• Journal of Microbiology and Biotechnology
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• v.18 no.12
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• pp.1927-1931
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• 2008

In this study, the enzymatic process for biodiesel production was optimized using a mixture of immobilized Rhizopus oryzae and Candida rugosa lipases. The optimal temperature and agitation speed for biodiesel production were $45^{\circ}C$ and 300 rpm, respectively. The optimal ratio of R. oryzae and C. rugosa lipases in the mixture was 3:1 (w:w). When 3 mmol of methanol was the initial reaction medium and 3 mmol of methanol was added every 1.5 h during biodiesel production, biodiesel conversion was over 98% at 4 h. In addition, when the immobilized lipase mixture was reused, biodiesel conversion exceeded 80% after 5 reuses.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.5
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• pp.369-373
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• 2004

In order to elucidate the possibility of artificial production of p. ferulae by solid-state culture, the optimization of culture conditions was carried out. When $NH_4H_2PO_4$ and $CaCO_3$ were used in the cultures using test tube with 30 g of Populus sawdust at $25^{\circ}C{\pm}1$ in the dark, the favored mycelial growth was observed with $1\%$ of $NH_4H_2PO_4$ and the production of polysaccharide was 7.85 mg/100 mg of mycelium with $1\%$ of $CaCO_3$. The mixtures of $80\%$ of Populus Sawdust and $20\%$ of rice bran at $60\%$ of water content were determined to be optimal for the production of fruiting bodies in the sawdust culture. When three treatments containing various ratios of garlic powder were conducted, yields of fruiting bodies were drasti[ally higher than those of Synthetic mixture without garlic powder The highest yield (143 g/bag) was obtained with $7\%$ garlic powder. The yield of synthetic mixture containing $7\%$ of garlic powder was $83\%$ higher than that of Sawdust culture. The reason why garlic powder did support growth was not clear but it is possible that garlic powder might contain effective components for the formation of fruiting body. The optimal synthetic mixture composition consisted of cotton seed $77\%$, lime $6.4\%,\;K_2HPO_4\;0.2\%,\;KH_2PO_4\;0.2\%,\;CaHPO_4\;0.2\%$, corn flour $4\%$, wheat flour $5\%$, and garlic pow-der $7\%$.

• Korean journal of food and cookery science
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• v.22 no.6 s.96
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• pp.815-824
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• 2006

This study was performed to determine the optimum ratio of each ingredient in the steamed foam cake with barley (Hordeum vulgare L.) sproutling powder. The experiment was designed according to the D-optimal design of mixture design, which showed 14 experimental points including 4 replicates for three independent variables (sugar 112${\sim}$139%, barley sproutling powder 1${\sim}$8%, and oil 5${\sim}$25%). The compositional and functional properties of test were measured, and these values were applied to the mathematical models. A canonical form and trace plot showed the influence of each ingredient on the mixture final product. The results of F-test, volume, color values (L, a, b), textural properties (hardness, gumminess, chewiness) and sensory characteristics (softness) decided a linear model, while the sensory characteristics (color, smell, taste, overall acceptance) decided a quadratic model. The volume of steamed foam cake was increased by sugar addition, and a negative effect was exerted by barley sproutling powder and oil. L and a of color values increased but the b value decreased with increasing sugar and oil content, whereas barley sproutling powder tended to decrease all color values. The addition of barley sproutling powder also had a positive effect on the textural properties (hardness, gumminess, chewiness). Sensory characteristics (color, smell, softness, taste, overall acceptance) could suffer counter results with the excessive addition of sugar, barley sproutling powder, and oil. The optimum formulations by numerical and graphical methods were similar: sugar, barley sproutling powder, and oil were 130.4%, 4.0%, and 10.7% by numerical method, compared to 130.4%, 4.0%, and 10.7% by graphical method, respectively.

• Journal of the Korean Home Economics Association
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• v.42 no.3
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• pp.145-158
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• 2004

