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This paper aims to develop a new scheme for the classification of power-quality disturbances (PQDs). We propose to employ two discriminative dictionaries, designed based on the structures of PQDs, to respectively decompose a disturbance signal. Matching pursuit optimized by particle swarm optimization (PSO-MP) is used as the decomposition method. Reconstruction errors after sparse coding are employed...
Last-write-touch prediction can reduce cache-to-cache transfer latency by converting 3-hop misses into 2-hop misses in directory-based shared-memory multiprocessors. By predicting a last-write-touch and self-downgrading a cache block in advance, a processor can get the data from the memory directly and the coherence overhead is significantly reduced. In this paper, we propose a new low overhead last-write-touch...
In the boxing, free combat, kickboxing combat events, the attack speed, strength, explosive force, blow impulse etc is an important measured against attack effect and diagnostic technique indicators for players. The general fighting coaches, athletes are very eager to solve the major problem which how to analysis and evaluation the athletes technical of action by effectively obtain these indexes....
SVM is one of the most commonly used methods in the field of text classification. But, SVM is, in essence, a kind of binary classifier. When the traditional SVM is applied in text classification, many SVM must be trained, So the text classification accuracy is not ideal. In this paper, a new kind hypersphere support vector machine is applied in text classification, just require training a SVM. The...
MapReduce is a parallel programming model, and used to handle large datasets. The MapReduce program can be automatically concurrent executed in large-scale commodity machines. We proposed an improved MapReduce programming model-Pipelined-MapReduce, to solve the data intensive of information retrieval problems. Pipelined-MapReduce allows data transfer by pipeline between the operations, expanding the...
In this paper we propose a coarse-to-fine method to detect pedestrians in video sequences. The detection process is divided into two stages: ROI (region of interest) generation stage and ROI classification stage. In the generation stage haar-like features are exploited to rapidly search the whole image and find interesting regions which may contain pedestrians. In the classification stage shapelet...
The purpose of this paper is to classify 93# and 97# gasoline by using principal component analysis (PCA) with self-organizing competitive neural network method and to establish near infrared transmission spectroscopy and reflectance spectroscopy qualitative identification model in 1100-1700nm spectral region. The spectral data is condensed by PCA method before modeling, and three principal components...
Image resolution is an important factor affecting face recognition by human and computer. We propose a new nonlinear warping method to align the facial images of the training set, which is then used to predict high resolution facial image from a signal input low resolution facial image. Using sparse initial mesh specified by the facial feature points and a special designed subdivision mesh algorithm,...
In many applications, one has to actively select among a set of expensive observations before making an informed decision. In this paper, we describe a hybrid of a simple artificial intelligence algorithm and a method based on class separability applied to the selection of feature subsets for classification problems. The method allows an expert to discover informative features for separation of normal...
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