• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.504-509
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• 2003

In this paper, a multi-step optimization using a G.A.(Genetic Algorithm) with variable penalty function is introduced to the structural design optimization of a high speed machining center. The design problem, in this case, is to find out the best cross-section shapes and dimensions of structural members which minimize the static compliance, the dynamic compliance, and the weight of the machine structure simultaneously. The first step is the cross-section shape optimization, in which only the section members are selected to survive whose cross-section area have above a critical value. The second step is a static design optimization, in which the static compliance and the weight of the machine structure are minimized under some dimensional constraints and deflection limits. The third step is a dynamic design optimization, where the dynamic compliance and the structure weight are minimized under the same constraints as those of the second step. The proposed design optimization method was successful applied to the machining center structural design optimization. As a result, static and dynamic compliances were reduced to 16% and 53% respectively from the initial design, while the weight of the structure are also reduced slightly.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.213-224
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• 2014

In this paper, we study the problem of transforming to normality. We propose to estimate the transformation parameter by minimizing a weighted squared distance between the empirical characteristic function of transformed data and the characteristic function of the normal distribution. Our approach also allows for other symmetric target characteristic functions. Asymptotics are established for a random sample selected from an unknown distribution. The proofs show that the weight function $t^{-2}$ needs to be modified to have thinner tails. We also propose the method to compute the influence function for M-equation taking the form of U-statistics. The influence function calculations and a small Monte Carlo simulation show that our estimates are less sensitive to a few outliers than the maximum likelihood estimates.

• Journal of Fisheries and Marine Sciences Education
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• v.21 no.2
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• pp.325-334
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• 2009

The aims of this study is to suggest the strategic development plan of Ulsan Port using SWOT/AHP method. In order to do this, 16 detailed factors for SWOT Matrix were identified both from previous studies and from brainstorming professionals of the port and these made into a 3 level hierarchy structure. AHP method identified the relative weight of SWOT level as threat(0.311), opportunity(0.259), strength(0.218) and weakness(0.212), also the composite relative weight of detailed factors as recession of global economy(0.125), strengthening of economic function in port(0.085), insufficiency of port facilities(0.080) and a government regulation of port management(0.075). As a result, the study suggests S/T strategy, W/T strategy, S/O strategy, W/O strategy as a strategic development plan of the Ulsan Port.

• Proceedings of the SCSK Conference
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• 2003.09a
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• pp.1-12
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• 2003

Instead of sensory evaluation, we designed an evaluation method of the setting function of hairstyling products, based on an original theory focusing on changes in bending stress observed when a load with continuous bending is applied to human hair. Specifically, we developed a device to measure bending stress to quickly and objectively evaluate the condition of human hair, particularly its dynamic properties such as the setting function, following the application of hairstyling products. This device generates a load with continuous bending while applying a pendulum motion to a hair tress, one end of which is anchored. The setting function and holding power of resins of various molecular weight and ionic properties were evaluated using this device. The results demonstrated a close correlation with those obtained by experts' sensory evaluation. The evaluation results of bending stress and holding rate confirmed that the combined use of two different resins could improve the function of setting preparations. Evaluation using this device was able to substitute for sensory evaluation, and offers quick objective evaluation and detection of changes in the holding power of hairstyling products over time. We conclude that evaluation using this device is a promising new method.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.59-65
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• 2003

In order to achieve the desired lightweight and robust design of a structure, it is preferable to design a structure and its control system, simultaneously, which is termed the combined optimal design. A constant-cross-sectional area cantilever beam was chosen as the optimum design method, An initial load and a time-varying disturbance were applied at the free end of the beam. Sliding mode control was selected, due to its insensitivity to the disturbance, compared with other modes. It is known that the sliding mode control is robust to the disturbance and is uncertain, only if a matching condition is met, after giving a switching hyper plane. In this study, the optimum method was used for the design of the switching hyper plane, and the objective function of the optimum switching hyper plane was assumed to be the objective of the control system. The total weight of the structure was treated as a constraint, and the cross sectional areas of the beam were considered as design variables, the result being a nonlinear programming problem. To solve it, the sequential linear programming method was applied. As a result of the optimum design, the effect of attenuating vibrations has been substantially improved. Moreover, the lightweight design of the structure became possible as a result of the relationship of the weight of the structure to the control objective function.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.45-51
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• 2002

To achieve the lightweight and robust design of a structure, it is requested to design a structure and its control system simultaneously, which is called as the combined optimal design. A constant-cross-sectional area cantilever beam was chosen as an example for the applying the optimum design method. An initial load and a time varying disturbance were applied at the free end of the beam. Sliding mode control was selected due to its insensitiveness to the disturbance compared with other modes. It is known that the sliding mode control is robust to the disturbance and the uncertainty only if a matching condition is met, after giving a switching hyper plane. In this study, the optimum method was used for the design of the switching hyper plane and the objective function of the optimum switching hyper plane was assumed to be the objective one of the control system. The total weight of the structure was treated as a constraint and the cross sectional areas of the beam were considered as design variables, which means a nonlinear programming problem. The sequential linear programming method was applied to solve it. As a result of the optimum design, the effect of attenuating vibrations has been improved obviously. Moreover, lightweight design of the structure became possible from the relationship of the weight of the structure and the control objective function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.141-156
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• 2011

In this paper we develop a link cost function for data delivery in sensor network. Usually most conventional methods determine the optimal coefficients in the cost function without considering the surrounding environment of the node such as the wireless propagation environment or the topological environment. Due to this reason, there are limitations to improve the quality of data delivery such as data delivery ratio and delay of data delivery. To solve this problem, we derive a new cost function using the concept of Partially Connected Neural Network (PCNN) which is modeled according to the input types whether inputs are correlated or uncorrelated. The correlated inputs are connected to the hidden layer of the PCNN in a coupled fashion but the uncoupled inputs are in an uncoupled fashion. We also propose the training technique for finding an optimal weight vector in the link cost function. The link cost function is trained to the direction that the packet transmission success ratio of each node maximizes. In the experimental section, we show that our method outperforms other conventional methods in terms of the quality of data delivery and the energy efficiency.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.405-413
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• 2015

This paper presents the motion accuracy simulation considering loads such as workpiece weight, cutting force, cogging force of a linear motor, and force caused by misalignment and runout error of a ballscrew in linear motion units. The transfer function method is basically utilized to estimate 5-DOF motion errors, together with the equilibrium equations of force and moment on the table. The transfer function method is modified in order to consider clearance changed according to the loads in the double sided hydrostatic/aerostatic bearings. Then, the analytic model for predicting the 5-DOF motion errors is proposed with the modified transfer function method. Motion errors were simulated under different loading conditions in the linear motion units using hydrostatic, aerostatic, and linear motion bearings, respectively. And the proposed analytic model was verified by comparing the estimated and measured motion errors.