• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.429-434
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• 2007

This study was conducted to estimate site productivity of Quercus acutissima and Quercus mongolica by four forest climatic zones. We used site environmental variables (28 geographical and pedological factors) and site index as a site productivity indicator from nation-wide 23,315 stands. Based on multiple regression analysis between site index and major environmental variables, the best-fit multivaliate models were made by each species and forest climatic zone. Most of site index prediction models by species were regressed with seven to eight factors, including altitude, relief, soil depth, and soil moisture etc. For those models, three evaluation statistics such as mean difference, standard deviation of difference, and standard error of difference were applied to the test data set for the validation of the results. According to the evaluation statistics, it was found that the models by climatic zones and species fitted well to the test data set with relatively low bias and variation. Also having above middle of site index range, total area of productive sites for the two Quercus spp. estimated by those models would be about 6% of total forest area. Northern temperate forest zone and central temperate forest zone had more productive area than southern temperate forest zone and warm temperate forest zone. As a result, it was concluded that the regressive prediction with site environmental variables by climatic zones and species had enough estimation capability of forest site productivity.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.37-45
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• 2008

It is expected that conditions of water resources will be changed in Korea in accordance with world wide climate change. In order to deal with this problem and find a way of minimizing the effect of future climate change, the usefulness of climate model simulation information is examined in this study. The objective of this study is to assess the applicability of GCM (General Circulation Model) information for Korean water resources management through uncertainty analysis. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. An estimator that accounts for climate model simulation and spatial association between the GCM data and observed data is used. Atmospheric general circulation model (AGCM) simulations done by ECMWF (European Centre for Medium-Range Weather Forecasts) with a resolution of $2^{\circ}{\times}2^{\circ}$, and METRI (Meteorological Research Institute, Korea) with resolutions of $2^{\circ}{\times}2^{\circ}$ and $4^{\circ}{\times}5^{\circ}$, were used for indicator variables, while observed mean areal precipitation (MAP) data, discharge data and mean areal temperature data on the seven major river basins in Korea were used for target variables. The results show that GCM simulations are useful in discriminating the high from the low of the observed precipitation, discharge, and temperature values. Temperature especially can be useful regardless of model and season.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.99-109
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• 2004

Most traffic congestion on a freeway occurs in the merge area, where conflicts between mainline traffic and on-ramp traffic are frequently generated. So far, research on the merge area has mainly dealt with free flow traffic and research on the congested traffic at the merge area is rare. This study investigates the relationships between mainline traffic and on-ramp traffic at three different segments of the merge area. For this purpose, new indicators based on such traffic variables as flow, speed, and density are used. The results show that a negative relationship exists between mainline and on-ramp flow. It is also found that the speed and the density of the right two lanes in the mainline traffic are significantly affected by the on-ramp flow. Based on the correlation analysis of the indicators, it is confirmed that the ramp influence area is the right two lanes of the freeway mainline. The revealed relationships between mainline and on-ramp traffic may help to analyze the capacity of the downstream freeway segment of the merging area in congested traffic. The findings of this studyalso provide a basis to develop a model that estimates the merge traffic volume in congested traffic, which is neither theoretically nor empirically sound in most other traffic flow models developed so far.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.391-401
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• 2017

This study develops an indicator to manage regional variations of approval rates for long-term care (LTC) service. We used LTC insurance data for grade assessment that include 433,155 applicants from 227 LTC centers across Korea in 2015. The approval rate for each center was defined as the proportion of the numbers of approved applicants out of all applicants. We assumed that the approval rates depended on the characteristics of applicants. We estimated the 'standard' approval rates from a multiple linear regression analysis using the characteristics of applicants as independent variables. The difference between the observed and the standard rates was then defined as an indicator for deviation. A center having a large difference could be considered as a center with a potential error in grade assessment. We also examined if the characteristics of investigators affected the approval rates. We found that the socio-demographic characteristics of applicants and reapplication rate for LTC grade were independent factors affecting the approval rates. Centers having the management indicator values falling outside the middle 95% of the distribution were identified as centers with an error in grading. We expect that this study will contribute to enhancing reliability and equity in LTC grading.

