• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.218-233
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• 2022

The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.

• Korean journal of applied entomology
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• v.57 no.3
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• pp.127-135
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• 2018

Climate change can affect variables related to the life cycle of insects, including growth, development, survival, reproduction and distribution. As it encourages alien insects to rapidly spread and settle, climate change is regarded as one of the direct causes of decreased biodiversity because it disturbed ecosystems and reduces the population of native species. Hypera postica caused a great deal of damage in the southern provinces of Korea after it was first identified on Jeju lsland in the 1990s. In recent years, the number of individuals moving to estivation sites has concerned scientists due to the crop damage and national proliferation. In this study, we examine how climate change could affect inhabitation of H. postica. The MaxEnt model was applied to estimate potential distributions of H. postica using future climate change scenarios, namely, representative concentration pathway (RCP) 4.5 and RCP 8.5. As variables of the model, this study used six bio-climates (bio3, bio6, bio10, bio12, bio14, and bio16) in consideration of the ecological characteristics of 66 areas where inhabitation of H. postica was confirmed from 2015 to 2017, and in consideration of the interrelation between prediction variables. The fitness of the model was measured at a considered potentially useful level of 0.765 on average, and the warmest quarter has a high contribution rate of 60-70%. Prediction models (RCP 4.5 and RCP 8.5) results for the year 2050 and 2070 indicated that H. postica habitats are projected to expand across the Korean peninsula due to increasing temperatures.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.617-623
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• 2001

To predict the seasonal variation of dissolved oxygen (DO) in Hakata bay, Japan, possible 20 time-series of different hourly-solar-radiation intensities were generated based on stochastically changing solar radiation intensity, and a numerical simulation on dissolved oxygen (DO) was carried out for each time series by using the Sediment-Water Ecological Model (SWEM). The model, consisting of two sub-models with hydrodynamic and biological models, simulates the circulation process of nutrient between water column and sediment, such as nutrient regeneration from sediments as well as ecological structures on the growth of phytoplankton and zooplankton, The results of the model calibration followed the seasonal variation of observed water quality well, and generated cumulative-frequency-distribution (CFD) curves of daily solar radiation agreed well with observed ones, The simulation results indicated that the exchange of sea water would have a great influence on the DO concentration, and that the concentration could change more than 1 mg/L in a day. This prediction method seems to be an effective way to examine a solution to minimize fishery damage when DO is depleted.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of the Korean housing association
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• v.21 no.2
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• pp.101-109
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• 2010

Various environmental problems due to rapid industrialization and urbanization have worsened to such an extent that they threaten the environmental restitution of the globe and become a critical international issue. Korean government has presented the concept of green growth as a new state vision for the next 60 years and is making efforts to solve these environmental problems. Daegu Metropolitan City has faced various environmental problems including overpopulation of the city, traffic pollution, household waste accumulation and the green zone problem because of the increase of urbanization over the last few decades. As such urbanization continues, the quality of residential environments is rapidly deteriorating and the intensive use of the land leads to an increase of building area, raising the temperatures of cities. There have therefore been demands for healthy, pleasant and satisfying residential environments and for the improvement of existing residential environments, and this demand has been fully recognized by society. Nevertheless, current residential complex developments concentrate only on raising the efficiency of land use. In related laws of the past (Daegu Metropolitan City, Urban Planning Municipal Ordinance as of October 10, 2003) an attempt was made to impose a standard to segmentalize the building-to-land ratio, floor area ratio and regulations of number of floors vertically. However, these laws have now been abolished and the regulations are being eased. The purpose of this study was to analyze the characteristics of the floating wind before and after the vertical segmentation of residential areas (Daegu Metropolitan City, Urban Planning Municipal Ordinance as of October 10, 2003) by using KLAM_21, a model that enables analysis and prediction of the flow and generation of cold wind. The purpose is also to present a plan to improve the quality of residential areas when developing a building lot and redeveloping housing areas.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.6
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• pp.889-896
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• 2012

