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arXiv 2024年

作者： Li, Zhaokang Zhang, Qian Xu, Jiayue Li, Chuntao Yang, Xi School of Artificial Intelligence Jilin University Changchun Jilin130000 China School of Archaeology Jilin University Changchun Jilin130000 China Key Laboratory of Ancient Chinese Script Cultural Relics and Artificial Intelligence Jilin University Changchun Jilin130000 China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence MoE Changchun Jilin130000 China

Museums, which are among the most popular science institutions outside schools, are usually used to display and introduce historical culture and cultural relics to tourists. Text and audio explanations are used by traditional museums to popularize historical knowledge and science for tourists, and general interactive systems are based on desktops. This learning method is relatively boring in terms of experience. As a result, tourists have no desire or interest in actively exploring and learning about bronze ware, so they only have a basic understanding about bronze ware. Since most tourists are familiar with games, they are more likely to be attracted by game content and will actively explore and interact with it. In addition, a certain degree of reality is created by virtual reality technology and an immersive experience through head-mounted devices is provided to users. In this paper, we take Chinese bronzes as the research objects. We first use 3D laser scanners to obtain bronze models;then, we build a virtual museum environment, and we finally design a virtual reality curation game based on this bronze digital museum. This game offers visitors an immersive museum roaming and bronze ware interactive experience. Through a combination of text, video learning, and games, visitors' curiosity and desire to explore bronze ware are stimulated, and their understanding and ability to remember bronze ware knowledge can be deepened. In terms of cultural heritage, this game is also conducive to the spread of traditional Chinese bronze culture throughout the world. Copyright © 2024, The Authors. All rights reserved.

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Optimal camera-robot pose estimation in linear time from points and lines

arXiv

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arXiv 2024年

作者： Zeng, Guangyang Mu, Biqiang Zeng, Qingcheng Song, Yuchen Dai, Chulin Shi, Guodong Wu, Junfeng School of Data Science Chinese University of Hong Kong Shenzhen China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Guangzhou China Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Sydney Australia

Camera pose estimation is a fundamental problem in robotics. This paper focuses on two issues of interest: First, point and line features have complementary advantages, and it is of great value to design a uniform algorithm that can fuse them effectively;Second, with the development of modern front-end techniques, a large number of features can exist in a single image, which presents a potential for highly accurate robot pose estimation. With these observations, we propose AOPnP(L), an optimal linear-time camera-robot pose estimation algorithm from points and lines. Specifically, we represent a line with two distinct points on it and unify the noise model for point and line measurements where noises are added to 2D points in the image. By utilizing Plücker coordinates for line parameterization, we formulate a maximum likelihood (ML) problem for combined point and line measurements. To optimally solve the ML problem, AOPnP(L) adopts a two-step estimation scheme. In the first step, a consistent estimate that can converge to the true pose is devised by virtue of bias elimination. In the second step, a single Gauss-Newton iteration is executed to refine the initial estimate. AOPnP(L) features theoretical optimality in the sense that its mean squared error converges to the Cramér-Rao lower bound. Moreover, it owns a linear time complexity. These properties make it well-suited for precision-demanding and real-time robot pose estimation. Extensive experiments are conducted to validate our theoretical developments and demonstrate the superiority of AOPnP(L) in both static localization and dynamic odometry systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

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Regeneration and functional recovery of the completely transected optic nerve in adult rats by CNTF-chitosan

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Signal Transduction and Targeted Therapy 2023年第3期8卷 912-915页

