• Journal of the Korean association of regional geographers
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• v.7 no.1
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• pp.83-95
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• 2001

The purpose of this study is to examine that we can estimate land use by land values in 5 great cities. For this purpose, I calculated the percentage that each lot value makes up of the highest land values in the city as a indicator. I think this rate is very useful in the comparative study about many cities. At first, I set up four hypotheses based on my preceding studies. Hypothesis 1, the range of CBD can be estimated as having about 10% of the peak land values. Hypothesis 2, when the peak rate of concentric circle of land values seperated from CBD circle is about 30% of the peak land values, that is sub-CBD. Hypothesis 3, generally, a lot of having about 5% of the peak land values represents residential land commercial land use. Hypothesis 4, a lot of having about 3% of the peak land values represents only residential land use. The data on land values in five great cities were got from public notification on land values(1999) of the Ministry of Construction & Transportation. I selected highest lot values from many standard lot value in each Tong(the minimum administrative unit) in each cities. And I drew land values isopleth. Through that isopleth, I identified CBD cmd sub-CBD. Through the book of public notification on land values, I identified what land use are lots of having over 10%, about 5%, below 3% of the peak land values. As a result, we identified land use can be estimated by the percentage that each lot value makes up of the highest land values in the city. The bigger urban size becomes and the more stable land use becomes, the higher fitness of hypotheses becomes. The lowest degree of fitness about 4 hypotheses among 5 great cities showed in Inchon. Because Inchon lies adjacent to the greatest Seoul. The percentage that showed the lowest degree of fitness is 5% of the highest land values. The land use on lots of having about 5% of the peak land values is different from each other according to regional character in city.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.1
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• pp.42-54
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• 2016

It is highly anticipated that warming temperature resulting from global climate change will affect the phenological pattern of kiwifruit, which has been commercially grown in Korea since the early 1980s. Here, we present the potential impacts of climate change on the variations of flowering day of a gold kiwifruit cultivar, Haegeum, in the Jeonnam Province, Korea. By running six global climate models (GCM), the results from this study emphasize the uncertainty in climate change scenarios. To predict the flowering day of kiwifruit, we obtained three parameters of the 'Chill-day' model for the simulation of Haegeum: $6.3^{\circ}C$ for the base temperature (Tb), 102.5 for chill requirement (Rc), and 575 for heat requirement (Rh). Two separate validations of the resulting 'Chill-day' model were conducted. First, direct comparisons were made between the observed flowering days collected from 25 kiwifruit orchards for two years (2014-15) and the simulated flowering days from the 'Chill-day' model using weather data from four weather stations near the 25 orchards. The estimation error between the observed and simulated flowering days was 5.2 days. Second, the model was simulated using temperature data extracted, for the 25 orchards, from a high-resolution digital temperature map, resulting in the error of 3.4 days. Using the RCP 4.5 and 8.5 climate change scenarios from six GCMs for the period of 2021-40, the future flowering days were simulated with the 'Chill-day' model. The predicted flowering days of Haegeum in Jeonnam were advanced more than 10 days compared to the present ones from multi-model ensemble, while some individual models resulted in quite different magnitudes of impacts, indicating the multi-model ensemble accounts for uncertainty better than individual climate models. In addition, the current flowering period of Haegeum in Jeonnam Province was predicted to expand northward, reaching over Jeonbuk and Chungnam Provinces. This preliminary result will provide a basis for the local impact assessment of climate change as more phenology models are developed for other fruit trees.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.207-224
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• 2006

It has been widely known that the seismic piezo-cone penetration test (SCPTu) is one of the most useful techniques for investigating the geotechnical characteristics such as static and dynamic soil properties. As practical applications in Korea, SCPTu was carried out at two sites in Busan and four sites in Incheon, which are mainly composed of alluvial or marine soil deposits. From the SCPTu waveform data obtained from the testing sites, the first arrival times of shear waves and the corresponding time differences with depth were determined using the cross-over method, and the shear wave velocity $(V_S)$ profiles with depth were derived based on the refracted ray path method based on Snell's law. Comparing the determined $V_S$ profile with the cone tip resistance $(q_t)$ profile, both trends of profiles with depth were similar. For the application of the conventional CPTu to earthquake engineering practices, the correlations between $V_S$ and CPTu data were deduced based on the SCPTu results. For the empirical evaluation of $V_S$ for all soils together with clays and sands which are classified unambiguously in this study by the soil behavior type classification index $(I_C)$, the authors suggested the $V_S-CPTu$ data correlations expressed as a function of four parameters, $q_t,\;f_s,\;\sigma'_{v0}$ and $B_q$, determined by multiple statistical regression modeling. Despite the incompatible strain levels of the downhole seismic test during SCPTu and the conventional CPTu, it is shown that the $V_S-CPTu$ data correlations for all soils, clays and sands suggested in this study is applicable to the preliminary estimation of $V_S$ for the soil deposits at a part in Korea and is more reliable than the previous correlations proposed by other researchers.

