• Korean Journal of Community Nutrition
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• v.21 no.4
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• pp.332-343
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• 2016

Objectives: Study purpose was to investigate perception on diet, diet problems and related factors among young adult women using focus group interviews (FGI) based on the Social Cognitive Theory (SCT). Methods: Eight groups of FGI were conducted with 47 female undergraduate or graduate students. Guide for FGI included questions regarding perception on optimal diet, diet problems and cognitive, behavioral, and environmental factors of SCT. FGI were video, audio-taped, transcribed and analyzed by themes and sub-themes. Results: Subjects showed irregular eating habits (skipping breakfast, irregular meal time) and selection of unhealthy foods as the main diet problems. Regarding cognitive factors related to optimal diet, subjects mentioned positive outcome expectations (e.g., health promotion, skin health, improvement in eating habits, etc.) and negative outcome expectations (e.g., annoying, hungry, expensive, taste). Factors that promoted optimal diet were mainly received from information from mobile or internet and access to menu or recipes. Factors that prevented optimal diet included influence from friends, lack of time and cooking skills. Behavioral factors for optimal diet included behavioral capability regarding snacks, healthy eating and smart food selection. Subjects mentioned mass media (mobile, internet, TV) as the influential physical environment, and significant others (parents, friends, grandparents) as the influential social environment in optimal diet. For education topics, subjects wanted to learn about healthy meals, basic nutrition, disease and nutrition, and weight control. They wanted to learn those aspects by using mobile or internet, lectures (cooking classes), campaign and events. Conclusions: Study results might be used for planning education regarding optimal diet for young adult women. Education programs need to focus on increasing positive outcome expectations (e.g., health) and behavioral capability for healthy eating and food selection, reducing negative outcome expectations (e.g., cost, taste) and barriers, making supportive environments for optimal diet, and incorporating topics and methods found in this study.

• Fire Science and Engineering
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• v.29 no.5
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• pp.51-56
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• 2015

In this study, optimal design methods were applied to the agent discharge flow of clean agent fire extinguishing systems. The methods combined optimal design theory and engineering theory for engineering analysis in a design program or coast savings in value engineering. Optimal design parameters were determined to optimize the agent discharge flow based on the design theory of the clean agent fire extinguishing systems and the theory of optimal design. The design factors were verified in regard to suitability for the performance of fire extinguishing systems. The results provide a foundation for optimal design method methods in other fire extinguishing systems. Optimization of the agent discharge flow of the discharge nozzle was confirmed by the constraints on the inner diameter of the discharge nozzle and the pipe, agent arrival time, flow, and pressure variation of the agent. The deviation of discharge pressure and agent time of the agent discharge nozzle were found to correlate with the pressure variation.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.319-326
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• 2015

Recently in the fields o f stochastic optimal control ( SOC) and reinforcemnet l earning (RL), there have been a great deal of research efforts for the problem of finding data-based sub-optimal control policies. The conventional theory for finding optimal controllers via the value-function-based dynamic programming was established for solving the stochastic optimal control problems with solid theoretical background. However, they can be successfully applied only to extremely simple cases. Hence, the data-based modern approach, which tries to find sub-optimal solutions utilizing relevant data such as the state-transition and reward signals instead of rigorous mathematical analyses, is particularly attractive to practical applications. In this paper, we consider a couple of methods combining the modern SOC strategies and approximate inference together with machine-learning-based data treatment methods. Also, we apply the resultant methods to a variety of application domains including financial engineering, and observe their performance.

• 전기의세계
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• v.28 no.3
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• pp.37-50
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• 1979

The time optimal control of dynamic systems with time delay is studied with emphasis on the practical realization of controllers. An extensive survey on various methods of control is included and a result for a time optimal regulator with signle delay in control is presented and simulated on a digital computer.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.62.1-62
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• 2001

This paper suggests an inverse optimal PID control design method for the trajectory tracking case of mechanical systems. Also, simple coarse/fine performance tuning laws are suggested based on the analysis for performance limitation of inverse optimal PID controller. Experimental results for a robot manipulator show the validity of our analysis for the performance tuning methods.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.243-248
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• 1995

The problem of optimal design for a nonparametric regression with binary data is considered. The aim of the statistical analysis is the estimation of a quantal response surface in two dimensions. Bias, variance and IMSE of kernel estimates are derived. The optimal design density with respect to asymptotic IMSE is constructed.

• Bulletin of the Korean Mathematical Society
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• v.50 no.1
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• pp.321-341
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• 2013

In this paper, we discuss the a posteriori error estimates of the semidiscrete mixed finite element methods for quadratic optimal control problems governed by linear hyperbolic equations. The state and the co-state are discretized by the order $k$ Raviart-Thomas mixed finite element spaces and the control is approximated by piecewise polynomials of order $k(k{\geq}0)$. Using mixed elliptic reconstruction method, a posterior $L^{\infty}(L^2)$-error estimates for both the state and the control approximation are derived. Such estimates, which are apparently not available in the literature, are an important step towards developing reliable adaptive mixed finite element approximation schemes for the control problem.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.339-351
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• 1998

Designs for discriminating between two linear regression models are studied under $\Lambda$-type optimalities maximizing the measure for the lack of fit for the designs with fixed model inadequacy. The problem of selecting an appropriate $\Lambda$-type optimalities is shown to be closely related to the estimation method. $\Lambda$-type optimalities for the least squares and minimum bias estimation methods are considered. The minimum bias designs are suggested for the designs invariant with respect to the two estimation methods. First order minimum bias designs optimal under $\Lambda$-type optimalities are then derived. Finally for the case where the lack of fit test is significant, an approach to the construction of a second order design accommodating the optimal first order minimum bias design is illustrated.

• Korean Journal of Computational Design and Engineering
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• v.4 no.1
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• pp.60-68
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• 1999

In reverse engineering (RE) sustems, the quality of the data aquisition process is crucial to the accuracy of the reverse engineered three dimensional computer-aided design (CAD) model. However, these tasks are predominantly done manually, and little work has been done to improve the efficiency of scanning by determining the minimum number of scans and the optimal scanning directions. In this paper, new scanning and registration methods using tooling balls are developed to assist in determining the optimal parameter for these processes. When the object to scanned has no concavity, attaching path of the object and its bounding rectangle are used for optimal scanning and registration. Then minimum number of tooling balls and their positions are calculated automatically. In the case of concave parts, the scanning plan should include a complete scan of the concave area. With the surface normal vector and the scanning direction, the minimum degree of rotating the part can be calculated. But the maximum rotation should be restricted in order to prevent occlusion of the part. Finally tow sample part ar scanned based on the proposed methods and the results are discussed.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.303-304
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• 2008

For the state estimation problem, the weighted least squares (WLS) method and the fast decoupled method are widely used at present. However, these algorithms can converge to local optimal solutions. Recently, modern heuristic optimization methods such as Particle Swarm Optimization (PSO) have been introduced to overcome the disadvantage of the classical optimization problem. However, heuristic optimization methods based on populations require a lengthy computing time to find an optimal solution. In this paper, we used PSO to search for the optimal solution of state estimation in power systems. To overcome the shortcoming of heuristic optimization methods, we proposed parallel processing of the PSO algorithm based on the PC cluster system. the proposed approach was tested with the IEEE-118 bus systems. From the simulation results, we found that the parallel PSO based on the PC cluster system can be applicable for power system state estimation.