• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6391-6396
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• 2015

Background: To analyze cervical cancer mortality trends in China from 1991-2013 and forecast the mortality distribution in future five years (2014-2018), and provide clues for prevention and treatment. Materials and Methods: Mortality data for cervical cancer in China from 1991 to 2013 were used to describe the epidemiological characteristics and distribution, including the trend of the standardized mortality rate, urban-rural differences, and age variation. Trend-surface analysis was used to analyze the geographical distribution of mortality. Curve estimation, time series, gray modeling, and joinpoint regression were performed to predict and forecast mortality trends. Results: In recent years, the mortality rate of cervical cancer has increased, and there is also a steady increase in the incidence from 2003 to 2013 in China. Mortality rates in rural areas are higher than in urban areas. The mortality dramatically increases in the 40+ yr age group, reaching a peak in the >85 yr age group. In addition, geographical analysis showed that the cervical cancer mortality increased from the southwest to west-central and from the southeast to northeast of the country. Conclusions: The incidence rate and the mortality rate are increasing from 1991 to 2013, and the predictions show this will continue in the future. Thus, implementation of prevention and management programs for cervical cancer are necessary in China, especially for rural areas, young women in urban areas, and high risk regions (the west-central).

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1141-1148
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• 2013

End-uses of household water have been influenced by a housing type, life style and housing area which are considered as internal factors. Also, there are external factors such as water rate, weather and water supply facilities. Analysis of influential factors on water consumption in households would give an explanation on the cause of changing trends and would help predicting the water demand of end-use in household. In this paper, we used real data to predict toilet and laundry water-uses and utilized the linear regression model with autoregressive errors. The results showed that the monthly autoregressive error models explained about 71% for describing the water demand of end-use in toilet and laundry water-uses.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5829-5834
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• 2015

Objective: To describe and analyze the epidemiological characteristics of lung cancer mortality in China from 1991 to 2013, forecast the future five-year trend and provide scientific evidence for prevention and management of lung cancer. Materials and Methods: Mortality data for lung cancer in China from 1991 to 2013 were used to describe epidemiological characteristics. Trend surface analysis was applied to analyze the geographical distribution of lung cancer. Four models, curve estimation, time series modeling, gray modeling (GM) and joinpoint regression, were performed to forecast the trend for the future. Results: Since 1991 the mortality rate of lung cancer increased yearly. The rate for males was higher than that for females and rates in urban areas were higher than in rural areas. In addition, our results showed that the trend will continue to increase in the ensuing 5 years. The mortality rate increased from age 45-50 and peaked in the group of 85 years old. Geographical analysis indicated that people living in northeast China provinces and the coastal provinces in eastern China had a higher mortality rate for lung cancer than those living in the centre or western Chinese provinces. Conclusions: The standardized mortality rate of lung cancer has constantly increased from 1991 to 2013, and been predicted to continue in the ensuing 5 years. Further efforts should be concentrated on education of the general public to increase prevention and early detection. Much better prevention and management is needed in high mortality areas (northeastern and eastern parts of China) and high risk populations (45-50-year-olds).

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.45-54
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• 1997

The correct estimation of the daily or hourly urban water demand is required for the efficient management and operation of the water supply facilities. The prediction of water supply demand are regression model and time series method, the optimum ARIMA (Auto Regressive Integrated Moving Average) model was sought for the daily urban water demand estimation in this paper. The data used for this study were obtained from the city of Kwangju Korea. The raw data used in this study were rearranged 15, 30, 60, 90 days for the purpose of analysis. The statistical analysis was applied to the data to obtain the ARIMA model. As a result, the parameters determining the ARIMA model was obtained. The accuracy of the model was 2% of water supply. The developed model was found to be useful for the practical operation and management of the water supply facilities.

