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7th IEEE International Symposium on Electromagnetic Compatibility, ISEMC 2023

作者： Wang, Chunxu Song, Jingcui Ao, Zhaohuan Li, Yan Li, Xueyang Li, Zhaohui School of Electronics and Information Technology and Guangdong Provincial Sun Yat-sen University Key Laboratory of Optoelectronic Information Processing Chips and Systems Guangzhou China Peng Cheng Laboratory Shenzhen China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai China

ISBN: (纸本)9798350333107

Chalcogenide glasses (ChGs) have been widely used in integrated photonics due to their excellent properties of low loss and high nonlinearity. However, the performance of the active waveguide amplifiers is merely adequate. Here, a hybrid waveguide amplifier in Ge25Sb10S65 planar waveguide by a highly erbium-doped Al2O3 layer is demonstrated. High-quality Er3+: Al2O3 thin film with high concentration of 9×1020 cm-3 is fabricated by atomic layer deposition technique. And the GeSbS waveguide is manufactured by thermal evaporation and plasma etching. Signal enhancement up to 11.93 ± 0.3 dB and internal net gain of approximately 1.28 dB/cm are obtained at 1533 nm in the 1.5-cm-long and 0.8-cm-long waveguides upon 1480 nm pumping, respectively. The hybrid configuration is proved to be an efficient strategy to implement ChG-based integrated waveguide amplifiers. © 2023 IEEE.

关键词： Germanium compounds

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SSD object detection algorithm based on knowledge map

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International Journal of Wireless and Mobile Computing 2024年第2期27卷 152-160页

作者： Huang, Li Wang, Xiaofeng Lu, Jianhua Hu, Wei Zhang, Changrong College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China

With the pervasive integration of artificial intelligence into all aspects of human life, talent emerges as a primary resource. Upon analysing the current state of talent training in higher education institutions, issues such as dispersed knowledge points, overlapping content, a singular practice approach and ineffective evaluation have been identified. In response to these challenges, this paper proposes a multidisciplinary and comprehensive practical teaching methodology grounded in the knowledge graph framework. It delves into diverse paths for practical teaching and assessment, including aspects like teaching objectives, problem decomposition, resource integration, implementation methods and performance evaluation. The practical application of the SSD algorithm in researching service robot indoor object detection serves as an illustrative example. Employing the holistic practical teaching approach facilitated by the knowledge graph, this model guides students in acquiring object detection expertise, thereby enhancing their comprehensive development. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Object detection

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Zhao, Yihan Duan, Xuting Zhou, Jianshan Zhang, Long School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

ISBN: (纸本)9798350316308

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time. © 2023 IEEE.

关键词： Autonomous vehicles

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Isolated FeN_(3)sites anchored hierarchical porous carbon nanoboxes for hydrazine-assisted rechargeable Zn-CO_(2)batteries with ultralow charge voltage

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Carbon Energy 2025年第1期7卷 121-132页

作者： Sanshuang Gao Hongyi Li Zhansheng Lu Songjie Meng Xue Zhao Xinzhong Wang Xijun Liu Guangzhi Hu Shenzhen Institute of Information Technology Shenzhen 518172China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures Guangxi Key Laboratory of Processing for Nonferrous Metals and Featured MaterialsSchool of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China School of Ecology and Environmental Science Institute for Ecological Research and Pollution Control of Plateau LakesYunnan UniversityKunming650504China State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources College of ChemistryXinjiang UniversityUrumqiChina School of Physics Henan Normal UniversityXinxiangChina Faculty of Chemistry and Chemical Engineering Yunnan Normal UniversityKunmingChina

