• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1151-1161
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• 2014

Despite the fact that the optimal design for nonlinear model depends on the unknown quantity of parameter to estimate basically, its popularity is growing in bio and engineering statistics area since all those models in the area are virtually nonlinear. In this paper we have dealt with the case when the researcher has multiple objectives in experimentation, decision among the competing models, protection against the departure from the assumed model, and the con icting interests among design criteria. To tackle these issues we attempted several new approaches which are taking advantage of the easiness of constrained optimal design. Several nonlinear models were tested.

• Clinical and Experimental Reproductive Medicine
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• v.45 no.2
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• pp.57-66
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• 2018

It has been estimated that approximately 15% of reproductive-age couples suffer from infertility. Male factors contribute to almost half of infertility cases, and in many patients the underlying cause of oligoasthenoteratozoospermia is unknown. Accumulating evidence suggests that oxidative stress plays a role as a contributing factor to male infertility, and reactive oxygen species have been shown to impair sperm function and motility and to damage sperm membrane and DNA. Therefore, this review explored the evidence provided by studies published from 2002 to 2017 on the impact of oral antioxidants (vitamin C, vitamin E, L-carnitine, coenzyme Q10, zinc, selenium, and pentoxifylline) on seminal fluid parameters in men with idiopathic oligoasthenoteratozoospermia. Most of the studies were randomized controlled studies that investigated the effect of single or combined antioxidants and reported improvements in at least one semen parameter. The most noteworthy effect that was found was that the use of multiple antioxidants increased sperm motility and concentration. Nonetheless, there is a lack of agreement on the dose, the duration of treatment, and whether individual or combined oral antioxidants should be used. Therefore, the current review provides evidence supporting the use of oral antioxidants in the treatment of infertile men with idiopathic oligoasthenoteratozoospermia.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.350-355
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• 1997

The problem of mathematical model for an unknown system by measureing its input-output data pairs is generally referred to as state estimates. The state estimation problem is often of importance in its own right since we may want to know the value of the states. For instance, in navigation, we may take noisy positional fixes using satelite or radar navigation, and the estimator can use these measurements to provide accurate estimates of current position, hedaing, and velocity. And the state estimates can also be used for control purposes. Then it is very important to know the state of plant. In this paper, the theory of the minimization of a loss function was used to design the fuzzy system. Here, the used teory is Least Square Esimation method. This parametrization has the Linear in the parameters charcteristic that allows standard parameter estimation technique to be used to estimate the parameters of the fuzzy system. The combination of the fuzzy system and the estimation m thod then performs as a nonlinear estimator. If several fuzzy label are defined for the input variables at the antecedent part, the fuzzy system then behaves as a collection of nonlinear estimators where different regions of rules have different parameters. In simulation results, the fuzzy model controlled a difference in the structure between the actual plant and the fuzzy estimator. It is also proved that the fuzzy system is equivalent to its transformed system. therefore we was able to get the state space equation of system with the estimated paramater.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.610-616
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• 2004

In the research of biomechanical engineering, robotics and neurophysiology, to clarify the mechanism of human bipedal walking is of major interest. It serves as a basis of developing several applications such as rehabilitation tools and humanoid robots. Nevertheless, because of complexity of the neuronal system that interacts with the body dynamics system to make walking movements, much is left unknown about the details of locomotion mechanism. Researchers were looking for the optimal model of the neuronal system by trials and errors. In this paper, we applied Genetic Programming to induce the model of the nervous system automatically and showed its effectiveness by simulating a human bipedal walking with the obtained model.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.4-9
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• 1999

