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Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone:A Stochastic Geometry Approach

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computer Modeling in engineering & Sciences 2024年第1期138卷 639-661页

作者： Yulei Wang Li Feng Shumin Yao Hong Liang Haoxu Shi Yuqiang Chen School of Computer Science and Engineering Macao University of Science and TechnologyTaipaMacaoChina Department of Broadband Communication Peng Cheng LaboratoryShenzhenChina School of Artificial Intelligence Dongguan PolytechnicDongguanChina

Interference management is one of the most important issues in the device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets)due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular *** alleviate the interference,an efficient interference management way is to set exclusion zones around the cellular *** this paper,we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled *** main difficulties contain three aspects:1)how to model the location randomness of base stations,cellular and D2D users in practical networks;2)how to capture the randomness and interrelation of cellular and D2D transmissions due to the existence of random exclusion zones;3)how to characterize the different types of interference and their impacts on the outage probabilities of cellular and D2D *** then run extensive Monte-Carlo simulations which manifest that our theoretical model is very accurate.

关键词： Device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets) exclusion zone stochastic geometry(SG) Matérn hard-core process(MHCP)

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State of Health Estimation of Lithium-Ion Batteries Based on Relaxation Voltage Reconstruction and AM-LSTM Method

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7261-7273页

作者： Wei, Liangliang Xu, Hongzhang Sun, Yiwen Diao, Qi Tan, Xiaojun Fan, Yuqian Liu, Han School of Intelligent Systems Engineering Shenzhen518107 China Henan Institute of Science and Technology School of Computer Science and Technology Henan Xinxiang453003 China Dongguan Institute Sun Yat-sen University Guangdong Dongguan523808 China Hong Kong Polytechnic University Department of Building and Energy Engineering Hong Kong

It is essential to accurately estimate the state of health (SOH) for lithium-ion batteries from the perspectives of safety and reliability. Most existing data-driven methods are, however, based on charging or discharging data, which is relatively difficult to apply. This article proposes a novel SOH estimation approach based on the relaxation voltage reconstruction and a long short-term memory network with an attention mechanism (AM-LSTM) method. First, based on the relaxation voltage data, a complete relaxation curve is reconstructed with a gated recurrent unit (GRU) neural network. Next, health feature (HF) extraction is carried out on the reconstructed data, and the correlation is analyzed based on Pearson correlation analysis. Then, the SOH estimation is performed based on the AM-LSTM model. Various comparative studies have been conducted to verify the effectiveness of the proposed method by comparing it with relaxation voltage reconstruction and different SOH estimation methods. The experimental results demonstrate that the proposed method can effectively reconstruct the relaxation voltage and have good accuracy in estimating the SOH with a partial relaxation voltage curve. © 2015 IEEE.

关键词： Voltage Batteries Estimation Feature extraction Long short term memory Logic gates Data models Integrated circuit modeling Data mining Transportation

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Research On the Evaluation System of Physical Rehabilitation Training Using computer Vision

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第4期9卷 2062-2083页

作者： Huang, Lingfeng Du, Qian Chen, Yeh-Cheng Chen, Ruey-Shun Liu, Lunan Huang, Shengwen School of Electronic Information Dongguan Polytechnic Dongguan523808 China School of Information Science and Engineering Linyi University Linyi27600 China Department of Computer Science University of California Davis94555 United States Department of Information Management National Yang Ming Chiao Tung University Hsinchu30050 Taiwan

In recent years, relevant policies of rehabilitation medical care have been released successively, and the development of the medical industry and the construction of rehabilitation medical service system have been vigorously promoted from the macro policy level. However, there is still a large shortage of rehabilitation therapists at this stage, and there is obviously a shortage of supply in the rehabilitation medical industry. This research focuses on the current social problem of insufficient professional guidance in the rehabilitation medical industry, mainly for the lack of professional guidance in home rehabilitation training, using computer vision recognition technology, with the help of home computer equipment, to develop a set of suitable for community rehabilitation services and home rehabilitation training, operation easy recovery system. At the same time, the system design achieves the three goals of "low cost, high efficiency, and easy operation". While solving the social problems of difficult home rehabilitation training, it also reduces the treatment cost and space constraints of rehabilitation patients, so that home rehabilitation patients can receive professional and accurate rehabilitation training guidance at any time. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Patient rehabilitation

