• Proceedings of the ESK Conference
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• 1994.04a
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• pp.136-144
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• 1994

In this study, the human gait trajectories during normal walking were synthesized using the inverse kinematics and optimization techniques. The synthesis based on a lower extremity model consisting of a torso and two legs. Each leg has three segments: thigh, shank, foot, and is assumed to move with six degrees-of-freedom. In order to synthesize trajectiories of this redundant system, the sum of angular displacements of articulating joints was selected as an objective function to be minimized. The proposed algorithm in this study is very useful for the analysis of human gait. For the gait analysis, the trajectories of four points in each leg should be measured. However, by using the algorithm, measuring the trajectories of two points is sufficient, and thus the experimental set-up can be simplified. The predicted joint trajectories showed a good agreement with those obtained from the experiment. The statistical analysis and graphic simula- tions are also presented.

• Geomechanics and Engineering
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• v.18 no.5
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• pp.527-534
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• 2019

Although ground investigation had carried out prior to the construction, many problems have arisen during the civil-engineering works because of the presence of the unexpected underground utility lines or anomalies. In this study, a new geophysical exploration method was developed to solve those problems by improving and supplementing the existing methods. This new method was based on the difference of electrical resistance values between anomalies and surrounding ground medium. A theoretical expression was suggested to define the characteristics of the anomalies such as location, size and direction, by applying the electric field analysis. An inverse analysis algorithm was also developed to solve the theoretical expression using the measured electrical resistance values which were generated by the voltage flowing the subsurface medium. To verify the developed method, field applications were conducted at the sites under construction or planned. From the results of the field tests, it was found that not only the new method was more predictive than the existing methods, but its results were good agreed with the measured ones. Therefore, it is expected that application of the new exploration method reduces the unexpected accidents caused by the underground uncertainties during the underground construction works.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1806-1813
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• 2002

It is well known that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select a trial solution initially for optimization because the defined objective function is heavily multimodal. A method is presented in this paper, which uses continuous evolutionary algorithms(CEAs). CEAs are effective for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising with high parallel efficiency over about 94%.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.731-742
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• 2007

This paper presents a new nonlinear analysis algorithm, that is, adaptive Newton-Raphson iteration method, The presented algorithm is based on the existing Newton-Raphson method, and the concept of it can be summarized as calculating the equivalent load for stiffness(ELS) and adapting this to the initial global stiffness matrix which has already been calculated and saved in initial analysis and finally calculating the correction displacements for the nonlinear analysis, The key characteristics of the proposed algorithm is that it calculates the inverse matrix of the global stiffness matrix only once irresponsive of the number of load steps. The efficiency of the proposed algorithm depends on the ratio of the active Dofs - the Dofs which are directly connected to the members of which the element stiffness are changed - to the total Dofs, and based on this ratio by using the proposed algorithm as a complementary method to the existing algorithm the efficiency of the nonlinear analysis can be improved dramatically.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.977-982
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• 2008

In this paper Haar functions are developed to approximate the solutions of continuous time linear system. Properties of Haar functions are first presented, and an explicit expression for the inverse of the Haar operational matrix is presented. Using the inverse of the Haar operational matrix the full order Stein equation should be solved in terms of the solutions of pure algebraic matrix equations, which reduces the computation time remarkably. Finally a numerical example is illustrated to demonstrate the validity of the proposed algorithm.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10a
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• pp.68-71
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• 2003

Heat treatment is one of the critical manufacturing processes that determine the quality of a product. This paper presents experimental and analytical results for the quench of a ring gear in stagnant oil. The goal of this study is to develop heat transfer predicting model in an overall analysis of the quenching process. Thermal conductivities which are dependant on temperatures and convection coefficients which are obtained by inverse method are used to develop the accurate heat transfer model. The results of heat transfer model have a good agreement with experimental results.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.4
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• pp.24-29
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• 1999

In this paper, a simple contour-preserving filtering algorithm is proposed. The goal of the contour-preserving filtering method is to remove noise ad granularity as the preprocessing for the image segmentation procedure. Our method finds edge map and separates the image into the edge region and the non-edge region using this edge map. For the non-edge region, typical smoothing filters could be used to remove the noise and the small areas during the segmentation procedure. The result of simulation shows that our method is slightly better than the typical methods such as the median filtering and gradient inverse weighted filtering in the point of view of analysis of variance (ANOVA).

• Transactions of Materials Processing
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• v.13 no.5
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• pp.441-448
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• 2004

Heat treatment is one of the critical manufacturing processes that determine the quality of a product. This paper presents experimental and analytical results for the quench of a ring gear in stagnant oil. The goal of this study is to develop heat transfer predicting model in an overall analysis of the quenching process, Thermal conductivities which are dependant on temperatures and convection coefficients which are obtained by inverse method are used to develop the accurate heat transfer model. The results of heat transfer model have a good agreement with experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.