Zn-CO_(2)batteries(ZCBs)are promising for CO_(2)conversion and electric energy ***,the ZCBs couple the electrochemical CO_(2)reduction(ECO_(2)R)with the oxygen evolution reaction and competitive hydrogen evolution reaction,which normally causes ultrahigh charge voltage and CO_(2)conversion efficiency attenuation,thereby resulting in~90%total power ***,isolated FeN_(3)sites encapsulated in hierarchical porous carbon nanoboxes(Fe-HPCN,derived from the thermal activation process of ferrocene and polydopamine-coated cubic ZIF-8)were proposed for hydrazine-assisted rechargeable ZCBs based on ECO_(2)R(discharging process:CO_(2)+2H+→CO+H_(2)O)and hydrazine oxidation reaction(HzOR,charging process:N_(2)H_(4)+4OH−→N_(2)+4H_(2)O+4e^(−)).The isolated FeN_(3)endows the HzOR with a lower overpotential and boosts the ECO_(2)R with a 96%CO Faraday efficiency(FECO).Benefitting from the bifunctional ECO_(2)R and HzOR catalytic activities,the homemade hydrazine-assisted rechargeable ZCBs assembled with the Fe-HPCN air cathode exhibited an ultralow charge voltage(decreasing by~1.84 V),excellent CO selectivity(FECO close to 100%),and high 89%energy *** situ infrared spectroscopy confirmed that Fe-HPCN can generate rate-determining*N_(2)and*CO intermediates during HzOR and ECO_(2)*** paper proposes FeN_(3)centers for bifunctional ECO_(2)R/HzOR performance and further presents the pioneering achievements of ECO_(2)R and HzOR for hydrazine-assisted rechargeable ZCBs.

关键词： electrochemical CO_(2)reduction Fe single atoms hierarchical porous carbon nanoboxes hydrazine-assisted Zn-CO_(2)batteries hydrazine oxidation reaction

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Stability Analysis of Load Frequency control System with Time-Varying Delays

Stability Analysis of Load Frequency Control System with Tim...

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2023 China Automation Congress, CAC 2023

作者： Fan, Chunling Chen, Chaoyang Zhou, Shaowu Lian, Honghai Chen, Zuguo Li, Pei School of Information and Electrical Engineering Hunan Provincial Key Laboratory of Intelligent Control and Maintenance of Complex Systems Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9798350303759

In this paper, the stability analysis of Load frequency control (LFC) systems with time-varying delay is conducted. Firstly, an augmented Lyapunov-Krasovskii (L-K) functional is designed to incorporate the relevant information of the delay state. Then, the functional derivatives are estimated using an auxiliary-function-based integral inequality in conjunction with an improved reciprocally convex inequality. Furthermore, the correlation function is processed through a quadratic function negative definite derivation. Finally, case studies established on a one-area LFC system are conducted to demonstrate the superiority of the method, and its accuracy is verified through a simulation case. © 2023 IEEE.

关键词： Electric control equipment

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Cluster routing algorithm based on agglomerative hierarchical clustering in wireless sensor networks

Cluster routing algorithm based on agglomerative hierarchica...

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2023 International Conference on Intelligent systems, Communications, and Computer Networks, ISCCN 2023

作者： Li, Hongbing Cui, Hao Ou, Jun Wang, Yuning Key Laboratory of Intelligent Information Processing Control of Chongqing Three Gorges University China Chongqing Key Laboratory of Geological Environment Monitoring Disaster Early Warning in Three Gorges Reservoir Area China Internet of Things and Intelligent Control Technology Chongqing Engineering Research Center China

ISBN: (纸本)9781510666238

To save the energy and extend the lifetime of the network, Cluster Routing Algorithm based on Agglomerative Hierarchical Clustering (CRAAHC) is proposed in wireless sensor networks. WSN is divided into a certain quantity of ring areas based on the energy consumption model. Clustering process is optimized by constraining the distance between clusters and the diameter of clusters to improve the quality of clustering algorithm. Cluster head selection strategy is improved by considering the residual energy of the node and energy consumption in communication with other nodes in one cluster. Simulation results show that CRAAHC algorithm can achieve energy efficiency and routing reliability. © 2023 SPIE.

关键词： Clustering algorithms

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A Generalized Subspace Distribution Adaptation Framework for Cross-Corpus Speech Emotion Recognition 48

A Generalized Subspace Distribution Adaptation Framework for...

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Li, Shaokai Song, Peng Ji, Liang Jin, Yun Zheng, Wenming Yantai University School of Computer and Control Engineering China Jiangsu Normal University School of Physics and Electronic Engineering China Research Center for Learning Science Southeast University Key Laboratory of Child Development and Learning Science Southeast University Ministry of Education China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province The State Key Laboratory of Tibetan Intelligent Information Processing and Application China

ISBN: (纸本)9781728163277

In this paper, we propose a novel transfer learning framework, named generalized subspace distribution adaptation (GSDA), to tackle the challenging cross-corpus speech emotion recognition problem. First, we learn a common low-dimensional feature subspace by utilizing a generalized subspace learning method. Second, we develop a novel distance metric to reduce the divergence between the source and target corpora, which can efficiently explore the similarity and dissimilarity information in the process of knowledge transfer. Third, to demonstrate the effectiveness of our framework, we apply GSDA to the traditional subspace learning algorithms. Finally, we conduct extensive experiments by using the low-level features and deep features on three popular emotional databases, i.e., Berlin, IEMOCAP, and CVE. The results demonstrate that the proposed framework can achieve better performance than several state-of-the-art transfer learning approaches. © 2023 IEEE.

