• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.299-306
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• 2006

Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The 'Hamilton-Jacobi (H-J)' equation and computationally robust numerical technique of 'up-wind scheme' lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H -J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes is not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.182-185
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• 2003

This paper presents a new design algorithm for the combination with the fuzzy classifier and the Bayesian classifier. Only few attempts have so far been made at providing an effective design algorithm combining the advantages and removing the disadvantages of two classifiers. Specifically, the suggested algorithms are composed of three steps: the combining, the fuzzy-set-based pruning, and the fuzzy set tuning. In the combining, the multi-inputs and multi-outputs (MIMO) fuzzy model is used to combine two classifiers. In the fuzzy-set-based pruning, to effectively decrease the complexity of the fuzzy-Bayesian classifier and the risk of the overfitting, the analysis method of the fuzzy set and the recursive pruning method are proposesd. In the fuzzy set tuning for the misclassified feature vectors, the premise parameters are adjusted by using the gradient decent algorithm. Finally, to show the feasibility and the validity of the proposed algorithm, a computer simulation is provided.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.3
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• pp.284-289
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• 2005

A structural design system is developed for the optimum design of double hull tankers based on the multi-objective function method. As a multi-objective function method, Pareto optimal based random search method is adopted to find the minimum structural weight and fabrication cost. The fabrication cost model is developed by considering the welding technique, welding poses and assembly stages to manage the fabrication man-hour and process. In this study, a new structural design is investigated due to the rapidly increased material cost. Several optimum structural designs on the basis of high material cost are carried out based on the Pareto optimal set obtained by the random search method. The design results are compared with existing ship, which is designed under low material cost.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.98-107
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• 2015

Hierarchical constraints and constraint satisfaction were analyzed in order to solve the problem of conflict detection in collaborative design. The constraints were divided into two sets: one set consisted of known constraints and the other of unknown constraints. The constraints of the two sets were detected with corresponding methods. The set of the known constraints was detected using an interval propagation algorithm, a back propagation (BP) neural network was proposed to detect the set with the unknown constraints. An immune algorithm (IA) was utilized to optimize the weights and the thresholds of the BP neural network, and the steps were designed for the optimization process. The results of the simulation indicated that the BP neural network that was optimized by IA has a better performance in terms of convergent speed and global searching ability than a genetic algorithm. The constraints were described using the eXtensible Markup Language (XML) for computers to be able to automatically recognize and establish the constraint network. The implementation of the conflict detection system was designed based on constraint satisfaction. A wind planetary gear train is taken as an example of collaborative design with a conflict detection system.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.669-681
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• 2006

In this work, a new method of design adaptive controllers for SISO systems based on multiple models and switching is presented. The controller selects the model from a given set, according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a predictive control law that ensures the robust stability of the closed-loop system and achieves the best performance for the current operating point. At each sample the proposed control scheme identifies a set of linear models that best characterizes the dynamics of the current operating region. Then, it carries out an automatic reconfiguration of the controller to achieve the best possible performance whilst providing a guarantee of robust closed-loop stability. The results are illustrated by simulations a nonlinear continuous and stirred tank reactor.

• Bulletin of the Korean Chemical Society
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• v.33 no.2
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• pp.613-619
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• 2012

We applied several machine learning methods for developing QSAR models for prediction of acute toxicity to fathead minnow. The multiple linear regression (MLR) and artificial neural network (ANN) method were applied to predict 96 h $LC_{50}$ (median lethal concentration) of 555 chemical compounds. Molecular descriptors based on 2D chemical structure were calculated by PreADMET program. The recursive partitioning (RP) model was used for grouping of mode of actions as reactive or narcosis, followed by MLR method of chemicals within the same mode of action. The MLR, ANN, and two RP-MLR models possessed correlation coefficients ($R^2$) as 0.553, 0.618, 0.632, and 0.605 on test set, respectively. The consensus model of ANN and two RP-MLR models was used as the best model on training set and showed good predictivity ($R^2$=0.663) on the test set.