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Improved Quaternion Discriminant Analysis for Feature Extraction and Classification of Hyperspectral Image

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12925-12945页

作者： Wang, Xinpeng Ling, Bingo Wing-Kuen Yu, Long Dai, Qingyun Liu, Shaopeng Zhao, Jiandong Kuang, Weichao Guangdong Polytechnic Normal University Faculty of Computer Science Guangzhou China Guangdong University of Technology School of Information Engineering Guangzhou China Sun Yat-sen University School of Geography and Planning Guangzhou510275 China Dongguan University of Technology Department of Electronic Engineering and Intellectualization Dongguan China

Real domain discriminant analysis (RDA) can not solve the crosstalk of strong correlation between adjacent spectral bands, and also causes spectral information loss of hyperspectral image (HSI). As a result, the effect of feature extraction is not ideal. Besides, in the case of small samples, using quaternion discriminant analysis (QDA) based on Cos-sin Decomposition, the matrix obtained by the first orthogonal trigonometric decomposition is not a diagonal matrix, that makes the projection axis not optimal. To solve these problems, firstly, a quaternion discriminant analysis method based on stable quaternion Cossin Decomposition (QDASG) is proposed to solve the small sample problem. Secondly, this paper theoretically analyzes that when the number of projection axes in QDASG is smaller than that in traditional DA methods, the discriminant formula can achieve optimal results, and verifies this conclusion through experiments. Then, according to the number of training samples, the implementation process of QDA is discussed in two cases. Finally, spatial filtering is used to extract spatial information, and the distance quotient formula between classes is proposed as the standard for selecting the the optimal number of stacking layers for the filter. Experimental results show that this method is effective compared with deep learning method and and other traditional machine learning methods, especially in the case of small samples. © 2008-2012 IEEE.

关键词： Discriminant analysis

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Multi-agent-based distributed text information filtering method

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International Journal of Reasoning-based Intelligent Systems 2021年第3期13卷 123-131页

作者： Jiang, Wuxue Department of Computer Engineering Dongguan Polytechnic No. 3 Daxue RoadGuangdong Province Songshanhu Dongguan City523808 China

In order to solve the problems of text information filtering, such as low filtering efficiency and accuracy, and too much use of network resources, a distributed text information filtering method based on multi-agent is proposed, which schemes out the architecture and working mechanism of distributed text information filtering, designs the scheduling response agent and learning agent in detail, and adopts dynamic interval adaptive load balancing migration (DRALM) strategy for load measurement. The experimental results show that the filtering method not only has high filtering accuracy, but also can process tasks in multiple machines, balance the computational load effectively, and has high filtering performance. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Multi agent systems

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Face feature matching based on semantic Information 2

Face feature matching based on semantic Information

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2nd International Conference on computer Vision and Data Mining, ICVDM 2021

作者： Guo, Jianlan Chen, Yuqiang Li, Jiaming Xie, Jiabao Department of Computer Engineering Dongguan Polytechnic Guangdong Dongguan523808 China

Face feature matching problems have always been a very important research topic in the field of image processing. Face feature matching is always the most important part of common face recognition algorithms, but how to match features quickly and accurately is a quite essential and urgent problem to be solved. Therefore, we propose a face feature matching method which can effectively improve the matching efficiency and accuracy. For each feature point in the input image, face feature matching based on nearest neighbor ratio method requires global search for the best matching in the reference image. However, we find that such matching method can achieve better matching results, but it costs a lot of computing resources and time. Therefore, we use the feature vectors constructed by CNN convolution feature map to provide the local matching region based on semantic information for handcrafted descriptors after feature matching. Although two feature matching processes are used in this paper, the matching efficiency is improved several times compared with the traditional global search scheme. Experiments show that our proposed can be used as an important module of face recognition system to improve the accuracy of face recognition. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Face recognition

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Assistant human facial recognition based on convolution feature-map

Assistant human facial recognition based on convolution feat...

