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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chen, Yunwang Kang, Yaozhong Zhao, Ziqi Hong, Yue Meng, Lingxiao Meng, Max Q.-H. Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen518055 China SUSTech Department of Electrical and Electronic Engineering Shenzhen China School of System Design and Intelligent Manufacturing SUSTech Shenzhen China

ISBN: (纸本)9781665481090

This paper presents a collaborative fall detection and response system integrating Wi-Fi sensing with robotic assistance. The proposed system leverages channel state information (CSI) disruptions caused by movements to detect falls in non-line-of-sight (NLOS) scenarios, offering non-intrusive monitoring. Besides, a companion robot is utilized to provide assistance capabilities to navigate and respond to incidents autonomously, improving efficiency in providing assistance in various environments. The experimental results demonstrate the effectiveness of the proposed system in detecting falls and responding effectively. © 2024 IEEE.

关键词： Fall detection

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A semantic and emotion-based dual latent variable generation model for a dialogue system

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CAAI Transactions on Intelligence Technology 2023年第2期8卷 319-330页

作者： Ming Yan Xingrui Lou Chien Aun Chan Yan Wang Wei Jiang State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijingChina School of Information and Communications Engineering Communication University of ChinaBeijingChina Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijingChina Department of Electrical and Electronic Engineering The University of MelbourneMelbourneVictoriaAustralia School of Data Science and Intelligent Media Communication University of ChinaBeijingChina

With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human *** emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate ***,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the *** propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional *** from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer ***,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and *** content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features ***,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the *** results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.

关键词： conditional variational autoencoder dual latent space emotional responses latent variable generation

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Requirement-Oriented TT&C Method for Satellite Based on BDS-3 Short-Message Communication System

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Space(Science & Technology) 2023年第1期3卷 311-324页

作者： Chao Li Peijie Liu Shiyuan Fu Yiwen Jiao Wei Zhang Department of Electronic and Optical Engineering Space Engineering UniversityBeijingChina Key Laboratory of Intelligent Space TT&C and Operation(Space Engineering University) Ministry of EducationBeijingChina State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System LuoyangChina Xi’an Satellite Control Center Xi’anChina

With the increasing number of satellites being launched in China,the demand for Telemetry,Tracking,and Command(TT&C)resources is also *** of the global coverage and resource requirements of TT&C management,this paper proposes a TT&C scheme based on the Global Short-Message Communication System(GSMCS)of the BeiDou-3 Navigation Satellite System(BDS-3).The system composition,workflow,and functions of satellite TT&C are analyzed using the GSMCS of *** the coverage analysis of the Medium Earth Orbit(MEO)constellation of BDS-3,scheme’s applicability is pointed out,and the correctness of the analysis results is verified via *** value range of the link distance is derived by calculating the range of the distance variation between any 2 satellites in the BDS-3 MEO constellation and combining the intersatellite routing *** calculation results show that the response time range of the autonomous request management application of in-orbit satellites based on the GSMCS of BDS-3 is 1.407 to 2.448 *** can meet the requirements of TT&C service.

关键词： Message Command service

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Method for the multi-view estimation of fish mass using a two-stage neural network with edge-sensitive module

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International Journal of Agricultural and Biological engineering 2024年第3期17卷 222-229页

作者： Zeyu Jiao Yingjie Cai Qi Zhang Zhenyu Zhong Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510070China Department of Electronic Engineering The Chinese University of Hong KongHong Kong 999077China College of Economics and Management Northwest A&F UniversityYangling 712100ShaanxiChina

The estimation of fish mass is one of the most basic and important tasks in *** the mass of fish at different growth stages is of great significance for feeding,monitoring the health status of fish,and making breeding plans to increase *** existing estimation methods for fish mass often stay in the 2D plane,and it is difficult to obtain the 3D information on fish,which will lead to the *** solve this problem,a multi-view method was proposed to obtain the 3D information of fish and predict the mass of fish through a two-stage neural network with an edge-sensitive *** the first stage,the side-and downward-view images of the fish and some 3D information,such as side area,top area,length,deflection angle,and pitch angle,were captured to estimate the size of the fish through two vertically placed *** the area of the fish at different views was estimated accurately through the pre-trained image segmentation neural network with an edgesensitive *** the second stage,a fully connected neural network was constructed to regress the fish mass based on the 3D information obtained in the previous *** experimental results indicate that the proposed method can accurately estimate the fish mass and outperform the existing estimation methods.

