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Semantic Communications:Theories,Technologies and Applications

中国通信（英文版） 2024年第7期21卷前插1-前插5页

作者： Zhang Ping Shi Guangming Cui Shuguang Zhang Zhaoyang Niu Kai Xiao Yong Qin Zhijin Dai Jincheng Shao Shuo Deniz Gündüz Eleonora Grassucci School of Information and Communication Engineering at Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology IMT-2020(5G)Experts Panel Experts Panel for China's 6G development Peng Cheng Laboratory School of Artifi-cial Intelligence Xidian University electrical and computer engineering with the University of Arizona Texas A&M University UC Davis Chinese Univer-sity of Hong Kong(Shenzhen)(CUHK-Shenzhen) Zhejiang University School of Artificial Intelli-gence BUPT School of Electron-ic Information and Communications at the Huazhong University of Science and Technology(HUST) WuhanChina Peng Cheng Laboratory Guang-zhouChina and the Pazhou Laboratory(Huangpu)Guang-zhouChina Tsinghua University BeijingChina Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and Telecommunications School of Electronics Informa-tion and Electrical EngineeringShanghai Jiao Tong Univer-sityChina Information Processing in the Electrical and Electronic Engineering Department at Imperial College London UK Intelligent Systems and Networks Group Department at Imperial College London UK Department of Information Engineering Electronicsand Telecommunications of the Sapienza University of Rome

The last seventy years have witnessed the transi-tion of communication from Shannon's theoretical concept to current high-efficiency practical *** respect to Shannon information theory,to fulfill the high-bandwidth utilization,any further increase in the data rate requires a significant augmentation in the received signal power unless the bandwidth is extended in proportion to the incre-mental data rate.

关键词： Special issues and sections Semantics Communication systems Data processing Information theory Data augmentation

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Interval type-2 enhanced possibilistic fuzzy c-means clustering for gene expression data analysis

arXiv

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arXiv 2021年

作者： Sotudian, Shahabeddin Zarandi, Mohammad Hossein Fazel Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston United States Knowledge/Intelligent Systems Laboratory Department of Mechanical and Industrial Engineering University of Toronto Toronto Canada Department of Industrial Engineering Amirkabir University of Technology Tehran Iran

Both FCM and PCM clustering methods have been widely applied to pattern recognition and data clustering. Nevertheless, FCM is sensitive to noise and PCM occasionally generates coincident clusters. PFCM is an extension of the PCM model by combining FCM and PCM, but this method still suffers from the weaknesses of PCM and FCM. In the current paper, the weaknesses of the PFCM algorithm are corrected and the enhanced possibilistic fuzzy c-means (EPFCM) clustering algorithm is presented. EPFCM can still be sensitive to noise. Therefore, we propose an interval type-2 enhanced possibilistic fuzzy c-means (IT2EPFCM) clustering method by utilizing two fuzzifiers (m1, m2)for fuzzy memberships and two fuzzifiers (θ1, θ2)for possibilistic typicalities. Our computational results show the superiority of the proposed approaches compared with several state-of-the-art techniques in the literature. Finally, the proposed methods are implemented for analyzing microarray gene expression data. © 2021, CC BY-NC-ND.

关键词： Cluster analysis

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Simultaneously Calibration of Multi Hand-Eye Robot System Based on Graph

arXiv

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arXiv 2023年

作者： Zhou, Zishun Ma, Liping Liu, Xilong Cao, Zhiqiang Yu, Junzhi The Institute of Automation Chinese Academy of Sciences Beijing100190 China The College of Electrical Engineering and Computer Science Australian National University Canberra2601 Australia The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

Precise calibration is the basis for the vision-guided robot system to achieve high-precision operations. systems with multiple eyes (cameras) and multiple hands (robots) are particularly sensitive to calibration errors, such as micro-assembly systems. Most existing methods focus on the calibration of a single unit of the whole system, such as poses between hand and eye, or between two hands. These methods can be used to determine the relative pose between each unit, but the serialized incremental calibration strategy cannot avoid the problem of error accumulation in a large-scale system. Instead of focusing on a single unit, this paper models the multi-eye and multi-hand system calibration problem as a graph and proposes a method based on the minimum spanning tree and graph optimization. This method can automatically plan the serialized optimal calibration strategy in accordance with the system settings to get coarse calibration results initially. Then, with these initial values, the closed-loop constraints are introduced to carry out global optimization. Simulation experiments demonstrate the performance of the proposed algorithm under different noises and various hand-eye configurations. In addition, experiments on real robot systems are presented to further verify the proposed method. © 2023, CC BY-SA.

关键词： Multipurpose robots

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A method for Rapid Deployment of Brushless DC Motor Servo System Model Based on FPGA

A method for Rapid Deployment of Brushless DC Motor Servo Sy...

