• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.319-331
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• 2022

In this paper, we develop a new statistical model to forecast the PM_2.5 level in Seoul, South Korea. The proposed model is based on the extreme quantile regression model with lasso penalty. Various meteorological variables and air pollution variables are considered as predictors in the regression model, and the lasso quantile regression performs variable selection and solves the multicollinearity problem. The final prediction model is obtained by combining various extreme lasso quantile regression estimators and we construct a binary classifier based on the model. Prediction performance is evaluated through the statistical measures of the performance of a binary classification test. We observe that the proposed method works better compared to the other classification methods, and predicts 'very bad' cases of the PM_2.5 level well.

• Journal of Korean Academy of Nursing Administration
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• v.5 no.2
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• pp.237-251
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• 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.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.375-377
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• 2006

This paper presents a method to calculate generation power for integrating Sihwa tidal power into power systems. The sea levels of 1 minute interval using cubic interpolation based on the forecasted levels of high and low water offered from Nori(National Oceanographic Research Institute) are calculated. If the sea level is greater than the lake level and the difference between sea level and lake level at high tide is over the default value, it begins to calculate the tidal power. It is seen that tidal power can supply power to demand side stably and economically from assessment of effect for integrating tidal power into power systems.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.133-135
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• 2012

The Fire growth rate(kW/s²) is significant impact on initial fire behavior in fire safety design of buildings. As a result of domestic existing combustibles, this study analyzed considering matters in techniques for calculating caloric values, and then made an investigation sheet. By utilizing written combustion sheets, the study could suggest a standard model at common houses and dense ones after getting caloric value information in dense ones. As a result, fire growth rate is experiment 1(0.01), experiment 2(0.0048), FDS(0.0072), MATSUYAMA equation(0.0144).

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.39-57
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• 2021

Time series prediction is an area of great interest to many people. Algorithms for time series prediction are widely used in many fields such as stock price, temperature, energy and weather forecast; in addtion, classical models as well as recurrent neural networks (RNNs) have been actively developed. After introducing the attention mechanism to neural network models, many new models with improved performance have been developed; in addition, models using attention twice have also recently been proposed, resulting in further performance improvements. In this paper, we consider time series prediction by introducing attention twice to an RNN model. The proposed model is a method that introduces H-attention and T-attention for output value and time step information to select useful information. We conduct experiments on stock price, temperature and energy data and confirm that the proposed model outperforms existing models.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.139-169
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• 2009

This paper introduces the modified VaR which takes into account the asymmetry and fat-tails of financial asset distribution, and then compares its out-of-sample forecast performance with traditional VaR model such as historical simulation model and Riskmetrics. The empirical tests using stock indices of 6 countries showed that the modified VaR has the best forecast accuracy. At the test of independence, Riskmetrics and GARCH model showed best performances, but the independence was not rejected for the modified VaR. The Monte Carlo simulation using skew t distribution again proved the best forecast performance of the modified VaR. One of many advantages of the modified VaR is that it is appropriate for measuring VaR of the portfolio, because it can reflect not only the linear relationship but also the nonlinear relationship between individual assets of the portfolio through coskewness and cokurtosis. The empirical analysis about decomposing VaR of the portfolio of 6 stock indices confirmed that the component VaR is very useful for the re-allocation of component assets to achieve higher Sharpe ratio and the active risk management.

• Applied Biological Chemistry
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• v.47 no.2
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• pp.157-163
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• 2004

The study was designed to forecast and derive future core technologies using Delphi method in Korea. The technologies will make agriculture for core and strategic industry that. has high value-added in 21 century. The target of the survey for Delphi is confined specialists in the area of processing.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.572-583
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• 2019

