• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.312-318
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• 2010

This study was carried out to develop and test a prototype program that recommends the nitrogen topdressing rate using the color digital camera image taken from rice field at panicle initiation stage (PIS). This program comprises four models to estimate shoot N content (PNup) by color digital image analysis, shoot N accumulation from PIS to maturity (PHNup), yield, and protein content of rice. The models were formulated using data set from N rate experiments in 2008. PNup was found to be estimated by non-linear regression model using canopy cover and normalized green values calculated from color digital image analysis as predictor variables. PHNup could be predicted by quadratic regression model from PNup and N fertilization rate at panicle initiation stage with $R^2$ of 0.923. Yield and protein content of rice could also be predicted by quadratic regression models using PNup and PHNup as predictor variables with $R^2$ of 0.859 and 0.804, respectively. The performance of the program integrating the above models to recommend N topdressing rate at PIS was field-tested in 2009. N topdressing rate prescribed for the target protein content of 6.0% by the program were lower by about 30% compared to the fixed rate of 30% that is recommended conventionally as the split application rate of N fertilizer at PIS, while rice yield in the plots top-dressed with the prescribed N rate were not different from those of the plots top-dressed with the fixed N rates of 30% and showed a little lower or similar protein content of rice as well. And coefficients of variation in rice yield and quality parameters were reduced substantially by the prescribed N topdressing. These results indicate that the N rate recommendation using the analysis of color digital camera image is promising to be applied for precise management of N fertilization. However, for the universal and practical application the component models of the program are needed to be improved so as to be applicable to the diverse edaphic and climatic condition.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Korean Journal of Ecology and Environment
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• v.48 no.4
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• pp.229-237
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• 2015

This study aims to offer basic data to effectively preserve and manage pine forests using more precise pine forests' distribution status. In this regard, this study predicts the geographical distribution change of pine forests growing in South Korea, due to climate change, and evaluates the spatial distribution characteristics of pine forests by age. To this end, this study predicts the potential distribution change of pine forests by applying the MaxEnt model useful for species distribution change to the present and future climate change scenarios, and analyzes the effects of bioclimatic variables on the distribution area and change by age. Concerning the potential distribution regions of pine forests, the pine forests, aged 10 to 30 years in South Korea, relatively decreased more. As the area of the region suitable for pine forest by age was bigger, the decreased regions tend to become bigger, and the expanded regions tend to become smaller. Such phenomena is conjectured to be derived from changing of the interaction of pine forests by age from mutual promotional relations to competitive relations in the similar climate environment, while the regions suitable for pine forests' growth are mostly overlap regions. This study has found that precipitation affects more on the distribution of pine forests, compared to temperature change, and that pine trees' geographical distribution change is more affected by climate's extremities including precipitation of driest season and temperature of the coldest season than average climate characteristics. Especially, the effects of precipitation during the driest season on the distribution change of pine forests are irrelevant of pine forest's age class. Such results are expected to result in a reduction of the pine forest as the regions with the increase of moisture deficiency, where climate environment influencing growth and physiological responses related with drought is shaped, gradually increase according to future temperature rise. The findings in this study can be applied as a useful method for the prediction of geographical change according to climate change by using various biological resources information already accumulated. In addition, those findings are expected to be utilized as basic data for the establishment of climate change adaptation policies related to forest vegetation preservation in the natural ecosystem field.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.199-205
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• 2001

