In practical applications, we often have to deal with high order data, such as a grayscale image and a video sequence are intrinsically 2nd-order tensor and 3rd-order tensor, respectively. For doing clustering or classification of these high order data, it is a conventional way to vectorize these data before hand, as PCA or FDA does, which often induce the curse of dimensionality problem. For t...

Goal-driven autonomy (GDA) is a reflective model of goal reasoning that controls the focus of an agent’s planning activities by dynamically resolving unexpected discrepancies in the world state, which frequently arise when solving tasks in complex environments. GDA agents have performed well on such tasks by integrating methods for discrepancy recognition, explanation, goal formulation, and goa...

A modified Particle Swarm Optimization (PSO) using Great Deluge Algorithm (GDA) called MPSO for optimization is presented in this paper. In the proposed algorithm, the range for achieved answers is defined that is the same parameter used in the GDA called “water level”. Amount of this range reduces or increases regarding to algorithm’s property being used in terms of minimum or maximum during t...

BACKGROUND Glycodelin A (GdA), also known as placental protein 14 (PP14), has been detected in endometrial, cervical and ovarian carcinoma cells. It is suspected to be a marker of human ovarian cancer tissues. MATERIALS AND METHODS We investigated serum, tissue and cyst fluid samples of patients with an ovarian carcinoma in contrast to patients with benign and malignant diseases such as uteri...

For high-dimensional data classification such as hyperspectral image classification, feature extraction is a crucial pre-process for avoiding the Hughes phenomena. Some feature extraction methods such as linear discriminant analysis (LDA), nonparametric weighted feature extraction (NWFE), and their kernel versions, generalized discriminant analysis (GDA) and kernel nonparametric weighted featur...