• 한국항만학회지
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• 제12권1호
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• pp.75-86
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• 1998

To design a coastal structure in the nearshore region, engineers must have means to estimate wave climate. Waves, approaching the surf zone from offshore, experience changes caused by combined effects of bathymetric variations, interference of man-made structure, and nonlinear interactions among wave trains. This paper has attempted to find out the effects of two of the more subtle phenomena involving nonlinear shallow water waves, amplitude dispersion and secondary wave generation. Boussinesq-type equations can be used to model the nonlinear transformation of surface waves in shallow water due to effect of shoaling, refraction, diffraction, and reflection. In this paper, generalized Boussinesq equations under the complex bottom condition is derived using the depth averaged velocity with the series expansion of the velocity potential as a product of powers of the depth of flow. A time stepping finite difference method is used to solve the derived equation. Numerical results are compared to hydraulic model results. The result with the non-linear dispersive wave equation can describe an interesting transformation a sinusoidal wave to one with a cnoidal aspect of a rapid degradation into modulated high frequency waves and transient secondary waves in an intermediate region. The amplitude dispersion of the primary wave crest results in a convex wave front after passing through the shoal and the secondary waves generated by the shoal diffracted in a radial manner into surrounding waters.

• 지능정보연구
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• 제23권3호
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• pp.139-153
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• 2017

기업의 부도는 이해관계자들뿐 아니라 사회에도 경제적으로 큰 손실을 야기한다. 따라서 기업부도예측은 경영학 연구에 있어 중요한 연구주제 중 하나로 다뤄져 왔다. 기존의 연구에서는 부도 예측을 위해 다변량판별분석, 로짓분석, 신경망분석 등 다양한 방법론을 이용하여 모형의 부도 예측력을 높이고 과적합의 문제를 해결하고자 시도하였다. 하지만 기존의 연구들이 시간적 요소를 고려하지 않아 발생할 수 있는 문제점들을 갖고 있음에도 불구하고 부도 예측에 있어서 동적 모형을 이용한 연구는 활발히 진행되고 있지 않으며 따라서 동적 모형을 이용하여 부도예측모형이 더욱 개선될 여지가 있다는 점을 확인할 수 있었다. 이에 본 연구에서는 RNN(Recurrent Neural Network)을 이용하여 시계열 재무 데이터의 동적 변화를 반영한 모형을 만들었으며 기존의 부도예측모형들과의 비교분석을 통해 부도 예측력의 향상에 도움이 된다는 것을 확인할 수 있었다. 모형의 유용성을 검증하기 위해 KIS Value의 재무 데이터를 이용하여 실험을 수행하였고 비교모형으로는 다변량판별분석, 로짓분석, SVM, 인공신경망을 선정하였다. 실험 결과 제안된 모형이 비교 모형에 비해 우수한 예측력을 보이는 것으로 나타났다. 따라서 본 연구는 변수들의 변화를 포착하는 동적 모형을 부도예측에 새롭게 제안하여 부도예측 연구의 발전에 기여할 수 있을 것으로 기대된다.

• 응용통계연구
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• 제34권5호
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• pp.697-710
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• 2021

상대오차를 이용한 예측법은 상대오차(혹은 퍼센트오차)가 중요시되는 분야, 특히 계량경제학이나 소프트웨어 엔지니어링, 또는 정부기관 공식통계 부분에서 기존 예측방법 외에 선호되는 예측방법이다. 그 동안 상대오차를 이용한 예측법은 선형 혹은 비선형 회귀분석 뿐 아니라, 커널회귀를 이용한 비모수 회귀모형, 그리고 정상시계열분석에 이르기까지 그 범위가 확장되어 왔다. 그러나, 지금까지의 분석은 고정효과(fixed effect)만을 고려한 것이어서 임의효과(random effect)에 관한 상대오차 예측법에 대한 확장이 필요하였다. 본 논문의 목적은 상대오차예측법을 일반화선형혼합모형(GLMM)에 속한 감마회귀(gamma regression), 로그정규회귀(lognormal regression), 그리고 역가우스회귀(inverse gaussian regression)의 패널자료(panel data)에 적용시키는데 있다. 이를 위해 실제 자동차 보험회사의 손해액 자료를 사용하였고, 최량예측량과 최량상대오차예측량을 각각 적용-비교해 보았다.

