Based on a previous literature about hospital capital structure(Shyam- Sunder & Myers, 1999), this study attempted comparison and analysis on whether the forecast of trade-off and pecking order theory could be validated in hospital's capital structure. First, this study analyzed whether hospitals follow the priority for each capital source as suggested by pecking order theory under lack of capital running in hospital. Next, it analyzed whether debt level is regressed on the average to target debt level so as to verify the validity of trade-off theory. Finally, it also analyzed possible associations between debt level and determinants of capital structure as adopted in static trade-off theory, so as to verify relative advantages of these two theories about hospital capital structure. The analysis over whole period showed that both trade-off theory and pecking order theory isn't supported particularly. This mean that each hospital's financing behaviors is different and that has not dominant financing behaviors. In the midst of separation of dispensary from medical practice, medical institutions in Korea first finances funds required using retained earnings and then use liabilities. however pecking order theory is supported, the preference of long-term liabilities and short-term liabilities is not clear. In addition, considering that debt level is in no average regression to target debt ratio, it is found that hospital capital structure following trade-off theory turns into that subject to pecking order theory via the separation of dispensary from medical practice.
The model using time series data can be considered as a flood forecasting model of a small river due to its efficiency for model development and the advantage of rapid simulation for securing predicted time when reliable data are obtained. Transfer Function Noise (TFN) model has been applied hourly flood forecast in Italy, and UK since 1970s, while it has mainly been used for long-term simulations in daily or monthly basis in Korea. Recently, accumulating hydrological data with good quality have made it possible to simulate hourly flood prediction. The purpose of this study is to assess the TFN model applicability that can reflect exogenous variables by combining dynamic system and error term to reduce prediction error for tributary rivers. TFN model with hourly data had better results than result from Storage Function Model (SFM), according to the flood events. And it is expected to expand to similar sized streams in the future.
There has been increasing offshore oil exploration, drilling, and production activities, as well as a huge amount of petroleum being transported by tankers and pipelines through the ocean and costal environment. Assessment must be made of the potential risk of damage resulting from the exploration, development and transportation activities. This is achieved through predictive impact evaluations of the fate of hypothetical or real oil spills. VVhen an oil spill occurs, planning and execution of cleanup measures also require the capability to forecast the short-term and long-term behavior of the spilled oil. A great amount of effort has been spent by government agencies, oil industries, and researchers over the past decade to develop more realistic models for oil spills. Numerous oil spill models have been developed and applied, most of which attempt to predict the oil spill fate and behavior. For an actual contingency planning, the oil fate and behavior model should be combined with an oil spill incident model, an environmental impact and risk model and a contingency planning model. The purpose of this review study is to give an overview of existing oil spill models that deal with the physical, chemical, biological, and socia-economical aspects of the incident, fate, and environmental impact of oil spills. After reviewing the existing models, future research needs are suggested. In the study, available oil spill models are separated into oil spill incident, oil spill fate and behavior, environmental impact and risk, and contingency planning models. The processes of the oil spill fate and behavior are reviewed in detail and the characteristics of existing oil spill fate and behavior models are examined and classified so that an ideal model may be identified. Finally, future research needs are discussed.
This paper develops a model to forecast container volumes of all Korean seaports using a Seasonal ARIMA (Autoregressive Integrated Moving Average) technique with the quarterly data from the year of 1994 to 2010. In order to verify forecasting accuracy of the SARIMA model, this paper compares the predicted volumes resulted from the SARIMA model with the actual volumes. Also, the forecasted volumes of the SARIMA model is compared to those of an ARIMA model to demonstrate the superiority as a forecasting model. The results showed the SARIMA Model has a high level of forecasting accuracy and is superior to the ARIMA model in terms of estimation accuracy. Most of the previous research regarding the container-volume forecasting of seaports have been focussed on long-term forecasting with mainly monthly and yearly volume data. Therefore, this paper suggests a new methodology that forecasts shot-term demand with quarterly container volumes and demonstrates the superiority of the SARIMA model as a forecasting methodology.
