Biochemical monitoring of black raspberry (Rubus coreanus Miquel) fruits according to maturation stage by H NMR using multiple solvent systems

Nuclear magnetic resonance (NMR) techniques coupled with multivariate data analysis were used to conduct monitoring of biochemical changes of black raspberry fruits at different stages of maturation and under various extraction and NMR dissolution solvent conditions: extraction with 50% methanol and D₂O as an NMR dissolution solvent, extraction with 50% methanol and 50% methanol-d₄ as an NMR dissolution solvent, and extraction with 100% ethyl acetate and 100% methanol-d₄ as an NMR dissolution solvent. Partial least-squares discriminant analysis reliably distinguished black raspberry fruits according to the maturation stage, whereby the relative levels of various compounds such as amino acids, organic acids, sugars and phenolic compounds were compared using analysis of variance. Sucrose and most of the amino acids, and organic acids decreased, whereas fructose, glucose, and cyanidins increased in relative concentration according to maturation of black raspberry fruits. The total number and kinds of assigned compounds of the three solvent systems were also compared. This research demonstrates that the metabolic profile of black raspberry fruits changes during maturation, and provides objective criteria for determining the stage of black raspberry fruit maturation via a ¹H NMR-based metabolomics technique using multiple solvent systems.     

Simulation of hydropower turbine performance in duct for system utilizing tidal jet generator

The marine hydropower system proposed in this study creates a tidal jet generator from a seawater exchange type breakwater, with empty space similar to a basin to store ocean water. Due to the water level difference between the inner and outer sides of the breakwater, strong and uni-directional jets are generated. The energy from the jets is captured by turbines in the breakwater ducts.

In this study, the proposed system is first introduced. The design process for a new turbine and its preliminary performance in openwater conditions, estimated using Computational fluid dynamics (CFD), are presented. Experiments with the turbine in a Circulating water channel (CWC) at Pusan National University were also carried out. The results from the simulations and experiments with the same conditions were compared to verify the CFD accuracy. The turbine performance in a duct is estimated; the target power can be generated using the newly developed turbine.

     

Application of interactive genetic algorithm to fashion design

In general, computer-aided design support systems have got an approach of traditional artificial intelligence, which statistically analyzes data such as the behavior of designer, to extract formal design behavior. This approach, however, can neither deal with continuous change of fashion nor reflect personal taste well, as it just depends on large amount of collected data. To overcome this sort of problem interactive genetic algorithm (IGA) has been recently proposed, as a new trend of evolutionary computation. IGA uses human's response as fitness value when the fitness function cannot be explicitly defined. This enables IGA to be applied to artistic domains, and we propose a fashion design aid system using it. Unlike the previous works that attempt to model the dress design by several spline curves, the proposed system is based on a new encoding scheme that practically describes a dress with three parts: body and neck, sleeve, and skirt. By incorporating the domain-specific knowledge into the genotype, we could develop a more realistic design aid system for women’s dress. We have implemented the system with OpenGL and VRML to enhance the system interface. The experiments with several human subjects show that the IGA approach to dress design aid system is promising.