It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotat...
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It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.
Modularity and rigor are two key elements for multi-agent technology. Hong Zhu's multi-agent system (MAS) development method provides proper language facilities supporting modularity. To enhance this method with r...
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Modularity and rigor are two key elements for multi-agent technology. Hong Zhu's multi-agent system (MAS) development method provides proper language facilities supporting modularity. To enhance this method with rigor advocates a DL method to map the specification of MAS into a DL TBox. Thus, we can use the existing DL reasoners and systems to verify and validate some system's properties.
Aiming at the shortcomings of the traditional butterfly optimization algorithm in solving the high-dimensional classification feature selection problem, which has low convergence and is prone to fall into local optima...
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In the heavy clutter environment, the information capacity is large,the relationships among information are complicated, and track initiationoften has a high false alarm rate or missing alarm rate. Obviously, it is ad...
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In the heavy clutter environment, the information capacity is large,the relationships among information are complicated, and track initiationoften has a high false alarm rate or missing alarm rate. Obviously, it is adifficult task to get a high-quality track initiation in the limited measurementcycles. This paper studies the multi-target track initiation in heavy *** first, a relaxed logic-based clutter filter algorithm is presented. In thealgorithm, the raw measurement is filtered by using the relaxed logic *** not only design a kind of incremental and adaptive filtering gate, but alsoadd the angle extrapolation based on polynomial extrapolation. The algorithm eliminates most of the clutter and obtains the environment with highdetection rate and less clutter. Then, we propose a fuzzy sequential Houghtransform-based track initiation algorithm. The algorithm establishes a newmeshing rule according to system noise to balance the relationship between thegrid granularity and the track initiation quality. And a flexible superpositionmatrix based on fuzzy clustering is constructed, which avoids the transformation error caused by 0–1 voting method in traditional Hough *** addition, the algorithm allows the superposition matrixes of nonadjacentcycles to be associated to overcome the shortcoming that the track can’t beinitiated in time when the measurements appear in an intermittent way. Anda slope verification method is introduced to detect formation-intensive serialtracks. Last, the sliding window method is employed to feedback the trackinitiation results timely and confirm the track. Simulation results verify thatthe proposed algorithms can initiate the tracks accurately in heavy clutter.
Image fusion technology is the basis of computer vision task,but information is easily affected by noise during *** this paper,an Improved Pigeon-Inspired Optimization(IPIO)is proposed,and used for multi-focus noisy i...
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Image fusion technology is the basis of computer vision task,but information is easily affected by noise during *** this paper,an Improved Pigeon-Inspired Optimization(IPIO)is proposed,and used for multi-focus noisy image fusion by combining with the boundary handling of the convolutional sparse *** two-scale image decomposition,the input image is decomposed into base layer and detail *** the base layer,IPIO algorithm is used to obtain the optimized weights for fusion,whose value range is gained by fusing the edge ***,the global information entropy is used as the fitness index of the IPIO,which has high efficiency especially for discrete optimization *** the detail layer,the fusion of its coefficients is completed by performing boundary processing when solving the convolution sparse representation in the frequency *** sum of the above base and detail layers is as the final fused *** results show that the proposed algorithm has a better fusion effect compared with the recent algorithms.
In order to improve the detection accuracy of spliced images, a new blind detection based on visual saliency was proposed in this paper. Firstly, create the edge conspicuous map by an improved OSF-based method, and ex...
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We present a novel object localization approach based on the Global Structure Constraint model (GSC) and Optimal Algorithm. In GSC, Objects are described as constellations of points satisfied with their specific globa...
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The multilevel thresholding problem is a challenge task due to the fact that the computation is usually very time-consuming for obtaining the optimal multilevel thresholds. Though the state-of-the-art multilevel thres...
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A process of gene expression which is designed and modeled by machine language, and by using to process complex data. At the molecular biological level, classifying and sorting the related substances involved in the t...
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The E-commerce information on the Surface Web is supported by the Deep Web, which can not be accessed directly by the search engines or the web crawlers. The only way to access the backend database is through query in...
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