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KPCA algorithm can solve the problem of nonlinear characteristic that the PCA algorithm can't handle with and the traditional curvelet decomposition algorithm cannot take full advantage of the fine scale component information. So we put forward KPCA algorithm and data fusion algorithm. The KPCA algorithm has a good effect on extracting face contour and the curve detail information through internal...
An important part for sign language expression is hand shape, and the 3D hand motion trajectories also contain abundant information to interpret the meaning of sign language. In this paper, a novel feature descriptor is proposed for sign language recognition, the hand shape features extracted from the depth images and spherical coordinate (SPC) feature extracted from the 3D hand motion trajectories...
DNA-binding proteins plays important role in a variety of vital biology processes. In this study, we apply a machine learning method for classify DNA-binding proteins from non-binding proteins based on sequence information. Using an evolutionary feature and residue composition feature extracted from primary structure, we have trained a support vector machine(SVM) to distinguish DNA-binding proteins...
Identification of DNA-binding residues in protein has made important function in several areas such as posttranscriptional regulation and protein function. in our work, we propose a method which combines a novel hybrid feature with the random forest (RF) algorithm to predict DNA-binding residues in protein sequences. the hybrid feature contains the second structure feature, predicted solvent accessibility...
We have shown that the slow eye movements extracted from electrooculogram (EOG) signals can be used to estimate human vigilance in our previous work. However, the traditional method for recording EOG signals is to place the electrodes near the eyes of subjects. This placement is inconvenient for users in real-world applications. This paper aims to find a more practical placement for acquiring EOG...
Protein-DNA interactions are vitally important in a wide range of biological processes such as gene regulation and DNA replication and repair. We predict DNA-binding residues in proteins from amino acid sequences by support vector machine (SVM) with a novel hybrid feature which incorporates evolutionary information of amino acid sequences and four physical-chemical properties, including the side chain...
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