• Geophysics and Geophysical Exploration
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• v.10 no.3
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• pp.173-182
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• 2007

It is well known that manganese nodules enriched with valuable metals are abundantly distributed in the abyssal plain area in the Clarion-Clipperton (C-C) fracture zone of the northeast Pacific. Previous studies using deep-sea camera (DSC) system reported different observations about the relation of seafloor topographic change and nodule abundance, and they were sometimes contradictory. Moreover, proper foundation on the estimation of DSC underwater position, was not introduced clearly. The variability of the mining condition of manganese nodule according to seafloor topography was examined in the Korea Deep Ocean Study (KODOS) area, located in the C-C zone. In this paper, it is suggested that the utilization of deep towing system such as DSC is very useful approach to whom are interested in analysing the distributional characteristics of manganese nodule filed and in selecting promising minable area. To this purpose, nodule abundance and detailed bathymetry were acquired using deep-sea camera system and multi-beam echo sounder, respectively on the seamount free abyssal hill area of southern part ($132^{\circ}10'W$, $9^{\circ}45'N$) in KODOS regime. Some reasonable assumptions were introduced to enhance the accuracy of estimated DSC sampling position. The accuracy in the result of estimated underwater position was verified indirectly through the comparison of measured abundances on the crossing point of neighboring DSC tracks. From the recorded seafloor images, not only nodules and sediments but cracks and cliffs could be also found frequently. The positions of these probable unminable area were calculated by use of the recorded time being encountered with them from the seafloor images of DSC. The results suggest that the unminable areas are mostly distributed on the slope sides and hill tops, where nodule collector can not travel over.

• Journal of the Korean Home Economics Association
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• v.46 no.8
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• pp.97-107
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• 2008

This study was conducted in order to identify the relationship between psychological factors, such as depression and self-esteem, and nutritional status, such as nutritional risk index and nutrient intake, among the elderly in Chunnam Province. The participants were 119 elderly individuals over the age of 65 years who visited the Senior Welfare Center in Chunnam province between January 29 and February 2, 2007. This study was conducted using a structured questionnaire that included, the Center for Epidemiologic Studies Depression Scale (CES-D), General Self Efficacy Scale (GSES), Nutritional Screening Initiative Checklist (NSI checklist), questions pertaining to the general characteristics of the participants and an estimation of nutrient intake using the 24-hour recall method. Data were analyzed by the SPSS program. Analysis of the participant's CES-D scores revealed that 43.7% of the subjects were normal and 56.3% had more than mild depression. The mean GSES score was 45.9 for the entire group of subjects (51.9 for men, 43.6 for women). The mean nutritional risk index value was 4.30 (5.03 for men, 4.01 for women). Analysis of the participant's scores on the NSI checklist revealed that 69.7% of the subjects were normal and 30.3% exhibited a moderate nutritional risk. The CES-D was positively correlated with the NSI checklist (p < 0.05) but negatively correlated with nutrient intake. However, the GSES was negatively correlated with the NSI checklist (p < 0.05), but positively correlated with nutrient intake (P < 0.01 for protein, calcium, phosphorus, zinc etc.). The results of this study indicate that it is necessary to manage psychological factors, including depression and self-esteem, in the elderly in order to decrease their nutritional risk and increase their nutrient intake.

• Tuberculosis and Respiratory Diseases
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• v.56 no.4
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• pp.393-404
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• 2004

Background : Nucleic acid hybridization has become an essential technique in the development of our understanding of gene structure and function. The quantitative analysis of hybridization has been used in the measurement of genome complexity and gene copy number. The filter hybridization assay is rapid, sensitive and can be used to measure RNAs complementary to any cloned DNA sequence. Methods : The authors assessed the accuracy, linearity, correlation coefficient and specificity of the hybridization depending on the added dose(0, 1, 5, and $10{\mu}g$) of non-specific rat spleen RNA to hybridization of surfactant protein A mRNA. Filter hybridization assays were used to obtain the equation of standard curve and thereby to quantitate the mRNA quantitation. Results : 1. Standard curve equation of filter hybridization assay between counts per minute (X) and spleen RNA input (Y) was Y=0.13X-19.35. Correlation coefficient was 0.98. 2. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) was Y=0.00066X-0.046. Correlation coefficient was 0.99. 3. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $1{\mu}g$ spleen RNA was Y=0.00056X-0.051. Correlation coefficient was 0.99. 4. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $5{\mu}g$ spleen RNA was Y=0.00065X-0.088. Correlation coefficient was 0.99. 5. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $10{\mu}g$ spleen RNA was Y=0.00051X-0.10. Correlation coefficient was 0.99. Conclusions : Comparison of cpm/filter in a linear range allowed accurate and reproducible estimation of surfactant protein A mRNA copy number irrespective of the addition dosage of non-specific rat spleen RNA over the range $0-10{\mu}g$.

• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.73-85
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• 1999

This study was conducted to reveal the characteristics of the early growth by locality for Korean white pine planted in Gapyung and Kwangju, Kyunggi-Do and Youngdong, Choongchungbuk-Do. The effects of local climatic conditions as one of environmental factors on the growth were also analyzed. For this, several stand variables such as number of trees survived, mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, periodic annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique, for the estimation of local climatic conditions, which makes use of empirical relationships between the topography and the weather in study areas was applied to produce reasonable estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine over remote land area where routine observations are rare. From these monthly estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc. which affect the tree growth, were computed for each locality. The periodic annual increments were then correlated with and regressed on the weather variables to examine effects of local weather conditions on the growth. Gapyung area provided the best conditions for the growth of Korean white pine in the early stage and Kwangju area ranked second. On the other hand, the growth pattern in Youngdong ranked last overall as expected. It is also found that the local growth patterns of Korean white pine in juvenile stage were affected by typical weather conditions. The conditions such as low temperature, high relative humidity, and large amount of precipitation provide favorable environment for the growth of Korean white pine. Especially, the diameter growth, basal area growth, and volume growth are mainly influenced by the amount of precipitation. However, it is proved that the height growth is affected by both the precipitation and temperature.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.235-246
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• 2009

This study theoretically reviews the basin storage coefficient and concentration time using the Nash model, a simple unit hydrograph theory. First, the storage coefficient and concentration time of Nash instantaneous unit hydrograph (IUH) are derived based on their definitions, whose characteristics as well as their relationship are also reviewed. Additionally, several empirical equations of storage coefficient and concentration time commonly used in Korea are evaluated by comparing them with those for the Nash IUH. Major results of this study are summarized as follows. (1) The concentration time of Nash IUH is approximately linearly proportional to the number of linear reservoirs, but the storage coefficient non-linearly to the square root. That is, if increasing the number of linear reservoirs by four times, the concentration time becomes also increased by about four times, but the storage coefficient only about two times. This result has a special meaning to understand the effect of basin subdivision on the concentration time and storage coefficient. (2) The storage coefficient and concentration time of Nash IUH are not independent each other, so their independent estimation does not make any physical sense. As the concentration time among the two is more sensitive to the number of linear reservoirs, which should be estimated first, then the storage coefficient considering the concentration time estimated. (3) Empirical equations of concentration time can be divided into two groups, one following the linear channel theory and the other not, whose equation forms are also found to be very similar. This result indicates that the characteristic factors dominating the concentration time are very similar, indicating the possibility of its regionalization over a basin with consistent equation forms. (4) Those for storage coefficient like the Russell formulae are found to consider the physical characteristics of a basin, so their unreasonable applications could sufficiently be excluded.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• The Korean Journal of Physiology
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• v.1 no.2
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• pp.169-175
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• 1967

An experiment was designed to see if the hippocampus exerts any influence upon the aggressive behavior of male rats. Fighting between rats was observed for the estimation of aggressiveness. Seventeen rats in which the hippocampus was almost totally removed through a small hole with a diameter around 3 mm made in the neocortex at the boundary between the parietal and occipital lobes (hippocampal group), 8 rats with similar neocortical damage alone (operated control group), and 17 normal control rats (normal group) were prepared and subjected to the experiment 3 months after the operation. Applying electric shock of short duration to the feet in a box with grid floor, a fight was provoked between an animal belonging to the hippocampal group and one belonging to the nor-mal group, between a rat of the hippocampal group and one of the operated control group, and also between a rat of the operated control group and one of the normal group. Three observers judged the performance of each animal independently and described it as winning, defeated, tied, or non-fighting. Fifteen shocked trials were administered to each pair of animals with around 2 minutes' interval between each trial. An animal received a 'judging score' of 3 when it won more frequently than was defeated, a judging score of 2 when it won as frequently as was defeated, when all fights were tied, or when no fighting occurred, while it received a judging score of 1 when it won less frequently than was defeated. Group differences in performances were analyzed in terms of judging score using Kolmogorov-Smirnov test for one sample. The results obtained were as follows: 1. In the fights between the hippocampal and the normal groups, the hippocampal animals made significantly better judging scores than the normal animals did (Table 1). 2. There was no significant difference between the hippocampal and the operated control group as to the judging scores they made in the course of fights between the two groups. However, the hippocampal animals tended to dominate over the operated control group as judged by comparing the total 'winning' of the former (30) to that of the latter (14) (Table 2). 3. The total judging score made by the operated control group in the course of the fights against the normal group was not significantly superior to that made by the normal group (Table 3). It was inferred from the above results that, though inconspicuous, the hippocampus tended to exert an inhibitory influence upon the aggressive behavior of male rats.