• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.27-32
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• 2020

This paper compare the adaptive equalization performance according to the values of adaptive step variation speed for adapting in VS-CCA (Variable Stepsize-Compact Constellation Algorithm) based on nonlinear function function of error signal. The VS-CCA algorithm compacts the 16-QAM nonconstant modulus signal into the 4 groups of 4-QAM constant modulus signal constellation in quadature plane, then the error signal is generated using the constant modulus of transmitted signal statistics. The adaptive equalizer coefficient were updated in order to achieve the minimum cost function by varying step based on the nonlinear function of error signal. In this time, the instantaneous adaptive step is determined according to the value of step variation speed of nonlinear function and the different equalization performance were obtained according to the step variation speed value. The equalizer internal index and external index which represents the robustness of external noise were used for the performance comparison index. As a result of computer simulation, it was confirmed that the value of variation speed less than 1.0 give more superior in every performance index compared to the greater than 1.0 in steady state.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.727-746
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• 2018

The hash function RIPEMD-160 is a worldwide ISO/IEC standard and the hash function HAS-160 is the Korean hash standard and is widely used in Korea. On the basis of differential meet-in-the-middle attack and biclique technique, a preimage attack on 34-step RIPEMD-160 with message padding and a pseudo-preimage attack on 71-step HAS-160 without message padding are proposed. The former is the first preimage attack from the first step, the latter increases the best pseudo-preimage attack from the first step by 5 steps. Furthermore, we locate the linear spaces in another message words and exchange the bicliques construction process and the mask vector search process. A preimage attack on 35-step RIPEMD-160 and a preimage attack on 71-step HAS-160 are presented. Both of the attacks are from the intermediate step and satisfy the message padding. They improve the best preimage attacks from the intermediate step on step-reduced RIPEMD-160 and HAS-160 by 4 and 3 steps respectively. As far as we know, they are the best preimage and pseudo-preimage attacks on step-reduced RIPEMD-160 and HAS-160 respectively in terms of number of steps.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.389-391
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• 1999

영상 압축 기법에는 여러 가지 알고리즘을 적용되고 있다. 이런 알고리즘들에는 주파수 영역 중복을 제거하기 위한 DCT, 시간 중복성 제거를 위한 움직임 측정, 압축기법에 의해서 만들어진 정보를 부호화하는 VLC들이 있다. 이런 부호화 알고리즘들은 부호화기를 구현하는데 많은 시간을 요구하며 특히 움직임 추정은 부호화기의 절반에 가까운 시간을 소비한다. 움직임 측정 기술의 복잡도는 search algorithm, cost function, search range parameter의 요인으로 나타낼 수 있다. 본 논문에서는 기존의 Full Search 알고리즘 대신에 three-step 알고리즘을 사용하여 움직임 측정 시간을 줄였다. Full Search 알고리즘은 search area에서 모든 지역에 대해 cost function을 사용하여 이전 블록과 얼마나 유사한지를 조사한다. 따라서 이전 블록과 가장 유사한 부분을 찾는 좋은 방법이지만 그만큼 시간이 많이 사용한다. Three-step 알고리즘은 search area의 일정 지역에 대해 cost function를 사용하여 이전 블록과의 유사성을 찾는 fast 알고리즘이다. Three-step 알고리즘을 사용한 경우 기존의 full search 알고리즘을 사용할 때 보다 60% 정도의 시간이 단축되었다. 그리고 생성되는 압축 데이터의 크기는 full search 알고리즘을 사용할 때 보다 많이 차지한다. 생성되는 H.263파일의 화질에서는 Three-step 알고리즘을 사용한 경우일지라도 full search 알고리즘을 사용한 경우와 거의 비슷한 화질을 보여준다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.241-244
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide resemblance between individuals and research optimum solutions by single point method in reconstructive research space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.143-154
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• 2023

The purpose of this study is to present the role and function of Smart Training Education Platform(STEP) as a public online platform that should be aimed at for the development of customized lifelong vocational skills as the existing Occupational Skills Development Act was revised to the National Lifelong Vocational Skills Development Act. To this end, the role and function of STEP's public service was derived based on domestic public online platform service case studies and expert FGI, and an expert verification meeting was held. Based on this, implications for the role and function of STEP as a public online platform were presented.

