• Smart Media Journal
• /
• v.1 no.1
• /
• pp.36-41
• /
• 2012

Feature selection is the important technique of selecting a subset of relevant features for building robust pattern recognition systems. Various methods have been studied for feature selection from sequential search algorithms to stochastic algorithms. In this work, we adopted a Quantum-inspired Genetic Algorithm (QGA) which is based on the concept and principles of quantum computing such as Q-bits and superposition of state for feature selection. The performance of QGA is compared to that of the Conventional Genetic Algorithm (CGA) with respect to the classification rates and the number of selected features. The experimental result using UCI data sets shows that QGA is superior to CGA.

• Journal of Environmental Science International
• /
• v.18 no.3
• /
• pp.299-308
• /
• 2009

We manufactured PVA-derived hydrogels using a foam generation technique that has been widely used to prepare colloidal gas aphrons(CGA). These gels were differentiated to the conventional gels such as for medical or pharmaceutical applications, which have tiny pores and some crystalline structure. Rather these should be used in de-pollution devices or adhesion of cells or biomolecules. The crosslinkers used in this work were amino acid, organic acid, sugars and lipids(vitamins). The structures of the gels were observed in a scanned electron microscope. Amino acids gels showed remarkably higher swelling ratios probably because their typical functional groups help constructing a highly crosslinked network along with hydrogen bonds. Boric acid and starch would catalyze dehydration while structuring to result in much lower water content and accordingly high gel content, leading to less elastic, hard gels. Bulky materials such as ascorbic acid or starch produced, in general, large pores in the matrices and also nicotinamide, having large hydrophobic patches was likely to enlarge pore size of its gels as well since the hydrophobicity would expel water molecules, thus leading to reduced swelling. Hydrophilicity(or hydrophobicity), functional groups which are involved in the reaction or physical linkage, and bulkiness of crosslinkers were found to be more critical to gel's cross linking structure and its density than molecular weights that seemed to be closely related to pore sizes. Microscopic observation revealed that pores were more or less homogeneous and their average sizes were $20{\mu}m$ for methionine, $10-15{\mu}m$ for citric acid, $50-70{\mu}m$ for L-ascorbic acid, $30-40{\mu}m$ for nicotinamide, and $70-80{\mu}m$ for starch. Also a sensory test showed that amino acid and glucose gels were more elastic meanwhile acid and nicotinamide gels turned out to be brittle or non-elastic at their high concentrations. The elasticity of a gel was reasonably correlated with its water content or swelling ratio. In addition, the PVA gel including 20% ascorbic acid showed fair ability of cell adherence as 0.257mg/g-hydrogel and completely degraded phenanthrene(10 mM) in 240 h.

• Structural Engineering and Mechanics
• /
• v.16 no.5
• /
• pp.557-580
• /
• 2003

Laminated composite structures find wide range of applications in many branches of technology. They are much suited for weight sensitive structures (like aircraft) where thinner and lighter members made of advanced fiber reinforced composite materials are used. The orientations of fiber direction in layers and number of layers and the thickness of the layers as well as material of composites play a major role in determining the strength and stiffness. Thus the basic design problem is to determine the optimum stacking sequence in terms of laminate thickness, material and fiber orientation. In this paper, a new optimization technique called Cellular Automata (CA) has been combined with Genetic Algorithm (GA) to develop a different search and optimization algorithm, known as Cellular Genetic Algorithm (CGA), which considers the laminate thickness, angle of fiber orientation and the fiber material as discrete variables. This CGA has been successfully applied to obtain the optimal fiber orientation, thickness and material lay-up for multi-layered composite hybrid beams plates and shells subjected to static buckling and dynamic constraints.