• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.2
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• pp.188-202
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• 1997

The seasonal variability of the sea surface winds over the last Sea of Korea (Japan Sea) is investigated by means of empirical orthogonal function (EOF) analysis. The combined representation of fields of three climatic variables by empirical orthogonal functions is discussed. The eigenvectors are derived from daily sea level pressure, wind speed and 10-day mean sea surface temperature (SST) during 15 years $(1978\~1992)$. The spatial patterns of the mean pressure are characterized by the high pressure in the western part and the low pressure in the eastern part. The spatial distribution of the standard deviation (SD) of pressure are characterized by max SD of 6.6 mb near the Vladivostok, and minima along the coast of the Japan. In Vladivostok, the maxima of SD of SST and south-north wind (WV) were also occurred. The representation of fields of individual meteorological variables by EOF shows that the first mode of the west-east wind (WU) explain over $47.3\%$ of the variance and the second mode of WU represents $30\%$. Especially, the first mode of the WV explain $70.9\%$ of the variance and their time series coefficients show 1-cpy, 0.5-cpy frequency spectrum. The spatial distribution of the first mode eigenvectors of SST are characterized by maximum near Vladivostok. The combined representation of fields of several variables (pressure, wind, SST) reveals that the first mode magnitudes of the variance of the combined eigenvectors (WU-PR) are increased. By means of this result, the 1-year peak and the 6-months peak are remarkable. In the three combined patterns (wind, pressure, SST), the second mode of the eigenvector (wind) is affected by the SST. Their time coefficients of the first mode show noticeable 1-year peak. The spectral analysis of the second mode shows broad seasonal signal with the period of 4-months and a significant peak of variability at 3-month period.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.2
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• pp.37-45
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• 2022

A simplified model using the lifetime distribution has been presented to estimate the Mean Residual Life (MRL) of rubble-mound breakwaters, which is not like a stochastic process model based on time-dependent history data to the cumulative damage progress of rubble-mound breakwaters. The parameters involved in the lifetime distribution can be easily estimated by using the upper and lower limits of lifetime and their likelihood that made a judgement by several experts taking account of the initial design lifetime, the past sequences of loads, and others. The simplified model presented in this paper has been applied to the rubble-mound breakwater with TTP armor layer. Wiener Process (WP)-based stochastic model also has been applied together with Monte-Carlo Simulation (MCS) technique to the breakwater of the same condition having time-dependent cumulative damage to TTP armor layer. From the comparison of lifetime distribution obtained from each models including Mean Time To Failure (MTTF), it has found that the lifetime distributions of rubble-mound breakwater can be very satisfactorily fitted by log-normal distribution for all types of cumulative damage progresses, such as exponential, linear, and logarithmic deterioration which are feasible in the real situations. Finally, the MRL of rubble-mound breakwaters estimated by the simplified model presented in this paper have been compared with those by WP stochastic process. It can be shown that results of the presented simplified model have been identical with those of WP stochastic process until any ages in the range of MTT F regardless of the deterioration types. However, a little of differences have been seen at the ages in the neighborhood of MTTF, specially, for the linear and logarithmic deterioration of cumulative damages. For the accurate estimation of MRL of harbor structures, it may be desirable that the stochastic processes should be used to consider properly time-dependent uncertainties of damage deterioration. Nevertheless, the simplified model presented in this paper can be useful in the building of the MRL-based preventive maintenance planning for several kinds of harbor structures, because of which is not needed time-dependent history data about the damage deterioration of structures as mentioned above.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.503-510
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• 2003

In CDMA cellular system, because all users share the frequency resource the signals of other user becomes interference which influences the communication quality. The system capacity defined the number of connected users within a cell is determined by the amount of interference, therefore the exact estimation of interference is important to system performance evaluation. In this paper, we propose an approximated function which calculates other cell interference in terms of Riemann-Zeta function in CDMA cellular systems, and compare with simulation results in other to verify its usefulness. The upper and lower bounds of system capacity calculated with the proposed approximated function gives almost alike result with the simulation. The proposed interference bounds are useful to calculate system capacity and to evaluate some algorithm in a hierarchical cellular systems where various propagation environments are mixed.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.543-549
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• 2013

Motion artifacts of central and autonomic nervous system signals degrades the performance of the bio-signal based human factor analysis. Firstly, we propose a defining method of motion artifact section by analyzing successive image frames. Motion artifact section is defined when the amount of motion is greater than the pre-defined threshold. In here, the amount of motion is estimated by first derivation of image frames at temporal domain. Secondly, we propose another defining method of motion artifact section through designing 2D Gaussian probability density function model by analyzing feature vectors of one cycle of signal such as length and amplitude. The defined motion artifact sections are interpolated on the basis of 1D Gaussian function. At result of applying the method into photoplethysmography signal, we confirmed that the calculated heartbeat rate from the restored photoplethysmography came up to the one from electrocardiography. Also, we found that the video based method generated relatively more false acceptance of motion artifact section and the probability density function based method generated relatively more false rejection of motion artifact section.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.32-41
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• 1999

In this paper, an inversion method using chirp signals and two near field receivers is proposed. Inversion problems can be formulated into the probabilistic models composed of signals, a forward model and noise. Forward model to simulate chirp signals is chosen to be the source-wavelet-convolution planewave modeling method. The solution of the inversion problem is defined by a posteriori pdf. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the ranges for a priori uniform distribution is based. The genetic algorithm can be applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L₂norm of the difference between measured and modeled signals. The observed signals can be separated into a set of two signals reflected from the upper and lower boundaries of a sediment. The separation of signals and successive applications of the genetic algorithm optimization process reduce the search space, therefore improving the inversion results. Not only the marginal pdf but also the statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm. The examples applied here show that, for synthetic data with noise, it is possible to carry out an inversion for sedimentary layers using the proposed inversion method.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.835-842
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• 2001

