In multimedia databases, the spatial index structures based on trees (like R-tree, M-tree) have been proved to be efficient and scalable for low-dimensional data retrieval. However, if the data dimensionality is too high, the hierarchy of nested regions (represented by the tree nodes) becomes spatially indistinct. Hence, the query processing deteriorates to inefficient index traversal (in terms...

anomaly detection (ad) has recently become an important application of hyperspectral images analysis. the goal of these algorithms is to find the objects in the image scene which are anomalous in comparison to their surrounding background. one way to improve the performance and runtime of these algorithms is to use dimensionality reduction (dr) techniques. this paper evaluates the effect of thr...

In the literature, The most mentioned issues about measuring poverty are its multi dimensionality and vagueness. Besides traditional approaches fuzzy approaches are widely employed. In this study fuzzy index of poverty (FIP) is calculated for Turkey based on approximately 25000 households. The indicators are disposable income, food expenditure, clothing and footwear expenditures and habitable a...

Given a point q, a reverse k nearest neighbor (RkNN) query retrieves all the data points that have q as one of their k nearest neighbors. Existing methods for processing such queries have at least one of the following deficiencies: (i) they do not support arbitrary values of k (ii) they cannot deal efficiently with database updates, (iii) they are applicable only to 2D data (but not to higher d...

Creating an accurate Speech Emotion Recognition (SER) system depends on extracting features relevant to that of emotions from speech. In this paper, the features that are extracted from the speech samples include Mel Frequency Cepstral Coefficients (MFCC), energy, pitch, spectral flux, spectral roll-off and spectral stationarity. In order to avoid the 'curse of dimensionality', statis...

Dimensionality Reduction (DR) has found many applications in hyperspectral image processing. This book chapter investigates Projection Pursuit (PP)-based Dimensionality Reduction, (PP-DR) which includes both Principal Components Analysis (PCA) and Independent Component Analysis (ICA) as special cases. Three approaches are developed for PP-DR. One is to use a Projection Index (PI) to produce pro...

This paper describes a system for indexing acoustic feature vectors for large-scale speaker search using random projections. Given one or more target feature vectors, large-scale speaker search enables returning similar vectors (in a nearest-neighbors fashion) in sublinear time. The speaker feature space is comprised of i-vectors, derived from Gaussian Mixture Model supervectors. The index and ...

BACKGROUND Despite the use of genetic services, counselees do not always share hereditary cancer information with at-risk relatives. Reasons for not informing relatives may be categorized as a lack of: knowledge, motivation, and/or self-efficacy. PURPOSE This study aims to develop and test the psychometric properties of the Informing Relatives Inventory, a battery of instruments that intend t...