• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.415-421
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• 2023

In this study, the piezoresistive properties of cementitious composites enhanced with carbon nanotubes for improved electrical conductivity were analyzed using a deep learning-based transformer algorithm. Experimental execution was performed in parallel for acquisition of training data. Previous studies on mixture design, specimen fabrication, chemical composition analysis, and piezoresistive performance testing are also reviewed in this paper. Notably, specimens in which fly ash substituted 50% of the binder material were fabricated and evaluated in this study, in addition to carbon nanotube-infused specimens, thereby exploring the potential enhancement of piezoresistive characteristics in conductive cementitious materials. The experimental results showed more stable piezoresistive responses in specimens with fly-ash substituted binder. The transformer model was trained using 80% of the gathered data, with the remaining 20% employed for validation. The analytical outcomes were generally consistent with empirical measurements, yielding an average absolute error and root mean square error between 0.069 to 0.074 and 0.124 to 0.132, respectively.

• Korean Journal of Community Nutrition
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• v.1 no.3
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• pp.376-394
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• 1996

This study evaluated the reproducibility and validity of the self-administered semiquantitative food frequency questionnaire used in a large prospective cohort study(Korean Cancer Research Survey) in middle-aged men. The questionnaire was administered twice at an interval of approximately two years(December, 1992-January, 1995), and four or five 24-hour recalls for each subject were collected at intervals of approximately three months. The results were as follows; 1) Although the distributions of the data estimated by the questionnaire were somewhat wider, the mean nutrient intakes of group estimated by our questionnaires and the multiple 24-hour recalls were roughly comparable. 2) The reproducibility determined by correlation of absolute(unadjusted nutrient intake) and calorie adjusted nutrient intakes from two semiquantitative food frequency questionnaires were more than 0.5, and the weighted kappa values were more than 0.4. 3) The Pearson correlation coefficients between unadjusted nutrient intakes values were average 0.40 on the average(Ca, 0.13-Carbohydrate, 0.58) at the first questionnaire vs. 24-hour recalls, and 0.28 at the second questionnaire vs. 24-hour recalls. The spearman rank order correlation coefficients were similar. When energy intake was adjusted, there was a slight reduction : 0.28 at the second questionnaire, 0.25 average on the second. In order to correct the measurement error of 24-hour recall data, the deattenuated correlation coefficient was calculated. It averaged 0.53 on the first questionnaire, 0.37 on the second questionnaire for unadjusted nutrient intake. for calorie-adjusted nutrient intake, it averaged 0.44 on the first questionnaire, 0.37 on the second questionnarie. 4) There was lower agreement(k<0.4) between the questionnaries and the 24-hour recalls. And the subjects classified in the same quartile by 24-hour recalls and first questionnaire were average 37$\%$(energy-adjusted values) and 40$\%$(unadjusted values) on the average. More than k10$\%$(average) of subjects were in the extreme quartile of the questionnarie and 24-hour recall method. But 8.2$\%$(average) of subjects classified in the lowest quartile of unadjusted nutrient intake level by the 24-hour recalls were in the highest quartile by the first questionnaire. These data indicate that our self-administered semiquantitative food frequency questionnarie is reproducible. Correlation coefficients comparing nutrient intakes measured by two different dietary assessment methods were less than 0.5. The validity of our questionnarie is not high enough.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.256-267
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• 2015

The intelligent transportation systems allow us to have valuable opportunities for collecting wide-area coverage traffic data. The significant efforts have been made in many countries to provide the reliable traffic conditions information such as travel time. This study analyzes the impacts of the fog weather conditions on the traffic stream. Also, a strategy for predicting the long-term traffic speeds is developed under foggy weather conditions. The results show that the average of speed reductions are 2.92kph and 5.36kph under the slight and heavy fog respectively. The best prediction performance is achieved when the previous 45 pattern cases data is used, and the 14.11% of mean absolute percentage error(MAPE) is obtained. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.171-181
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• 2006

The Wald confidence interval has been considered as a standard method for the difference of proportions. However, the erratic behavior of the coverage probability of the Wald confidence interval is recognized in various literatures. Various alternatives have been proposed. Among them, Agresti-Caffo confidence interval has gained the reputation because of its simplicity and fairly good performance in terms of coverage probability. It is known however, that the Agresti-Caffo confidence interval is conservative. In this note, a confidence interval is developed using the weighted Polya posterior which was employed to obtain a confidence interval for the binomial proportion in Lee(2005). The resulting confidence interval is simple and effective in various respects such as the closeness of the average coverage probability to the nominal confidence level, the average expected length and the mean absolute error of the coverage probability. Practically it can be used for the interval estimation of the difference of proportions for any sample sizes and parameter values.

• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Fire Science and Engineering
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• v.18 no.3
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• pp.30-38
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• 2004

An important characteristics during fire growth is the phenomena of flashover, which is the transition from the local combustion to the full-room fire. The aim of this study is to predict the flashover times, the ignition times and HRR(heat release rate) of flashover for building interior materials. By using the literature data and RSM(response surface methodology), the new equations for predicting the flashover time, the ignition time and the HRR of building interior materials are proposed. The A.A.P.E.(average absolute percent error) and the A.A.D.(average absolute deviation) of the reported and the calculated flashover times were 38.74sec and 51.24sec respectively, and the correlation coefficient was 0.975. The A.A.P.E and the A.A.D of the reported and the calculated ignition times were 10.96sec and 1.97sec, and the correlation coefficient was 0.962. Also the A.A.P.E and the A.A.D. of the reported and the calculated the HRR of flashover by means of times were 29.92 and 514, and the correlation coefficient was 0.830. The values calculated by the proposed equations were in good agreement with the literature data. Therefore, it is expected that this proposed equations will support the use of the research for other building interior materials.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Progress in Medical Physics
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• v.16 no.4
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• pp.166-175
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• 2005

The purpose of this study is to develop the optimization method for adjusting the film isocenter shift and to suggest the quantitative acceptable criteria for film dosimetry after optimization In the dynamic conformal arc radiation therapy (DCAR). The DCAR planning was peformed In 7 patients with brain metastasis. Both absolute dosimetry with ion chamber and relative film dosimetry were peformed throughout the DCAR using BrainLab's micro-multileaf collimator. An optimization method for obtaining the global minimum was used to adjust for the error in the film isocenter shift, which is the largest pan of systemic errors. The mean of point dose difference between measured value using ion chamber and calculated value acquired from planning system was $0.51{\pm}0.43\%$ and maximum was $1.14\%$ with absolute dosimetry These results were within the AAPM criteria of below $5\%$. The translation values of film isocenter shift with optimization were within ${\pm}$1 mm in all patients. The mean of average dose difference before and after optimization was $1.70{\pm}0.35\%$ and $1.34{\pm}0.20\%$, respectively, and the mean ratios over $5\%$ dose difference was $4.54{\pm}3.94\%$ and $0.11{\pm}0.12\%$, respectively. After optimization, the dose differences decreased dramatically and a ratio over $5\%$ dose difference and average dose difference was less than $2\%$. This optimization method is effective in adjusting the error of the film isocenter shift, which Is the largest part of systemic errors, and the results of this research suggested the quantitative acceptable criteria could be accurate and useful in clinical application of dosimetric verification using film dosimetry as follows; film isocenter shift with optimization should be within ${\pm}$1 mm, and a ratio over $5\%$ dose difference and average dose difference were less than $2\%$.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.2
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• pp.143-149
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• 1996

Forecasts of the monthly catches of anchovy in Korea were carried out by the seasonal Autoregressive Integrated Moving Average (ARIMA) model and spectral analysis. The seasonal ARIMA model is as follows: $$(1-0.431B)(1-B^{12})Z_t=(1-0.882B^{12})e_t$$ where: $Z_t=value$ at month $t;\;B^{p}$ is a backward shift operator, that is, $B^pZ_t=Z_{t-p};$ and $e_t=error$ term at month t, which is to forecast 24 months ahead the anchovy catches in Korea. The prediction error by the Box-Cox transformation on monthly anchovy catches in Korea was less than that by the logarithmic transformation. The equation of the Box-Cox transformation was $Y'=(Y^{0.58}-1)/0.58$. Forecasts of the monthly anchovy catches for $1991\~1992$, which were compared with the actual catches, had an absolute percentage error (APE) range of $1.0\~63.2\%$. Total observed annual catches in 1991 and 1992 were 170,293 M/T and 168,234 M/T respectively, while the predicted catches were 148,201 M/T and 148,834 M/T $(API\;13.0\%\;and\;11.5\%,\;respectively)$. The spectrum analysis of the monthly catches of anchovy showed some dominant fluctuations in the periods of 2.2, 6.1, 10.2 12.0 and 14.7 months. The spectrum analysis was also useful for selecting the ARIMA model.