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arXiv 2023年

作者： Liu, Jin Mao, Junbin Lin, Hanhe Kuang, Hulin Pan, Shirui Wu, Xusheng Xie, Shan Liu, Fei Pan, Yi Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of software Xinjiang University Wulumuqi830000 China Hunan Province Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China School of Science and Engineering University of Dundee DundeeDD1 4HN United Kingdom School of Information and Communication Technology Griffith University Gold CoastQLD4215 Australia Shenzhen Health Development Research and Data Management Center Shenzhen518109 China

Graph learning-based multi-modal integration and classification is one of the most challenging tasks for disease prediction. To effectively offset the negative impact among modalities in the process of multi-modal integration and heterogeneous information extractions from graphs, we propose a novel method called Multi-modal Multi-Kernel Graph Learning (MMKGL). To solve the problem of negative impact among modalities, we propose a multi-modal graph embedding module to construct a multi-modal graph. Different from conventional methods that manually construct static graphs for all modalities, each modality generates a separate graph by adaptive learning, where a function graph and a supervision graph are introduced for optimization during the multi-graph fusion embedding process. We then propose a multi-kernel graph learning module to extract heterogeneous information from the multi-modal graph. The information in the multi-modal graph at different levels is aggregated by convolutional kernels with different receptive field sizes, followed by generating a cross-kernel discovery tensor for disease prediction. Our method is evaluated on the benchmark Autism Brain Imaging Data Exchange (ABIDE) dataset and outperforms the state-of-the-art methods. In addition, discriminative brain regions associated with autism are identified by our model, providing guidance for the study of autism pathology. The source code will be available at https://***/yutian0315/MMKGL. © 2023, CC BY-NC-ND.

关键词： Graph embeddings

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An Efficient Evolutionary Algorithm for High-Speed Train Rescheduling Under a Partial Station Blockage

SSRN

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SSRN 2023年

作者： Wang, Rongsheng Zhang, Qi Dai, Xuewu Yuan, Zhiming Zhang, Tao Ding, Shuxin Jin, Yaochu China Academy of Railway Sciences Corporation Limited Beijing100081 China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Train Operation Control Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing100081 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Faculty of Technology Bielefeld University BielefeldD-33615 Germany Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

This paper investigates the high-speed train rescheduling (HSTR) problem under a partial station blockage and proposes an efficient problem-specific strengthen elitist genetic algorithm (PS-SEGA) for HSTR. An HSTR model that is subject to train operation constraints is established to minimize the total train delay. The PS-SEGA framework consists of the following main steps. Firstly, a permutation-based encoding method is developed to define an efficient search space based on a train departure sequence. A decoding method is employed to output the rescheduled timetable and objective value based on the departure sequence. Moreover, a hybrid initialization method involving an efficient heuristic strategy (EHS) is put forward to accelerate the convergence speed of Evolutionary algorithms (EAs). Using problem-specific knowledge, EHS generates an efficient and feasible solution for the initial population. Finally, a restart strategy is presented to maintain genetic diversity. Compared with other advanced EAs and their improved variants also using the PS-SEGA framework, experimental results demonstrate the effectiveness of the proposed PS-SEGA for addressing HSTR scenarios under the partial station blockage. As for the scenarios that CPLEX can not obtain optimal solutions within 10 minutes, PS-SEGA can all provide quasi-optimal solutions in real-time. Furthermore, compared with the other two strategies (i.e., First-Scheduled-First-Served and EHS), PS-SEGA can find the best departure sequence that can output the timetable with a quasi-optimal solution. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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Depth-Map-Based Augmented Reality Holographic Stereogram: Method and Verification

SSRN

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SSRN 2022年

作者： Liu, Yunpeng Jing, Tao Lei, Ming Hu, Hairong Chen, Zhuo Lin, Min Li, Pei Jiang, Xiaoyu Yan, Xingpeng Department of Information Communication Army Academy of Armored Forces Beijing100072 China China Defense Science and Technology Information Center Beijing100037 China Department of Basic Education Army Academy of Armored Forces Beijing100072 China R & D Center for Intelligent Control and Advanced Manufacturing Research Institute of Tsinghua University in Shen Zhen Shen Zhen518057 China Department of Artificial Intelligence College of Information Systems Engineering Strategic Support Force Information Engineering University Zhengzhou450001 China

In this paper, a perspective image fusion algorithm of real-world and artificial scenes based on depth maps is proposed and applied to holographic printing to realize augmented reality display of holographic stereograms. The basic principle of the fusion algorithm is introduced, and the perspective image fusion with correct occlusion relation is implemented theoretically. Under the condition of sampling only once, an image generation algorithm with adjustable depth of artificial scenes is proposed and implemented. We use effective perspective image segmentation and mosaicking method for optical experiments, and verify the effectiveness of the proposed method. © 2022, The Authors. All rights reserved.

关键词： Three dimensional displays

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Spectrum Allocation and Aggregation in Cognitive Radio Satellite communications

Spectrum Allocation and Aggregation in Cognitive Radio Satel...

