Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate t...
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Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem Brain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of a-helical membrane proteins. Mem Brain achieves aprediction accuracy of 97.9% of ATMH, 87.1% of AP,3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. Mem BrainContact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction,respectively. And Mem Brain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of13.593. These prediction results provide valuable hints for revealing the structure and function of membrane *** Brain web server is free for academic use and available at ***/bioinf/Mem Brain/.
This paper presents a neural network sliding mode control algorithm for position control of modular robot. This method adopts BP neural network to approximate the functional relation between the sliding hyperplane and...
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ISBN:
(纸本)9781467355339
This paper presents a neural network sliding mode control algorithm for position control of modular robot. This method adopts BP neural network to approximate the functional relation between the sliding hyperplane and the exponential approximation rate. At the same time, the saturation function of sliding mode control algorithm is replaced by a hyperbolic tangent function to realize the boundary design method of the sliding mode control. The results of real-time simulation show that the algorithm proposed in this paper has the merits of fast response, strong robustness, and reducing the chattering of sliding mode control. This method solves the problems that conventional PID algorithm can’t solve under some circumstances, such as complicated environment, great load change, etc.
An important class of radiometric degradations we are faced with often in practice is image blurring. Special attention is paid to the recognition of the blurred image by moment invariant approach. Some important rule...
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Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the proces...
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ISBN:
(纸本)9781479947249
Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.
This paper proposes a novel method to deal with overexposure for C-arm CT reconstruction. The proposed method is based on recent progress of one bit compressive sensing (1bit-CS), which is to recover sparse signals fr...
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The human visual system as a functional unit including the eyes, the nervous system, and the corresponding parts of the brain certainly ranks among the most important means of human information processing. The e?cienc...
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ISBN:
(数字)9780387216430
ISBN:
(纸本)9780387950662;9781475775174
The human visual system as a functional unit including the eyes, the nervous system, and the corresponding parts of the brain certainly ranks among the most important means of human information processing. The e?ciency of the biological systems is beyond the capabilities of today’s technical systems, even with the fastest available computer systems. However, there are areas of application where digital image analysis systems produce acceptable results. Systems in these areas solve very specialized tasks, they operate in a limited environment, and high speed is often not necessary. Several factors determine the economical application of technical vision systems: cost, speed, ?exibility, robu- ness, functionality, and integration with other system components. Many of the recent developments in digital imageprocessing and patternrecognition show some of the required achievements. Computer vision enhances the capabilities of computer systems • in autonomously collecting large amounts of data, • in extracting relevant information, • in perceiving its environment, and • in automatic or semiautomatic operation in this environment. The development of computer systems in general shows a steadily increasing need in computational power, which comes with decreasing hardware costs.
This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two-polarity trend. According to the observation that the...
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Object detection is an important and fundamental task in computer vision. Recently, the emergence of deep neural network has made considerable progress in object detection. Deep neural network object detectors can be ...
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In this paper we present SIMBA, a content based image retrieval system performing queries based on image appearance. We consider absolute object positions irrelevant for image similarity here and therefore propose to ...
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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 b...
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