• Journal of Communications and Networks
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• v.12 no.6
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• pp.600-604
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• 2010

A method of width adaptation in the radial basis function network (RBFN) using stochastic gradient (SG) algorithm is introduced. Using Taylor's expansion of error signal and differentiating the error with respect to the step-size, the optimal time-varying step-size of the width in RBFN is derived. The proposed approach to adjusting widths in RBFN achieves superior learning speed and the steady-state mean square error (MSE) performance in nonlinear channel environment. The proposed method has shown enhanced steady-state MSE performance by more than 3 dB in both nonlinear channel environments. The results confirm that controlling over step-size of the width in RBFN by the proposed algorithm can be an effective approach to enhancement of convergence speed and the steady-state value of MSE.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.463-473
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• 2015

We consider a nonparametric AR(1) model with nonparametric ARCH(1) errors. In order to estimate the unknown function of the ARCH part, we apply the stationary bootstrap procedure, which is characterized by geometrically distributed random length of bootstrap blocks and has the advantage of capturing the dependence structure of the original data. The proposed method is composed of four steps: the first step estimates the AR part by a typical kernel smoothing to calculate AR residuals, the second step estimates the ARCH part via the Nadaraya-Watson kernel from the AR residuals to compute ARCH residuals, the third step applies the stationary bootstrap procedure to the ARCH residuals, and the fourth step defines the stationary bootstrapped Nadaraya-Watson estimator for the ARCH function with the stationary bootstrapped residuals. We prove the asymptotic validity of the stationary bootstrap estimator for the unknown ARCH function by showing the same limiting distribution as the Nadaraya-Watson estimator in the second step.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.261-268
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• 2020

Machine learning is achieved by making a cost function from a given digital signal data and optimizing the cost function. The cost function here has local minimums in the cost function depending on the amount of digital signal data and the structure of the neural network. These local minimums make a problem that prevents learning. Among the many ways of solving these methods, our proposed method is to change the learning step-size. Unlike existed methods using the learning rate (step-size) as a fixed constant, the use of multivariate function as the cost function prevent unnecessary machine learning and find the best way to the minimum value. Numerical experiments show that the results of the proposed method improve about 3%(88.8%→91.5%) performance using the proposed method rather than the existed methods.

• Journal of the Korean Statistical Society
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• v.26 no.1
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• pp.1-22
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• 1997

In the linear regression model $y_{i}$ = .alpha. $x_{i}$ $^{T}$ .beta. + .epsilon.$_{i}$ , i = 1,2,...,n, the weighted pairwise absolute deviation (WPAD) estimator was defined by minimizing the dispersion function D (.beta.) = .sum..sum.$_{{i $w_{{ij}}$$\mid$ $r_{j}$ (.beta.) $r_{i}$ (.beta.)$\mid$, where $r_{i}$ (.beta.)'s are residuals and $w_{{ij}}$'s are weights. This estimator can achive bounded total influence with positive breakdown by choice of weights $w_{{ij}}$. In this paper, we consider a more general type of dispersion function than that of D(.beta.) and propose a pairwise GM-estimator based on the dispersion function. Under some regularity conditions, the proposed estimator has a bounded influence function, a high breakdown point, and asymptotically a normal distribution. Results of a small-sample Monte Carlo study are also presented. presented.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.3
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• pp.21-31
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• 2020

Purpose : The purpose of this study was to determine the effects of a cognitive-exercise program using step on the cognitive function, gait, and depression of elderly with mild cognitive impairment. Methods : The subjects comprised 30 elderly people with mild cognitive impairment who used elderly welfare centers in the provinces A, B, and C between March 21 and June 7, 2019. They were divided into an experimental group (n=15) and a control group (n=15) before undergoing an experiment based on a pretest-posttest control group design. The lowenstein occupational therapy cognitive assessment-geriatric population was used to assess the subjects' cognitive function, while the 4-stage balance test, 30-second chair-stand test, timed up & go test, and functional reach test were employed to evaluate their gait. In addition, the beck depression inventory was used to measure their levels of depression. Results : The cognitive-exercise program using step enhanced the subjects' cognitive function and gait and reduced their levels of depression. Furthermore, statistically significant differences were found between the experimental group and the control group. Conclusion : The cognitive-exercise program using step promoted the process of sensorimotor and cognition through the learning process of various steps taking left and right steps and cognitive activities. It improves gait by activating the coordination of the musculoskeletal and nervous systems of the body and positively affecting posture control, balance, flexibility, and lower extremity muscles. It also relieved depression by performing successful step learning and cognitive activities with forward-looking (doing) that leads to pleasure and achievement. The present study confirmed the value of a cognitive-exercise program using step to treat multiple domains of functional decline in elderly patients with mild cognitive impairment. This is therefore proposed as an intervention program for this patient group.