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International Conference on communications, Signal Processing, and Systems, CSPS 2018

作者： Fu, Rong Xue, Yuhong Song, Meng He, Shi Yang, Zhen Liu, Jinghui Yan, Suna Liu, Xin Beijing Institute of Control Engineering China Academy of Space Technology Beijing100094 China School of Information and Communication Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789811362637

With the rapid development of satellite communications, more and more users and services are flooding into satellite communications networks, causing a shortage of network resources. The most serious of these is the shortage of spectrum resources, which has become one of the bottlenecks to the development of satellite communications. The introduction of cognitive radio technology has greatly eased this conflict. In this paper, focusing on the shortage of KU-band satellite spectrum resources, combining the cutting-edge cognitive radio and spectrum aggregation technology in the field of communications, a KU satellite spectrum allocation strategy based on cognitive radio technology is proposed. By dynamically assigning frequency resources, the use efficiency of spectrum resources is greatly improved and user satisfaction is improved. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Cognitive radio

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Life-Time Maximization of Wireless Sensor Network Using Jaya Algorithm

Life-Time Maximization of Wireless Sensor Network Using Jaya...

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2019 IEEE International Conference on Clean Energy and Energy Efficient Electronics Circuit for Sustainable Development, INCCES 2019

作者： Ce, Jency Gurusamy, Saravanakumar Kadher K, Mohaideen Abdul Dr. Mahalingam College of Engineering and Technology Department of Electronics and Communication Engineering Pollachi626121 India Kalasalingam Academy of Research and Education Department of Instrumentation and Control Engineering Srivilliputhur626121 India

ISBN: (纸本)172814406X

Clustering is an effective way to enhance the lifetime of the Wireless Sensor Network. Moreover, due to the additional workload, cluster heads (CHs) use extra power to obtain data from other sensor nodes, combine the collected data and communicate the corresponding data to the base station. Moreover, inaccurate cluster formation may overload the cluster heads with extra nodes. Because of these excess nodes, cluster heads can rapidly die, leading to degradation of the effectiveness of WSN. In this work, a grid-based CHs assignment methodology is proposed for even distribution of CHs in the WSN to maximize lifetime, and Jaya algorithm does optimization. Results of the simulation showed that grid-based CH assignment provides maximum lifetime as compared to the random CH assignment method, and the jaya algorithm provides a better solution than the existing one. © 2019 IEEE.

关键词： Sensor nodes

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Unsupervised Domain Adaptation on Person Re-Identification via Dual-level Asymmetric Mutual Learning

arXiv

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arXiv 2023年

作者： Wu, Qiong Li, Jiahan Dai, Pingyang Ye, Qixiang Cao, Liujuan Wu, Yongjian Ji, Rongrong Institute of Artificial Intelligence The Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen University Xiamen361005 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221000 China The Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen University Xiamen361005 China The Peng Cheng Laboratory Shenzhen518066 China The School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China The Media Analytics and Computing Lab Department of Computer Science School of Informatics Xiamen University Xiamen361005 China The Youtu Laboratory Tencent Shanghai200233 China The Fujian Engineering Research Center of Trusted Artificial Intelligence Analysis and Application Institute of Artificial Intelligence Xiamen University Xiamen361005 China

Unsupervised domain adaptation person re-identification (Re-ID) aims to identify pedestrian images within an unlabeled target domain with an auxiliary labeled source-domain dataset. Many existing works attempt to recover reliable identity information by considering multiple homogeneous networks. And take these generated labels to train the model in the target domain. However, these homogeneous networks identify people in approximate subspaces and equally exchange their knowledge with others or their mean net to improve their ability, inevitably limiting the scope of available knowledge and putting them into the same mistake. This paper proposes a Dual-level Asymmetric Mutual Learning method (DAML) to learn discriminative representations from a broader knowledge scope with diverse embedding spaces. Specifically, two heterogeneous networks mutually learn knowledge from asymmetric subspaces through the pseudo label generation in a hard distillation manner. The knowledge transfer between two networks is based on an asymmetric mutual learning manner. The teacher network learns to identify both the target and source domain while adapting to the target domain distribution based on the knowledge of the student. Meanwhile, the student network is trained on the target dataset and employs the ground-truth label through the knowledge of the teacher. Extensive experiments in Market-1501, CUHK-SYSU, and MSMT17 public datasets verified the superiority of DAML over state-of-the-arts. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

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DeepSeek or ChatGPT: Can brain-computer interfaces/brain-inspired computing achieve leapfrog development with large AI models?

