• Journal of the Society of Naval Architects of Korea
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• v.31 no.4
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• pp.58-65
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• 1994

It is very important to understand characteristics of solution due to the variation of computational grid sizes, especially when turbulence model not incorporating wall-function is used. The present paper performs numerical investigation on the grid dependency of numerical solution for three dimensional turbulent flow field around a ship. In the present study a finite volume method with a modified sub-grid scale turbulence model and a numerically constructed non-orthogonal curvilinear coordinate system capable of conforming complex ship geometries are used. Numerical studies are then performed for a mathematical Wigley hull and the Series 60, $C_B=0.8$ hull forms. The results for various grid sizes are compared with each other and with measured data to show grid dependencies of numerical solutions.

• Convergence Security Journal
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• v.22 no.3
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• pp.79-86
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• 2022

Voice phishing is a cyber crime in which fake financial institutions, the Public Prosecutor's Office, and the National Police Agency are impersonated to find out an individual's Certification number and credit card number or withdraw a deposit. Recently, voice phishing has been carried out in a subtle and secret way. Analyzing the trend of voice phishing that occurred in '18~'21, it was found that there is a seasonality that occurs rapidly at a time when the movement of money is intensifying in the trend of voice phishing, giving ambiguity to time series analysis. In this research, we adjusted seasonality using the X-12 seasonality adjustment methodology for accurate prediction of voice phishing occurrence trends, and predicted the occurrence of voice phishing in 2022 using the ARIMA model.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.150-150
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• 2022

This study investigates the roles of decomposition methods on high accuracy in daily rainfall prediction from light gradient boosting machine (LightGBM) algorithm. Here, empirical mode decomposition (EMD) and singular spectrum analysis (SSA) methods were considered to decompose and reconstruct input time series into trend terms, fluctuating terms, and noise components. The decomposed time series from EMD and SSA methods were used as input data for LightGBM algorithm in two hybrid models, including empirical mode-based light gradient boosting machine (EMDGBM) and singular spectrum analysis-based light gradient boosting machine (SSAGBM), respectively. A total of four parameters (i.e., temperature, humidity, wind speed, and rainfall) at a daily scale from 2003 to 2017 is used as input data for daily rainfall prediction. As results from statistical performance indicators, it indicates that the SSAGBM model shows a better performance than the EMDGBM model and the original LightGBM algorithm with no decomposition methods. It represents that the accuracy of LightGBM algorithm in rainfall prediction was improved with the SSA method when using multivariate dataset.

• Asian Journal of Business Environment
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• v.14 no.3
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• pp.1-11
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• 2024

Purpose: This study analyzes the impact of weather conditions, holidays, and sporting events on beer sales, providing insights for market strategy and inventory management in the beer industry. Research design, data and methodology: Beer types were classified into Lagers and Ales, with further subcategories. The study utilized weekly retail sales data from January 2018 to August 2020, provided by Nielsen Korea. An ARMAX model was employed for time-series analysis. Results: The analysis revealed that increasing temperatures positively influence sales of Pilsners and Pale Lagers. Conversely, higher precipitation levels negatively affect overall Lager sales. Among Ales, only Stout sales showed a significant decrease with increased rainfall. Sunshine duration did not significantly impact sales for any beer type. Humidity generally had little effect on beer sales, with the exception of Amber Lagers, which showed sensitivity to humidity changes. Holidays and sporting events were found to significantly boost sales across most beer types, although the specific impacts varied by beer category. Conclusions: This study offers a detailed analysis of how weather conditions and specific events influence different beer type sales. The findings provide valuable insights for breweries, beer processors, and retailers to optimize their market strategies and inventory management based on weather forecasts and seasonal events. By understanding the consumption patterns of each beer type in relation to environmental factors, businesses can better anticipate demand fluctuations and tailor their operations accordingly.

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.103-122
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• 1992

The objective of this research is to develop a traffic accident forecasting model using traffic accident data in pusan from 1963 to 1991 and then to make short-term forecasts('93~'94) of traffic accidents in pusan. In this research, several forecasting models are developed. They include a multiple regression model, a time-series ARIMA model, a Logistic curve model, and a Gompertz curve model. Among them, the model which shows the most significance in forecasting accuracy is selected as the traffic accident forecasting model. The results of this research are as followings. 1. The existing model such as Smeed model which was developed for foreign countries shows only 47.8% explanation for traffic accident deaths in Korea. 2. A nonliner regression model ($R^2$=0.9432) and a Logistic curve model are appeared to be th gest forecasting models for the number of traffic accidents, and a Logistic curve model shows th most significance in predicting the accident deaths and injuries. 3. The forecasting figures of the traffic accidents in pusan are as followings: . In 1993, 31, 180 accidents are predicted to happen, and 430 persons are predicted to be deaths and 29, 680 persons are predicated to be injuries. . In 1994, 33, 710 accidents are predicted to happen, and 431.persons are predicted to be deat! and 30, 510 persons are predicted to be injuried. Therefore, preventive measures against traffic accidents are certainly required.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.3
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• pp.57-66
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• 1993

This research proposes a high frequency series resonant inverter consisting of equivalent half - bridge model in combination with two L-C linked full-bridge inverter circuits using MOSFET. As a output power control strategy, the sequential gate control method is applied. Also, analysis of operating MODE and state equation is described. From the computer simulation results, the inverters and devices can be shared properly voltage and current rating of the system in accordance with series and parallel operations. And it is confirmed that the proposed system has very stable performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1176-1179
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• 2011

In this paper, design of series-fed microstrip antennas with sum and difference patterns is presented for millimeter-wave applications. The antenna was designed to exhibit high-gain and low side-lobe level(SLL) below -20 dB. A conventional transmission-line model, Taylor and Bayliss distributions were employed to determine current distribution for sum and difference patterns. Moreover, connecting lines between microstrip patches were tuned to achieve an optimized design. The measurement was also performed to validate the designed antennas.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.95-101
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• 2011

This study proposes the accident estimation model developed based on the time-series cross-sectional data at 50 intersections in Cheongju. The data were collected repeatedly and accumulated from 2004 to 2007. This study focused on deriving the optimal among the various models including TSCSREG(Time Series Cross Section Regression). Four different models utilizing various elements affecting accidents were developed. Through a statistical test, it was found that the t values of independent variables of the fixed effect models were less than those of the random effect models. Two variables were then found to be positive to the accidents: the number of crosswalks at an intersection and the number of intersections.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.1
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• pp.87-94
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• 2006

In this paper, we investigated a feasibility of applying highest and lowest temperatures of the next day forecasted from a meteorological observatory to operation of an air-conditioning system with thermal storage. First we investigated specific characteristics of the time series of forecasted temperatures and errors in Osaka from 1994 to 1996. Since the forecast error is not always small, it might be difficult to use the forecasted data without correction for the sizing and the control of the thermal storage system. On the other hand, the autocorrelation functions of the forecast errors decrease relatively slowly during high summer season when cooling thermal storage is required. Since the values of the autocorrelation function; for one day are larger than 0.4, not small, the forecast errors can be predicted by proper statistical analysis. Thus, the forecasted values of the highest temperatures for the next day were improved by using the stochastic time series models.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.139-153
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• 2018

This paper investigates solar power forecasting based on several time series models. First, we consider weather variables that influence forecasting procedures as well as compare forecasting accuracies between time series models such as ARIMAX, Holt-Winters and Artificial Neural Network (ANN) models. The results show that ten models forecasting 24hour data have better performance than single models for 24 hours.