A general-purpose useful parameter in data analysis is the intrinsic dimension of a data set, corresponding to the minimum number of variables necessary to describe the data without significant loss of information. Feature extraction, including linear or nonlinear mapping technique, is efficient to estimate the intrinsic dimension of the data set, which is a key issue to machine fault diagnosis...

Many studies have highlighted the importance of personalized learning, and most current e-learning systems are able to personalize materials, activities, etc., based on individualized learner-factors. However, none of the extant word-learning systems provides a personalized learning experience that is guided by a comprehensive word learning theory. In this study, we develop such a system based ...

This paper presents novel technique for recognizing faces. The proposed method uses hybrid feature extraction techniques such as Chi square and entropy are combined together. Feed forward and self-organizing neural network are used for classification. We evaluate proposed method using FACE94 and ORL database and achieved better performance. Keywords-Biometric; Chi square test; Entropy; FFNN; SOM.

the brain – computer interface (bci) provides a communicational channel between human and machine. most of these systems are based on brain activities. brain computer-interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. the success of this methodology depends on the selection of methods to process the brain signals in each pha...

We describe a systematic analysis on the effectiveness of features commonly exploited for the problem of predicting machine translation quality. Using a feature selection technique based on Gaussian Processes, we identify small subsets of features that perform well across many datasets for different language pairs, text domains, machine translation systems and quality labels. In addition, we sh...

Texture analysis plays an increasingly important role in computer vision. Since the textural properties of images appear to carry useful information for discrimination purposes, it is important to develop significant features for texture. This paper presents a novel technique for texture extraction and classification. The proposed feature extraction technique uses 2D–DFT transformation. A combi...

Voice biometric feature extraction is the core task in developing any speaker identification system. This paper proposes a robust feature extraction technique for the purpose of speaker identification. The technique is based on processing monaural speech signal using human auditory system based Gammatone Filterbank (GTF) and Independent Component Analysis (ICA). The measures used to assess the ...

Motion estimation (ME) is one of the most time-consuming parts in video encoding system, and significantly affects the quality of the reconstructed sequences. In this paper, we propose a new fast algorithm, or the Feature Assisted Search Technique for Motion Estimation (FASTME), which is a gradient descent search combined with a new search strategy, namely, one-dimensional feature matching base...