In this study, the atmospheric vertical structure (AVS) associated with summertime (June, July, and August) heavy rainfall in Seoul was classified into three patterns (Loaded Gun: L, Inverted V: IV, and Thin Tube: TT) using rawinsonde soundings launched at Osan from 2009 to 2018. The characteristics of classified AVS and precipitation property were analyzed. Occurrence frequencies in each type were 34.7% (TT-type), 20.4% (IV-type), 20.4% (LG-type), and 24.5% (Other-type), respectively. The mean value of Convective Available Potential Energy (1131.1 J kg^-1) for LG-types and Storm Relative Helicity (357.6 ㎡s^-2) for TT-types was about 2 times higher than that of other types, which seems to be the difference in the mechanism of convection at the low level atmosphere. The composited synoptic fields in all cases showed a pattern that warm and humid southwesterly wind flows into the Korean Peninsula. In the cases of TT-type, the low pressure center (at 850 hPa) was followed by the trough in upper-level (at 500 hPa) as the typical pattern of a low pressure deepening. The TT-type was strongly influenced by the low level jet (at 850 hPa), showing a pattern of connecting the upper- and low-level jets. The result of analysis indicated that precipitation was intensified in the first half of all types. IV-type precipitation induced by thermal instability tended to last for a short term period with strong precipitation intensity, while TT-type by mechanical instability showed weak precipitation over a long term period.

• Management & Information Systems Review
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• v.36 no.3
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• pp.151-165
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• 2017

This study investigates the effect of revenue recognition by percentage of completion method on financial analysts' earnings forecasting information in order industry. Specifically, we examines how the analysts' earnings forecast errors and biases differ according to whether or not to report the unbilled revenue account balance and the level of unbilled revenue account balance. The sample consists of 453 firm-years listed in Korea Stock Exchange during the period from 2010 to 2014 since the information on unbilled revenue accounts can be obtained after the adoption of K-IFRS. The results are as follows. First, we find that the firms with unbilled revenue account balances have lower analysts' earnings forecast accuracy than the firms who do not report unbilled revue account balances. In addition, we find that the accuracy of analysts' earnings forecasts decreases as the amount of unbilled revenue increases. Unbilled revenue account balances occur when the revenue recognition of the contractor is faster than the client. There is a possibility that managerial discretionary judgment and estimation may intervene when the contractor calculates the progress rate. The difference between the actual progress of the construction and the progress recognized by the company lowers the predictive value of financial statements. Our results suggest that the analysts' earnings forecasts may be more difficult for the firms that report unbilled revenue balances as applying the revenue recognition method based on the progress criteria. Second, we find that the firms reporting unbilled revenue account balances tend to have higher the optimistic biases in analysts' earnings forecast than the firms who do not report unbilled revenue account balances. And we find that the analysts' earnings forecast biases are increases as the amount of unbilled revenue increases. This study suggests an effort to reduce the arbitrary adjustment and estimation in the measurement of the progress as well as the introduction of the progress measurement method which can reflect the actual progress. Investors are encouraged to invest and analyze the characteristics of the order-based industry accounting standards. In addition, the results of this study empower the accounting transparency enhancement plan for order industry proposed by the policy authorities.

• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.31-61
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• 2013

The purpose of this study is to calculate the economic value of transport demand forecasting risks in the road PPP project. Under the assumption that volatility of the road PPP project value occurs only in regard with uncertainty of traffic volume forecasting, this study calculates the economic value of the traffic forecasting risks in the case of the road PPP project. To that end, forecasted traffic volume is assumed to be a stochastic variable and to follow the Geometric Brownian motion as time passes. In particular, this study attempts to differentiate itself from existing studies that simply use an arbitrary assumption by presenting the application of different traffic volume growth volatility and the rates before and after the ramp-up period. Analysis of the case projects reveals that the risk premium related to traffic volume forecast of the project turns out as 7.39~8.30%, without considering option value-such as minimum revenue guarantee-while the project value volatility caused by transport demand forecasting risks is 17.11%. As the discount rate grows higher, the project value volatility tends to decrease and volatility in project value is always suggested to be larger than that in transport volume influenced by leverage effect due to fixed expenditure. The market value of transport demand forecasting risk-calculated using the project value volatility and risk premium-is analyzed to be between 0.42~0.50, implying that a 1% increase or decrease in the transport amount volatility would lead to a 0.42~0.50% increase or decrease in risk premium of the project.