A new control method for precision robust position control of a brushless DC (BLDC) motor using asymptotically stable adaptive load torque observer is presented in the paper. Precision position control is obtained for the BLDC motor system approximately linearized using the field-orientation method Recently, many of these drive systems use BLDC motors to avoid backlashe. However, the disadvantages of the motor are high cost and complex control because of nonlinear characteristics. Also, the load torque disturbance directly affects the motor shaft. The application of the load torque observer is published in [1] using fixed gain. However, the motor flux linkage is not exactly known for a load torque observer. There is the problem of uncertainty to obtain very high precision position control. Therefore a model reference adaptive observer is considered to overcome the problem of unknown parameter and torque disturbance in this paper. The system stability analysis is carried out using Lyapunov stability theorem. As a result, asymptotically stable observe gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current which gives fast response. The experimenta results are presented in the paper.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.163-168
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• 2002

This paper present a new verb efficient numerical algorithm for arcing faults detection and fault distance estimation in transmission line. It is based on the fundamental differential equations describing the transients on a transmission line before, during and alter the fault occurrence, and on the application of the "Least Error Squares Technique"for the unknown model parameter estimation. If the arc voltage estimated is a near zero, the fault is without arc, in other words the fault is permanent fault. If the arc voltage estimated has any high value, the faust is identified as an fault, or the transient fault. In permanent faults case, fault distance estimation is necessary. This paper uses the model of the arcing fault in transmission line using ZnO arrestor and resistance to be implemented within EMTP. One purpose of this study is to build a structure for modeling of arcing fault detection and fault distance estimation algorithm using Matlab programming. In this paper, This algorithm has been designed in Graphic user interface(GUI).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.413-415
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• 2001

In this paper, Polynomial Neural Networks(PNN) is proposed to overcome some problems, such as the conflict between overfitting and good generation, and low reliability and to control nonlinearity and unknown parameter of complex system. PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be generated according to the system environments. The performances depend on two factors, number of inputs and order of polynomials in each node directly. In most cases these factors are decided by the trial and error of designer so optimization is needed in deciding procedure of the factors. Evolutionary algorithm is applied to decide the factors in PNN. The study is illustrated with the aid of representative time series data for gas furnace process used widely for performance comparison, and shows the designed PNN architecture with evolutionary algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.11
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• pp.1072-1078
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• 2008

An adaptive control algorithm for spacecraft rendezvous and docking in a Keplerian orbit is presented. The equations of relative motion of two spacecrafts expressed in a local-vertical-local-horizontal rectangular frame are converted to a general Hamiltonian form, then an adaptive control method developed for the uncertain Hamiltonian system is applied to the rendezvous and docking problem. A smooth projection algorithm is applied to keep the parameter estimates inside a singularity-free region, and a numerical example shows that the developed controller successfully deals with the unknown mass of the chaser spacecraft.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.11 no.1
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• pp.98-103
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• 2000

Background and Objectives : The etiology and pathophysiology of spasmodic dysphonia is yet unknown. This study was performed to determine if any laryngeal aerodynamic parameter distinguish the voice of patient diagnosed as having adductor spasmodic dysphonia from individuals with normal voice production and to investigate the pathophysiology of spasmodic dysphonia. Materials and Methods : fifteen women diagnosed as having adductor spasmodic dysphonia and fifteen normal control women participitated in this study Maximum phonation time, mean air flow rate, subglottic pressure, vocal efficiency, Vfo, NHR, VTI, FTRI, ATRI, Jitter percent, Shimmer percent were obtained from the participants using 'MDVP(multi-dimensional voice program)' of CSL(Computerized Speech lab, Kay Elemetrics, Co., Model No. 4300), and 'maximum sustained phonation' and 'IPIPI test' of AP II(Aerophone II, Kay Elemetrics, Co., Model 6800). Results : T-test statistical analysis revealed statistically different values for vocal efficiency, Vfo, NHR, MPT, litter percent, Shimmer percent between the spasmodic dysphonia group and the control group. Conclusions : Spasmodic dysphonia affects the ability of the laryngeal mechanism to function effectively. Results from our study demonstrate that certain aerodynamic and acoustic parameters distinguish adductor spasmodic dysphonia from normal voice.