Since the threshold segmentation methods can't divide the interested objects from intricate background perfectly, in this paper, we proposed a new method that combined graph theory with optimal threshold method. W...
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Since the threshold segmentation methods can't divide the interested objects from intricate background perfectly, in this paper, we proposed a new method that combined graph theory with optimal threshold method. With this method we have made a good integration of the two methods above to ensure that the segment results have smooth boundary and complete regions. Through a lot of experiments, we can draw the conclusion that the proposed method can extract the objects from intricate background perfectly and meet the need of applications.
作者:
Yang, XinDing, Ming-YueZhou, Cheng-Ping
Huazhong Unvi. of Sci. and Tech. Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Wuhan 430074 Hubei China School of Life Science and Technology
Huazhong Unvi. of Sci. and Tech. Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Wuhan 430074 Hubei China
Huazhong Unvi. of Sci. and Tech. State Key Laboratory for Multi-spectral Information Processing Technologies Wuhan 430074 Hubei China
This paper focuses on route planning, especially for unmanned aircrafts in marine environment. Firstly, new heuristic information is adopted such as threat-zone, turn maneuver and forbid-zone based on voyage heuristic...
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The paper presents a foot pressure measuring system connected with EEG It can quantify the relationship between human gait cycle and EEG signals. Understanding the relationship will help in the prevention of potential...
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The paper presents a foot pressure measuring system connected with EEG It can quantify the relationship between human gait cycle and EEG signals. Understanding the relationship will help in the prevention of potential motor dysfunction disease and the development of rehabilitation tools. The whole system is composed of three parts: EEG signal acquisition, foot landing signal acquisition and the synchronization of these two signals. EEG signal can be acquired by Neuroscan EEG system. The plantar pressure measuring system (PPMS) is designed in details. With PVDF piezoelectric film sensor insole, PPMS could measure the plantar pressure precisely, and send a TTL signal as a mark to EEG system synchronously with EEG signal when the foot contacts the ground at beginning of each gait cycle. The experiment results shows that EEG signals are in line with human gait cycle on dynamic response. From that, some potential diseases can be predict, such as dyskinesia, peripheral neuropathy, neurological disorder, musculoskeletal disease and so on. It can also be used to monitor improvements in rehabilitation.
Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic started to be considered also in the framework of (synchronized) spiking neural P system...
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Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic started to be considered also in the framework of (synchronized) spiking neural P systems. In this work, it is focused on small universal spiking neural P systems working in a non-synchronized manner. Specifically, it is proved that there is an asynchronous spiking neural P system with 76 neurons that is equivalent to a universal register machine for computing functions. As generator of sets of numbers, a universal asynchronous spiking neural P system with 75 neurons is constructed.
In this paper, an improved formulation of optimal guidance law (OGL) based on genetic algorithms (GAs) is proposed. Linear quadratic optimal control theory is derived to consider terminal velocity maximisation, also G...
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Robotic-assisted therapy is of benefit to the recovery of upper limb motor function for the patients survived stoke. Whereas, there are few emphases on the patients' motion intention during the rehabilitation proc...
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Robotic-assisted therapy is of benefit to the recovery of upper limb motor function for the patients survived stoke. Whereas, there are few emphases on the patients' motion intention during the rehabilitation process. The goal of this study is to combine the control strategies based on patients' motion intention with an upper limb rehabilitation robot to improve the recovery for the patients. In this paper, we propose an integrated robot-assist rehabilitation system, in which a 3 degree-of-freedom (DOF) exoskeletal rehabilitation robot, an EMG-based intention recognition module and a VR game environment are seamlessly combined. According toharacteristics of EMG signals, the wavelet package analysis approach is applied to extract the features of EMG. The node energy is used to construct the feature vector instead of the original coefficients of wavelet package decomposition to resolve the time-invariance problem. Then feature projection results in the singularity problem of with-in scatter matrix during the feature dimension reduction. To overcome the disadvantage of the with-in scatter matrix, this paper uses a recursive algorithm which is proposed in our previous work. The reduced feature vector is recognized by a neural network classifier and the output of the classifier is used for the control inputs. Preliminary experiments are also performed to implement the control of the rehabilitation robotic system by using the proposed EMG reorganization method, together with a dart game realized in the virtual reality environment. Experimental results show that the performance of motion intention recognition is satisfactory and the entire integrated system is feasible.
Roadmap methods were widely used in route planning fields, both for robots and unmanned aircrafts. Traditional roadmap is constituted by connecting the vertexes of convex obstacle, which is related to the locations of...
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Real-world optimization involving multiple objectives in changing environment known as dynamic multi-objective optimization (DMO) is a challenging task, especially special regions are preferred by decision maker (DM)....
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ISBN:
(纸本)9781450300728
Real-world optimization involving multiple objectives in changing environment known as dynamic multi-objective optimization (DMO) is a challenging task, especially special regions are preferred by decision maker (DM). Based on a novel preference dominance concept called sphere-dominance and the theory of artificial immune system. (AIS), a sphere-dominance preference immune-inspired algorithm (SPIA) is proposed for DMO in this paper. The main contributions of SPIA are its preference mechanism and its sampling study, which are based on the novel spheredominance and probability statistics, respectively. Besides, SPIA introduces two hypermutation strategies based on history information and Gaussian mutation, respectively. In each generation, which way to do hypermutation is automatically determined by a sampling study for accelerating the search process. Furthermore, The interactive scheme of SPIA enables DM to include his/her preference without modifying the main structure of the algorithm. The results show that SPIA can obtain a well distributed solution set efficiently converging into the DM's preferred region for DMO. Copyright 2010 ACM.
In conventional techniques for modeling Pneumatic artificial muscle, there are difficulties such as poor knowledge of the process, inaccurate process or complexity of the resulting mathematical model. Trying to solve ...
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In conventional techniques for modeling Pneumatic artificial muscle, there are difficulties such as poor knowledge of the process, inaccurate process or complexity of the resulting mathematical model. Trying to solve these problems, this study investigates the method of establishing the model using a novel network—Echo State Network (ESN). We introduce the mechanism of this net and apply it to our modeling work. The relevant parameters of the net were optimized using Particle Swarm Optimization (PSO). Then we get the simulation results which reveal that it can get quite satisfactory results.
Temporal lobe epilepsy (TLE) is a neurological disease that affects millions of individuals in the world. Majority of TLE patients suffer from refractory seizures. Determining abnormal/damaged regions of the brain tha...
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