• Economic Analysis
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• v.27 no.1
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• pp.67-90
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• 2021

This study found an interesting fact that the nonlinear relationship structure between volatility and trading volume changed before and after the COVID-19 pandemic according to empirical analysis using Bitcoin (BTC) market data that sensitively reflects investors' trading behavior. That is, their relationship appeared positive (+) in a stable market state before COVID-19 pandemic, as in theory based on the information flow paradigm. In a state under severe market stress due to COVID-19 pandemic, however, their dependence structure changed and even negative (-). This can be seen as a consequence of increased market stress caused by COVID-19 pandemics from a behavioral economics perspective, resulting in structural changes in the asset market and a significant impact on the nonlinear dependence of volatility and trading volume (in particular, their dependence at extreme quantiles). Hence, it should be recognized that in addition to information flows, psychological phenomena such as behavioral biases or herd behavior, which are closely related to market stress, can be a key in changing their dependence structure. For empirical analysis, this study performs a test of Ross (2015) for detecting a structural change, and proposes a Copula Regression Quantiles (CRQ) approach that can identify their nonlinear relationship structure and the asymmetric dependence in their distribution tails without the assumption of i.i.d. random variable. In addition, it was confirmed that when the relationship between their extreme values was analyzed by linear models, incorrect results could be derived due to model specification errors.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.4
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• pp.399-405
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• 2010

The grasping motion of a person's hand for a simplified degree of freedom was modeled by using the photographic motion measured by a high-speed camera. The mathematical expression of distal interphalangeal (DIP) motion was developed by using relation models of the metacarpophalangeal (MCP) and proximal interphalangeal (PIP) motions to reduce the degree of freedom. The mathematical expression for humanoid-hand operation obtained using a learning algorithm with a neural network and using a kernel regression model were compared. A feasible model of hand operation was obtained on the basis of comparative data analysis by using the kernel regression model.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.17-17
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• 2021

계획하폭의 수리설계는 수문분석에 의하여 결정되는 설계홍수량을 주변지역 주택이나 농지 침수를 방지하지 않도록 하도내에서 수위를 과다하게 상승시키지 않은 상태에서 안전하게 하류로 소통시킬 수 있는 가장 경제적인 하도의 폭을 결정하는 것이라 할 수 있다. 현재 소하천 하폭의 수리설계는 지형 또는 현장 여건에 따라 계획홍수량을 결정하고, 경험식에 의한 방법 또는 도식에 의한 방법(방정식과 수리학 공식에 의한 방법)등을 이용하여 하류수위를 산정함으로써 이루어진다. 그러나 하도내 흐름이 자유수면을 가지는 개수로 흐름인 경우 도표 또는 간략화된 경험식을 이용해서는 정확한 하폭을 산정할 수 없다. 기존에 개발된 계획하폭 경험식은 홍수량에 기반한 단일 회귀식과 다양한 하천특성과 흐름특성을 이용한 다중 회귀식으로 구분된다. 그러나 현재 계획하폭 결정에 가장 많이 사용되는 경험식은 홍수량을 이용한 단일 회귀식인데, 이들은 자료수집의 어려움 때문에 지역과 하천특성을 고려하지 않고 모든 하천에 적용 가능하도록 개발되어 적용 시 세심한 주의가 요구된다. 본 연구에서는 기존의 경험식을 보완함으로써 적용성을 제고하기 위하여 전국 소하천을 지역에 따라 세분화하고 흐름특성과 하천특성 자료를 수집하였다. 이렇게 수집된 자료를 위치에 따라 세분화하고 기존에 개발된 경험식과 동일한 형태로 계획하폭 경험식을 개발하였다. 개발된 경험식을 검증하는 방법은 자료를 두 개의 그룹으로 분리하고 개발에 사용되지 않은 자료 그룹을 사용함으로써 검증의 신뢰성을 확보하였다. 더불어 기존의 경험식과 비교하는 방법으로 개발된 회귀식의 적용성을 검증하였다. 본 연구에서 개발한 계획하폭 경험식은 지역특성과 흐름특성을 고려한 계획하폭 산정에 활용이 가능함으로써 홍수에 안전한 소하천 수리설계에 활용이 가능할 것으로 기대된다.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.275-283
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• 2011

