• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.45-52
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• 2005

A general approximate optimization technique by sequential design domain(SDD) did not save response values for getting an approximate function in each step. It has a disadvantage at aspect of an expense. In this paper, previous response values are recycled for constructing an approximate function. For this reason, approximation function is more accurate. Accordingly, even if we did not determine move limit, a system is converged to the optimal design. Size and shape optimization using approximate optimization technique is carried out with SDD. Algorithm executing Pro/Engineer and ANSYS are automatically adopted in the approximate optimization program by SDD. Convergence criterion is defined such that optimal point must be located within SDD during the three steps. The PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information in the direction finding problem and uses the active set strategy.

• ETRI Journal
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• v.45 no.4
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• pp.704-712
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• 2023

This paper presents a flexible finite-difference technique for analyzing the nonuniform guiding structures. Because the voltage and current variations along the nonuniform structure differ for each segment, this work considers the adaptable discretization steps. This technique increases the accuracy of the final response. Moreover, by applying the singular value decomposition and discarding the nonprincipal singular values, an optimal lower rank approximation of the discretization matrix is obtained. The computational cost of the introduced method is significantly reduced using the optimal discretization matrix. Also, the proposed method can be extended to the nonuniform waveguides. The technique is verified by analyzing several practical transmission lines and waveguides with nonuniform profiles.

• ETRI Journal
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• v.5 no.2
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• pp.17-28
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• 1983

This paper deals with the problem of optimally controlling traffic flows in urban transportation traffic networks. For this, a nonlinear discrete-time model of urban traffic network is first suggested in order to handle the phenomenon of traffic flows such as oversaturatedness and/or undersaturatedness. Then an optimal control problem is formulated and a hierarchical optimization technique is applied, which is based upon a prediction-type two-level method of Hirvonen and Hakkala.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.289-290
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• 2003

This paper gives a method for the minimization of the fuel cost by optimal generation. Derivation of the sensitivity of system loss by optimization technique is introduced and the loss sensitivities are substituted into the optimality conditions to obtain the minimized fuel cost.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1410-1413
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• 2003

This paper presents the design technique for controlling the oscillation in the Disk Drive Read System via Derivative State Constrained (DSC)-Optimal $H_2$ Controller. The Optimal $H_2$, DSC-Optimal $H_2$ and Incorporating of Stability Degree Specification DSC Optimal $H_2$ are discussed. The results among these schemes are compared to verify the merit of DSC that effectively suppresses the oscillation in oscillatory system. The suggestions of how to select the weights of optimal controls are given.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.7
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• pp.743-751
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• 2013

In this paper, an approach to deal with model uncertainty using norm-optimal iterative learning control (ILC) is mentioned. Model uncertainty generally degrades the convergence and performance of conventional learning algorithms. To deal with model uncertainty, a worst-case norm-optimal ILC is introduced. The problem is then reformulated as a convex minimization problem, which can be solved efficiently to generate the control signal. The paper also investigates the relationship between the proposed approach and conventional norm-optimal ILC; where it is found that the suggested design method is equivalent to conventional norm-optimal ILC with trial-varying parameters. Finally, simulation results of the presented technique are given.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.177-184
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• 2003

In this study we performed optimal design for the vehicle mechanical component which satisfies both a sufficient stiffness and a lightweight using topology optimization technique. The FEA for the initial model before optimal design is performed by ABAQUS/Standard. And, we suggest optimization model using the topology optimal design program Altair Optisturuct 3.6. The FEA of optimal design is performed under the same condition as the initial model. We performed the FEA fur the topology optimal design model and verified the validity of the present method.

• IE interfaces
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• v.24 no.3
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• pp.173-186
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• 2011

In this paper, we evaluate life annuity plans for Korean pre-retired single and married couple participating Korea National Pension (KNP) and find optimal life annuity strategy by using utility-based measurements called AEW (Annuity Equivalent Wealth). Specifically, we extend a previous study to obtain a detailed optimal combination of annuitizing age and wealth in terms of percentage of net wealth at the time of retirement. A nonlinear optimization model is formulated with the objective of maximizing utility on consumption and bequest, and the dynamic programming (DP) technique is used to solve this problem. We find that there exist consistent patterns in optimal combinations of annuitizing age and wealth. Also, for all cases the optimal combination is significantly better than several other combinations. The results indicate that using the optimal approach can be beneficial to practitioners in insurance industry and prospective purchasers of life annuity. We conclude the paper with some discussions and suggestions.

• PNF and Movement
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• v.14 no.1
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• pp.59-65
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• 2016

Purpose: The purpose of this study was to review articles in order to establish optimal contraction intensity and duration in the performance of relaxation techniques for maximal increase in range of motion. Methods: The Cochrane, EBSCO, Embase, Medline, ProQuest, PubMed, ScienceDirect, and Scopus databases were used to search articles from 1990 to January 2016. The search terms were "contract relax," "hold relax," "muscle energy technique (MET)," and "proprioceptive neuromuscular facilitation (PNF) stretching." Only experimental human studies (randomized controlled trials) that compared the effects of varying intensity and duration of isometric contraction were included. Non-English language and unpublished studies were excluded. Results: A total of 2,156 articles were initially identified, with only five eventually meeting the inclusion and exclusion criteria. Three studies compared the effects of varying intensity in isometric contraction and two studies compared the effects of varying duration in isometric contraction with regard to range of motion (ROM). Two articles suggested that submaximal voluntary isometric contraction was more effective than maximum voluntary isometric contraction (MVIC) in the improvement of ROM. One article showed that a longer contraction time led to greater increases in ROM. Conclusion: Submaximal voluntary isometric contraction was recommended during contract-relax exercises in healthy people. Lack of evidence makes it difficult to suggest the optimal duration of isometric contraction during relaxation techniques. For future research, high-quality evidence will be needed to establish the optimal contraction intensity for maximum improvement of ROM.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.232-241
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• 2000

This study suggests an integrated method based on concept hierarchies, information gain, and rough set theory for efficient discovery rules from a large amount of data, and implements an optimal rules discovery system. Our approach applies attribute-oriented concept ascension technique to extract generalized knowledge from a database, knowledge reduction technique to remove superfluous attributes and attribute values, and significance of attributes to induce optimal rules. The system first reduces the size of database by removing the duplicate tuples through the condition attributes which have no influences on the decision attributes, and finally induces simplified optimal rules by removing the superfluous attribute values by analyzing the dependency relationships among the attributes. And we induce some decision rules from actual data by using the system and test rules to new data, and evaluate that the rules are well suited to them.