• Journal of Distribution Science
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• v.14 no.3
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• pp.63-71
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• 2016

Purpose - A variety of indicators are used for the diagnosis of economic situation. However, most indicators explain the past economic situation because of the time difference between the measurement and announcement. This study aims to argue for the resurrection of an idea: electricity demand can be used as an indicator of economic activity. In addition, this study made an endeavor to develop a new Real Business Index(RBI) which could quickly represent the real economic condition based on the sales statistics of industrial and public electricity. Research design, data, and methodology - In this study monthly sales of industrial and public electricity from 2000 to 2015 was investigated to analyze the relationship between the economic condition and the amount of electricity consumption and to develop a new Real Business Index. To formulate the Index, this study followed next three steps. First, we decided the explanatory variables, period, and collected data. Second, after calculating the monthly changes for each variable, standardization and estimating the weighted value were conducted. Third, the computation of RBI finalized the development of empirical model. The principal component analysis was used to evaluate the weighted contribution ratio among 3 sectors and 17 data. Hodrick-Prescott filter analysis was used to verify the robustness of out model. Results - The empirical results are as follows. First, compatibility of the predictability between the new RBI and the existing monthly cycle of coincident composite index was extremely high. Second, two indexes had a high correlation of 0.7156. In addition, Hodrick-Prescott filter analysis demonstrated that two indexed also had accompany relationship. Third, when the changes of two indexes were compared, they were found that the times when the highest and the lowest point happened were similar, which suggested that it is possible to use the new RBI index as a complementing indicator in a sense that the RBI can explain the economic condition almost in real time. Conclusion - A new economic index which can explain the economic condition needs to be developed well and rapidly in a sense that it is useful to determine accurately the current economic condition to establish economic policy and corporate strategy. The salse of electricity has a close relationship with economic conditions because electricity is utilized as a main resource of industrial production. Furthermore, the result of the sales of electricity can be gathered almost in real time. This study applied the econometrics model to the statistics of the sales of industrial and public electricity. In conclusion, the new RBI index was highly related with the existing monthly economic indexes. In addition, the comparison between the RBI index and other indexes demonstrated that the direction of the economic change and the times when the highest and lowest points had happened were almost the same. Therefore, this RBI index can become the supplementary indicator of the official indicators published by Korean Bank or the statistics Korea.

• 한국해양학회지
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• v.29 no.2
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• pp.132-144
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• 1994

The relationship of zooplankton communities and distributions of copepods as indicator species to environmental variables, such as temperature, salinity, chemical oxygen demand (COD) and total inorganic nitrogen (TIN) was studied in Pusan Harbor in October 1990 and January, April and July 1991. Zooplankton communities were analysed by using cluster analysis and species diversity index. Four groups of copepods as indicator species were Acrocalanus gacilis, Euchaeta plana, pareuchaeta russell and Pleuromamma gracilis as the oceanic warm water species; Cemtropages abdominalis as the neritic cold water species; Meridian lucens as the oceanic cold water species Acartia omorii as the polluted water species. the offshore waters of Pusan harbor was dominated by the oceanic warm water species in October and by the neritic cold water species in January and April. This area showed the low values of COD and Tin. the inshore waters of Pusan harbor, where the high values of cod And Tin and the low value of diversity were recorder was represented by A.. omorii. Cluster analysis of the zooplankton community revealed two or three regional areas in Pusan harbor. Area I, the offshore area of Pusan harbor, not only was represented high species diversity and low density of A. omorii but also was dominated copepods in zooplankton roups. Areas II and III were grouped horizontally from offshore to inshore of Pusan harbor. Area II was showed intermediate values in diversity, density of A. omorii and percentage composition of copepods. Area III was revealed the lowest diversity,density of A.omorii and percentage composition of Cladocerans.Coperpoda was a dominant zooplankton group in each area during the study periods except two special cases.Area II was dominated by Noctiluca scintillans in April and Area III was occupied by Cladocerans in July.Distribution of Indicator species and areas demarcated based on cluster analysis showed a close relationship with environments.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.909-917
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• 2020

