• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.147-150
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• 1996

Human posture prediction and motion simulation methods try to solve inverse kinematic problems using the optimization technique based on the concept of minimum principle. It is very important to select a cost function which relfects the human posture acurately. In this study, lifting postures were predicted using the five biomechanical cost functions and compared with real human postures in order to evaluate the predictivities of the cost functions. The result showed that all the biomechanical cost functions used in this study could not predict lifting postures accurately. The cost function which minimizes the sum of joint moments showed the smallest mean prediction error, while the one which minimizes the MUR showed statistically better performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.3
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• pp.273-286
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• 2017

We develop an inspection method for bearing faults with a rapid change in the rotation speed and present indexes for the pass/fail inspection. At the end of line, impulse noises generated by the operation of machines and conveyors may distort the inspection results. In this paper, we present robust inspection indexes for bearing faults under impulse noises, by taking into account fault signals having pulse train. Using logistic regression, we optimize the pass/fail criterion for each index and evaluate the performance of the inspection indexes based on the total error rate.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.85-93
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• 2001

The basic concept of the model is to minimize the error range between forecasted flood inflow and actual flood inflow, and forecast accurately the flood discharge some hours in advance depending on the concentration time(Tc) and soil moisture retention storage(Sa). Simplex method that is a multi-level optimization technique was used to search for the determination of the best parameters of RETFLO (REal-Time FLOod forecasting) model. The flood forecasting model developed was applied to several strom event of Yedang reservoir during past 10 years. Model perfomance was very good with relative errors of 10% for comparison of total runoff volume and with one hour delayed peak time.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.295-299
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• 2001

To protect the flooding damages in Medium and Small watershed, it needs to set up flood warning system and develope Flood forecasting Model in real-time basis for medium and small watershed. In this study, it was able to minimize the error range between forecasted flood inflow and actual flood inflow, and forecast accurately the flood discharge some hours in advance by using simplex method recursively for the determination of the best parameters of RETFLO model. The result of RETFLO performance applied to several storm of Yugu river during 3 past years was very good with relative errors of 10% for comparison of total runoff volume and with one hour delayed peak time.

• International Journal of Contents
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• v.9 no.1
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• pp.33-37
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• 2013

BCH code is one of the most widely used error correcting code for the detection and correction of random errors in the modern digital communication systems. The conventional BCH encoder that is operated in bit-serial manner cannot adequate with the recent high speed appliances. Therefore, parallel encoding algorithms are always a necessity. In this paper, we introduced a new systolic array type BCH parallel encoder. To study the area and speed, several parallel factors of the systolic array encoder is compared. Furthermore, to prove the efficiency of the proposed algorithm using tree-type structure, the throughput and the area overhead was compared with its counterparts also. The proposed BCH encoder has a great flexibility in parallelization and the speed was increased by 40% than the original one. The results were implemented on synthesis and simulation on FPGA using VHDL.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.155-160
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• 2011

In distributed source localization where sensors transmit measurements to a fusion node, we address the sensor selection problem where the goal is to find the best set of sensors that maximizes localization accuracy when quantization of sensor measurements is taken into account. Since sensor selection depends heavily upon rate assigned to each sensor, joint optimization of rate allocation and sensor selection is required to achieve the best solution. We show that this task could be accomplished by solving the problem of allocating rates to each sensor so as to minimize the error in estimating the position of a source. Then we solve this rate allocation problem by using the generalized BFOS algorithm. Our experiments demonstrate that the best set of sensors obtained from the proposed sensor selection algorithm leads to significant improvements in localization performance with respect to the set of sensors determined from a sensor selection process based on unquantized measurements.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.366-371
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• 2002

Because of the environmental problems, automotive companies are trying to reduce the weight of car body. Therefore, TRIP(TRansformation Induced Plasticity) steels, which have high strength and ductility have been developed. Welding process is a complex process; therefore deciding the optimal welding conditions on the basis of experimental data is an effective method. However, trial-and-error method to decide the optimal conditions requires too many experiments. To overcome these problems, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are used in the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. This method was applied to the resistance spot welding process of the TRIP steel to optimize the welding parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.440-445
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• 1994

An application of H$_{\infty}$ synthesis to contact control of a manipulator is suggested. Based on computed torque linearization of a manipulator, a target dynamics for contact motion control is defined and used as a reference model. The target dynamics relates position and force errors through free motion impedance and force error compensators. The H$_{\infty}$ control synthesis is adopted to find an optimum the compensator for position tied force control in various directions of the end-effector. The optimization is performed on the augmented criteria, which trades off the sensitivity function of the errors and the input load at the joints. A design example of the compensator is provided that meets the design specifications.s.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.737-741
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• 1994

We show an application of a genetic algorithm to, control systems including neural networks. Genetic algorithms are getting more popular nowadays because of their simplicity and robustness. Genetic algorithms are global search techniques for optimization and many other problems. A feed-forward neural network which is widely used in control applications usually learns by error back propagation algorithm(EBP). But, when there exist certain constraints, EBP can not be applied. We apply a modified genetic algorithm to such a case. We show simulation examples of two cart-pole nonlinear systems: single pole and double pole.