关键词： fish mass multi-view estimation two-stage neural network edge-sensitive module image segmentation

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Vortex light bullets in Rydberg atoms trapped in twisted PT-symmetric waveguide arrays

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Physical Review A 2024年第2期110卷 023508-023508页

作者： Siliu Xu Junhao Li Yiheng Hou Jun-Rong He Zhou Fan Yuan Zhao Liangwei Dong Key Laboratory of Optoelectronic Sensing and Intelligent Control School of Biomedical Engineering and Imaging Xianning Medical College School of Electronic and Information Engineering Department of Physics

We present a theoretical scheme for generating vortex light bullets (LBs) in a Rydberg atomic system. The stability property and propagation dynamics of vortex LBs with different topological charges are investigated in twisted circular waveguide arrays with a parity-time (PT) symmetry. The numerical solutions of the corresponding nonlinear Schrödinger equation are obtained by the modified square operator method and split-step Fourier method. The longitudinal twist changes the stabilities of six-core vortex LBs and enriches the modulation diversity as the states with the opposite charges degenerate by the introducing of rotation frequency. Specifically, we reveal that the energy exchange between waveguides and media gives rise to the formation of necklace breathers, which is crucial for implementing light storage. These unique characteristics arise from the balance or quasibalance among the rotation frequency, the Rydberg-Rydberg interaction, and the nonequivalent gain/loss distribution along the azimuthal direction. We thus provide examples of robust high-charge vortex LBs and necklace breathers in the Rydberg atomic system with a PT symmetry.

关键词： Cold gases in optical lattices Light-matter interaction Nonlinear optics Van der Waals interaction

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Multiple Sensor Fusion-Based Positioning Robot for Steam Generator Inspection 2

Multiple Sensor Fusion-Based Positioning Robot for Steam Gen...

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2nd International Symposium on Sensor Technology and control, ISSTC 2023

作者： You, Jingwei Wei, Shouqi Wu, Xiong Sun, Jianquan Guilin University of Electronic Technology Department of Electrical Engineering Guilin541004 China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518000 China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen518000 China

ISBN: (纸本)9798350314465

Nuclear energy is presently the clean energy source most likely to massively displace fossil energy, and the secondary side of the steam generator is an important part of a nuclear power plant. Due to the small space of the secondary side of the steam generator and the confinement of the vessel, the precise positioning of the robot inside the steam generator cannot be achieved by a single sensor alone. This paper introduces a multi-sensor fusion steam generator secondary side inspection robot. Primary emphasis is on data fusion of multiple sensors, such as laser sensors, cameras, IMU, and wheel encoder. First of all, this paper integrates data from wheel encoder data and IMU data by using extended Kalman filtering (EKF), which decreases the drift error during the motion and enhances the robot positioning precision. Afterwards, we incorporate laser ranging sensors and camera picture data to enhance the overall spatial sensitivity of the robot through particle filtering algorithms. Experiments show that the robot works reliably and has high positioning accuracy. © 2023 IEEE.

关键词： Steam generators

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Surrogate-Assisted Multiobjective Gene Selection for Cell Classification from Large-Scale Single-Cell RNA Sequencing Data

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IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital Department of Pathology Wuhan University Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20,000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Hou, Muyang Lei, Zhenya Hu, Haidong Wang, Zhong Wang, Yong Xie, Le Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Beijing Institute of Control Engineering Beijing100190 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant;on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A∗ which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion. © 2024 IEEE.

关键词： Trajectories

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear Systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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Automatic speaker identification system based on MLP network and deep learning in the presence of severe interference

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Multimedia Tools and Applications 2025年 1-42页

作者： Shafik, Amira Sedik, Ahmed El-Shafai, Walid Khalaf, Ashraf A. M. El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Faculty of Engineering Minia University Minia61519 Egypt Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafr Elsheikh University Kafr El‑Shaikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Automatic Speaker Identification (ASI) is so crucial for security. Current ASI systems perform well in quiet and clean surroundings. However, in noisy situations, the robustness of an ASI system against additive noise and interference is a crucial factor. An investigation of the impact of interference on ASI system performance is presented in this paper, which introduces algorithms for achieving high ASI system performance. The objective is to resist the interference of various forms. This paper presents two models for the ASI task in the presence of interference. The first one depends on Normalized Pitch Frequency (NPF) and Mel-Frequency Cepstral Coefficients (MFCCs) as extracted features and Multi-Layer Perceptron (MLP) as a classifier. In this model, we investigate the utilization of a Discrete Transform (DT), such as Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST), to increase the robustness of extracted features against different types of degradation through exploiting the sub-band decomposition characteristics of DWT and the energy compaction property of DCT and DST. This is achieved by extracting features directly from contaminated speech signals in addition to features extracted from discrete transformed signals to create hybrid feature vectors. The enhancement techniques, such as Spectral Subtraction (SS), Winer Filter, and adaptive Wiener filter, are used in a preprocessing stage to eliminate the effect of the interference on the ASI system. In the second model, we investigate the utilization of Deep Learning (DL) based on a Convolutional Neural Network (CNN) with speech signal spectrograms and their Radon transforms to increase the robustness of the ASI system against interference effects. One of this paper goals is to introduce a comparison between the two models and build a more robust ASI system against severe interference. The experimental results indicate that the two proposed models lead to satisfa

关键词： Additive noise

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