作者： Xiao Liu Fei Hao Peng Hao Jingxue Zhang Liqiang Wang Si-Wei You Ningli Wang Zhaoyang Yang Kwok-Fai So Xiaoguang Li Department of Neurobiology School of Basic Medical SciencesCapital Medical University100069 BeijingChina School of Engineering Medicine Beijing Key Laboratory for Biomaterials and Neural RegenerationBeihang University100083 BeijingChina Beijing Tongren Eye Center Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology and Visual Sciences Key Laboratory100005 BeijingChina Department of Ophthalmology The Third Medical CenterChinese PLA General Hospital100089 BeijingChina Department of Ophthalmology Xijing HospitalThe Fourth Military Medical University710032 Xi’anShanxi ProvinceChina Guangdong-Hongkong-Macao Institute of CNS Regeneration Ministry of Education CNS Regeneration Collaborative Joint LaboratoryJinan University510632 GuangzhouGuangdong ProvinceChina Bioland Laboratory(Guangzhou Regenerative Medicine and Health Guangdong Laboratory) 510530 GuangzhouGuangdong ProvinceChina Department of Ophthalmology and State Key Laboratory of Brain and Cognitive Sciences The University of Hong Kong999077 Hong KongChina Center for Brain Science and Brain-Inspired Intelligence Guangdong-Hong Kong-Macao Greater Bay Area510515 GuangzhouGuangdong ProvinceChina Co-innovation Center of Neuroregeneration Nantong University226001 NantongJiangsu ProvinceChina Beijing International Cooperation Bases for Science and Technology on Biomaterials and Neural Regeneration Beijing Advanced Innovation Center for Big Data-Based Precision MedicineBeihang University100083 BeijingChina

Dear Editor,The optic nerve,which belongs to the central nervous system(CNS),cannot regenerate when injured in adult mammals.1 Up to now,no readily translatable measures are available for repairing a severely injured optic *** we demonstrated that ciliary neurotrophic factor(CNTF)-chitosan enabled the reconstruction and functional recovery of the adult rat visual system,thus shedding light on the clinical potential for repairing the severely injured optic nerve.

关键词： Regeneration functional CNTF

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Chinese News Text Classification and Its Application Based on Combined-Convolutional Neural Network

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Journal of Computers (Taiwan) 2022年第4期33卷 1-14页

作者： Liu, Kai-Feng Zhang, Yu Zhang, Quan-Xin Wang, Yan-Ge Gao, Kai-Long Jiangsu Vocational College of Finance and Economics Huaian223003 China School of Electrical and Information Engineering Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture Beijing100044 China State Key Laboratory in China for GeoMechanics and Deep Underground Engineering China University of Mining & Technology Beijing100083 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China

A method based on combined-convolutional neural network (Combined-CNN) for Chinese news text classification is proposed. First of all, in order to solve the problem of a lack of special term set for Chinese news classification, a vocabulary suitable for Chinese long text classification is made by constructing a data index method. The Word2Vec pre-trained model was used to embed the text features word vectors. Second, by optimizing the structure of the classical convolutional neural network (CNN) model, a new idea of Combined-CNN model is proposed, which solves the problem of incomplete feature extraction of local text blocks and improves the accuracy rate of Chinese news text classification. Effective model regularization and RAdam optimization algorithm are designed in the model to enhance the model training effect. The experimental results show that the precision of the Combined-CNN model for Chinese news text classification reaches 93.69%. Compared with traditional machine learning methods and deep learning algorithms, the accuracy rate is improved by a maximum of 11.82% and 1.9%, respectively, and it is better than the comparison model in Recall and F-Measure. Finally, the Chinese news classification algorithm of the Combined-CNN is applied to realize a personalized recommendation system. © 2022 Computer Society of the Republic of China. All rights reserved.

关键词： Recommender systems

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Surface crack width measurement based on digital image processing

Surface crack width measurement based on digital image proce...

