检索结果-内蒙古大学图书馆

作者： Zhou, Hui Xu, Qi He, Jiping Ren, Hangkong Zhou, Houlun Zheng, Kejia Control Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Huazhong University of Science and Technology Wuhan China Department of Anatomy Tongji medical college Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424450893

This paper describes a wearable stimulating system to investigate the effects of epidural spinal cord stimulation (ESCS) on the improvement of locomotion performance in rats with incomplete spinal cord injury (ISCI). The preliminary experiment was conducted in a 240 g Sprague Dawley rat. With different spinal cord stimulation intensities, the EMG signal was recorded from hindlimb using needle recording electrode in rats under anesthesia. It is shown that the proposed stimulating system is available for the chronic stimulation in the ISCI rodent model to investigate the mechanism of ESCS on the improvement of locomotion performance for ISCI patients. © 2011 IEEE.

关键词： Rats

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Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1104-1112页

作者： Yuling Hu Xiwei Liu School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing 100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing 100044China State Key Laboratory fo Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing 100190China Qingdao Academy of Intelligent Industries Qingdao 266109China

It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.

关键词： Computational experiments grouping evacuation graph theory high-rise building fire management strategies

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Algorithm for elliptic curve diffie-hellman key exchange based on DNA tile self-assembly

Algorithm for elliptic curve diffie-hellman key exchange bas...

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作者： Cheng, Zhen Huang, Yufang Chen, Zhihua Shi, Xiaolong Xu, Jin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China School of Electronics Engineering and Computer Science Peking University 100871 Beijing China

DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly maybe scalable. In this paper, we propose the algorithm for elliptic curve Diffie-Hellman key exchange based on DNA tile self-assembly. First we give the DNA tile self-assembly model to compute the scalar multiplication, then we can successfully implement the Diffie-Hellman key exchange over elliptic curve by extracting the result strand of the scalar multiplication. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Self assembly

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Fog images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network 42

Fog Images Generation About Unmanned Surface Vessels with Im...

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42nd Chinese control Conference, CCC 2023

作者： Tang, Yifeng Huang, Zhihui Tang, Chuancong Luo, Chuanshang Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Generative adversarial networks

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Task Allocation and Path Planning for Multiple Destinations Oriented Towards Task Updates 6

Task Allocation and Path Planning for Multiple Destinations ...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Yang, Yong He, Dingxin Mao, Huantao Chen, Hong Wu, Hongtao Liu, Zhi-Wei Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350356618

This study addresses the complexities of orchestrating multi-target transportation tasks within multi-agent systems, constrained by load capacity. The primary objective is to engineer an advanced path planning framework that assures collision avoidance and optimal load distribution. Diverging from conventional single-path strategies, this research incorporates load factors and requires continuous dynamic multi-target point and path planning to ensure agents can efficiently navigate through a series of predetermined key points. To address this complex requirement, a two-stage multi-agent task allocation and path planning method is proposed. First, an initial solution is obtained using a suboptimal algorithm, followed by optimization iterations using the large neighborhood search algorithm to improve task allocation. In the second stage, an accelerated algorithm based on priority search is used to plan optimal paths for each agent in a predetermined order. The proposed algorithm's effectiveness is comprehensively evaluated through a series of experimental evaluations and comparisons with the commercial solver Gurobi within a limited time. The results show that the proposed method achieves optimality in both running time and minimum path cost while ensuring the load balance of agents. © 2024 IEEE.

关键词： Motion planning

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Fast KNN search for big data with set compression tree and best bin first 2

Fast KNN search for big data with set compression tree and b...

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2nd International Conference on Cloud Computing and Internet of Things, CCIOT 2016

作者： Chen, Zhenjie Yan, Jingqi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of Ministry of Education for System Control and Information Processing China Shanghai China

ISBN: (纸本)9781467398213

This paper proposes k nearest neighbors (kNN) search based on set compression tree (SCT) and best bin first (BBF) to deal with the problem for big data. The large compression rate by set compression tree is achieved by compressing the set of descriptors jointly instead of compressing on a per-descript or basis. So set compression tree has a good performance in kNN search at a low bit rate. At the same time, the best bin first (BBF) is a very efficient algorithm to find the approximately kNN from a large number of high dimensional feature descriptors. SCT-BBF is a novel exploration and it improves search performance in three aspects: First, SCT-BBF requires less memory footprint, which is important in big data age. Second, it increases accuracy compared traditional method like KD-Tree and original SCT. SCT-BBF can be used with other data processing methods like PCA and SIFT to perform better. Third, this paper adopts finer search to increase accuracy at a slight loss of speed. And it can extend to big data easily. © 2016 IEEE.

