• Korea Real Estate Review
• /
• v.28 no.1
• /
• pp.79-90
• /
• 2018

The purpose of this study was to estimate the pricing factors of residential lands in new cities by estimating the pricing model of residential lands. For this purpose, hedonic equations for each quantile of the conditional distribution of land prices were estimated using quantile regression methods and the sale price date of Jangyu New Town in Gimhae. In this study, a quantile regression method that models the relation between a set of explanatory variables and each quantile of land price was adopted. As a result, the differences in the effects of the characteristics by price quantile were confirmed. The number of years that elapsed after the completion of land construction is the quadratic effect in the model because its impact may give rise to a non-linear price pattern. Age appears to decrease the price until certain years after the construction, and increases the price afterward. In the estimation of the quantile regression, land age appears to have a statistically significant impact on land price at the traditional level, and the turning point appears to be shorter for the low quantiles than for the higher quantiles. The positive effects of the use of land for commercial and residential purposes were found to be the biggest. Land demand is preferred if there are more than two roads on the ground. In this case, the amount of sunshine will improve. It appears that the shape of a square wave is preferred to a free-looking land. This is because the square land is favorable for development. The variables of the land used for commercial and residential purposes have a greater impact on low-priced residential lands. This is because such lands tend to be mostly used for rental housing and have different characteristics from residential houses. Residential land prices have different characteristics depending on the price level, and it is necessary to consider this in the evaluation of the collateral value and the drafting of real estate policy.

• Environmental and Resource Economics Review
• /
• v.31 no.2
• /
• pp.165-204
• /
• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Korea Journal of Hospital Management
• /
• v.11 no.3
• /
• pp.19-41
• /
• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• Asian-Australasian Journal of Animal Sciences
• /
• v.28 no.9
• /
• pp.1345-1353
• /
• 2015

This study was conducted to investigate the influence of dietary rapeseed meal (RSM) on growth performance, blood profiles, nutrient digestibility and economic benefit of growing-finishing pigs. A total of 120 growing pigs ($[Yorkshire{\times}Landrace]{\times}Duroc$) with an initial body weight (BW) $29.94{\pm}0.06kg$ were used in this experiment. Pigs were randomly allotted into 1 of 5 treatments in a randomized complete block design and 6 replicates with 4 pigs per pen. Treatments were divided by dietary RSM supplementation levels (0%, 3%, 6%, 9%, or 12%) in growing-finishing diets. A linear decrease (p<0.05) of BW and average daily gain (ADG) were observed at 13th wk of finishing and overall periods of pigs. Additionally, gain-to-feed ratio (G/F) tended to decrease by dietary RSM supplementation in growing-finishing diets (linear, p = 0.07 and quadratic, p = 0.08). Concentrations of serum triiodothyronine and thyroxine were not influenced by dietary RSM treatments whereas thyroid gland and liver weight were increased at 13th wk of finishing period (linear, p<0.05; p<0.01) by increasing dietary RSM supplementation level. In blood profiles, serum total cholesterol and low density lipoprotein cholesterol concentrations were not differed by dietary treatments at 13th wk of finishing period whereas concentration of serum high density lipoprotein cholesterol was affected by the supplementation level of RSM, resulting in a linear RSM level responses (p<0.05). Serum blood urea nitrogen concentration tended to decrease (linear, p = 0.07; p = 0.08) at 6th wk of growing and 13th wk of finishing periods and digestibility of dry matter tended to decrease by dietary RSM (linear, p = 0.09). Crude protein, crude fat and nitrogen retention, whereas, were not affected by dietary RSM supplementation level. In the economic analysis, feed cost per weight gain was numerically decreased when RSM was provided up to 9%. Consequently, RSM could be supplemented to growing-finishing diets up to 9% ($3.07{\mu}mol/g\;Gls$) without detrimental effects on growth performance of growing-finishing pigs.