The research aims to analyze the firm-specific and macroeconomic factors that affect insurance company's financial performance. The research explores the variables that influence the financial performance of the United Arab Emirates (UAE)' insurance companies. The analysis for determining financial performance considers the following variables: the firm's age, retention ratio, capital adequacy, underwriting risk/loss ratio, financial-leverage, reinsurance dependency, and macro-economic factors such as GDP per capita, inflation rate considered as independent factors. The return-on-asset (ROA) is the key measuring indicator; it is regarded as the dependent variable for financial performance measures. The research focuses on secondary information obtained from insurance companies' financial statements. The researcher targeted 18 insurance companies listed on the UAE stock exchanges for study purposes. The research examines the overall factors that influence the financial performance of an insurance company. For analysis of data, software package of social sciences (SPSS version 20) is used. The studies used correlation and multiple linear regression analysis to determine financial performance and their effects. The analysis suggests that there are important and constructive relationships between the size, capital adequacy, and reinsurance dependency, while loss ratio, retention ratio, and financial leverage indicate a major negative relationship. And there's no link between GDP per capita and inflation.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.109-116
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• 2020

The study examines the nexus between financial development and economic growth in India during Q1: 1996 to Q3: 2018. This study employs time-series data of real GDP and ratio of broad money to GDP as a proxy for economic and financial development, respectively. The data are obtained from RBI database on the Indian economy. All variables are seasonally adjusted using X12-arima technique and expressed in natural logarithm form. Non-linear Autoregressive Distributed Lag (NARDL) bound test has been used to check for cointegrating relationship of these two variables. Empirical findings suggest that, unlike in the short run, in the long run financial development does impact economic growth positively. Further, a symmetric effect of positive and negative components of financial development is found for the Indian economy, whereas the effect of control variable like exchange rate and trade openness is in consonance with common economic intuition. Exchange rate is in consonance with intuitive economic logic that a fall in exchange rate makes exports cheaper and increases the quantity of export, which improves the balance of payment and leads to a rise in aggregate demand, hence improves economic growth. This paper contributes to the existing literature on India by breaking down financial indicator into positive and negative components to examine the finance-growth relationship.

• Physical Therapy Korea
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• v.10 no.3
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• pp.141-149
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• 2003

Median frequency can be regarded as a valid indicator of local muscle fatigue. As local muscle fatigue develops, the muscle fiber conduction velocity decreases, the fast twitch fibers are recruited less, and consequently the median frequency shifts toward the lower frequency area. The aim of this study was to test the characteristics of the median frequency according to exercise load (30% and 60% of MVC on the biceps brachii, 40% and 80% of MVC on the vastus lateralis) during the fatiguing isometric exercise. Thirteen healthy male volunteer students of Yonsei University were recruited. After the testing maximal voluntary isometric contraction, three variables (initial median frequency, regression slope, fatigue index) from the regression line of MDF data were measured in each exercise load. The results showed that the regression slope and fatigue index were significantly different for the biceps brachii, but not for the vastus lateralis initial MDF was not significant difference according to the exercise load on both muscles. The regression slope and fatigue index could monitor physiologic muscle change during fatiguing isometric exercise. The results showed that two MDF variables reflect the local muscle fatigue according to the exercise load.

• Korean Journal of Human Ecology
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• v.15 no.6
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• pp.1025-1035
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• 2006

Brand Relationship Quality(BRQ) reflects the intensity and viability of the enduring association between a consumer and a brand so it is assumed to be the indicator which can affect brand performance such as brand satisfaction, brand attitude, and brand loyalty. The purpose of this study is to analyze the structural equation model showing the path between BRQ and brand performance. The subjects were women in their 20s to 40s living in Seoul and other metropolitan areas. 482 copies of questionnaire were analyzed by reliability, Pearson's correlation analysis, confirmatory factor analysis using SPSS 11.0 Package and AMOS 5.0 Package. The results showed that BRQ had positive influence on the brand performance-brand satisfaction, brand attitude, brand loyalty. As for the total effect about brand loyalty, BRQ was the most influential variable compared with other variables- brand satisfaction, brand attitude. The indirect impact of BRQ on brand loyalty is bigger than the direct impact of BRQ and brand satisfaction emerged as the important intermediate variable between BRQ and brand loyalty. Therefore, effective marketing strategy can be accomplished according to differential impact of the BRQ facets to induce consumer's satisfaction, which can lead to brand loyalty.