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作者： Wang Bolun Zhang Tao Shi Zhengjin Zhang Hualiang Xie Feng Liu Zihong School of Automation and Electrical Engineering Shenyang Ligong University Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology

Recently,with the development of technology and the lucubrate of automation technology,the dependence of modern industry on synchronous motors has gone deep into the *** fact,the current complex control algorithms consume the computing power of the data processing chips and put forward a higher request to the ability of ***,the emphasis of this study lies in a rapid deployment method of a brushless DC motor servo control system based on the model *** using Simulink software to simulate and verify the three-closed-loop servo model of the DC brushless motor,Verilog or VHDL language code will be generated,which can automatically configure the project according to the ***,a drive and control hardware platform based on Xilinx Zynq-7000 chips was built to verify the feasibility,the experimental results indicate that the proposed method can effectively simplify the deployment of complex algorithm codes,reduce the development cycle of brushless DC motor servo system with strong engineering practicability.

关键词： MBD HDL Coder BLDC Servo Control

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Hierarchical Deep Reinforcement Learning for Age-of-Information Minimization in IRS-aided and Wireless-powered Wireless Networks

arXiv

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arXiv 2022年

作者： Gong, Shimin Cui, Leiyang Gu, Bo Lyu, Bin Hoang, Dinh Thai Niyato, Dusit The School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen518055 China Key Laboratory of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications China The School of Electrical and Data Engineering University of Technology Sydney Australia School of Computer Science and Engineering Nanyang Technological University Singapore

In this paper, we focus on a wireless-powered sensor network coordinated by a multi-antenna access point (AP). Each node can generate sensing information and report the latest information to the AP using the energy harvested from the AP’s signal beamforming. blueWe aim to minimize the average age-of-information (AoI) by adapting the nodes’ transmission scheduling and the transmission control strategies jointly. To reduce the transmission delay, an intelligent reflecting surface (IRS) is used to enhance the channel conditions by controlling the AP’s beamforming bluevector and the IRS’s phase shifting bluematrix. blueConsidering dynamic data arrivals at different sensing nodes, we propose a hierarchical deep reinforcement learning (DRL) framework to bluefor AoI minimization in two steps. The users’ transmission scheduling is firstly determined by the outer-loop DRL approach, e.g. the DQN or PPO algorithm, and then the inner-loop optimization is used to adapt either the uplink information transmission or downlink energy transfer to all nodes. A simple and efficient approximation is also proposed to reduce the blueinner-loop rum time overhead. Numerical results verify that the hierarchical learning framework outperforms typical baselines in terms of the average AoI and proportional fairness among different nodes. © 2022, CC BY.

关键词： Reinforcement learning

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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Towards an Interaction Architecture for the iCub Robot: Social Gaze Space Model Adaptation for Social Interaction 23

Towards an Interaction Architecture for the iCub Robot: Soci...

引用

23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Shaghaghi, Sahand Aliasghari, Pourya Tripp, Bryan Anderson, Britt Dautenhahn, Kerstin Nehaniv, Chrystopher L. Social & Intelligent Robotics Research Lab University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Dept. of Systems Design Enginering University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Dept. of Electrical & Computer Engineering University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Dept. of Psychology University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Centre for Theoretical Neuroscience University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada

ISBN: (纸本)9798350373578

Gaze behaviour plays a crucial role in social interactions extending to Human-Robot Interactions. Humanoid robots equipped with anthropomorphic vision systems may be expected to employ natural gaze behaviour in interactions with humans. Here, we implemented a novel first-person human gaze state detection tool on the iCub robot and assessed its gaze detection accuracy. Using this tool, we then developed two social gaze interaction architectures for the iCub robot. The Social Gaze Space theory (SGS) of Jording and colleagues was the theoretical framework for building our first architecture, SGS Base (SGS-B). Our second architecture, SGS Interaction Architecture (SGS-IA), is the extended version of SGS Base that lets the robot take on different higher-level goals in an interaction, including being attentive to the interaction partner or attempting to direct their attention to an object. These architectures support dyadic social interactions involving initiating and responding to joint attention towards objects of interest, and are expected to allow the robot to interact in a more human-like manner in social interactions. The gaze detection accuracy of the iCub robot equipped with our choice of algorithms exceeded that of previously implemented methods. System validation trials confirmed that the robot detects the social gaze states correctly in the majority of the instances, allowing for behavioural control according to the Social Gaze Space theory. Validation tests presented in this article demonstrate the functionality of the SGS Interaction Architecture and also highlight the differences in personal interaction dynamics when the humanoid robot has no particular goals as opposed to when it has interactional goals appropriate to a teaching scenario. © 2024 IEEE.

