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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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Gravel image Segmentation in Noisy Background Based on Partial Entropy Method

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中国地质大学学报(英文版) 2000年第1期11卷 92-94页

作者： Wang Guangjun Tian Jinwen Chen Zhenyu Liu Jian Wu Guoping State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology WuHan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.

关键词： partial entropy segmentation mathematical morphology gravel threshold filter

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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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A Memristive Spiking Neural Network Circuit for Bio-inspired Navigation Based on Spatial Cognitive Mechanisms

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IEEE Transactions on Biomedical Circuits and Systems 2024年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation,a high-level and crucial function for organisms' survival in nature,enables autonomous exploration and navigation within the environment. However,most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation,capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application,the entire SNN is quantized and deployed on a real memristive hardware platform,achieving about a 21× reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： intelligent robots

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MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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Computers, Materials & Continua 2024年第6期79卷 4371-4393页

作者： Huiling Lu Tao Zhou School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China School of Computer Science and Engineering North Minzu UniversityYinchuan750021China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission NorthMinzu UniversityYinchuan750021China

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided ***,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are *** solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung *** pixel dependence relationship is established in local and non-local fields to improve the model perception ***,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained ***,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic ***,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image *** results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this *** method has positive significance for the detection of lung tumors.

关键词： PET/CT images instance segmentation mask RCNN interactive fusion transformer

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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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Research on the optimization of water-cooling control in high-speed steel rolling system based on Bayesian network

Research on the optimization of water-cooling control in hig...

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4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Zhang, Chong Tan, Gangjun Shi, Xiaolong Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781612843735

The existing high-speed wire production line of Wuhan Iron and Steel Group Corporation has the shortage that reliability of water-cooling control system is poor, the temperature of rolling line fluctuation range is large. Taking these problems into consideration, we build a water-cooling temperature model based on Bayesian network in order to improve the control accuracy. And the optimized system works well in the industrial site. © 2011 IEEE.

关键词： Bayesian networks

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Algorithmic tile assembly for solution of the maximum clique problem

Algorithmic tile assembly for solution of the maximum clique...

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

The maximum clique problem has diverse applications in the field of pattern recognition, computer vision, information processing etc. The connection between self-assembly and computation has implied that the tile assembly can perform arithmetical computation. Approaches to algorithmic self- assembly require the use of DNA nanostructures, called tiles, which have efficient computational power, and convenient input and output mechanisms. We present a theoretical tile assembly model for the maximum clique problem. We take some transformation to the maximum clique problem and convert it into the 0-1 programming problem. By use of the huge parallelism inherent in the arithmetic tile assembly, it outputs a reporter strand which includes the solution to the problem. It is proved that this method can be extended to the maximum independent set problem and 0-1 programming problem. The arithmetic tile assembly model proposed here can give the answer by use of 0(2n2 + 2mn+ 12n) tile types in time linear with the input size. Copyright © 2010 American Scientific Publishers. All right resered.

关键词： Computational complexity

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An overview of Hierarchical Temporal Memory: A new neocortex algorithm

An overview of Hierarchical Temporal Memory: A new neocortex...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Chen, Xi Wang, Wei Li, Wei Institute of System Engineering Huazhong University of Science and Technology Education Ministry of China Wuhan Hubei 430074 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory Education Ministry of China China

ISBN: (纸本)9780956715715

The overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive method based on the principle of how human brain works. The method invites hierarchical structure and proposes a memory-prediction framework, thus making it able to predict what will happen in the near future. This overview mainly introduces the developing process of HTM, as well as its principle, characteristics, advantages and applications in vision, image processing and robots movement, some potential applications by using HTM, such as thinking process, are also put forward. © 2012 Huazhong Univ of Sci & Tec.

关键词： Forecasting

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Four development stages of collective intelligence

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Frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 903-916页

作者： Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

The new generation of artificial intelligence(AI)research initiated by Chinese scholars conforms to the needs of a new information environment changes,and strives to advance traditional artificial intelligence(AI 1.0)to a new stage of AI *** one of the important components of AI,collective intelligence(CI 1.0),i.e.,swarm intelligence,is developing to the stage of CI 2.0(crowd intelligence).Through in-depth analysis and informative argumentation,it is found that an incompatibility exists between CI 1.0 and CI ***,CI 1.5 is introduced to build a bridge between the above two stages,which is based on biocollaborative behavioral *** 1.5 is the transition from CI 1.0 to CI 2.0,which contributes to the compatibility of the two ***,a new interpretation of the meta-synthesis of wisdom proposed by Qian Xuesen is *** meta-synthesis of wisdom,as an improvement of crowd intelligence,is an advanced stage of bionic intelligence,i.e.,CI *** is pointed out that the dual-wheel drive of large language models and big data with deep uncertainty is an evolutionary path from CI 2.0 to CI 3.0,and some elaboration is *** a result,we propose four development stages(CI 1.0,CI 1.5,CI 2.0,and CI 3.0),which form a complete framework for the development of *** different stages are progressively improved and have good *** to the dominant role of cooperation in the development stages of CI,three types of cooperation in CI are discussed:indirect regulatory cooperation in lower organisms,direct communicative cooperation in higher organisms,and shared intention based collaboration in *** division is the main form of achieving cooperation and,for this reason,this paper investigates the relationship between the complexity of behavior and types of labor ***,based on the overall understanding of the four development stages of CI,the future development direction and research issues of CI are explored.

关键词： Collective intelligence Meta-synthesis of wisdom Incompatibility Labor division Cooperative behavior Collective intelligence emergence Large language model

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