We propose a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase. The time-dependent behavior of testing effort expenditures is described by a Weibull curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, we discuss the relations between testing time and reliability and between duration following failure fixing and reliability are studied in this paper. The release time making the testing cost to be minimum is determined through studying the cost for each condition. Also, the release time is determined depending on the conditions of the specified reliability. The optimum release time is determined by simultaneously studying optimum release time issue that determines both the cost related time and the specified reliability related time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.706-713
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• 2020

To control the LED lighting for broadcasting, LED current control using tri-stimulus values is used for RGB LEDs. For the convenience of control, this control is approximated as a linear function or used as an appropriate value through trial and error. Also, it is not suitable for broadcast lighting because it does not use a diffuser plate applied for mixing sufficient light and color required for actual it. In this study, a neural network with excellent nonlinear function approximation is used as a control method for LED panels for broadcast lighting. We intend to implement an LED panels controller suitable for the desired chromaticity coordinates and dimming values of intensity. As a result of the performance evaluation, the errors of the xy chromaticity coordinates are mostly ±0.02 and the acceptable range of ANSI C78.377A was satisfied. The average errors of the xy chromaticity coordinate are xerror=0.0044 and yerror=0.0030, respectively, and we confirmed the superiority and stable performance of the proposed algorithm.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.265-283
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• 2022

MovieLens data consists of recorded movie evaluations that was often used to measure the evaluation score in the recommendation system research field. In this paper, we provide additional information obtained by clustering user-specific genre preference information through movie evaluation data and movie genre data. Because the number of movie ratings per user is very low compared to the total number of movies, the missing rate in this data is very high. For this reason, there are limitations in applying the existing clustering methods. In this paper, we propose a convex clustering-based method using the pairwise fused penalty motivated by the analysis of MovieLens data. In particular, the proposed clustering method execute missing imputation, and at the same time uses movie evaluation and genre weights for each movie to cluster genre preference information possessed by each individual. We compute the proposed optimization using alternating direction method of multipliers algorithm. It is shown that the proposed clustering method is less sensitive to noise and outliers than the existing method through simulation and MovieLens data application.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.333-333
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• 2021

최근 전 지구적인 기후변화 및 온난화의 영향으로 태풍 및 집중호우가 빈번하게 일어나고 있으며, 이로 인한 한천범람 등 홍수재해로 인명 및 재산 피해가 크게 증가하고 있다. 우리나라에서도 태풍 및 집중호우로 인한 호수피해는 매년 발생하고 있으며, 피해 빈도와 강도가 증가하고 있는 실정이다. 이러한 현실을 고려하였을 때에 하천 인근 주민의 생명과 재산을 보호하기 위하여 실시간으로 홍수위 예측을 수행하는 것은 매우 중요하다 할 수 있다. 국내에서 수위예측을 위하여 대표적으로 저류함수모형(Storage Function Model, SFM)을 채택하고 있지만, 유역면적이 작아 홍수 도달시간이 짧은 중소하천에서는 충분한 선행시간과 정확도를 확보하기 어려운 문제점이 있다. 이는 유역면적이 작은 중소하천에서는 유역 및 기상 특성과 관련된 여러 인자 사이의 비선형성이 대하천 유역에 비해 커지는 문제점이 있기 때문이다. 본 연구에서는 위와같은 문제를 해결할 수 있도록, 수문자료와 딥러닝 기법을 적용하여 실시간으로 홍수위를 예측할 수 있는 방법론을 제시하였다. 지난 태풍 및 집중호우로 인하여 급격한 수위상승이 있던 낙동강 지류하천에 대하여 LSTM(Long-Short Term Memory) 모형 기반 실시간 수위예측 모형을 개발하였으며, 선행시간 30~180분 별로 홍수위를 예측하고 관측 수위와 비교함으로써 모형의 적용성을 검증하였다. 선행시간 180분 기준으로 영강 유역 수위예측 결과와 실제 관측치의 평균제곱근 오차는 0.29m, 상관계수는 0.92로 나타났으며, 밀양강 유역의 경우 각각 0.30m, 0.94로 나타났다. 본 연구에서 제시된 딥러닝 기반모형에 10분 단위 실시간 수문자료가 입력된다면, 다음 관측자료가 입력되기 전 홍수예측 결과가 산출되므로 실질적인 홍수예경보체계에 유용하게 사용될 수 있을 것이라 보인다. 모형에 적용할 수 있는 더욱 다양한 수문자료와 매개변수 조정을 통하여 예측결과에 대한 신뢰성을 더욱 높일 수 있다면, 기존의 저류함수모형과 연계하여 홍수대응 능력을 향상시키는데 도움이 될 수 있다.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1
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• pp.36-42
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• 2006

A Principal component analysis (PCA)-based Mel-Frequency Discrete Wavelet Coefficients (MFDWC) feature Parameters for speaker verification system is Presented in this Paper In this method, we used the 1st-eigenvector obtained from PCA to calculate the energy of each node of level that was approximated by. met-scale. This eigenvector satisfies the constraint of general weighting function that the squared sum of each component of weighting function is unity and is considered to represent speaker's characteristic closely because the 1st-eigenvector of each speaker is fairly different from the others. For verification. we used Universal Background Model (UBM) approach that compares claimed speaker s model with UBM on frame-level. We performed experiments to test the effectiveness of PCA-based parameter and found that our Proposed Parameters could obtain improved average Performance of $0.80\%$compared to MFCC. $5.14\%$ to LPCC and 6.69 to existing MFDWC.