• 산업경영시스템학회지
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• 제39권1호
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Coupled systems mechanics
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• 제7권5호
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• pp.509-524
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• 2018

A hierarchical multi-scale modeling strategy devoted to the study of a Bitumen-Bound Gravel (BBG) is presented in this paper. More precisely, the paper investigates the temperature-dependent linear viscoelastic of the material when submitted to low deformations levels and moderate number of cycles. In such a hierarchical approach, 3D digital Representative Elementary Volumes are built and the outcomes at a scale (here, the sub-mesoscale) are used as input data at the next higher scale (here, the mesoscale). The viscoelastic behavior of the bituminous phases at each scale is taken into account by means of a generalized Maxwell model: the bulk part of the behavior is separated from the deviatoric one and bulk and shear moduli are expanded into Prony series. Furthermore, the viscoelastic phases are considered to be thermorheologically simple: time and temperature are not independent. This behavior is reproduced by the Williams-Landel-Ferry law. By means of the FE simulations of stress relaxation tests, the parameters of the various features of this temperature-dependent viscoelastic behavior are identified.

• 대한토목학회논문집
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• 제26권3B호
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• pp.279-289
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• 2006

최근에 수문시계열로부터 저차원의 비선형 거동을 재구성하고자 하는 연구가 활발히 진행되고 있다. 이러한 관점에서 본 연구에서는 Support Vector Machine(SVM)을 이용하여 우수한 상태-공간 재구성 능력을 갖는 비선형 예측모형을 구성하여 Great Salt Lake(GSL) Volume에 적용하였다. SVM은 Kernel 함수로부터 유도된 고차원의 특성공간 안에서 선형함수의 가상공간을 이용하는 Machine Learning 방법론이다. 또한 SVM은 훈련자료로부터 얻어지는 평균제곱오차가 아닌 일반화된 오차를 최소화함으로써 상대적으로 기존 방법에 비해 적은 수의 매개변수와 과적합(over fitting)을 피하면서 비선형 함수의 최적화가 가능하다. 본 연구에서 제시한 SVM 회귀분석의 적용성은 미국의 GSL의 2주 간격 Volume을 대상으로 검토하였다. SVM을 이용한 비선형 예측모형은 GSL Volume의 2주(1-Step), 8주(4-Step)와 반복예측(Iterated Prediction, 121-Step)까지 적용되었다. 본 연구에서는 극치사상 즉, 급격한 감소 및 증가 구간을 예측하는데 있어서 훈련구간과 예측구간을 구분하여 모형의 신뢰성을 평가하였다. 예측결과SVM은 훈련자료로부터 적은 수의 관측치를 이용하여 동역학적 거동을 추출할 수 있었으며 실제 관측자료와 거의 유사한 예측이 가능함을 통계적 지표로 확인할 수 있었다. 따라서 비선형 수문시계열의 단기 예측을 위한 모형으로 적용이 가능할 것으로 판단된다.

• 한국간호교육학회지
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• 제21권3호
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• pp.350-360
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• 2015

Purpose: The purpose of this study was to evaluate the effectiveness and retention period of immediate remediation for infant cardiopulmonary resuscitation (CPR) in child care teachers. Methods: This study used a nonequivalent comparison pre- and post-test design to measure knowledge about and confidence in infant CPR and an interrupted time-series design to determine skill performance. The experimental group (n=25) received both immediate remediation and video learning for infant CPR, and the comparison group (n=28) received video learning only. Knowledge and confidence were measured before and after 4 weeks. Their skill performance was tested immediately, and 4 weeks, 8 weeks, 12 weeks, and 24 weeks after intervention. Data analysis consisted of ${\chi}^2$ tests, t-tests, paired t-tests, and a generalized linear mixed model. Results: There were significant increases in knowledge and confidence within the experimental group. Skill performance showed a significant difference according to the group factor (F=10.81, p=.002) and measurement time (F=146.80, p<.001). The experimental group maintained significantly higher skill performance than did the comparison group. Conclusion: These findings support the necessity of immediate remediation education for infant CPR to maintain skill performance. In addition, appropriate renewal time and the improvement of training programs for child care teachers are necessary.