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Chinese Control and Decision Conference, CCDC

作者： Zongyuan Xie Hongyan Ma Yongxue Ye Jiaming Dou Shengyan Li Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture Beijing China National Virtual Simulation Experimental Center for Smart City Education Beijing China

ISBN: (纸本)9781665478977

Cracks are common and dangerous hazards in buildings. Aiming at the defects of low accuracy and poor feasibility in traditional crack width detection, proposing a crack width measurement method based on an orthogonal skeleton line. Firstly, the crack image is processed by grayscale. Secondly, the processed image is median filtering and threshold segmentation. Finally, the skeleton and outline of the crack image were extracted by this method, and the measurement and comparison of simulated cracks and actual cracks are completed. The simulation results show that this method has high accuracy and feasibility and can meet the accuracy of engineering practice.

关键词： Image segmentation Simulation Buildings Process control Position measurement Gray-scale Skeleton

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Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach

arXiv

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arXiv 2024年

作者： Zheng, Jiakang Zhang, Jiayi Du, Hongyang Zhang, Ruichen Niyato, Dusit Dobre, Octavia A. Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong The College of Computing and Data Science Nanyang Technological University Singapore Faculty of Engineering and Applied Science Memorial University Canada The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China

Cell-free (CF) massive multiple-input multiple-output (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Rate-splitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, which combines strengths and mitigates weaknesses of both approaches. Considering imperfect channel state information (CSI) resulting from both pilot contamination and noise, we derive a closed-form expression for the sum spectral efficiency (SE) of the RS-based CF massive MIMO system under a spatially correlated Rician channel. Moreover, we propose low-complexity heuristic algorithms based on statistical CSI for power-splitting of common messages and power-control of private messages, and genetic algorithm is adopted as a solution for upper bound performance. Furthermore, we formulate a joint optimization problem, aiming to maximize the sum SE of the RS-based CF massive MIMO system by optimizing the power-splitting factor and power-control coefficient. Importantly, we improve a generative AI (GAI) algorithm to address this complex and non-convexity problem by using a diffusion model to obtain solutions. Simulation results demonstrate its effectiveness and practicality in mitigating interference, especially in dynamic environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Click-Through Rate Prediction Models based on Interest Modeling 5

Click-Through Rate Prediction Models based on Interest Model...

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5th International Conference on Big data engineering, BDE 2023

作者： Luo, Zhen Zhang, Yingfang Hu, Chengxuan Xia, Yuxuan Zhu, Shengxin Department of Statistical Science University College London United Kingdom Department of Statistics and Actuarial Science University of Hong Kong Hong Kong Hong Kong Department of Industrial and Systems Engineering Polytechnic University of Hong Kong Hong Kong Hong Kong School of Mathematics University of Southampton United Kingdom Research Center for Mathematics Advanced Institute of Natural Science Beijing Normal University Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College China

ISBN: (纸本)9798400708695

Deep learning frameworks have achieved extraordinary results in popular technological frontiers, which also greatly inspires considerable researchers in recommender system. As one of the mainstream research frontiers, click-through rate (CTR) predictions have received increasing attention from both industrial and academic circles. Recently, Alibaba group has come up with novel idea of interest modeling that can effectively overcome the limitations brought by previous deep learning CTR prediction models, which is also the key to improve performance. For the past few years, more and more relevant works begin to explore approaches taking advantage of the learning, representation, and interpretation ability from neural networks. However, there are few comprehensive surveys targeted at this topic. In this paper, we systematically review and summarize recent CTR prediction models based on interest modeling. First, we elaborate their different design ideas and pay additional attention to their intrinsic relationship including improvements and extensions, similarities and differences, advantages and disadvantages and so on. Next, we deploy them separately according to official open-source code and compare their performance assessment in terms of accuracy and speed, looking for best optimizers and other hyperparameters. Furthermore, we briefly discuss some possible refinement directions and future research trends. © 2023 ACM.

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Study of PSO Optimized BP Neural Network and Smith Predictor for MOCVD Temperature Control in 7nm 5G Chip Process 6th

Study of PSO Optimized BP Neural Network and Smith Predictor...