关键词： Big data

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Attention-stacking adaptive fuzzy neural networks for autism diagnosis

Attention-stacking adaptive fuzzy neural networks for autism...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Shuzhan Xiao, Lei Huang, Hui Hu, Zhongyi Wenzhou University Institute of Intelligent Information System Wenzhou University Key Laboratory of Intelligent Image Processing and Analysis College of Computer Science and Artificial Intelligence Wenzhou China

ISBN: (纸本)9798350386226

The current diagnostic methods for Autism Spectrum Disorder (ASD) based on Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) face two significant challenges. Firstly, the functional connectivity networks (FCNs) of the brain are subject to uncertainty due to noise interference during the rs-fMRI acquisition process. Secondly, variations in equipment parameters across different imaging sites lead to diverse distributions of collected features. To address these issues, this paper introduces a novel Multi-Task Stacked Adaptive Fuzzy Neural Network (AT-STTSK) specifically designed for Autism Spectrum Disorder (ASD) classification. The proposed network seamlessly integrates a Multi-Output TSK (MO-TSK) fuzzy system, a Stacked Autoencoder (SAE), and a Transformer. This integration aims to reduce the impact of uncertainty factors, enhance the model's interpretability, and leverage the multi-head attention mechanisms to capture both local and global information, thus strengthening feature learning. Additionally, we explore the utilization of a Contrastive Learning (CL) strategy to further optimize the model. By incorporating these advancements, our AT-STTSK network offers a promising approach for improving the accuracy and reliability of ASD diagnosis based on rs-fMRI data. The validity of the method in this paper is verified on ABIDE dataset, and the result shows that the accuracy rate can reach 85.7% at most. © 2024 IEEE.

关键词： Diseases

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image fusion algorithm using nonsubsampled contourlet transform

Image fusion algorithm using nonsubsampled contourlet transf...

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MIPPR 2007: Multispectral image processing

作者： Yang, Xiao Zhiguo, Cao Kai, Wang Zhengxiang, Xu Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong Uni. of Sci. and Tech. Wuhan 430074 China

ISBN: (纸本)9780819469519

In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-sacle NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.

关键词： image fusion

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Motion Blurred Star image Centroid Optimized Extraction Based on Prior Gaussian Distribution 29

Motion Blurred Star Image Centroid Optimized Extraction Base...

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第29届中国控制与决策会议

作者： Peng Dingbang Chen Hao Sang Xiaochong Li Jianxun School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Institute of Spaceflight Control Technology Shanghai Key Laboratory of Aerospace Intelligent Control Technology

ISBN: (纸本)9781509046584

Star centroid extraction is the precondition of star recognition in star navigation *** image will be motion blurred under high dynamic *** methods such as Wiener filter method,restore the blurred star image with an estimated PSF to calculate the star *** unique characteristic of star images different from general images is ignored in conventional *** addition,the error of motion blur parameters estimation and the approximate linear motion model can decrease the accuracy of star centroids *** paper proposes a method utilizing the prior Gaussian distribution information of star energy to deal with the motion blurred star *** experimental results demonstrate that the proposed method gets smaller error in star centroids calculation compared with the conventional estimation method.

关键词： Motion blur Star image restoration Centroid extraction Gaussian distribution Optimize

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Design and control of an intelligent walking-aid robot 6

Design and control of an intelligent walking-aid robot

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6th International Conference on Modelling, Identification and control, ICMIC 2014

作者： Han, Rui Tao, Chunjing Huang, Jian Wang, Yongji Yan, Heping Ma, Lifang Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China RandD Department of National Research Center for Rehabilitation Technical Aids Beijing China

ISBN: (纸本)9780956715746

An intelligent walking-aid robot is presented for walking assistance, training and rehabilitation of the elderly. The robot is intended to provide physical support and mobility aid for the old people during their walking based on recognizing their motion intentions online. A force measuring system comprised of force sensing resisters (FSRs) is designed to obtain the interaction forces between the user and the robot. The user's motion intention is then estimated by analyzing the relationship between the measured interaction forces and human intention force/torque. Further the estimated intention is used to guide the admittance based motion control of robot. To ensure a safe walking, a laser range finder (LRF) is used to detect the distance between the robot and the user's legs. A distance restraint control is also designed and taken into action when the distance is found beyond a safe threshold. Experiments were conducted and the results verified the effectiveness of the developed robot system and control methods. © 2014 Swinburne University of Technology, Australia.

关键词： Walking aids

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