Brain-X

引用

Brain-X 2025年第1期3卷

作者： Bai, Long Chen, Shugeng Wang, Peng Chen, He Yan, Jiaqing Zhu, Xiaojian Song, Enming Tian, Bobo Su, Jiacan Li, Xiaoli Organoid Research Center Institute of Translational Medicine Shanghai University Shanghai China Department of Orthopedics Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China National Center for Translational Medicine (Shanghai) SHU Branch Shanghai University Shanghai China Wenzhou Institute of Shanghai University Zhejiang Wenzhou China Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai China Department of Language Literature and Communication Faculty of Humanities Vrije Universiteit Amsterdam Amsterdam Netherlands School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou China Pazhou Laboratory Guangdong Guangzhou China School of Electrical and Control Engineering North China University of Technology Beijing China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Ningbo China Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai China Key Laboratory of Polar Materials and Devices Department of Electronics Ministry of Education East China Normal University Shanghai China

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A novel airplane detection algorithm based on deep CNN 4th

A novel airplane detection algorithm based on deep CNN

引用

4th International Conference of Pioneer Computer Scientists, Engineers and Educators, ICPCSEE 2018

作者： Wang, Ying Wang, Aili Hu, Changyu Higher Education Key Lab for Measure and Control Technology and Instrumentations of Heilongjiang Harbin University of Science and Technology Harbin150080 China Department of Communication Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China

ISBN: (纸本)9789811322020

Driven by the massive natural scene image and computer’s high speed computation ability, deep CNN becomes the mainstream method for completing the computer vision task by the power of feature representation capability. Because object detections based on deep CNN are unable to achieve optimization due to lack of training set of remote sensing images, a novel method based on transfer learning and deep CNN combined with SVM is proposed in this paper. Firstly, we obtain the deep CNN model AlexNet trained on a large-scale data set. Then, we truncate the first five convolution layers and get the initial parameters through transfer learning. Then, Deep CNN is used as feature extractor to extract the depth feature for training SVM, and the final remote sensing image airplane detection model is obtained. Experimental results show that the average precision of the proposed algorithm outperforms other traditional algorithms. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Remote sensing

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A Sufficient Condition for General QAM Complementary Sequence Pairs

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Canadian Journal of Electrical and Computer engineering 2019年第1期43卷 43-56页

作者： Fanxin Zeng Yue Zeng Lisheng Zhang Xiping He Guixin Xuan Zhenyu Zhang Chongqing Engineering Laboratory for Detection Control and Integrated System Chongqing Technology and Business University Chongqing China College of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China Communication NCO Academy Army Engineering University of PLA Chongqing China

This paper investigates the construction of QAM Golay complementary sequence pairs (CSPs) based on standard binary Golay–Davis–Jedwab (GDJ) CSPs. In order to guarantee that the proposed construction produces QAM Golay CSPs, a sufficient condition that the coefficients of offsets should satisfy is developed, which is fit for finding all the coefficients by a computer. In particular, all the coefficients of offsets over the 64- and 256-QAM constellations are given. The proposed construction includes Zeng’s and Ma et al.’s ones as special cases. The inputs of resultant sequence pairs are binary signals rather than quaternary ones, which means that the resulting sequences are fit for such QAM systems that merely depend on binary inputs. The obtained QAM Golay CSPs can be applied to orthogonal frequency division multiplexing systems so as to reduce peak envelope power of their signals.

关键词： Quadrature amplitude modulation Standards Correlation Upper bound Peak to average power ratio Programmable logic arrays

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Performance Analysis of OWMR Directional Wheels Robot Arm based on (ANFIS+PID) controller

Performance Analysis of OWMR Directional Wheels Robot Arm ba...

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2018 International Conference on Computer, control, Electrical, and Electronics engineering, ICCCEEE 2018

作者： Omer, Zeinab Mahmoud Al-Agha, Osman Ibrahim Bakr, Aatif Osman Altahir Bilal, Khalid Hamid Department of Electrical and Control Engineering University of Bahri Khartoum Sudan Department of Electrical and Control Engineering Academy of Eng. Science College Khartoum Sudan Department of Communication Engineering University of Science and Technology Khartoum Sudan

ISBN: (纸本)9781538641231

The main objective of this study is to design an Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm to solve the problem of finding the inverse kinematics to control the movement of the modified PUMA 560 arm in robotic *** and stability are two major issues that face designers when control system design is intended. Tuning the system to coup with the variations and changes in the environment where the system is expected to work. In this paper the mechanical design of modified PUMA 560 robotic arm with 6 DoF was revisited and implemented with new powerful features and the experimental results were tracked. The main problem is the dynamic equations which are nonlinear and time-varying in the extreme. The challenge was how to manipulate these equations in such a way leading to a better performance regarding accuracy and stability of the system. The method used to control the base of robot arm which consists of 3-wheels with 120 degrees apart was designed and implemented. After that accurate trajectory control methods which use Adaptive Neuro Fuzzy Inference System of 3-wheels omni-directional mobile robot were implemented. Thus the design of full new robot system structure was used in the validation and testing the performance of proposed methods. This included modification of the PUMA 560 arm by the addition of an omini-directinal wheeled mobile robot (OWMR) base structure to the robotic arm. This base consisted of three motors for 3-wheels which are positioned 120 degrees apart. The resulting robot was a modified PUMA 560 robotic arm with 6 axes. The results obtained showed a significant improvement in both accuracy and stability of the system proposed. Hence, objectives were met to a great extent. © 2018 IEEE.

关键词： Mobile robots

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