关键词： Anthropomorphic robots

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A Deployment Optimization for Wireless Sensor Networks Based on Stacked Auto Encoder and Probabilistic Neural Network

引用

Digital Communications and Networks 2024年

作者： Hui Feng Chen Xu Bo Jin Min Zhang School of Intelligent Engineering Technology Jiangsu Vocational College of Finance and Economics Huai'an 223003 China School of Computer Science and Information Engineering Shanghai Institute of Technology Shanghai 200235 China Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra 3030-290 Portugal

In the field of consumer electronics, Wireless Sensor Networks (WSNs) can be used to build large-scale IoT systems and achieve intelligent data collection and processing. This paper proposes a deep neural network model SAE-PNN by Stacked Auto Encoder (SAE) and Probabilistic Neural Network (PNN) in a stack manner. A comprehensive training algorithm of SAE-PNN based on a group of orthogonal function bases is established by introducing a time-varying input and connection weight function, based on the conventional algorithm of unsupervised layer-by-layer initialization and gradient descent of deep neural network. Our proposed SAE-PNN model is used to predict the distance from unknown nodes to known nodes. Based on the collaborative work of nodes and network coverage, an optimal set of working nodes is established to reduce the energy loss of network nodes. A balance relationship between network coverage and energy consumption has been established to solve the problem of optimizing the balance in location coverage and the contradiction between individual nodes and the overall performance of the network. The experimental results show that the proposed method can improve the coverage of the monitored area and the perceived quality of service, and uses a distributed node synchronous scheduling mechanism to reduce the overall energy consumption of the network.

关键词： Wireless sensor networks Stacked auto encoder Probabilistic neural network Deep neural network Deployment strategy Node energy consumption

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Low-Cost, High Sensitivity Paper-Based Bacteria Impedance Sensor Based on Vertical Flow Assay

SSRN

引用

SSRN 2022年

作者： Long, Yifan Ai, Zhehong Zhang, Longhan Zhang, Han Jiang, Jing Logan, G. Liu Research Center for Intelligent Sensing Systems Zhejiang Laboratory Zhejiang Hangzhou311100 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Zhejiang Hangzhou310024 China Department of Electrical & Computer Engineering the University of Illinois at Urbana-Champaign UrbanaIL61801 United States

This study proposed a low-cost, portable paper-fluidic vertical flow assay bacteria counter at high accuracy. We designed the sensor at a low fabrication cost based on e-beam evaporation and 3D printing based on the impedance measurement principle. Interdigitated (IDT) electrodes were coated on the filter membrane by e-beam evaporation with a shadow mask. We could print wafer-scale frames with low-melting temperature 3D printing material to confine liquid bacteria samples within the IDT sensing region. This novel fabrication technique significantly reduced the chip cost to less than 1% of silicon-based chips. Two equivalent circuit models were proposed for different concentration ranges to analyze the principle of paper-based impedance bacteria sensors. We proposed an "improved model" based on the Randles model for low concentration by considering the leaky double layer capacitor effect and spherical diffusion from nano-structural electrodes of the gold-coated filter membrane. The hook effect was found and explained at a high concentration range by the pearl chain effect. We modeled the pearl chain effect as a pair of RC parallel to the low concentration model. When users apply both models properly for analysis, this sensor could quantitatively measure cell concentrations from 40 to 400M per milliliter with superior linearity. © 2022, The Authors. All rights reserved.

关键词： Bacteria

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EFaR 2023: Efficient Face Recognition Competition

EFaR 2023: Efficient Face Recognition Competition

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Jan Niklas Kolf Fadi Boutros Jurek Elliesen Markus Theuerkauf Naser Damer Mohamad Alansari Oussama Abdul Hay Sara Alansari Sajid Javed Naoufel Werghi Klemen Grm Vitomir Štruc Fernando Alonso-Fernandez Kevin Hernandez Diaz Josef Bigun Anjith George Christophe Ecabert Hatef Otroshi Shahreza Ketan Kotwal Sébastien Marcel Iurii Medvedev Bo Jin Diogo Nunes Ahmad Hassanpour Pankaj Khatiwada Aafan Ahmad Toor Bian Yang Fraunhofer Institute for Computer Graphics Research IGD Germany TU Darmstadt Germany Department of Electrical and Computer Engineering Khalifa University Abu Dhabi United Arab Emirates Laboratory for Machine Intelligence Faculty of Electrical Engineering University of Ljubljana Slovenia Halmstad University Sweden Idiap Research Institute Martigny Switzerland École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Université de Lausanne (UNIL) Lausanne Switzerland Institute of Systems and Robotics University of Coimbra Coimbra Portugal Department of Information Security and Communication Technology eHealth and Welfare Security Group Norwegian University of Science and Technology Norway

This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size. The evaluation of submissions is extended to bias, cross-quality, and large-scale recognition benchmarks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines. The submitted solutions use small, efficient network architectures to reduce the computational cost, some solutions apply model quantization. An outlook on possible techniques that are underrepresented in current solutions is given as well.

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