Kim, Eunyoung;Jeon, Seong-Woo;Lee, Jung-Won;Park, Yong-Ha;Lee, Dong-Kun
Journal of Environmental Impact Assessment
/
v.21
no.1
/
pp.71-80
/
2012
Against the backdrop of the clear impact of climate change, it has become essential to analyze the influence of climate change and relevant vulnerabilities. This research involved evaluating the impact of heat waves in Seoul, from among many local autonomous bodies that are responsible for implementing measures on adapting to climate change. To carry out the evaluation, the A1B scenario was used to forecast future temperature levels. Future climate scenario results were downscaled to $1km{\times}1km$ to result in the incorporation of regional characteristics. In assessing the influence of heat waves on people-especially the excess mortality-we analyzed critical temperature levels that affect excess mortality and came up with the excess mortality. Results of this evaluation on the impact of climate change and vulnerabilities indicate that the number of days on which the daily average temperature reaches $28.1^{\circ}C$-the critical temperature for excess mortality-in Seoul will sharply increase in the 2050s and 2090s. The highest level of impact will be in the month of August. The most affected areas in the summer will be Songpa-gu, Gangnam-gu, and Yeongdeungpo-gu. These areas have a high concentration of residences which means that heat island effects are one of the reasons for the high level of impact. The excess mortality from heat waves is expected to be at least five times the current figure in 2090. Adaptation plan needs to be made on drawing up long-term adaptation measures as well as implementing short-term measures to minimize or adapt the impact of climate change.
Korean Journal of Agricultural and Forest Meteorology
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v.4
no.3
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pp.133-140
/
2002
Site-specific minimum temperature forecasts are critical in a short-term decision making procedure for preventive measures as well as a long-term strategy such as site selection in fruits industry. Nocturnal cold air pools frequently termed in mountainous areas under anticyclonic systems are very dangerous to the flowering buds in spring over Korea, but the spatial resolution to detect them exceeds the current weather forecast scale. To supplement the insufficient spatial resolution of official forecasts, we developed a GIS - assisted frost risk assesment scheme for using in mountainous areas. Daily minimum temperature data were obtained from 6 sites located in a 2.1 by 2.1 km area with complex topography near the southern edge of Sobaek mountains during radiative cooling nights in spring 2001. A digital elevation model with a 10 m spatial resolution was prepared for the entire study area and the cold air inflow was simulated for each grid cell by counting the number of surrounding cells coming into the processing cell. Primitive temperature surfaces were prepared for the corresponding dates by interpolating the Korea Meteorological Administration's automated observational data with the lapse rate correction. The cell temperature values corresponding to the 6 observation sites were extracted from the primitive temperature surface, and subtracted from the observed values to obtain the estimation error. The errors were regressed to the flow accumulation at the corresponding cells, delineating a statistically significant relationship. When we applied this relationship to the primitive temperature surfaces of frost nights during April 2002, there was a good agreement with the observations, showing a feasibility of site-specific frost warning system development in mountainous areas.
Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.
For power energy, optimal generation and distribution plans based on accurate demand forecasts are necessary because it is not recoverable after they have been delivered to users through power generation and transmission processes. Failure to predict power demand can cause various social and economic problems, such as a massive power outage in September 2011. In previous studies on forecasting power demand, ARIMA, neural network models, and other methods were developed. However, limitations such as the use of the national average ambient air temperature and the application of uniform criteria to distinguish seasonality are causing distortion of data or performance degradation of the predictive model. In order to improve the performance of the power demand prediction model, we divided Korea into five major regions, and the power demand prediction model of the linear regression model and the neural network model were developed, reflecting seasonal characteristics through regional characteristics and migration period learning techniques. With the proposed approach, it seems possible to forecast the future demand in short term as well as in long term. Also, it is possible to consider various events and exceptional cases during a certain period.