关键词： Speech recognition

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Multi-Branch Spatial-Temporal Attention Graph Convolution Network for Skeleton-based Action Recognition 41

Multi-Branch Spatial-Temporal Attention Graph Convolution Ne...

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第41届中国控制会议

作者： Daoshuai Wang Dewei Li Yaonan Guan Gang Wang Haibin Shao Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Skeleton-based human action reco gnition has attracted considerable research interest due to its robustness to dynamic environments and complex *** based on graph neural networks have achieved great success in this ***,most of these graph neural network based methods adopt a single-branch or two-stream structure with limited input *** to the separation of space and time,many methods cannot pay attention to the critical information of human skeleton sequence,and multi-scale spatial-temporal dependent attention modeling becomes the key to *** paper proposes a novel multi-branch Spatio-temporal attention graph convolutional neural network(MB-STAGCN) to recognize human actions from skeleton *** proposed model adopts a multi-branch structure,fuses three-stream features,and then inputs them into the backbone network to extract features from multiple perspectives to a greater ***,we design a new temporal convolutional block for multi-scale extraction of information in the backbone *** also propose an attention block named Spatio-temporal Concat Attention(STCatAtt) to capture critical *** on benchmark datasets show remarkable performance for human action reco gnition,demonstrating the effectiveness of our method.

关键词： Skeleton-based human action recognition MB-STAGCN STCatAtt

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Learning Knowledge Evolution with Time Duration from Finer-Time-Granularity Temporal Knowledge Graph

Learning Knowledge Evolution with Time Duration from Finer-T...

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2023 China Automation Congress, CAC 2023

作者： Du, Shaochong Chen, Kang Yang, Shijie Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

How to represent the temporal information corresponding to each fact in temporal knowledge graphs (TKGs) effectively is always challenging. Most existing representation learning methods usually map the timelines of knowledges into multiple points and ignore the underlying continuous time property and periodic characteristics behind those dense timestamps in finer-time granularity temporal knowledge graphs. A novel Knowledge Evolution with Time Duration (KETD) model is proposed for knowledge representation of temporal knowledge graphs with finer-time granularities. It represents the entity embedding as a time-varying nonlinear function to find the specific continuous time property from dense timestamps. To the best of our knowledge, it is the first attempt to learn embeddings of time durations and combines them into embeddings of entities and relations to predict potential periodic facts. It also uses the temporal point process to capture the impact of historical facts on the current fact. The experiments on self-built finer-time granularity TKG of Satellite-to-Earth Communication (STEC) and two public datasets have demonstrated the superiority of KETD compared to some baseline approaches. © 2023 IEEE.

关键词： Knowledge graph

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An Integrated Scheduling Algorithm of Satellite Observation and Data Download Based on Multi-Agent Deep Reinforcement Learning

An Integrated Scheduling Algorithm of Satellite Observation ...

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2023 China Automation Congress, CAC 2023

作者： Chen, Kang Du, Shaochong Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

The earth observation satellite scheduling has always been critical for the maximum use of limited satellite resources, which basically includes scheduling ground target observation and observation data downloading. Due to the complexity of the mathematical model and its NP-hardness, current research usually splits it into two problems to simplify the model. In this paper, we propose a model of the integrated scheduling problem of satellite observation and data downloading (ISP-SODD) based on the decentralized partially observable Markov decision process (Dec-POMDP), treating each satellite as an agent with autonomous decision-making capability. A multi-agent deep reinforcement learning-based (MADRL-based) algorithm is proposed to solve it. A series of simulation experiments of different scales validate the effectiveness of the method and its advantages compared with the traditional heuristic algorithms. To the best of our knowledge, this study is the first attempt to apply multi-agent reinforcement learning to a multi-satellite scheduling scenario with downloading considerations. © 2023 IEEE.

关键词： Reinforcement learning

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