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6th International Conference on Advanced Intelligent Systems and Informatics, AISI 2020

作者： Chang, Kuo-Chi Zhou, Yu-Wen Wang, Hsiao-Chuan Lin, Yuh-Chung Chu, Kai-Chun Hsu, Tsui-Lien Pan, Jeng-Shyang School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan Department of Business Management Fujian University of Technology Fuzhou China Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Computer Science and Engineering Shandong University of Science and Technology Shandong China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9783030586683

The key industries of information technology in the semiconductor integrated circuit industry will have an important role after 2020, In the third generation of advanced semiconductor of 7nm 5G chips GaN is be used, MOCVD is a key technology for preparing high-quality communication semiconductor crystals. This study proposes PID controller of PSO and BP neural network algorithm to improve the control ability of MOCVD temperature. From the research results, it is found that the method proposed in this study adopts the PSO and BP neural network intelligent PID algorithm controller with Smith predictor, which has better dynamic performance, and the value from 150 to 500s is stable from 0 to 1 no vibration, any overshoot and short adjustment time, ideal control. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Controllers

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Modeling and Simulation for Battery Energy Storage System Participating in Power System Frequency Modulation Based on Power System Analysis Software Package 1

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16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020

作者： Cao, Pengcheng Li, Peiqiang Sun, Peidong Zhang, Zhongkai Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Kota Kinabalu Sabah Malaysia

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

Battery energy storage technology, with its fast and accurate power response, has become the focus of the auxiliary means of power system frequency modulation. However, the traditional simulation software lacks an accurate battery energy storage system component model, which affects the accuracy of analyzing the response characteristics of the energy storage system to a certain extent. This paper presents an electromechanical transient model of battery energy storage system without time delay, which considers the participation of energy storage system in frequency modulation dead zone and battery charging and discharging power. The control model is built based on the node current injection method by using the power system analysis integrated program, and the EPRI-7 standard system is selected for simulation analysis. The simulation results show that the model has good implant ability. And when the load is cut off in the power system, the energy storage system participating in frequency modulation can effectively maintain the frequency stability. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer software

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PHY Secure Hybrid Precoding with Max-Min Fair Energy Harvesting for mm Wave MU-MIMO-SWIPT Communications

PHY Secure Hybrid Precoding with Max-Min Fair Energy Harvest...

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International Conference on Communication Technology (ICCT)

作者： Bowen Xue Chi Zhang Dandan Mao Zhengyu Zhu Wenxiang Shi Ning Wang School of Electrical and Information Engineering Zhengzhou University Zhengzhou China China Information Technology Designing and Consulting Institute Co. Ltd. Beijing China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou China State Key Laboratory of Millimeter Waves Southeast University Nanjing China

Physical Layer Secure (PLS) hybrid precoding for Simultaneous Wireless Information and Power Transfer (SWIPT) in a multi-user multiple-input-multiple-output (MU-MIMO) communication system over the millimeter wave (mmWave) band is investigated. Because a limited radio frequency (RF) chain architecture is adopted at the Base Station (BS) of the system, the precoding scheme is divided into two parts, i.e. the analog precoding part and the digital precoding part. Considering a typical use case where the users are Internet-of-Things (IoT)-type devices whose proper operations rely on the harvested energy from wireless power transfer, a fairness problem for harvested energy among users is considered, and a constrained max-min optimization problem is formulated accordingly. Given specific analog precoding based on quantized phase shifter array, the formulated problem aims to maximize the minimum received power of the users by jointly optimizing the digital precoding, the additive Artificial Noise (AN) for improved secrecy, and the power allocation, subject to the secrecy rate constraint and the total transmission power constraint. Due to the non-convexity property of the original optimization problem with the design variables coupled in both the objective function and the constraints, an iterative Successive Convex Approximation (SCA) method is employed to give sub-optimal solutions. Effectiveness and convergence of the proposed design are validated through extensive simulation with different system setting parameters, and tradeoffs between the secrecy rate, the wireless energy transfer, and the hardware complexity are discussed.

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