In this study, simulation results of nitrogen and phosphorus removals and microbial activities for an $A_2O$ process in wastewater treatment plant are presented by using Activated Sludge Models (ASMs). Simulations were performed using pre-calibrated model and layout implemented in GPS-X simulation software. The models were used to investigate variations of SRT, water temperature, DO and C/N ratio effect on nutrients removal and microbial activity. According to the simulated results, the successful nitrification required SRT higher than 10.3 days, whereas increase of $NO_3$-N loading in the anaerobic reactor caused phosphorus release by PAOs; the effluent $NH_4$-N showed rapid change between $12^{\circ}C$(21.7 mg/L) and $13^{\circ}C$(3.2 mg/L); the effluent phosphorus was increased up to 1.9 mg/L at water temperature of $25^{\circ}C$; the DO increase was positive for heterotrophs and autotrophs growths but negative for PAOs growth; the PAOs showed low activity when C/N ratio was lower than 2.5. The experimental results indicated that the calibrated models can assure the prediction quality of the ASMs and can be used to optimize the $A_2O$ process.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.6
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• pp.764-771
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• 2012

Direct and maternal genetic heritabilities and their correlations with body weight at 5 stages in the life span of purebred Berkshire pigs, from birth to harvest, were estimated to scrutinize body weight development with the records for 5,088 purebred Berkshire pigs in a Korean farm, using the REML based on an animal model. Body weights were measured at birth (Birth), at weaning (Weaning: mean 22.9 d), at the beginning of a performance test (On: mean 72.7 d), at the end of a performance test (Off: mean 152.4 d), and at harvest (Finish: mean 174.3 d). Ordinary polynomials and Legendre with order 1, 2, and 3 were adopted to adjust body weight with age in the multivariate animal models. Legendre with order 3 fitted best concerning prediction error deviation (PED) and yielded the lowest AIC for multivariate analysis of longitudinal body weights. Direct genetic correlations between body weight at Birth and body weight at Weaning, On, Off, and Finish were 0.48, 0.36, 0.10, and 0.10, respectively. The estimated maternal genetic correlations of body weight at Finish with body weight at Birth, Weaning, On, and Off were 0.39, 0.49, 0.65, and 0.90, respectively. Direct genetic heritabilities progressively increased from birth to harvest and were 0.09, 0.11, 0.20, 0.31, and 0.43 for body weight at Birth, Weaning, On, Off, and Finish, respectively. Maternal genetic heritabilities generally decreased and were 0.26, 0.34, 0.15, 0.10, and 0.10 for body weight at Birth, Weaning, On, Off, and Finish, respectively. As pigs age, maternal genetic effects on growth are reduced and pigs begin to rely more on the expression of their own genes. Although maternal genetic effects on body weight may not be large, they are sustained through life.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.32.2-32.2
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• 2013

We examine large-scale environmental effects on the formation and the mass growth of dark matter halos. To facilitate this, we constructed dark matter halo merger trees from a cosmological N-body simulation, which enabled us to trace the merger information and the assembly history of individual halos. In fact, since the massive halos are more likely to be distributed in denser regions than in less dense regions (Mo & White, 1996), the large-scale environment dependence of the properties of halos can be partly originated from the halo mass effect. In order to avoid such contamination, caused by the mass dependence of halo properties, we carefully measured the local overdensity as the indicator of large-scale environment, which was calculated to be as independent of halo mass as possible. Small halos (${\sim}10^{11-12}M_{\odot}$), which usually host isolated single galaxies, show a notable difference on the formation time of galaxies depending on their large-scale environments, which reconfirms halo assembly bias (Gao & White, 2007). Furthermore, we investigate how this environmental effect on small halos is correlated with the mass assembly history of galaxies by using our semi-analytic model. We found that assembly bias in small halos does not have significant effects on the formation time or on the star formation history of galaxies residing in those halos except for the individual stellar mass of galaxies at z = 0. On average, isolated galaxies in high-density regions tend to be slightly more massive than those in low-density regions. Although the observational data from the current galaxy surveys is not yet sufficient for testing this prediction, future galaxy surveys will be able to explore these small galaxies more thoroughly.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.14-22
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• 1994

This paper proposes two Bayes estimators and their evaluation algorithms of the software reliability at the end testing stage in the Smith's Bayesian software reliability growth model under the data prior distribution BE(a, b), which is more general than uniform distribution, as a class of prior information. We consider both a squared-error loss function and the Harris loss function in the Bayesian estimation procedures. We also compare the MSE performances of the Bayes estimators and their algorithms of software reliability using computer simulations. And we conclude that the Bayes estimator of software reliability under the Harris loss function is more efficient than other estimators in terms of the MSE performances as a is larger and b is smaller, and that the Bayes estimators using the beta prior distribution as a conjugate prior is better than the Bayes estimators under the uniform prior distribution as a noninformative prior when a＞b.