• Journal of Microbiology and Biotechnology
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• v.17 no.12
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• pp.1930-1936
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• 2007

A sequential optimization strategy based on statistical experimental designs was employed to enhance the production of cyclosporin A (CyA) by Tolypocladium inflatum DSMZ 915 in a submerged culture. A 2-level Plackett-Burman design was used to screen the bioprocess parameters significantly influencing CyA production. Among the 11 variables tested, sucrose, ammonium sulfate, and soluble starch were selected, owing to their significant positive effect on CyA production. A response surface methodology (RSM) involving a 3-level Box-Behnken design was adopted to acquire the best process conditions. Thus, a polynomial model was created to correlate the relationship between the three variables and the CyA yield, and the optimal combination of the major media constituents for cyclosporin A production, evaluated using the nonlinear optimization algorithm of EXCEL-Solver, was as follows (g/l): sucrose, 20; starch, 20; and ammonium sulfate, 10. The predicted optimum CyA yield was 113 mg/l, which was 2-fold the amount obtained with the basal medium. Experimental verification of the predicted model resulted in a CyA yield of 110 mg/l, representing 97% of the theoretically calculated yield.

• Advances in concrete construction
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• v.3 no.4
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• pp.253-268
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• 2015

This paper investigates the influence of various mix design parameters on the characteristics of concrete containing recycled coarse aggregates and Nano-Silica using Taguchi method. The present study adopts Water-cement ratio, Recycled Coarse Aggregate (%), Maximum cement content and Nano-Silica (%) as factors with each one having three different levels. Using the above mentioned control parameters with levels an Orthogonal Array (OA) matrix experiments of L9 (34) has selected and nine number of concrete mixes has been prepared. Compressive Strength, Split Tensile Strength, Flexural Tensile Strength, Modulus of Elasticity and Non-Destructive parameters are selected as responses. Experimental results are analyzed and the optimum level for each response is predicted. Analysis of 28 days CS depicts that NS (%) is the most significant factor among all factors. Analysis of the tensile strength results indicates that the effect of control factor W/C ratio is ranked one and then NS (%) is ranked two which suggests that W/C ratio and NS (%) have more influence as compared to other two factors. However, the factor that affects the modulus of elasticity most is found to be RCA (%). Finally, validation experiments have been carried out with the optimal mixture of concrete with Nano-Silica for the desired engineering properties of recycled aggregate concrete. Moreover, the comparative study of the predicted and experimental results concludes that errors between both experimental and predicted values are within the permissible limits. This present study highlights the application of Taguchi method as an efficient tool in determining the effects of constituent materials in mix proportioning of concrete.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.649-658
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• 2019

The purpose of this study was to investigate the current status of postpartum depression intervention program performed in Korea and to evaluate its effectiveness. Of the Korean academic journals reported until November 2018, 13 experimental studies were selected and used for final analysis. The average age of the subjects was 26.9 to 34.4 years, and subjects were puerperal women or couples. The sample size was 6~39 (mean: 20.4) in the experimental group, 5~40 in the control group (mean: 20.0), and the intervention program consisted of 0.5~12 weeks/2~14 sessions/10~120 minutes per session. The design of all the studies was a non-equivalent control group pre-post test design. The main dependent variables, postpartum depression, fatigue, and maternal role self-confidence, were all found to have a statistically significant median level of effect size in the meta-analysis. This study confirms the composition and effects of various experimental studies used to mediate postpartum depression in Korea. This could be used as specific evidence-based data to form an optimal postpartum intervention program.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.2
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• pp.55-62
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• 2012

In this paper we propose a control system to preserve the interior angle between back section and upper leg section to be larger than 90 degrees using a single limit switch. To design the control system we analyze the kinematics of actuation mechanisms for the back section and the upper leg section, and find out an optimal solution for the controller design. Using a prototype control system we perform experiments to test the controller performance, and show that the interior angle between the back section and the upper leg section is always preserved larger than 90 degree. From the experimental results, we show the proposed control system is feasible to keep the body posture stability.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.408-421
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• 2015

