The research work presented in this paper is to achieve the tissue classification and automatically diagnosis the abnormal tumor region present in Computed Tomography (CT) images using the wavelet based statistical texture analysis method. Comparative studies of texture analysis method are performed for the proposed wavelet based texture analysis method and Spatial Gray Level Dependence Method ...

Clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. K-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. In recent years, several algorithms are provided based on evolutionary algorithms for cluster...

Genetic Algorithm (GA), Ant Colony Optimization (ACO) algorithm and Particle Swarm Optimization (PSO) are proposed for feature selection, and their performance is compared. The Spatial Gray Level Dependence Method (SGLDM) is used for feature extraction. The selected features are fed to a three-layer Backpropagation Network hybrid with Ant Colony Optimization and Particle Swarm Optimization (BPN...

The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorit...

Relative performance of the back propagation neural network (BPN) algorithm combined with genetic algorithm (GA) approach for the prediction/optimization of the properties of yarn produced on jet ring spinning system has been studied. Yarn samples of various linear densities have been produced on ring spinning machines using air-jet nozzles as retrofit by varying the nozzle parameter and the ya...

Artificial Neural Networks are applied to the literature data pertaining to adsorption batch studies to develop and validate a model that can predict the Pollutant Removal Efficiency (PRE). Back-Propagation Network (BPN) is used with one hidden layer. The BPN model is systematically trained with 440 data points and is validated with 73 data points from the database. Three different combinations...

Regarding psychological responses to exercise, this study aimed to analyze the mediating effects of motivational regulations and intensity in the association between basic psychological needs satisfaction and emotional responses. This was a cross-sectional study of 495 health club members (M = 40.50 years; SD = 13.54); of these, 186 were women (37.6%) and 309 men (62.4%), with an average attend...

This paper provides a kind of Bayesian Petri net model and presents a fault diagnosis method for power grid based on this model. Firstly, the BPN models for each component are established in power cut area separately, according to the fault spread directions. Secondly, the failed component is determined by the application of Petri net reasoning and Bayesian probability calculation. At last, the...

This paper deals with the problem of distributed causal model-based diagnosis on interacting Behavioral Petri Nets (BPNs). The system to be diagnosed comprises different interacting subsystems (each modeled as a BPN) and the diagnostic system is defined as a multi-agent system where each agent is designed to diagnose a particular subsystem on the basis of its local model, the local received obs...

Subtilisin BPN' hydrolysed N-acetyl-l-3-(2-naphthyl)-alanine methyl ester, N-acetyl-l-leucine methyl ester and N-acetyl-l-valine methyl ester, faster than alpha-chymotrypsin. Of eight ;locked' substrates tested, only methyl 5,6-benzindan-2-carboxylate was hydrolysed faster by subtilisin, whereas the other esters were better substrates for chymotrypsin. Compared with the values for chymotrypsin,...