This study was conducted to figure out temperature profiles of a partially developed paddy rice canopy, which are necessary to run plant disease forecasting models. Air temperature over and within the developing rice canopy was monitored from one month after transplanting (June 29) to just before heading (August 24) in 1999 and 2001. During the study period, the temporal march of the within-canopy profile was analyzed and an empirical formula was developed for simulating the profile. A partially developed rice canopy temperature seemed to be controlled mainly by the ambient temperature above the canopy and the water temperature beneath the canopy, and to some extent by the solar altitude, resulting in alternating isothermal and inversion structures. On sunny days, air temperature at the height of maximum leafages was increased at the same rate as the ambient temperature above the canopy after sunrise. Below the height, the temperature increase was delayed until the solar noon. Air temperature near the water surface varied much less than those of the outer- and the upper-canopy, which kept increasing by the time of daily maximum temperature observed at the nearby synoptic station. After sunset, cooling rate is much less at the lower canopy, resulting in an isothermal profile at around the midnight. A fairly consistent drop in temperature at rice paddies compared with the nearby synoptic weather stations across geographic areas and time of day was found. According to this result, a cooling by 0.6 to 1.2$^{\circ}C$ is expected over paddy rice fields compared with the officially reported temperature during the summer months. An empirical equation for simulating the temperature profile was formulated from the field observations. Given the temperature estimates at 150 cm above the canopy and the maximum deviation at the lowest layer, air temperature at any height within the canopy can be predicted by this equation. As an application, temperature surfaces at several heights within rice fields were produced over the southwestern plains in Korea at a 1 km by 1km grid spacing, where rice paddies were identified by a satellite image analysis. The outer canopy temperature was prepared by a lapse rate corrected spatial interpolation of the synoptic temperature observations combined with the hourly cooling rate over the rice paddies.

• Korean Journal of Psychosomatic Medicine
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• v.8 no.1
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• pp.46-57
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• 2000

Objectives : The purpose of the present study was to examine the effect of subacute treatment with the selective serotonin reuptake inhibitors(paroxetine and sertraline) on immobility in the forced swim test(FST) and on FST-induced changes in immune parameters of the mice. Methods : Authors applied a modified method of FST by Porsolt et al. Over 5 BALB/c mice were used for each group of experiments. To explore the changes in immune parameters by FST, authors investigated the production of anti-rat RBC antibody, concanavalin A(ConA)- or lipopolysaccharide(LPS)-stimulated splenocytes proliferation assay and cytokine gene expression. Results : Both paroxetine and sertraline decreased the duration of immobility in a dose-related manner. FST-performed mice showed a significant decrease in mitogenic responses of splenocytes and a slight increasing tendency in anti-rat RBC antibody response. All these responses were attenuated significantly by paroxetine and attenuated nearly nominal significance level by sertraline. The cytokine profiles of ConA-stimulated splenocytes from FST-performed mice showed stronger expression of IL-4 and weaker expression of IL-2 than control mice, and no changes in the expressions of IFN-$\gamma$ and lymphotoxin. IL-6 and IL-10 were not expressed in both group of mice. The pretreatment of paroxetine and sertraline attenuated the altered cytokine expressions in FST-performed mice to some extent. Some alterations of the expressions of IL-6 and IL-10 were observed in the mice which the selective serotonin reuptake inhibitors had been pretreated. Conclusion : The subacute treatment of paroxetine and sertraline attenuated the FST-induced behavioral and immune changes, and these serotonin reuptake inhibitors may exert some modulating effects on the immune system by the induction of cytokine gene expression, especially IL-6 and IL-10.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.89-101
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• 2017

Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.

• Journal of dental hygiene science
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• v.17 no.2
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• pp.134-141
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• 2017

This study examined 191 pregnant women before delivery in an obstetrics and gynecology clinic in North Gyeongsang Province from May to September 2016 by using a questionnaire after obtaining informed consent for voluntary participation in the study. The study was performed to investigate the association of depression with sociodemographic characteristics, pregnancy-related characteristics, social support, sleep quality and Oral Health Impact Profile (OHIP) in pregnant women. The prevalence of depression among the pregnant women was 25.1% in the healthy group and 74.9% in the depression group. The depression level was significantly higher in women in the depression group who were unsatisfied with their marriage life, had no occupation, had lower social support, had poor sleep quality and had higher OHIP scores. The results of the logistic regression analysis indicated that, the risk ratio for more severe depression was significantly higher in the group with no experience of miscarriage and induced childbirth than in the group with childbirth experience. Conversely, the risk ratio for more severe depression was significantly lower in the group with high social support than in the group with low social support. Depression in the respondents significantly positively correlated with sleep quality and OHIP score but significantly negatively correlated with social support. The multiple regression analysis revealed that the depression level was significantly higher by 22.3% among pregnant women with lower marital satisfaction, no childbirth experience, lower social support and higher OHIP scores. In summary, depression was related to marital satisfaction, childbirth experience, social support, and OHIP score, among others, in pregnant women in this study. Therefore, further investigation is warranted to construct programs and measures that will help build positive thinking by designing and verifying a three-dimensional study model by taking into consideration various variables to reduce the incidence of depression in pregnant women.

