• Electronics and Telecommunications Trends
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• v.4 no.1
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• pp.93-117
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• 1989

Computational Geometry is concerned with the design and analysis of computational algorithms which solve geometry problems. Geometry problems have a large number of applications areas such as pattern recognition, image processing, computer graphics, VLSI design and statistics since they involve inherently geometric problems for which efficient algorithms have to be developed. Several parallel algorithms, based on various parallel computation models, have been proposed for solving geometric problems. We review the current status of the parallel algorithms in computational geometry.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.492-497
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• 2004

Three methods for design sensitivity such as numerical differentiation, analytical method and semi-analytical method have been developed for the last three decades. Although analytical design sensitivity analysis is exact, it is hard to implement for practical design problems. Therefore, numerical method such as finite difference method is widely used to simply obtain the design sensitivity in most cases. The numerical differentiation is sufficiently accurate and reliable for most linear problems. However, it turns out that the numerical differentiation is inefficient and inaccurate because its computational cost depends on the number of design variables and large numerical errors can be included especially in nonlinear design sensitivity analysis. Thus semi-analytical method is more suitable for complicated design problems. Moreover semi-analytical method is easy to be performed in design procedure, which can be coupled with an analysis solver such as commercial finite element package. In this paper, implementation procedure for the semi-analytical design sensitivity analysis outside of the commercial finite element package is studied and computational technique is proposed, which evaluates the pseudo-load for design sensitivity analysis easily by using the design variation of corresponding internal nodal forces. Errors in semi-analytical design sensitivity analysis are examined and numerical examples are illustrated to confirm the reduction of numerical error considerably.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.215-221
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• 1997

A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.82-86
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• 1989

In this paper, digital autopilot design methods are investigated and a new method is suggested in order to improve existing problems. The method is based on .delta. transform (1) and overcome numerical problems occurring in the process of discretization. We illustrate design procedures using .delta. transform and suggest a hardware and software structure for digital autopilot implemented by microprocessor.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.746-752
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• 2001

Design sensitivity analysis for nonlinear structural problems has been emerged in the last decade as a glowing area of engineering research. As a result, theoretical formulations and computational algorithms have already developed for design sensitivity of nonlinear structural problems. There is not enough research for practical nonlinear problems using multi-element, due to difficulties of implementation into FEA. Therefore, nonlinear response analysis for stiffened shell which consists of Mindlin plate and Timoshenko beam, was considered. Specially, it presents the backward-Euler method which is adopted to describe an exact yield state in the stress computation procedure. Then, design sensitivity analysis of nonlinear structures, particularly elasto-perfectly-plastic structure, is developed using direct differentiation method. The accuracy of the developed sensitivity analysis was compared with the central finite difference method. Finally, on the basis of above results, design improvement for stiffened shell is suggested.

• Korean Management Science Review
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• v.24 no.2
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• pp.73-80
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• 2007

Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.704-710
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• 2018

For the optimal design of electromagnetic device involving uncertainties in design variables, this paper proposes a new reliability-based optimal design algorithm for multiple constraints problems. Through optimizing the nominal objective function and maximizing the minimum reliability, a set of global optimal reliable solutions representing different reliability levels are obtained by the multi-objective particle swarm optimization algorithm. Applying the sensitivity-assisted Monte Carlo simulation method, the numerical efficiency of optimization procedure is guaranteed. The proposed reliability-based algorithm supplying multi-reliable solutions is investigated through applications to analytic examples and the optimal design of two electromagnetic problems.

• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.105-112
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• 2015

Product Lifecycle Management (PLM) ranges from design concepts of products to disposal. In this paper, we focus on the production planning phase in PLM, which is related to process planning and production scheduling and so on. In this study, key decisions for the creation of production plans are defined as production-planning attributes. Production-planning attributes correlate complexly in production-planning problems. Traditionally, the production-planning problem splits sub-problems based on experiences, because of the complexity. In addition, the orders in which to solve each sub-problem are determined by priorities between sub-problems. However, such approaches make solution space over-restricted and make it difficult to find a better solution. We have proposed a representation of combinations of alternatives in production-planning attributes by using Zero-Suppressed Binary Decision Diagrams. The ZDD represents only feasible combinations of alternatives that satisfy constraints in the production planning. Moreover, we have developed a solution search method that solves production-planning problems with ZDDs. In this paper, we propose an approach for managing solution candidates by ZDDs' network for addressing larger production-planning problems. The network can be created by linkages of ZDDs that express constraints in individual sub-problems and between sub-problems. The benefit of this approach is that it represents solution space, satisfying whole constraints in the production planning. This case study shows that the validity of the proposed approach.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.21 no.2
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• pp.94-101
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• 2008

Objectives : To discuss the types of control groups in randomized controlled trials (RCTs) of herbal medicine, and to provide suggestions for improving the design of control group in future clinical trials. Methods : We reviewed the 8 articles about clinical trial design of Chinese herbal preparation which were published from 2005 through 2008. We selected those articles from CNKI(中國知識基礎施設工程(http://www.cnki.net)). Results : It is necessary to have control group in randomized controlled trials(RCTs) of Korean herbal preparation. But there are problems in the selection of appropriate control group drug. This paper lists several problems about the choice of control drug and puts forward some proposals and countermeasures. There are problems such as ethics and manufacturing matching placebo and positive control herbal drug. Conclusion : To improve the quality of control group design, we introduce standard drug plus placebo drug method and add-on research for placebo control group design, double dummy technique, using negative control drug or composite control drug for active control group design.

• Journal of Ship and Ocean Technology
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• v.5 no.2
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• pp.14-26
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• 2001

This paper presents a novel design approach that could generate structural design alternatives having different topologies and then, select the optimum structure from them with simulataneously determining its optimum design variables related to geometry and the member size subjected to the multiple objective design environments. For this purpose, a specialized genetic algorithm, called StrGA_DeAl + MOGA, which can handle the design alternatives and multi-criteria problems very effectively, is developed for the optimal structural design. To validate the developed method, method, plain truss design problems are considered as illustrative example. To begin with, some possible topological of the truss structure are suggested based on the stability criterion that should be satisfied under the given loading condition. Then, with the consideration of the given multi-criteria, several different topology forms are selected as design alternatives for the second step of the conceptual design process. Based on the chosen topolgy of truss structures, the sizing or shaping optimization process starts to determine the optimum design parameters. Ten-bar truss problems are given in the paper to confirm the above concept and methodology.