• Journal of Korean Society of Transportation
• /
• v.18 no.6
• /
• pp.89-99
• /
• 2000

To cope with the limits of conventional O-D trip matrix collecting methods, several approaches have been developed. One of them is bilevel Programming method Proposed by Yang(1995), which uses Sensitivity Analysis Based(SAB) algorithm to solve Generalized Least Square(GLS) problem. However, the SAB a1gorithm has revealed two critical short-comings. The first is that when there exists a significant difference between target O-D matrix and true O-D matrix, SAB algorithm may not produce correct solution. This stems from the heavy dependance on the historical O-D information, in special when gravel Patterns are dramatically changed. The second is the assumption of iterative linear approximation to original Problem. Because of the approximation, SAB algorithm has difficulty in converging to Perfect Stackelberg game condition. So as to avoid the Problems. we need a more robust and stable solution method. The main purpose of this Paper is to show the problem of the dependency of Previous models and to Propose an alternative solution method to handle it. The Problem of O-D matrix estimation is intrinsically nonlinear and nonconvex. thus it has multiple solutions. Therefore it is necessary to require a method for searching globa1 solution. In this paper, we develop a solution algorithm combined with genetic algorithm(GA) , which is widely used as probabilistic global searching method To compare the efficiency of the algorithm, SAB algorithm suggested by Yang et al. (1992,1995) is used. From the results of numerical example, the Proposed algorithm is superior to SAB algorithm irrespective of travel patterns.

• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.3
• /
• pp.439-446
• /
• 2014

Many studies on methane ($CH_4$) and nitrous oxide ($N_2O$) emissions from livestock industries have revealed that livestock production directly contributes to greenhouse gas (GHG) emissions through enteric fermentation and manure management, which causes negative impacts on animal environment sustainability. In the present study, three essential values for GHG emission were measured; i.e., i) maximum $CH_4$ producing capacity at mesophilic temperature ($37^{\circ}C$) from anaerobically stored manure in livestock category ($B_{0,KM}$, Korean livestock manure for $B_0$), ii) $EF_{3(s)}$ value representing an emission factor for direct $N_2O$ emissions from manure management system S in the country, kg $N_2O-N$ kg $N^{-1}$, at mesophilic ($37^{\circ}C$) and thermophilic ($55^{\circ}C$) temperatures, and iii) $N_{ex(T)}$ emissions showing annual N excretion for livestock category T, kg N $animal^{-1}$ $yr^{-1}$, from different livestock manure. Static incubation with and without aeration was performed to obtain the $N_2O$ and $CH_4$ emissions from each sample, respectively. Chemical compositions of pre- and post- incubated manure were analyzed. Contents of total solids (% TS) and volatile solid (% VS), and the ratio of carbon to nitrogen (C/N) decrease significantly in all the samples by C-containing biogas generation, whereas moisture content (%) and pH increased after incubation. A big difference of total nitrogen content was not observed in pre- and post-incubation during $CH_4$ and $N_2O$ emissions. $CH_4$ emissions (g $CH_4$ kg VS-1) from all the three manures (sows, layers and Korean cattle) were different and high C/N ratio resulted in high $CH_4$ emission. Similarly, $N_2O$ emission was found to be affected by % VS, pH, and temperature. The $B_{0,KM}$ values for sows, layers, and Korean cattle obtained at $37^{\circ}C$ are 0.0579, 0.0006, and 0.0828 $m^3$ $CH_4$ kg $VS^{-1}$, respectively, which are much less than the default values in IPCC guideline (GL) except the value from Korean cattle. For sows and Korean cattle, $N_{ex(T)}$ values of 7.67 and 28.19 kg N $yr^{-1}$, respectively, are 2.5 fold less than those values in IPCC GL as well. However, $N_{ex(T)}$ value of layers 0.63 kg N $yr^{-1}$ is very similar to the default value of 0.6 kg N $yr^{-1}$ in IPCC GLs for National greenhouse gas inventories for countries such as South Korea/Asia. The $EF_{3(s)}$ value obtained at $37^{\circ}C$ and $55^{\circ}C$ were found to be far less than the default value.

• Water for future
• /
• v.27 no.1
• /
• pp.89-99
• /
• 1994

Flood forecasting in Korea has been based on the off-line parameter estimation method. But recent flood forecasting studies explore on-line recursive parameter estimation algorithms. In this study, a simultaneous adaptive estimation of system states and parameters for rainfall-runoff model is investigated for on-line real-time flood forecasting and parameter estimation. The proposed flood routing system is composed of Flood forecasting in Korea has been based on the off-line parameter estimation method. But recent flood forecasting studies explore on-line recursive parameter estimation algorithms. In this study, a simultaneous adaptive estimation of system states and parameters for rainfall-runoff model is investigated for on-line real-time flood forecasting and parameter estimation. The proposed flood routing system is composed of ø-index in the assessment of effective rainfall and the cascade of nonlinear reservoirs accounting for translation effect in flood routing. To combine the flood routing model with a parameter estimation model, system states and parameters are treated with the extended state-space formulation. Generalized least squares and maximum a posterior estimation algorithms are comparatively examined as estimation techniques for the state-space model. The sensitivity analysis is to investigate the identifiability of the parameters. The index of sensitivity used in this study is the covariance matrix of the estimated parameters.-index in the assessment of effective rainfall and the cascade of nonlinear reservoirs accounting for translation effect in flood routing. To combine the flood routing model with a parameter estimation model, system states and parameters are treated with the extended state-space formulation. Generalized least squares and maximum a posterior estimation algorithms are comparatively examined as estimation techniques for the state-space model. The sensitivity analysis is to investigate the identifiability of the parameters. The index of sensitivity used in this study is the covariance matrix of the estimated parameters.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.4
• /
• pp.138-147
• /
• 2007

