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Visually impaired people have difficulty in walking freely because of the obstacles or the stairways along their walking paths, which can lead to accidental falls. Many researchers have devoted to promoting safe walking for visually impaired people by using smartphones and computer vision. In this research we propose an alternative approach to achieve the same goal - we take advantage of the power...
With the popularity of Web 2.0, social networks have become an important channel for people to keep in contact. It is common to have hundreds of friends for a user on Face book. Thus it is quite difficult for the user to keep track on all friends¡¦ emotion and to express his/her care to them in a timely manner, which we think is essential in keeping the friendship. The Wall on Face book includes a...
Microarray technology is a big step in bioinformatics. Hidden information within the large amounts of data provides scientists with molecular functions or essential biological meanings to study and analyze. However, these data often contain a certain portion of entities that are missing. Several methods to estimate these missing values are developed, but most of them are with disadvantages. In this...
We develop a new approach for gender recognition. In this paper, our approach uses the rectangle feature vector (RFV) as a representation to identify humans' gender from their faces. The RFV is computationally fast and effective to encode intensity variations of local regions of human face. By only using few rectangle features learned by AdaBoost, we present a gender identifier. We then use nonlinear...
Using X-ray crystallography to determine the 3D structure of a protein is a costly and time-consuming process. One of the major reasons is that the protein needs to be purified and crystallized first, and the failure rate of protein crystallization is quite high. Thus it is desired to use a computational method to predict protein crystallizability based on the primary structure information before...
Microarray is an important tool in gene analysis research. It can help identify genes that might cause various cancers. In this paper, we use feature selection methods and the support vector machine (SVM) to search for the disease-causing genes in microarray data of three different cancers. The feature selection methods are based on Euclidian distance (ED) and Pearson correlation coefficient(PCC)...
This paper uses the SVM to predict the protein disordered region. Nevertheless, the number of features used in this paper is 440. Both time and space complexity is high while performing the support vector machine (SVM) training and testing. So this paper proposes a hybrid feature selection mechanism to reduce the dimensionality of the feature space. The filter and wrapper feature selection methods...
In proteomics, a proteinpsilas function is always strongly related to its structure. But, while some parts of a protein have a fixed definite structure, such as alpha-helix, beta-sheet, or coil, other parts are not associated with well-defined conformations. Previously, these so-called disordered regions were not thought to have a specific function of their own. But, recent studies suggest that some...
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