PURPOSES : LED based Variable Message Signs(VMS) have been widely used to inform safety messages to the drivers in advance. Legibility Distance of VMS is the most important factor to provide the safety messages to drivers in timely and effective way. However, current National Standards on legibility distance design considers letter size only even there is a difficulty to read the signs at adverse weather conditions such as heavy fog. So, this study examined the legibility issue under fog by evaluating the legibility distance with two design factors such as letter size and luminance. METHODS : Two foggy weather conditions, intermediate and heavy fog, were simulated at real-road-scale Proving Ground. Legibility distance at daytime and nighttime was evaluated by test subjects. Subjects were asked to fill the legible distance on the test sheet and statistical significant was analysed at the lab. RESULTS : The legibility distance(LD) under fog was observed only 22 to 41% of LD observed under normal weather condition at daytime, and 26 to 45% at nighttime condition. Study results showed a consistent increase in LD with higher luminance even at same letter size and vice versa conditions, However, statically significant difference between groups was only revealed when both letter size and luminance level increased conditions. In order to apply the test results in terms of engineering benefits, LD results from significantly different groups was evaluated with relative to Stopping Sight Distance(SSD) within conceptual frame suggested in this study. CONCLUSIONS : From the study results, current National Standard on legibility distance design needs to consider letter size and luminance simultaneously to response the legibility issue in adverse weather conditions.

국제적인 선박 배출 가스에 대한 환경 규제가 점차 강화됨에 따라 전기추진 및 하이브리드 추진선박에 대한 관심이 증대되고 있으며, 이러한 선박에 적용하기 위한 다양한 솔루션이 개발 및 적용되고 있는데 특히 전력계통의 안정화, 시스템의 효율성을 높이기 위 한 방안으로 직류배전시스템이 적용되고 있다. 또한, 선박용 직류배전시스템에 대한 안전 및 성능에 대한 검증 및 시험의 중요성이 요구 되고 있다. 본 연구는 직류배전 테스트베드 구축 및 직류배전(가변속 발전)시스템에 대한 성능을 검증하고 연료소모량 분석한 결과로서 선박용 직류배전에 적용되고 있는 가변속 발전시스템을 적용하였으며, 발전기에서 출력되는 전력을 정류기를 통해 직류전력으로 변환하 여 시스템에 연계하고 이러한 장치들을 감시 및 제어하기 위한 시스템을 개발하였다. 이러한 직류배전 시스템을 적용한 시험을 통해 최 대 전압은 751.5V이고 최소전압은 731.4V가 계측되어 전압변동률은 2.7%로 3% 이내에서 안정적으로 전압이 공급되는 것을 확인하였고 부 하변동에 따라 가변속 발전시스템을 적용하였을 경우 연료소모량이 기존 정속발전시스템과 비교하여 구간에 따라 최대 20%이상 연료절 감이 되는 것을 시험을 통해 확인하였다.

The global power generation industry is becoming a key power generation industry with gas power generation and renewable energy solar power generation. This research aims to focus on solving two problems as a method to improve the solar light collection efficiency among fixed variable deformation methods. Maintaining the proper temperature of the water injection device through automatic temperature detection to solve efficiency degradation, and establishing an automatic operation system by finding the optimal angle for each season, are intended to derive a value that can represent the optimal power generation.

It is getting more intensified with the competition among participating companies for global market share in major industrial fields. The situation is accelerating especially within the top 5 market share, and these include electric vehicles, semiconductors, chemicals, and shipbuilding industries. The key to the advantage over the competition within a strategic group is which company leads the innovation in the field. On-the-ground innovation refers to job-based innovation. This paper aims to analyze job unit innovation in the structure of empowerment, LMX, and job crafting. Existing studies on job crafting have suggested a causal structure based on job design in the traditional sense, and there are not many scholars who study the causal structure using a job situational model. Therefore, this paper takes an approach from the perspective of the job situation. As a result of the study, LMX showed a moderating effect on the relationship between autonomy provision and job crafting. While, in the relationship between meaing-giving and cognitive crafting, there is no significant moderating effect shown on the relationship between autonomy provision and cognitive crafting. Therefore, the results of the analysis in this study suggest that the meaning of jobs and participation in decision-making should be managed in an integrated way in structural and design areas, not just qualitative factors such as empowerment and leadership.

