We have worked on the development of a character recognition system in the soft computing paradigm. In this paper we present a genetic algorithm used for feature selection with a Feature Quality Index (FQI) metric. We generate feature vectors by defining fuzzy sets on Hough transform of character pattern pixels. Each feature element is multiplied by a mask vector bit before reaching the input o...

Genetic Algorithm is used in this paper, which presents the designing an optimized tool for face detection application with idea of “Survival of the fittest”. If higher level of adaption can be achieved, existing systems can perform their functions longer & better. Popular method in feature extraction is principal component analysis (PCA), for feature subset selection used Genetic algorithm (GA...

A plausible architecture of an ancient genetic code is derived from an extended base triplet vector space over the Galois field of the extended base alphabet {D, G, A, U, C}, where the letter D represent one or more hypothetical bases with unspecific pairing. We hypothesized that the high degeneration of a primeval genetic code with five bases and the gradual origin and improvements of a primit...

BACKGROUND A capable expression vector is mainly characterized by its production efficiency, stability and induction response. These features can be influenced by a variation of modifications and versatile genetic modules. RESULTS We examined miscellaneous variations of a rhaPBAD expression vector. The introduction of a stem loop into the translation initiation region of the rhaPBAD promoter ...

Genetic manipulation that reduces the competence of a vector population to transmit pathogens would provide a useful tool to complement current control strategies, which are based primarily on the reduction/exclusion of vector populations and the prophylactic/therapeutic treatment of the vertebrate host population. Genetic drive is an important component of vector population replacement strateg...

This work presents a new method proposal applied to Multi-Labelers scenarios. This is a situation where labelling individuals in a set of data based on certain characteristics in the process of determining labels to individuals in a set of data based on certain characteristics. Our approach consists in processing a Support Vector Machine classifier to each labelers substantiated on his answers....

When the standard genetic algorithm is used to solve the fuzzy programming problem, poor convergence occurs. In order to overcome this defect, this paper presents a hybrid intelligent evolutionary algorithm based on nonlinear support vector machine (SVM) to solve the fuzzy programming problem. Firstly, based on the research of genetic algorithm, evolutionary strategy and genetic algorithm are c...

Background: Multiple sclerosis (MS) is a degenerative inflammatory disease which is most commonly diagnosed by magnetic resonance imaging (MRI). But, since the MRI device uses of a magnetic field, if there are metal objects in the patient's body, it can disrupt the health of the patient, the functioning of the MRI, and distortion in the images. Due to limitations of using MRI device, screening ...

the purpose of this research was to classify buffaloes from different areas of the two azari (west and east azarbayjan and ardabil provinces) and north (guilan province) ecotypes using support vector machine method. a total of 258 buffalo were sampled and genotyped using the axiom buffalo 90k genotyping array at the parco technologic padano lab in italy. two metric methods of cross validation a...

New approaches targeting metastatic neovasculature are needed. Payload capacity, cellular transduction efficiency, and first-pass cellular uptake following systemic vector administration, motivates persistent interest in tumor vascular endothelial cell (EC) adenoviral (Ad) vector targeting. While EC transductional and transcriptional targeting has been accomplished, vector administration approa...