• Earthquakes and Structures
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• v.9 no.5
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• pp.1045-1067
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• 2015

A performance-based design (PBD) procedure, initially proposed for the seismic design of buildings, is tailored herein to the structural configurations commonly adopted in bridges. It aims at the efficient design of bridges for multiple performance levels (PLs), achieving control over a broad range of design parameters (i.e., strains, deformations, ductility factors) most of which are directly estimated at the design stage using advanced analysis tools (a special type of inelastic dynamic analysis). To evaluate the efficiency of the proposed design methodology, it is applied to an actual bridge that was previously designed using a different PBD method, namely displacement-based design accounting for higher mode effects, thus enabling comparison of the alternative PBD approaches. Assessment of the proposed method using nonlinear dynamic analysis for a set of spectrum-compatible motions, indicate that it results in satisfactory performance of the bridge. Comparison with the displacement-based method reveals significant cost reduction, albeit at the expense of increased computational effort.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.847-857
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• 2012

This article is concerned with choice-based conjoint analysis versus rating-based and ranking-based conjoint analysis. Choice-based conjoint analysis has a definite advantage in that the respondent's task of choosing the most preferred profile from several competing profiles adequately mimics consumer marketplace behavior. It is crucial to design the choice sets appropriate for the choice-based conjoint. Thus, this article suggests a new method to design the choice sets that are well-balanced. It augments the balanced incomplete block design and then obtains the dual design of the result to accommodate various numbers of profiles. In consequence, the choice sets designed by the new method have the desirable characteristics that each profile is presented to the same number of respondents, and pairs of any two distinct profiles occur together in the same number of choice sets. The balancing of the design increases the efficiency of the conjoint analysis. In addition, the pair-comparison scheme can improve the quality of data through the identification of contradictory responses.

• Journal of the Korean Society of Costume
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• v.60 no.9
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• pp.16-25
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• 2010

This study reinterpreted the formative design elements of traditional grate patterns to create new lattice patterns and come up with a design concept for fashion-cultural products that highlight the uniqueness of traditional Korean culture and its characteristic features. Methodologically, the computer design software programs Adobe Illustrator CS2 and Adobe Photoshop were used to make grate patterns motifs. and they were applied to scarves and again to blouses using a three-dimensional simulation technique. In this study, three basic motifs for a new formative image were set using graphical functions such as omitting, simplifying, overlapping, repeating and reducing shapes based on the images of traditional 亞-shaped, arched and floral lattices, and each motif was expanded to have two variations with different colors applied to them. The direction of basic motif design was set to fit for each of fashion-cultural items such as scarves and blouses. Basic colors for motifs were arranged to create a colorful and modern but staid image in pink, blue, purple, green, yellow and brown tones. Based on a developed motif, changes were made in blouse design with lattice patterns through a variety of effects such as repetition, rotation, cross-arrangement, and oblique arrangement, and three-dimensional simulation was used to bring the design to life. Scarf design employed and applied the existing motifs in an appropriate manner for design purposes and reconstructed them through such effects as repetition, rotation, compositional variation and gradation to express a gorgeous and refined image.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.1
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• pp.81-89
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• 2015

This study takes shear wall of reinforced concrete structure as study object, and the purpose of this study is to suggest structure BIM based on automatic reinforcing bar placement system applying set-based design through the most optimum reinforcing bar placement group that was selected by applying AHP (analytical hierarchy process) method from design step. For this, the most optimum reinforcing bar placement group was selected by pairwise comparison analysis on complex standard of multiple alternatives. And shear wall automatic reinforcing bar placement system has been developed, which can automatically generate members and arrange reinforcing bar by structure design algorithm and using open API (application programming interface) provided by a BIM software vendor. As a result, the most optimum reinforcing bar placement group of the highest weight, ALT1, was selected and was generated using Tekla Structure program.