• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.856-867
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• 1990

In this paper, the convergence and the learning accuracy of the back-propagation (BP) method in neural network are investigated by 1) analyzing the reason for decelerating the convergence of BP method and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative and 2) proposing the modified logistic activation function by defining, the convergence factor based on the analysis. Learning on the output patterns of binary as well as analog forms are tested by the proposed method. In binary output patter, the test results show that the convergence is accelerated and the learning accuracy is improved, and the weights and thresholds are converged so that the stability of neural network can be enhanced. In analog output patter, the results show that with extensive initial transient phenomena the learning error is decreased according to the convergence factor, subsequently the learning accuracy is enhanced.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.95-98
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• 2010

The Electro Magnetic (EM) Acceleration and Deceleration (ACC/DCC) system of the Ferromagnetic Ball(FB) is the linear motor's final structural development which can be used for devices that conserve energy, gaming or rail gun. By accelerating the FB within the coil structure, it is difficult to utilize the FB's magnetizing feature via the ACC/DCC system. There is much monopole space inside the monopole coil. By using this particular feature of the FB, starting coil and Monopole Coil Structure (MCS) can be structurally separated and another simple electric related control system can be experimented for further development. For the purpose of development a review is needed of the control system of both basic stepper motor and BLDC motor.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.90-94
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• 2008

It is well-blown that the convergence rate gets worse when an input signal to an adaptive filter is correlated. In this paper we propose a new adaptive filtering algorithm that makes the convergence rate much improved even for highly correlated input signals. By introducing an orthogonal constraint between successive input signal vectors we overcome the slow convergence problem of the LMS algorithm with the correlated input signal. Simulation results show that the proposed algerian yields fast convergence speed and excellent tracking capability under both time-invariant and time-varying environments, while keeping both computation and implementation simple.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.213-220
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• 2023

Falling occurs unexpectedly during daily activities, causing many difficulties in life. The purpose of this study was to establish a system for fall detection of high-risk occupations and to verify their effectiveness by collecting data and applying it to predictive models. To this end, a wearable device was configured to detect fall by calculating acceleration signals and azimuths through acceleration sensors and gyro sensors. In addition, the study participants wore the device on their abdomen and measured necessary data from falls-related movements in the process of performing predetermined activities and transmitted it to the computer through a Bluetooth device present in the device. The collected data was processed through filtering, applied to fall detection prediction models based on deep learning algorithms which are 1D CNN, LSTM and CNN-LSTM, and evaluate the results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.5
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• pp.899-909
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• 1992

An iterative solution technique is presented to analyze the dynamic systems of rigid bodies subjected to kinematic constraints. Lagrange multipliers associated with the constraints are iteratively computed by monotonically reducing an appropriately defined constraint error vector, and the resulting equation of motion is solved by a well-established ODE technique. Constraints on the velocity and acceleration as well as the position are made to be satisfied at joints at each time step. Time integration is efficiently performed because decomposition or orthonormalization of the large matrix is not required at all. An acceleration technique is suggested for the faster convergence of the iterative scheme.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.103-112
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• 2022

The goal of pattern mining is to identify novel patterns in a database. High utility itemset mining (HUIM) is a research direction for pattern mining. This is different from frequent itemset mining (FIM), which additionally considers the quantity and profit of the commodity. Several algorithms have been used to mine high utility itemsets (HUIs). The original BPSO algorithm lacks local search capabilities in the subsequent stage, resulting in insufficient HUIs to be mined. Compared to the transfer function used in the original PSO algorithm, the V-shaped transfer function more sufficiently reflects the probability between the velocity and position change of the particles. Considering the influence of the acceleration factor on the particle motion mode and trajectory, a nonlinear acceleration strategy was used to enhance the search ability of the particles. Experiments show that the number of mined HUIs is 73% higher than that of the original BPSO algorithm, which indicates better performance of the proposed algorithm.

• Korean Journal of Mathematics
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• v.7 no.2
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• pp.245-269
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• 1999

Multigrid method and acceleration by conjugate gradient method for first-order system least squares (FOSLS) using bilinear finite elements are developed for various boundary value problems of planar linear elasticity. They are two-stage algorithms that first solve for the displacement flux variable, then for the displacement itself. This paper focuses on solving for the displacement flux variable only. Numerical results show that the convergence is uniform even as the material becomes nearly incompressible. Computations for convergence factors and discretization errors are included. Heuristic arguments to improve the convergences are discussed as well.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.3
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• pp.207-214
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• 2006

In this paper, the stability of SA(Spectral Acceleration) fragility curves is studied for the two sets of elastic modulus of concrete. In doing that, general purpose structural analysis program and generally used probability density function are used. The results of structural analysis are represented by Bernoulli distribution which says damage or no damage. By the use of Maximum Likelihood Method, two parameters of lognormal distribution - median and standard deviation - are found. With them, the fragility curves are constructed.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.2
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• pp.141-147
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• 2001

This paper presents a developing algorithm of checking errors of feed mechanism in the NC machine tool with DAC method. It is useful to check static and dynamic rigidity with relation between lost motion and current of rotor. For checking error of feed in assembly tuning with machining center proposed checking algorithm is useful.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1632-1632
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• 2022