicamp SP Campinas13083-852 Brazil

This paper presents an online method for joint channel estimation and decoding in massive MIMO-OFDM systems using complex-valued neural networks (CVNNs). The study evaluates the performance of various CVNNs, such as the complex-valued feedforward neural network (CVFNN), split-complex feedforward neural network (SCFNN), complex radial basis function (C-RBF), fully-complex radial basis function (FC-RBF) and phase-transmittance radial basis function (PT-RBF), in realistic 5G communication scenarios. Results demonstrate improvements in mean squared error (MSE), convergence, and bit error rate (BER) accuracy. The C-RBF and PT-RBF architectures show the most promising outcomes, suggesting that RBF-based CVNNs provide a reliable and efficient solution for complex and noisy communication environments. These findings have potential implications for applying advanced neural network techniques in next-generation wireless systems. © 2024, CC BY.

关键词： Radial basis function networks

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A Cooperative Co-Evolution Algorithm with Variable-Importance Grouping for Large-Scale Optimization 13

A Cooperative Co-Evolution Algorithm with Variable-Importanc...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Li, Yongfeng Zhang, Yuze Ma, Lijia Ji, Junkai Liu, Dugang Leung, Victor C. M. Li, Jianqiang Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen518123 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China The University of British Columbia Department of Electrical and Computer Engineering VancouverV6T 1Z4 Canada

ISBN: (纸本)9798350308365

Cooperative co-evolution (CC) is a promising direction in solving large-scale multiobjective optimization problems (LMOPs). However, most existing methods of grouping decision variables face some difficulties when searching in the huge search space. Specifically, the methods of grouping decision variables can be classified into two types, i.e., high-consumption grouping methods and non-consumption grouping methods. On the one hand, the former ones divide the decision variables into different groups based on the correlation analysis between variables, which consume much evaluation. This way may lead to premature convergence within limited computational resources. On the other hand, the later ones allocate the decision variables into sub-groups based on some metrics, e.g., order and size, which consume no evaluation while may cause the search fall into local optima. To alleviate the above issues, this paper proposes a CC-based algorithm with a variable-importance grouping (VIG) method, called VICCA. Firstly, the decision variables are classified into several subgroups according to their importance quantified by a meta-gene construction method. Secondly, a CC strategy is designed to simultaneously optimize all subgroups of decision variables formed by VIG using the differential evolution operator, which aims to accelerate the convergence speed. Thirdly, a global evolutionary strategy is proposed to optimize original decision variable space by the competitive swarm optimizer, aiming to maintain the diversity. Finally, the experiments demonstrate that our proposed VICCA has the significant advantage in solving LMOPs when compared with state-of-the-art evolutionary algorithms. © 2024 IEEE.

关键词： Optimization algorithms

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High-Speed Silicon Waveguide 3-to-8 Decoder Based on Electro-Optic Effects 18

High-Speed Silicon Waveguide 3-to-8 Decoder Based on Electro...

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Silicon Photonics XVIII 2023

作者： Akhmet, Alisher Gaziz, Almar Alipbayeva, Nazym Nakarmi, Bikash Ukaegbu, Ikechi A. Integrated Device Solutions and Nanophotonics Laboratory Electrical and Computer Engineering Department School of Engineering and Digital Sciences Nazarbayev University Kabanbay batyra prospekt 53 Nur-Sultan010000 Kazakhstan Key Laboratory of RADAR Imaging and Microwave Photonics College of Electronics and Information Engineering Nanjing University of Aeronautics and Astronautics 29 Jiangjun St Jiangning Jiangsu Nanjing211106 China

ISBN: (纸本)9781510659575

A high-performance silicon waveguide-based electro-optical 3-to-8 decoder is proposed in this work. Generic 500x220 nm dimensions of the waveguide provide compatibility with other devices and circuits. The length of the active region is 4.5 microns. The n-to-m electro-optical switching circuits utilize both forward and reversed bias NOT gates with a voltage input of -2.5 V and 2.5 V, for logic zero and logic high, respectively. The 3-to-8 decoder showed an input power of the optical signal of 1.26 mW, which is distributed within the circuit, resulting in the maximum output power of approximately 0.3 mW on each of the 8 terminals. 20000 dB/cm mode loss is achieved with a logic input controlled by ±2.5 V. Results show that a data-rate of up to 100 Gbit/s is achieved. © 2023 SPIE.

关键词： Silicon

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Silicon photonics micro-ring resonator-based SR latch for optical memory applications

Silicon photonics micro-ring resonator-based SR latch for op...

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Smart Photonic and Optoelectronic Integrated Circuits 2023

作者： Otynshy, Dinmukhammedali Alipbayeva, Nazym Nurgali, Assylkhan Nakarmi, Bikash Ukaegbu, Ikechi A. Integrated Device solutions Laboratory Electrical and Computer Engineering Department School of Engineering and Digital Sciences Nazarbayev University Kabanbay batyra prospekt 53 Nur-Sultan010000 Kazakhstan Key Laboratory of RADAR Imaging and Microwave Photonics College of Electronics and Information Engineering Nanjing University of Aeronautics and Astronautics 29 Jiangjun St Jiangning Jiangsu Nanjing211106 China

ISBN: (纸本)9781510659551

This work proposes the design of optical SR latch. The fundamental component of the latch is a micro-ring resonator (MRR), which utilizes a plasma dispersion effect with an applied reverse bias voltage to tune its resonance wavelength. The proposed SR latch is made up of two identical micro-ring resonators with similar doped regions and the same logic mode of operation. The memory properties are realized by implementing the feedback loop between the input and output of the circuit. A time-varying simulation is carried out by applying two pseudorandom electrical input signals S and R into the circuit at a data rate of 25 Gbps. The work concludes with a comparative analysis between two optical SR latches (NOR-based and NAND-based). © 2023 SPIE.

关键词： Silicon photonics

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A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of Control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic Control Society.

关键词： Trucks

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