Journal of Korean Academy of Nursing Administration
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v.5
no.2
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pp.237-251
/
1999
The purpose of this study is to suggest successful strategies through which the effect of the information system of a hospital can be forecasted at the nursing department. In order to set up successful strategies, in the first place, both the methods of CSF(Critical Success Factor: Rockart, 1979) and ULD(User-Led Development) method and the method suggested by the Korea Productivity Center were applied. In order to measure the improvement of nursing productivity, the Dissonance theory was used. The data were collected from 100 employees serving at the clinic department of Kwangju Patriots' and Veterans' Hospital from July 4 to July 25, 1998 with reference to all 222 cases, for sampling work; then the part of the efficiency of the treatment or management of hospital business - simplification of the process of the treatment of hospital business and reduction of the time of the treatment of hospital business were measured; and in order to forecast organizational behavior, 100 cases of organization behavior were analysed, based on the well structured, questionnaires. In order to forecast the user's organizational behavior, a tool(Ronald. 1988; Stephen, 1982: Senn, 1992: Olsen, 1980: Anderson, 1988: Kim. 1992: Cho. 1994) to measure the extent or degree of the user's recognition or understanding whose reliability coefficient is 0.63 was used: and regarding the items expected by the users concerning the convenience of the system, a tool created by Bernadett, Szajna and Richard W. Scamell(1993) whose reliability coefficient is 0.88 was used. And finally, those data were analysed, utilizing the statistical package of SPSS/PC 6.0. successful strategies are suggested as follows: 1. In order that the Kwangju Patriots' and Veterans' Hospital's purpose can be successful through its strategic, information system, the quality of its services should be elevated. and for elevating the quality of medical services, elevation of the quality of medical expertism or specialty is an important factor in determining such quality. 2. In order to make the hospital information system to be successful, the hospital's top manager should participate in the effort making it successful with helping hands of the members or personnel of the hospital. 3. In order to make users participate in the hospital information system, it is prerequisite that all nurses in a hospital should voluntarily participate in the system 4. In order to reduce the expense, the time in coping with business per duty should be reduced by 10${\sim}$33.23%. The time of the direct nursing care which added value is relatively high should be elongated in order to elevate the quality of hospital services. 5. Since the introduction and spread of the hospital information system are influenced by the duration in the experience of computer use, the user of the hospital information system should have a plan to receive well-planned computer education. Finally it is suggested that the forecast of long-term productivity through a review of the user's expectation of the system should be inspected and tested through continuous studies of its effectiveness.
Lim, Myeong Soon;Moon, Il-Ju;Cha, Yu-Mi;Chang, Ki-Ho;Kang, Ki-Ryong;Byun, Kun Young;Shin, Do-Shick;Kim, Ji Young
Atmosphere
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v.24
no.3
/
pp.283-301
/
2014
In 2010, only 14 tropical cyclones (TCs) were generated over the western North Pacific (WNP), which was the smallest since 1951. This study summarizes characteristics of TCs generated in 2010 over the WNP and investigates the causes of the record-breaking TC genesis. A long-term variation of TC activity in the WNP and verification of official track forecast in 2010 are also examined. Monthly tropical sea surface temperature (SST) anomaly data reveal that El Ni$\tilde{n}$o/Southern Oscillation (ENSO) event in 2010 was shifted from El Ni$\tilde{n}$o to La Ni$\tilde{n}$a in June and the La Ni$\tilde{n}$a event was strong and continued to the end of the year. We found that these tropical environments leaded to unfavorable conditions for TC formation at main TC development area prior to May and at tropics east of $140^{\circ}E$ during summer mostly due to low SST, weak convection, and strong vertical wind shear in those areas. The similar ENSO event (in shifting time and La Ni$\tilde{n}$a intensity) also occurred in 1998, which was the second smallest TC genesis year (16 TCs) since 1951. The common point of the two years suggests that the ENSO episode shifting from El Ni$\tilde{n}$o to strong La Ni$\tilde{n}$a in summer leads to extremely low TC genesis during La Ni$\tilde{n}$a although more samples are needed for confidence. In 2010, three TCs, DIANMU (1004), KOMPASU (1007) and MALOU (1009), influenced the Korean Peninsula (KP) in spite of low total TC genesis. These TCs were all generated at high latitude above $20^{\circ}N$ and arrived over the KP in short time. Among them, KOMPASU (1007) brought the most serious damage to the KP due to strong wind. For 14 TCs in 2010, mean official track forecast error of the Korea Meteorological Administration (KMA) for 48 hours was 215 km, which was the highest among other foreign agencies although the errors are generally decreasing for last 10 years, suggesting that more efforts are needed to improve the forecast skill.
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