Metabolic pathway is a series of chemical reactions occuning within a cell and can be used for drug development and understanding of life phenomenon. Many biologists are trying to extract metabolic pathway information from huge literatures for their metabolic-circuit regulation study. We propose a text-mining technique based on the keyword and pattern. Proposed technique utilizes a web robot to collect huge papers and stores them into a local database. We use gene ontology to increase compound recognition rate and NCBI Tokenizer library to recognize useful information without compound destruction. Furthermore, we obtain useful sentence patterns representing metabolic pathway from papers and KEGG database. We have extracted 66 patterns in 20,000 documents for Glycosphingolipid species from KEGG, a representative metabolic database. We verify our system for nineteen compounds in Glycosphingolipid species. The result shows that the recall is 95.1%, the precision 96.3%, and the processing time 15 seconds. Proposed text mining system is expected to be used for metabolic pathway reconstruction.

• Korean Journal of Social Welfare Studies
• /
• no.37
• /
• pp.117-144
• /
• 2008

This is a timeseries study on the riving forces behind the changes of Korean welfare state. There are a few previous studies on the determinants of korean welfare state. These previous studies have some limitations in terms of reliability of the data source and validity of the statistical method used. Using the Comparative Social Policy Data-set(CSPD), we try to overcome the limitation of these previous studies. And adapting the time series regression, we examine the hypotheses about the changes of korean welfare state. In this study, four dependent variables are examined: the ratio of public social welfare expenditure to the GDP(WELGDP), the ratio of public social welfare expenditure to the government budget(WELGOV), the ratio of social expenditure to the GDP(SOCX), social welfare expenditure per capita. And independent variables were selected based on the theoretical background on the changes of welfare state. The results of this study as follows: First, the variables based on structural functionalism (industrialization) are the major driving forces behind the changes of korean welfare state since 1960s. Second, the effect of unemployment variable may be reasonably interpreted as reflecting the residual characteristics of korean welfare state. Third, the politics of the left based on power resource theory should be restrictedly interpreted. Ultimately, korean welfare state is still at rudimentary stage where the theory of industrialization is well applied as a driving forces behind the changes of welfare state.

• Journal of Environmental Science International
• /
• v.28 no.2
• /
• pp.225-233
• /
• 2019

In this study, we investigated the in vitro anti-biofilm activities of plant extracts of chives (Allium tuberosum), garlic (Allium sativum), and radish (Raphanus sativus L.) against environment harmful bacteria (gram-positive Staphylococcus aureus and, gram-negative Salmonella typhimurium and Escherichia coli O157:H7). In the paper disc assay, garlic extracts exhibited the highest anti-biofilm activity. The Minimal Inhibitory Concentration (MIC) of all plant extracts was generally higher for gram-negative bacteria than it was for gram-positive bacteria. Gram-negative bacteria were more resistant to plant extracts. The tetrazolium dye (XTT) assay revealed that, each plant extract exhibited a different anti-biofilm activity at the MIC value depending on the pathogen involved. Among the plant extracts tested, garlic extracts (fresh juice and powder) effectively reduced the metabolic activity of the cells of food-poisoning bacteria in biofilms. These anti-biofilm activities were consistent with the results obtained through light microscopic observation. Though the garlic extract reduced biofilm formation for all pathogens tested, to elucidate whether this reduction was due to antimicrobial effects or anti-biofilm effects, we counted the colony forming units of pathogens in the presence of the garlic extract and a control antimicrobial drug. The garlic extract inhibited the E. coli O157:H7 biofilm effectively compared to the control antimicrobial drug ciprofloxacin; however, it did not inhibit S. aureus biofilm significantly compared to ciprofloxacin. In conclusion, garlic extracts could be used as natural food preservatives to prevent the growth of foodborne pathogens and elongater the shelf life of processed foods.