• Korean journal of applied entomology
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• v.56 no.4
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• pp.387-394
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• 2017

Temperature-dependent oviposition model and life table parameters of Paromius exiguus (Distant), the causal agent of 'pecky' rice grain were examined at eight constant temperatures (17.5, 20, 22.5, 25, 27.5, 30, 32.5, and $35{\pm}^{\circ}C$) and a photoperiod of 14:10 (L:D) h. Unit functions of the oviposition model were developed and life table parameters were estimated. The longevity of P. exiguus adults decreased with increasing temperature (123.8 days at $17.5^{\circ}C$ and 23.6 days at $32.5^{\circ}C$). Total fecundity was highest at $30^{\circ}C$ (585.2 eggs/female) and lowest at $17.5^{\circ}C$ (21.5 eggs/female). In order to develop a temperature-dependent oviposition model, adult aging-rate, temperature-dependent fecundity, age-specific survival rate, and age-specific cumulative oviposition rate equations were estimated. All unit equations ($r^2=0.92{\sim}0.98$) except for the temperature-dependent fecundity equation ($r^2=0.83{\sim}0.85$), described oviposition characteristics of P. exiguus adequately. Life table parameters of P. exiguus were estimated at various constant temperatures. Net reproduction rate ($R_0$) was highest at $30^{\circ}C$ (118.21). Mean generation time (T) was shortest at $32.5^{\circ}C$ (32.99 days) and doubling time (Dt) was shortest at $30^{\circ}C$ (5.69 days). The highest values of intrinsic rate of increase ($r_m$) and finite rate of increase (${\lambda}$) were 0.122 and 1.129 at $30^{\circ}C$, respectively.

• Korea journal of population studies
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• v.28 no.2
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• pp.1-32
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• 2005

The optimum population of a society or country can be defined as 'the population growth path that maximizes the welfare level of the society over the whole generations of both the present and the future, under the paths allowed by its endowments of production factors such as technology, capital and labor'. Thus, the optimum size or growth rate of population depends on: (i) the social welfare function, (ii) the production function, and (iii)demographic economic interrelationship which defines how the national income is disposed into consumption(birth and education of children included) and savings on the one hand and how the demographic and economic change induced thereby, in turn, affect production capacities on the other. The optimum population growth path can, then, be derived in the process of dynamic optimization of (i) under the constraints of (ii) and (iii), which will give us the optimum population growth rate defined as a function of parameters thereof. This paper estimates the optimum population growth rate of Korea by: specifying (i), (ii), and (iii) based on the recent development of economic theories, solving the dynamic optimization problem and inserting empirical estimates in Korea as the parametric values. The result shows that the optimum path of population growth in Korea is around TFR=1.81, which is affected most sensitively, in terms of the size of the partial elasticity around the optimum path, by the cost of children, share of capital income, consumption rate, time preference, population elasticity of utility function, etc. According to a survey implemented as a follow up study, there are quite a significant variations in the perceived cost of children, time preference rate, population elasticity of utility across different socio-economic classes in Korea, which implied that, compared to their counterparts, older generation and more highly educated classes prefer higher growth path for the population of Korea.

• Journal of the Korean Home Economics Association
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• v.37 no.5
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• pp.61-84
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• 1999

The purpose of this study is to understand the context of cosumers' lives in Korea with a narrative analysis method. The epistemological orientation of eh narrative analysis is Interpretivism, which blends the two polar philosophical perspectives, Empiricism and Rationalism, and includes Narrotology, Hermeneneutics, Semiotics, and Structural Criticism. Narrative analysis takes as its object of investigation the story itself. This study collects eleven narrative plots from four housewives, into which Labov's structural approach is applied. This study shows clearly that the socio-cultural environment in which consumers live has strong influence on their consumption behavior and also reveals that narrativization tells not only about past actions but how individuals understand those actions, that is, meaning.