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2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021

作者： Guo, Jianlan Chen, Yuqiang Li, Jiaming Xie, Jiabao Department of Computer Engineering Dongguan Polytechnic Guangdong Dongguan523808 China

Face recognition is a very important research direction in the field of image processing. In daily life, there are various problems that require face recognition everywhere, but how to accurately identify faces from images is a very important and urgent problem. To this end, we propose an assistant face recognition method that can effectively improve the recognition accuracy. The face recognition method based on deep learning will convolve the input image into five different convolution kernels to obtain the convolution feature-map of each layer. At the end, the corresponding description vector of the input image is generated by using the two layers fully connected layer and the pooling layer. Therefore, in the process of face recognition, it is only necessary to calculate the similarity between the description vectors of the two frames of images. Because of its recognition accuracy and room for improvement, we use the features of the fifth-level convolution feature-map, combined with the image description vector finally generated by the deep learning method, can significantly improve the recognition accuracy in the face recognition process. Through a large number of experiments, the method can be used to assist the image recognition problem based on the deep learning method, which can effectively improve the recognition accuracy. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Face recognition

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Iterative Shaping of Multi-Particle Aggregates Based on Action Trees and VLM

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IEEE Robotics and Automation Letters 2025年第7期10卷 7102-7109页

作者： Lee, Hoi-Yin Zhou, Peng Duan, Anqing Yang, Chenguang Navarro-Alarcon, David The Hong Kong Polytechnic University Department of Mechanical Engineering Kowloon Hong Kong The Great Bay University School of Advanced Engineering Dongguan 523000 China Mohamed Bin Zayed University of Artificial Intelligence Department of Robotics Abu Dhabi United Arab Emirates University of Liverpool Department of Computer Science Liverpool L693BX United Kingdom

In this paper, we address the problem of manipulating multi- particle aggregates using a bimanual robotic system. Our approach enables the autonomous transport of dispersed particles through a series of shaping and pushing actions using robotically controlled tools. Achieving this advanced manipulation capability presents two key challenges: high-level task planning and trajectory execution. For task planning, we leverage Vision Language Models (VLMs) to enable primitive actions such as tool affordance grasping and non-prehensile particle pushing. For trajectory execution, we represent the evolving particle aggregate's contour using truncated Fourier series, providing efficient parametrization of its closed shape. We adaptively compute trajectory waypoints based on group cohesion and the geometric centroid of the aggregate, accounting for its spatial distribution and collective motion. Through real-world experiments, we demonstrate the effectiveness of our methodology in actively shaping and manipulating multi- particle aggregates while maintaining high system cohesion. © 2016 IEEE.

关键词： action trees multi-particle manipulation Robot manipulation shape control VLM

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Tangentially-Magnetized-Slot-PM-Assisted Magnet Saturation Relieving Design for Doubly Salient Reluctance Machine Position Sensorless Drive Electric Propulsion Applications 6

Tangentially-Magnetized-Slot-PM-Assisted Magnet Saturation R...

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6th International Conference on Electrical engineering and Control Technologies, CEECT 2024

作者： Wang, Weiyu Zhang, Xiaodong Niu, Shuangxia Zhao, Xing Pan, Jianfei Fu, Weinong Great Bay University School of Engineering Dongguan China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong University of York Department of Electronic Engineering York United Kingdom Shenzhen University College of Mechatronics and Control Engineering Shenzhen China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen China

ISBN: (纸本)9798331528096

For doubly salient reluctance machines, the magnetic saturation effect easily occurs, thereby the saturated inductance with complex analytical expression brings difficulties to the inductance modeling procedure during position sensorless control. To tackle this issue, a direct solution from electrical machine design is introduced to regulate magnetic flux distribution. The key is to insert tangentially-magnetized-slot-permanent-magnet into stator slots, thus relieving the magnetic saturation in the stator teeth. Consequently, unsaturated inductance characteristics can be acquired through the magnetic saturation relieving effect, thereby the inductance modeling effort can be significantly decreased, and such design is friendly for doubly salient reluctance machine position sensorless drive application. © 2024 IEEE.

关键词： Stators

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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

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engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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