• 한국구조물진단유지관리공학회 논문집
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• 제8권2호
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• pp.195-204
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• 2004

본 연구에서는 약액주입 사질고결토에 대해 일정재하크리프시험과 반복재하크리프시험을 실시하여 점 탄소성 거동 규명과 크리프예측을 수행하였다. 일정재하크리프 시험결과 총 변형률은 탄성, 소성 그리고 점탄성변형률로 구분되었으며 이러한 변형률은 응력의 증가에 비례하여 증가하였고 회복된 변형률은 제하시간에 무관함을 알았다. 일정재하크리프시험 예측결과 일반화된 모델과 지수함수모델은 시험결과와 잘 일치하였다. 반복재하크리프시험에서 순간회복변형률은 반복횟수에 무관하였고 누적소성 변형률은 반복횟수에 따라 증가하였으며 응력레벨에 비례함을 알 수 있었다. 반복재하크리프시험의 예측결과 첫 사이클에서는 잘 일치하였으나 반복횟수가 증가함에 따라 약간의 오차가 발생되었다.

• Journal of Preventive Medicine and Public Health
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• 제51권6호
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• pp.265-274
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• 2018

Objectives: A positive association between air pollution and both the incidence and prevalence of diabetes mellitus (DM) has been reported in some epidemiologic and animal studies, but little research has evaluated the relationship between air pollution and diabetic coma. Diabetic coma is an acute complication of DM caused by diabetic ketoacidosis or hyperosmolar hyperglycemic state, which is characterized by extreme hyperglycemia accompanied by coma. We conducted a time-series study with a generalized additive model using a distributed-lag non-linear model to assess the association between ambient air pollution (particulate matter less than $10{\mu}m$ in aerodynamic diameter, nitrogen dioxide [$NO_2$], sulfur dioxide, carbon monoxide, and ozone) and emergency department (ED) visits for DM with coma in Seoul, Korea from 2005 to 2009. Methods: The ED data and medical records from the 3 years previous to each diabetic coma event were obtained from the Health Insurance Review and Assessment Service to examine the relationship with air pollutants. Results: Overall, the adjusted relative risks (RRs) for an interquartile range (IQR) increment of $NO_2$ was statistically significant at lag 1 (RR, 1.125; 95% confidence interval [CI], 1.039 to 1.219) in a single-lag model and both lag 0-1 (RR, 1.120; 95% CI, 1.028 to 1.219) and lag 0-3 (RR, 1.092; 95% CI, 1.005 to 1.186) in a cumulative-lag model. In a subgroup analysis, significant positive RRs were found for females for per-IQR increments of $NO_2$ at cumulative lag 0-3 (RR, 1.149; 95% CI, 1.022 to 1.291). Conclusions: The results of our study suggest that ambient air pollution, specifically $NO_2$, is associated with ED visits for diabetic coma.

• Wind and Structures
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• 제10권3호
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• pp.233-247
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• 2007

The insertion of steel braces has become a common technique to limit the deformability of steel framed buildings subjected to wind loads. However, when this technique is inadequate to keep floor accelerations within acceptable levels of human comfort, dampers placed in series with the steel braces can be adopted. To check the effectiveness of braces equipped with viscoelastic (VEDs) or friction dampers (FRDs), a numerical investigation is carried out focusing attention on a three-bay fifteen-storey steel framed building with K-braces. More precisely, three alternative structural solutions are examined for the purpose of controlling wind-induced vibrations: the insertion of additional diagonal braces; the insertion of additional diagonal braces equipped with dampers; the insertion of both additional diagonal braces and dampers supported by the existing K-braces. Additional braces and dampers are designed according to a simplified procedure based on a proportional stiffness criterion. A dynamic analysis is carried out in the time domain using a step-by-step initial-stress-like iterative procedure. Along-wind loads are considered at each storey assuming the time histories of the wind velocity, for a return period $T_r=5$ years, according to an equivalent wind spectrum technique. The behaviour of the structural members, except dampers, is assumed linear elastic. A VED and an FRD are idealized by a six-element generalized model and a bilinear (rigid-plastic) model, respectively. The results show that the structure with damped additional braces can be considered, among those examined, the most effective to control vibrations due to wind, particularly the floor accelerations. Moreover, once the stiffness of the additional braces is selected, the VEDs are slightly more efficient than the FRDs, because they, unlike the FRDs, dissipate energy also for small amplitude vibrations.