A local or site-specific water temperature is downscaled from the nation-wide air temperature that represents simulation by General Circulation Model (GCM). Both two-step and one-step method are tested and compared in three sites: Masan Bay, Lake Sihwa, and Nakdong River Estuary. Two-step method uses a linear regression model as the first step that converts nation-wide air temperature into local air temperature, and the corresponding coefficient of determination is in the range of 0.98~0.99. The second step that converts air temperature into water temperature uses a nonlinear curve, so called S-curve, and the corresponding root mean squared error (RMSE) is 2.07 for rising limb in Masan Bay, 1.93 for falling limb in Masan Bay, 2.59 for Lake Sihwa, and 1.58 for Nakdong River Estuary. In a similar way, one-step method is performed to directly convert nation-wade air temperature into local water temperature, and the corresponding RMSE is 2.28 for rising limb in Masan Bay, 1.89 for falling limb in Masan Bay, 2.55 for Lake Sihwa, and 1.52 for Nakdong River Estuary. Consequently both methods show a similar level of performance, and one-step method is recommendable in that it is simple and practical in relative terms.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.822-831
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• 2021

Although programs have been developed to evaluate the risk of dragging anchors, it is practically difficult for VTS(vessel traffic service) operators to calculate and evaluate these risks by obtaining input factors from anchored ships. Therefore, in this study, the gross tonnage (GT) that could be easily obtained from the ship by the VTS operators was set as an independent variable, and linear and nonlinear regression analyses were performed using the input factors as the dependent variables. From comparing the fit of the polynomial model (linear) and power series model (nonlinear), the power series model was evaluated to be more suitable for all input factors in the case of container ships and bulk carriers. However, in the case of tanker ships, the power supply model was suitable for the LBP(length between perpendiculars), width, and draft, and the polynomial model was evaluated to be more suitable for the front wind pressure area, weight of the anchor, equipment number, and height of the hawse pipe from the bottom of the ship. In addition, all other dependent variables, except for the front wind pressure area factor of the tanker ship, showed high degrees of fit with a coefficient of determination (R-squared value) of 0.7 or more. Therefore, among the input factors of the dragging anchor risk assessment program, all factors except the external force, seabed quality, water depth, and amount of anchor chain let out are automatically applied by the regression analysis model formula when only the GT of the ship is provided.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Journal of the Korea Concrete Institute
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• v.24 no.4
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• pp.423-433
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• 2012

The axial load on the concrete-filled steel tube (CFT) column produces confinement stress, which enhances strength of the core concrete. The amount of strength increase in concrete depends on the magnitude of produced confinement stress. From nonlinear analyses, the ultimate resisting capacity of the CFT columns subjected to axial loads was calculated. Nonlinear material properties such as Poisson's ratio and stress-strain relation were considered in the suggested model, and the maximum confining stress was obtained by multi axial yield criteria of the steel tube. This proposed model was verified by comparing the analytical results with experimental results. Then, regression analyses were conducted to predict the maximum confining stress according to D/t ratio and material properties without rigorous structural analysis. To ensure the validity of the suggested regression formula, various empirical formulas and Eurocode4 design code were compared.

• Journal of The Korean Society of Grassland and Forage Science
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• v.11 no.4
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• pp.209-214
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• 1991

The germination of seeds is developmentally complex process requiring water uptake, which is regulated by both genotypic and environmental factors. The present study was undertaken to determine the difference in germination characteristics, and to compare the ability of the logistic and Weibull functions to describe the cumulative germination curve when two levels of osmotic potential(0, -5 bar) were put to seeds of alfalfa, tall fescue, orchardgrass, and Kentucky bluegrass. The effects of grass type, osmotic potential, and their interaction on the total germination and coefficient of germination velocity were significant(P<0.01). The Weibull equation for predicting percent cumulative germination curve of alfalfa had significantly lower residuals than the logistic equation regardless of osmotic potential(P<0.01), indicating that the Weibull equation was more efficient than the logistic equation to fit the data of the percent cumulative germination of alfalfa. The rate parameter from the logistic equation was decreased under water stress, whereas the scale and shape parameters were increased. There were significant differences in days to 20% germination estimated from the logistic and Weibull equations.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.4
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• pp.127-134
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• 2012

This study was carried out to suggest an experimental base in selecting the cold tolerance of plants. The cold tolerance of the plants were subject to laboratory low temperature treatments and cold processing time were evaluated using both electrolyte leakage and regrowth test. The Logistic model of nonlinear regression analysis was used to evaluate the lethal temperatures that were predicted with the range of $-16.1{\sim}-24.4^{\circ}C$. The order of low-temperature resistance was Sedum reflexum > S. spurium > Ophiopogon japonicus > S. album > S. takevimense > Dianthus chinensis. At the lowest temperature of $13.4^{\circ}C$ the electrolyte leakage value of the plants were lower than 50% demonstrating that they could be applied stably to the roof installed in Korea during the winter with the lowest temperature of $-13.5^{\circ}C$.