Experimental conditions for evaluating chitosan antibacterial activities were established. The chitosan antibacterial activities were measured against the Staphylococcus aureus and evaluated for their application to antibacterial textile finishing. The strain of Staphylococcus aureus used in this experiments was KCTC 1916. The chitosan antibacterial activities were estimated from the bacterial densities or ％reduction of bacteria in chitosan solutions and bacterial culture mixtures after incubation under specific conditions. Six parameters as follows were evaluated to optimize the experimental conditions for measuring antibacterial activities. The different combinations of mixtures according to the different ratios of chitosan solutions to the bacterial cultures showed different antibacterial activities. However, the chitosan antibacterial activities could be evaluated by comparing the data obtained from the same combinations of mixtures. The solvent influence on the chitosan solution antibacterial activities could be eliminated using control solution containing the same concentration of acetic acid. The initial pH of the chitosan -bacterial mixtures also affected the chitosan antibacterial activity; at a higher pH, higher activity in terms of ％reduction of bacteria was observed. In case of the bacterial solution without either the acetic acid or chitosan, the initial pH of the solution did not significantly affect bacterial growth. The ％ reduction of bacteria increased when contact times of bacteria with chitosan in the chitosan -bacterial mixture were expended upto 24 hours. However, the chitosan antibacterial activities could be successfully evaluated at contact time 0 where the chitosan-bacterial mixture was plated immediately after mixing and incubated to measure the bacterial number to 24 hours. Evaluating ％reduction of bacteria in the test mixtures after incubation were not changed when the inoculated bacterial concentrations were 2.3${\times}$10$\^$0/ml to 2.3${\times}$10$\^$6/ml. The optimal range of incubation time of the petri-Dish after plating the chitosan-bacterial mixture was 24 to 72 hours depending on the antibacterial activities of the test solutions.

• Journal of the Korea Concrete Institute
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• v.20 no.5
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• pp.627-634
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• 2008

This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.

• Applied Biological Chemistry
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• v.40 no.3
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• pp.225-231
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• 1997

Optimization theory was applied to a native and two imported soybeans. Failure stress and stress relaxation curve was measured with rheometer, and color was measured by colorimeter. The effects of each soybean upon the tofu texture were expressed through a non-linear canonical regression model and trace plot. Compared to the other imported soybeans, native soybean produced a higher strength in tofu texture, and showed the positive increase in viscoelastic properties such as instantaneous stress, equilibrium stress and relaxation time, whereas it had no effect on whiteness from reference blend, represented that native soy-bean showed the individual strength upon the selected rheological texture properties. Higher soaking ability in native soybean was selected as a new response for the optimization mixture process, and it contributed positively to the rheological properties of tofu. New soaking process control system during processing and desirability for the mathematical model should be applied for a better mixture design in varieties of soybeans.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.5
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• pp.614-622
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• 2018

Based on army operating road profile, the endurance test of military vehicle aims to reproduce the similar loading conditions with mixture of proving ground tracks. It is so called as endurance test mode and its optimal generation is important to meet high reliability of endurance test. In this paper, proving ground optimization is proposed to achieve a close match to the target profile. Several performance measures such as torque-revolution counts or transmission ratio for the powertrain system can be considered as one of the objective functions. However, the one-side optimal endurance test mode may give the poor solution in the whole system point of view. To incorporate several goals simultaneously, this paper employs multi-objective optimization technique to generate endurance test mode. One of the most widely used method, weighted-sum method is applied here and the case study is discussed.

• Fire Science and Engineering
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• v.22 no.4
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• pp.65-69
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• 2008

An accurate knowledge of the flash point is important in developing appropriate preventive and control measures in industrial fire protection. The lower flash points for the n-propanol+formic acid system were measured by Pensky-Martens closed cup apparatus. This binary mixture exhibited MFPB (minimum flash point behavior), which leads to the minimum on the flash point vs composition curve. The Raoult's law and optimization method using Wilson equation were used to predict the lower flash points and were compared with experimental data. The calculated values based on the optimization method were found to be better than those based on the Raoult's law.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.151-160
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• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.

• Speech Sciences
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• v.5 no.1
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• pp.7-21
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• 1999

This paper proposes an improved training procedure in speech recognition based on the continuous density of the Hidden Markov Model (CDHMM). Of the three parameters (initial state distribution probability, state transition probability, output probability density function (p.d.f.) of state) governing the CDHMM model, we focus on the third parameter and propose an efficient algorithm that determines the p.d.f. of each state. It is known that the resulting CDHMM model converges to a local maximum point of parameter estimation via the iterative Expectation Maximization procedure. Specifically, we propose two independent algorithms that can be embedded in the segmental K -means training procedure by replacing relevant key steps; the adaptation of the number of mixture Gaussian p.d.f. and the initialization using the CDHMM parameters previously estimated. The proposed adaptation algorithm searches for the optimal number of mixture Gaussian humps to ensure that the p.d.f. is consistently re-estimated, enabling the model to converge toward the global maximum point. By applying an appropriate threshold value, which measures the amount of collective changes of weighted variances, the optimized number of mixture Gaussian branch is determined. The initialization algorithm essentially exploits the CDHMM parameters previously estimated and uses them as the basis for the current initial segmentation subroutine. It captures the trend of previous training history whereas the uniform segmentation decimates it. The recognition performance of the proposed adaptation procedures along with the suggested initialization is verified to be always better than that of existing training procedure using fixed number of mixture Gaussian p.d.f.