• Annual Conference of KIPS
• /
• 2021.11a
• /
• pp.868-871
• /
• 2021

기후, 경영, 경제 등 여러 분야의 회귀분석에서 설명변수가 반응변수에 일정 시차를 두고 영향을 미치는 경우들이 많다. 하지만 지금까지 대부분의 회귀분석은 설명변수가 반응변수에 즉각적으로 영향을 미치는 경우만을 가정하고 있으며, 설명변수와 반응변수 간에 존재하는 시차를 탐색하는 연구는 거의 이루어지지 않았다. 그러나 보다 정확한 회귀분석을 위해서는 설명변수와 반응변수 간에 존재하는 시차를 파악하는 것이 중요하다. 본 논문은 회귀분석 데이터가 주어졌을 때 설명변수와 반응변수 간에 존재하는 시차를 파악하는 딥러닝 모델을 제안한다. 제안하는 딥러닝 모델은 설명변수의 과거 값들 중 어떤 값이 현재 반응변수에 가장 큰 영향을 미치는지를 노드 간 가중치로 표현하고, 회귀모델의 오차를 최소화하는 가중치를 탐색한다. 훈련이 끝나면 이 가중치들을 사용하여 각 설명변수와 반응변수 간에 존재하는 시차를 파악한다. 실험을 통해 제안 방법은 시차를 고려하지 않는 기존 회귀모델에 비해 시차까지 고려함으로써 오차가 1/100 수준에 불과한 더 정확한 회귀모델을 찾을 수 있음을 확인하였다.

• The Korean Journal of Applied Statistics
• /
• v.29 no.5
• /
• pp.873-885
• /
• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Journal of Digital Convergence
• /
• v.16 no.10
• /
• pp.89-99
• /
• 2018

The purpose of this study is to analyse the determinants of the change in the welfare expenditure of local governments in 2015. This study analyzed the spatial correlation of welfare expenditure among neighboring local governments and determined the factors affecting the welfare expenditures. According to the results of the study, spatial correlation of welfare expenditure among local governments appears. Determinants, such as socio-economic factors, administrative factors, public financial factors are affecting the amount of the welfare expenditures, but local political factors, and local tax, last year's budgets are not correlated with the amount of local welfare expenditures. In this study, it is significant to found out that the spatial correlation of welfare expenditure among the local governments and to examine the determinants. If possible, it is necessary to analyze the time-series analysis using the multi-year welfare expenditure data, expecially self-welfare expenditures.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.10 no.1
• /
• pp.99-108
• /
• 1990

A Synthetic Unit Hydrograph Method was investigated for representation of the effective rainfall-direct runoff hydrograph by using a Geomorphologic Instantaneous Unit Hydrograpb(GIUH) proposed by Gupta et al(1980). The response function of the basin was assumed to be the two-parameter gamma probability density function. The physical parameters of the response function(Nash Model) was determined by using the regression eqs. were parameterized in terms of Horton order ratios and the relations between the basin lag time and time-scale parameter. The capability of the Synthetic Unit Hydrograph to the real basin was tested for the Pyungchang river basin and Wi Stream basin, and its capability to reproduce the hydrologic response was investigate and compared with the Moment Method and the Least Square Method used incomplete gamma function. The representation of the peak flow, the time to peak and the hydrographs the derived Synthetic Unit Hydrograph were tested on some obseved flood data and showed promising, and it was approved to be used for prediction of the ungaged basins.

• Food Science of Animal Resources
• /
• v.32 no.1
• /
• pp.62-67
• /
• 2012

This study calculated kinetic parameters of Escherichia coli O157:H7 and developed a probabilistic model to estimate growth probabilities of E. coli O157:H7 on polyethylene cutting boards as a function of temperature and time. The surfaces of polyethylene coupons ($3{\times}5$ cm) were inoculated with E. coli O157:H7 NCCP11142 at 4 Log $CFU/cm^2$. The coupons were stored at 13 to $35^{\circ}C$ for 12 h, and cell counts of E. coli O157:H7 were enumerated on McConkey II with sorbitol agar every 2 h. Kinetic parameters (maximum specific growth rate, Log $CFU/cm^2/h$; lag phase duration, h; lower asymptote, Log $CFU/cm^2$; upper asymptote, Log $CFU/cm^2$) were calculated with the modified Gompertz model. Of 56 combinations (temperature${\times}$time), the combinations that had ${\geq}$0.5 Log $CFU/cm^2$ of bacterial growth were designated with the value of 1, and the combinations that had increases of <0.5 Log $CFU/cm^2$ were given the value 0. These growth response data were fitted to the logistic regression to develop the model predicting probabilities of E. coli O157:H7 growth. Specific growth rate and growth data showed that E. coli O157:H7 cells were grown at $28-35^{\circ}C$, but there were no obvious growth of the pathogen below $25^{\circ}C$. Moreover, the developed probabilistic model showed acceptable performance to calculate growth probability of E. coli O157:H7. Therefore, the results should be useful in determining upper limits of working temperature and time, inhibiting E. coli O157:H7 growth on polyethylene cutting board.