Algal bloom is an ongoing issue in the management of freshwater systems for drinking water supply, and the chlorophyll-a concentration is commonly used to represent the status of algal bloom. Thus, the prediction of chlorophyll-a concentration is essential for the proper management of water quality. However, the chlorophyll-a concentration is affected by various water quality and environmental factors, so the prediction of its concentration is not an easy task. In recent years, many advanced machine learning algorithms have increasingly been used for the development of surrogate models to prediction the chlorophyll-a concentration in freshwater systems such as rivers or reservoirs. This study used a light gradient boosting machine(LightGBM), a gradient boosting decision tree algorithm, to develop an ensemble machine learning model to predict chlorophyll-a concentration. The field water quality data observed at Daecheong Lake, obtained from the real-time water information system in Korea, were used for the development of the model. The data include temperature, pH, electric conductivity, dissolved oxygen, total organic carbon, total nitrogen, total phosphorus, and chlorophyll-a. First, a LightGBM model was developed to predict the chlorophyll-a concentration by using the other seven items as independent input variables. Second, the time-lagged values of all the input variables were added as input variables to understand the effect of time lag of input variables on model performance. The time lag (i) ranges from 1 to 50 days. The model performance was evaluated using three indices, root mean squared error-observation standard deviation ration (RSR), Nash-Sutcliffe coefficient of efficiency (NSE) and mean absolute error (MAE). The model showed the best performance by adding a dataset with a one-day time lag (i=1) where RSR, NSE, and MAE were 0.359, 0.871 and 1.510, respectively. The improvement of model performance was observed when a dataset with a time lag up of about 15 days (i=15) was added.

As a nation experiencing rapid economic growth, South Korea and its government have made a continuous effort toward efficient research investments to achieve transformation of the Korean industry for the fourth industrial revolution. To achieve the maximum effectiveness of the research investments, it is necessary to evaluate its funding’s worth and default risk. Thus, incorporating the concepts of the Black-Scholes-Merton model and the Greeks, this study develops a default-risk evaluation model in the foundation of a system dynamics methodology. By utilizing the proposed model, this study estimates the monetary worth and the default risks of research funding in the public and private sectors of Information and Communication technologies, along with the sensitivity of the R&D economic worth of research funding to changes in a given parameter. This study finds that the public sector has more potential than the private sector in terms of monetary worth and that the default risks of three types of research funding are relatively high. Through a sensitivity analysis, the results indicate that uncertainty in volatility, operation period, and a risk-free interest rate has trivial impacts on the monetary worth of research funding, while volatility has large impacts on the default risk among the uncertain factors.

확률론적 지진취약도 평가는 구조물 혹은 기기의 손상확률을 각 취약도 변수별 조합을 통해 이루어진다. 지진취약도로부터 구해지는 2개 이상 기기의 동시손상확률 계산은 기존에는 각 기기의 손상확률을 독립으로 가정해왔다. 하지만 기기별 손상확률에 상관성이 있으며, 이를 평가한 결과 상관성에 따라 동시손상확률이 변화할 수 있는 결과를 보였다. 이 지진상관성을 무시하면 비보수적인 결과가 나오고 따라서 이를 고려해서 계산되어야 한다. 이 연구에서는 지진상관계수를 해석적으로 평가하기 위해 몇 가지 확률 변수를 선정하여 각 변수별로 혹은 통합하여 평가하고 그 차이를 비교했다. 그리고 단순화된 모델과, 복잡한 모델에 대한 상관계수 차이도 비교 하였다. 이들 방법에 따른 상관계수의 결과와 차이를 분석했다. 그 결과 각 변수별로 평가하는 것과 통합하여 평가할 때 변수별 영향의 차이에 따라 상관성이 변화함을 확인하였고, 모델이 단순할수록 상관성이 높아짐을 확인하였다.

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

그동안 북한선교는 통일 담론에 휘둘려 제대로 된 선교전략을 세울 수 없었고, 혼재된 대북 관계와 북미 관계로 인해 이행할 수도 없었다. 북한선교는 자체의 정체성(일명: 상수)을 재정립하고 정치적 과제(일명: 변수)와 연관되지 않아야 가능하다. 북한선교의 변하지 않는 상수의 선교정체성과 변하는 변수의 배경을 분리해야 하는 것이 다. 그러면 비로소 통일 이전과 이후의 북한선교의 전략적 정책이 수립될 수 있을 것이다. 북한선교의 통일 이전의 전략은 복음의 직접 사역과 비즈니스 선교전략이다. 통일 이후에는 관계성을 중심으로 한 민족복음화 선교전략으로 이어져야 한다. 통일 이전과 이후에도 북한선교는 여전히 양 교회 간의 갈등과 대립, 오해와 비난 등으로 상당한 문제가 야기될 것이다. 통일 이후 북한선교는 민족복음화를 변곡점으로 해서 시작될 것이다.