• Journal of the Korean Mathematical Society
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• v.46 no.3
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• pp.561-576
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• 2009

We introduce two iterative algorithms for finding a common element of the set of fixed points of an asymptotically k-strict pseudo-contraction and the set of solutions of a mixed equilibrium problem in a Hilbert space. We obtain some weak and strong convergence theorems by using the proposed iterative algorithms. Our results extend and improve the corresponding results of Tada and Takahashi [16] and Kim and Xu [8, 9].

• Journal of Industrial Technology
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• v.22 no.A
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• pp.19-28
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• 2002

The Nelder-Mead simplex algorithm has been one of the most widely used methods for the nonlinear unconstrained optimization, since 1965. Recently, the new algorithm, (so-called the Fuzzy Simplex Algorithm), with fuzzy logic controllers for the expansion, reflection and contraction process of this algorithm has been proposed. In this paper, this new algorithm is developed. And, the formulation for the optimum design of the power screw's efficiency is made. And then, the developed fuzzy simplex algorithm as well as the original one is applied to this optimum design problem. The Fuzzy simplex algorithm results in a faster convergence in this problem, as reported in other study, too.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.613-622
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• 2012

In this paper, we propose a new algorithm to modify the standard Mann' process to have strong convergence for $k$-strictly pseudo-contractive non-self mapping in Hilbert spaces.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.156-161
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• 1994

In this paper, we consider an optimal control problem of a nonlinear stochastic system. Dynamic programming approach is employed for the formulation of a stochastic optimal control problem. As an optimality condition, dynamic programming equation so called the Bellman equation is obtained, which seldom yields an analytical solution, even very difficult to solve numerically. We obtain the numerical solution of the Bellman equation using an algorithm based on the finite difference approximation and the contraction mapping method. Optimal controls are constructed through the solution process of the Bellman equation. We also construct a test case in order to investigate the actual performance of the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.984-993
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• 2003

In Gravure printing process, there are a lot of printing errors caused by expansion and contraction of printing materials and difficulty of printing of small letters, accordingly we cannot detect those errors with eyes. In this paper, we describe the algorithm which can detect small errors automatically in Gravure printing process and a real-time detection system adopting the algorithm. We present the Perimetric Mask algorithm that can eliminate tiny errors occurring near the contour of printing objects to achieve accurate inspection, and also construct an algorithm utilizing symmetry transform which can emphasize tiny errors to make a robust inspection system. We have made a system running in real-time and verified the efficiency of the algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.29-35
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• 2007

This study was designed to investigate the feasibility to utilize the electromyogram (EMG) for estimating the muscle torque. The muscle torque estimation plays an important role in functional electrical stimulation because electrical stimulation causes muscles to fatigue much faster than voluntary contraction, and the stimulation intensity should then be modified to keep the muscle torque within the desired range. We employed the neural network method which was trained using the major EMG parameters and the corresponding knee extensor torque measured and extracted during isometric contractions. The experimental results suggested that (1) our neural network algorithm and protocol was feasible to be adopted in a real-time feedback control of the stimulation intensity, (2) the training data needed to cover the entire range of the measured value, (3) different amplitudes and frequencies made little difference to the estimation quality, and (4) a single input to the neural network led to a better estimation rather than a combination of two or three. Since this study was done under a limited contraction condition, the results need more experiments under many different contraction conditions, such as during walking, for justification.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.344-351
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• 2006

The fatigue of back muscle in the repetitive lifting motion was studied using multiple parameters(FFT_MDF, RMS, 2C, NT) in this study. Recent developments in the time-frequency analysis procedures to compute the IMDF(instantaneous median frequency) were utilized to overcome the nonstationarity of EMG signal using Cohen-Posch distribution. But the above method has a lot of computation time because of its complexity. So, in this study, FFT_MDF(median frequency estimation based on FFT) algorithm was used for median frequency estimation of back muscle EMG signal during muscle work in uniform velocity portion of lumbar movement. The analysis period of EMG signal was determined by using the run test and lumbar movement angle in dynamic task, such as lifting. Results showed that FFT_MDF algorithm is well suited for the estimation of back muscle fatigue from the view point of computation time. The negative slope of a regression line fitted to the median frequency values of back muscle EMG signal was taken as an indication of muscle fatigue. The slope of muscle fatigueness with FFT_MDF method shows the similarity of 77.8% comparing with CP_MDF(median frequency estimation based on Cohen Posch distribution) method.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.533-539
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• 2012

The purpose of this study is to estimate a validity of control signal through a design of Exoskeleton Robot Arm's capable of intelligent recognition as a human arm's motion by using realtime processed data of generated EMG signals. By an intelligent algorithm, the EMG output value of human biceps and triceps muscles contraction can be recognized and used for the control over exoskeleton arm corresponding to human's recognition and judgement. The EMG sensing data of muscles contraction and relaxation are used as the input signal from human's body to operate the Exoskeleton Robot Arm thus copying human arm motion. An intelligent control of Exoskeleton Robot Arm is to design the analog control circuit which processes the input data, and then to manufacture an integrated control board. And then abstracted signal is passed by DSP signal processing, Fuzzy logic algorithm is designed for a accurate prediction of weight or load through the intelligent algorithm, and design an Exoskeleton Robot Arm to express a human's intention.

• KSTLE International Journal
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• v.1 no.2
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• pp.76-82
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• 2000

Turbulence in journal bearing operation is examined and the thermal variability is studied for isothermal, convective and adiabatic conditions on the walls under aligned and misaligned conditions. Also, the effects of a contraction ratio at the cavitation region and the mixing between re-circulating oil and inlet oil on the fluid field of oil film are included. An algorithm for the solution of the coupled turbulent Reynolds and energy equations is used to examine the effects of the various factors. Heat convection is found to play only a small role in determining friction and load under no mixing condition. However, under realistic mixing condition, the heat convection cannot be ignored. The wall temperature and heat transfer have been found to be of secondary important factors to the mixing effectiveness at the groove and the final mixture temperature.