• Fisheries and Aquatic Sciences
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• v.10 no.1
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• pp.43-52
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• 2007

The relationships among long-term climatic change in the southern part of the Korean peninsula, oceanic conditions of the South Sea, Korea, and winter catches of major small pelagic fishes were analyzed using 33 years of time-series data from 1971-2003. In the early 1990s, winter climatic conditions in the southern part of the Korean peninsula shifted to a warmer regime with higher air temperature, weaker wind speed, and lower relative humidity. Also, winter sea surface temperature (SST) became consistently higher in the South Sea. The annual catch of major small pelagic fishes in the South Sea increased dramatically in the mid 1990s, whereas the catch of total fishes decreased in the late 1980s. In particular, the winter catch started to increase markedly in the late 1980s, and has remained over 120,000 M/T since the late 1990s. Correlation analysis of the winter catch of major small pelagic fishes and environmental factors showed that catch was correlated with air temperature (r=0.468, P< 0.01), wind speed (r=-0.732, P< 0.01), relative humidity (r=-0.73l, P< 0.01), and SST (r=0.672, P< 0.01). Multiple regression analysis between the winter catch of major small pelagic fishes (Y) and environmental factors (X) resulted in the equation: $Y=-0.017-0.217\;X_3-0.486\;X_4+0.325\;X_5(R^2=0.754,\;P<0.000)$.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.546-556
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• 2006

The purpose of this study is to improve the polluted stream water quality by pilot-scale five different constructed wetlands (CWs). Cell 1 to 3 are newly designed 2SFCW (Surface-subsurface flow CW) with 1 to 3 flow shifters (FS) in the middle of the wetland system. Cell 4 and 5 are control CW (CCW), but Cell 5 is the same type as Cell 3. The FS, which converts the route of surface and subsurface flow between two wetlands connected in series, was able to enhance the treatability of TN via nitrification and denitrification and of SS due to filtration and sedimentation. The void fraction and dispersion number of Cell 1, 2 and 3 obtained from the RTD analysis were found to be 0.73 and 0.17, respectively. COD and TP removal efficiencies of Cell 1 to 3 were similar to that of Cell 4 and 5. SS removal efficiencies of Cell 1 to 3 and 5 with FS were 5-10% higher than that of Cell 4 without FS. TN removal efficiencies of Cell 1 to 3 were 3-14% higher than that of Cell 4 and 5. The average $R^2$ values of COD, SS, TN and TP obtained from nonlinear regression analysis were similar to the results of other researchers.

• Korean Journal of Social Welfare Studies
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• v.49 no.3
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• pp.35-60
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• 2018

This paper investigates the effects of fiscal decentralization on public welfare finance, focusing that welfare status experienced a post-industrial society has proposed decentralization as a response. The decentralization includes local government responsibilities and expanded roles under the background of fiscal distress of center governments and new social risks. For the analysis, the first theory is established to find out the effect of fiscal decentralization on social expenditure. Also, the second theory is set up for the relationship between the level of fiscal decentralization and composition of social expenditure. Findings indicate that the level of social expenditure of state would decrease as the level of fiscal decentralization increases. Also, the more the level of fiscal decentralization increases, the more the in-kind benefits among total welfare expenditure increase.

• Journal of the Korea Concrete Institute
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• v.18 no.3 s.93
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• pp.389-395
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• 2006

For the assessment of exsiting concrete structures, it is important to get the real strength of concrete. The load test or core test has many problems due to cost time, easiness, structural damage, and reliability and so on. Thus, various non-destructive test and statistical analysis techniques for strength assessment have been developed. As a result the real strength of concrete can be obtained by both direct and indirect test. In this study, a series of experimental tests of core strength and Schmidt hammer tests on 3, 7, 14, 28, 90, 180, 365, and 730 days' were done for predicting the compressive strength of high strength concrete with 65.0MPa of 28-days' strength. Each experimental results was analyzed by simple regression analysis. Then, reliability level and error rate between the proposed equations and the existing ones was examined. However, the application of the exsisting equations was inadequate to high strength concrete, because they were conducted under normal strength concrete. Therefore, the following compressive strength equations were proposed for predicting the compressive strength of high strength concrete by Schmidt hammer test. The proposed equations by Schmidt hammer test are as follows.

• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.19-41
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• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• 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.