• KDI Journal of Economic Policy
• /
• v.32 no.4
• /
• pp.75-114
• /
• 2010

This paper examines empirically whether information and communication technology(ICT) has improved total factor productivity at industry level in Korea, considering time lag between ICT capital accumulation and improvement of productivity. To evaluate if ICT is pervasive enough to raise productivity, ICT capital stock of Korea is compared with those of advanced economies. From the perspective of aggregate economy, the ICT capital in Korea has increased fast since the mid-1990s and became comparable with advanced economies. However it is mostly attributed to rapid growth of ICT-producing industries. In other industries, ICT capital are still less accumulated than advanced economies. Growth accounting results exhibit that the productivity has risen faster since 2000 in industries using ICT intensively, but looking into specific industries, it is not likely for ICT to be the main factor of productivity improvement except in business service industry. Regression results provide some evidence that ICT is useful in raising productivity only after considerable amount of time allowed. To fully exploit the positive effect of ICT on productivity, it may be necessary for the Korean economy to create institutional environment facilitating complementary innovations as well as ICT captial accumulation.

• Journal of Environmental Health Sciences
• /
• v.43 no.6
• /
• pp.516-524
• /
• 2017

Objectives: The annual catch of the common squid Todarodes pacificus in Korean coastal waters has gradually increased since the late 1980s. We investigated the long-term effects of climate variability on the variation in catches of the squid in the offshore fisheries of Korea. Methods: Moving average method, correlation analysis, and regression analysis were used to determine the relationship between the environmental factors and fluctuation in the catch of the squid during the past 30 years (1981- 2010). A ten-year moving average was calculated and used for each variable. Results: Squid catches in Korean coastal waters increased over time, and there were significant variations within every ten years (p < 0.001). Air temperature, atmospheric pressure, and wind grade among the meteorological factors, alongside sea surface temperature (SST) and concentrations of phosphate phosphorous, and nitrite/nitrate nitrogen in the sea water increased and were positively related with the catch size of squid (p < 0.001). However, salinity decreased and was negatively related with the catch size (p < 0.001). The increase in air temperature and SST was almost parallel, although there was a time lag between the two factors. Conclusion: These results suggest that there is a causal association between climate change and squid populations. Climate change, especially ocean warming, appears to have been largely favorable for squid range expansion into Korean seas. Although the expansion may be helpful for the human food supply, the safety of the squid caught should be monitored since the concentrations of phosphorous and nitrogen in the sea water increased, which indicates that Korean seas have grown gradually more polluted.

• The Journal of the Korea Contents Association
• /
• v.22 no.1
• /
• pp.58-73
• /
• 2022

The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.

• Korea Trade Review
• /
• v.42 no.6
• /
• pp.111-129
• /
• 2017

According to the World Bank statistics, China's contribution to global economic growth during the year of 2013-2016 was estimated at 31.6 percent. This figure is even larger than 29.0 percent, the contribution by summing each contribution of the United States, EU and Japan. The Chinese commodity trade accounts for up to 11.5 percent of world trade volume. Thus, we can consider that the Chinese economy has a strong influence on the global economy. The primary purpose of this study is to analyze the contribution level of Chinese seaborne trade volume on world economy. First, this study conducted a time-lag analysis using Moran test, so we can find that China's level of contribution to global economic growth varies from time to time. The contribution of the first phase (1999-2007) was nearly three times higher than the contributions from the second phase (2008-2016), suggesting that the overall contraction of the global trade volume starting from the subprime mortgage crisis in 2008 has continued until recently and recovery has not even occurred. Second, using the econometrics model, this study conducted an regression analysis of the impact of Chinese imports and exports in chemicals, grain, steel, crude oil, and container on global economic growth. Fixed effects model with time series data has been applied to examine the effect of Chinese seaborne trade volume on global economic growth. According to the empirical analysis of this study, China's exports of steel products, exports of container, imports of containers, imports of crude oil and imports of grain have significant contributions to global economic growth. Estimates of China's exports of steel products, exports of container, imports of containers, imports of crude oil and imports of grain are 1.023, 1.020, 1.019, 1.007 and 1.006, respectively. For example, the estimated value 1.023 of China's exports of steel products means that the growth rate can be 1.023 times higher than the current world GDP growth rate if Chinese seaborne trade volume of exports of steel products increased by one unit (one million tons). This study concludes that the expansion of China's imports and exports should be realized first to increase the global GDP growth rate. The expansion of Chinese trade can lead to a simultaneous stimulus of production and consumption in China, which can even lead to global economic growth ultimately. Thus, depending on how much China's trade will be broaden in the future, the width of global economic growth can be determined.

• Journal of Environmental Health Sciences
• /
• v.46 no.3
• /
• pp.276-284
• /
• 2020

Objectives: This study was conducted to identify the effects of PM₁₀ and PM_2.5 on hospital visits in the Incheon area over the period of 2016-2018. Methods: We applied correlation analysis and Poisson regression to perform the analysis using cardiovascular disease and respiratory disease data from the National Health Insurance Service and the daily average PM₁₀ and PM_2.5 from the Korea Environment Corporation adjusting for time lag. Results: When the daily average PM₁₀ concentration increased by 10 ㎍/㎥, the number of cardiovascular disease patients were 1.002 times higher (95% CI [Confidence Interval]; 1.000-1004) in Ganghwa County. As the daily average PM_2.5 concentration increased by 10 ㎍/㎥, the number of cardiovascular disease patients were 1.012 times higher (95% CI; 1.008-1.016) in Ganghwa County. As the daily average PM₁₀ concentration increased by 10 ㎍/㎥, the respiratory disease patients were 1.003 times (95% CI; 1.002-1.004) higher in Gyeyang and Michuhol Counties. As the PM_2.5 concentration increased by 10 ㎍/㎥, the respiratory disease patients were 1.003 times higher (95% CI; 1.002-1.005) in Bupyeong County. Conclusions: In some parts of the Incheon area there was a correlation between the number of patients with respiratory and cardiovascular conditions and the concentration of PM₁₀ and PM_2.5.