Because the wheel of V-belt continuously variable transmission (CVT) system driven by permanent magnet synchronous motor (PMSM) has much unknown nonlinear and time-varying characteristics, the better control performance design for the linear control design is a time consuming job. In order to overcome difficulties for design of the linear controllers, a hybrid recurrent Chebyshev neural network (NN) control system is proposed to control for a PMSM servo-driven V-belt CVT system under the occurrence of the lumped nonlinear load disturbances. The hybrid recurrent Chebyshev NN control system consists of an inspector control, a recurrent Chebyshev NN control with adaptive law and a recouped control. Moreover, the online parameters tuning methodology of adaptive law in the recurrent Chebyshev NN can be derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, the optimal learning rate of the parameters based on discrete-type Lyapunov function is derived to achieve fast convergence. The recurrent Chebyshev NN with fast convergence has the online learning ability to respond to the system's nonlinear and time-varying behaviors. Finally, to show the effectiveness of the proposed control scheme, comparative studies are demonstrated by experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2606-2611
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• 2003

Comprehensive study on the control system design for a RTP process has been conducted. The purpose of the control system is to maintain maximum temperature uniformity across the silicon wafer achieving precise tracking for various reference trajectories. The study has been carried out in two stages: thermal balance modeling on the basis of a semi-empirical radiation model, and optimal iterative learning controller design on the basis of a linear state space model. First, we found through steady state radiation modeling that the fourth power of wafer temperatures, lamp powers, and the fourth power of chamber wall temperature are related by an emissivity-independent linear equation. Next, for control of the MIMO system, a state space modeland LQG-based two-stage batch control technique was derived and employed to reduce the heavy computational demand in the original two-stage batch control technique. By accommodating the first result, a linear state space model for the controller design was identified between the lamp powers and the fourth power of wafer temperatures as inputs and outputs, respectively. The control system was applied to an experimental RTP equipment. As a consequence, great uniformity improvement could be attained over the entire time horizon compared to the original multi-loop PID control. In addition, controller implementation was standardized and facilitated by completely eliminating the tedious and lengthy control tuning trial.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.75-81
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• 2017

This paper presents a design and parallel control strategy of 1.8 kW low-voltage DC-DC converter (LDC) for mild hybrid electric vehicles to improve their power density, system efficiency, and operation stability. Topology and control scheme are important on the LDC for mild hybrid electric vehicles to achieve high system efficiency and power density because of their very low voltage and large current in input and output terminals. Therefore, the optimal topological structure and control algorithm are examined, and a detailed design methodology for the power and control stages is presented. A working sample of 1.8 kW LDC is designed and implemented by applying the adopted topology and control strategy. Experimental results indicate 92.45% of the maximum efficiency and 560 W/l of power density.

• Journal of ILASS-Korea
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• v.1 no.3
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• pp.37-50
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• 1996

Computational fluid dynamics was used to optimize an A/C duct. Three dimensional flow analysis in an automotive A/C duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. Additionally, we studied the effect of location variation of 2nd branch on exit flow ratio and could find optimal location of 2nd branch. The design of an A/C duct was modeled and calculated to enhance the airflow distribution in each outlet using the STAR-CD computational fluid dynamics software. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the future, adoption of CFD to design an A/C duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.144-149
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• 2017

There have been lots of interest on service and entertainment robots. To ensure that robots work in harmony with humans, their stability and compactness are some of the key issues. Obviously, robots with fewer wheels occupy a smaller floor area compared to those with more wheels. In addition, robots with fewer wheels, whose posture stabilities are maintained by feedback control, are stable even under larger accelerations and/or higher locations of the center of mass. To facilitate controller design, it is assumed that both pitch and roll dynamics are decoupled. The dynamic equations of motion for the proposed robot are derived from the Euler-Lagrange equation. To obtain the optimal balancing control law, linear quadratic regulator control methods are applied to the linearized dynamic equations. Simulation and experimental results verify the effectiveness and performance of the proposed balancing control algorithm for a single-wheeled mobile robot.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.57-62
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• 2005

Microarray gene expression profiling technology is one of the most important research topics in clinical diagnosis of disease. Given thousands of genes, only a small number of them show strong correlation with a certain phenotype. To identify such an optimal subset from thousands of genes is intractable, which plays a crucial role when classify multiple-class genes express models from tumor samples. This paper proposes an efficient classifier design method to simultaneously select the most relevant genes using an intelligent genetic algorithm (IGA) and design an accurate classifier using Support Vector Machine (SVM). IGA with an intelligent crossover operation based on orthogonal experimental design can efficiently solve large-scale parameter optimization problems. Therefore, the parameters of SVM as well as the binary parameters for gene selection are all encoded in a chromosome to achieve simultaneous optimization of gene selection and the associated SVM for accurate tumor classification. The effectiveness of the proposed method IGA/SVM is evaluated using four benchmark datasets. It is shown by computer simulation that IGA/SVM performs better than the existing method in terms of classification accuracy.