• KOREAN JOURNAL OF CROP SCIENCE
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• v.2
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• pp.39-45
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• 1964

The phenotypic and genotypic correlations and heritabitities were calculated on 10 characters measured, using 10 native and 10 of introduced soybean varieties planted on 7 times with 15 days interval from April 15th. The genotypic correlations associated with grain yield were partitioned in to direct and indirect effects through the path coefficient analysis. The results are summarized as follows; 1. Generally high associations between characters were found, with high genotypic correlations than phenotypic, due to, probably, the fact that non segregating fixed varieties were used, and that the environmental effects were not elliminated appropreately here. Neverthless, the relative degree of association could be estimated. 2. The degree of associations of characters were different according the planting time, requiring the considerations on the specific characteristics depending on the specific planting time. 3. The introduced varieties were different with native ones in many respects, especially on the associations with stem length, stem diameter and seed weight. Here, the degree and the directions of the associations in the introduced ones were some peculier. 4. The less significant differences of characters between native varieties caused the heritability of native lower than that of introduced except the heritability of days from blooming to mature and seed weight. 5. The genetic associations of characters, measured, with grain yield were partitioned in to direct and indirect effects, calculating path coefficients. The days to bloom, stem length and stem diameter were most significantly affected the grain yield in the 5th planting of native ones.

• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.236-246
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• 2014

Pesticide is used to protect the crops, but also become a cause of polluting the environment. Perform a risk assessment using physical and chemical properties, environmental fate and toxicity data in order to determine the pesticide registration. The aquatic model estimates pesticide concentrations in water bodies that result from pesticide applications to rice paddies and apple orchard. The used models are the PRZM, EXAMS and AGRO shell (PA5), Rice Water Quality Model (RICEWQ) and Screening Concentration In GROund Water (SCI-GROW). The residual concentration of water body was estimated using meteorological data, crop calendar and soil series of Korea. The chosen pesticides were butachlor, carbofuran, iprobenfos and tebuconazole. It has shown the potential that the RICEWQ is possible to predict residue level in water of butachlor and iprobenfos, because the maximum value in water monitoring data is lower than the peak concentration of the model, and the minimum value is lower than the average annual concentration of the model. But RICEWQ was insufficient to predict exposure concentrations in ground water. The estimated exposure concentrations of carbofuran in ground water is very higher than in surface water because of its low soil adsorption coefficient. Although tebuconazole were not detected in the water monitoring that means very low concentration, it is possible that the PA5 can be used to predict residue level in water.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6159-6166
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• 2012

A discharge measurement is difficult in flood season which is especially important in the water resources field and the continuous discharge measurement for all rivers is impossible on the present system. So, the stage-discharge curve has been used for a long time to produce discharge data of rivers. However, there has been problems from a reliability angle due to the fact that this method uses only stage-discharge relationship, although the stage-discharge curve has the convenience. Therefore, a new mean velocity equation was derived by using Chiu's 2D velocity formula of the entropy concept in this paper. The derived equation reflected hydraulic characteristics such as the depth, gravity acceleration, hydraulic radius, energy slope, kinematic coefficient of viscosity, etc. and estimated also a maximum velocity. In addition, this method verified the relationship between a mean and maximum velocity and estimates an equilibrium state ${\phi}(M)$ well presenting properties of a river cross section as the results. The mean velocity was estimated by using the equilibrium state ${\phi}(M)$, and then the discharge was estimated. To prove this equation to be accurate, the comparison between the measured and estimated discharge is conducted by using the measured laboratory data in the unsteady condition flow showing loop state and the results are consistent. If this study is constantly carried out by using various laboratory and river data, this method will be widely utilized in water resources field.

• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.595-625
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• 2012

Recently environment-friendly pellet boilers have interests as emissions of greenhouse gases are regulated internationally and energy security becomes more important to oil addicted countries including Republic of Korea. But the Korean market for pellet boilers is on the initial stage due to the high production costs relative to other conventional boilers. Hence the Korean government has supported financially and promoted the pellet boiler business. In this sense, it would contribute market stratergy and effective promotion policy for both of the government and private companies if we can forecast market shares of pellet boilers appropriately. For this purpose, this study surveyed potential consumers' preferences on pellet boilers among various alternatives using a choice experiment reflecting intangible costs. As the market share of new technology increases, intangible costs decline. According to different intangible cost scenarios, we experimented people's preferences on oil, gas, electric, and pellet boilers. A multinomial logit model was employed to estimate coefficient parameters of common attributes for various alternative boilers. Based on the estimates, we forecasted market shares of individual boilers. We found that as intangible costs decline, the market share of pellet boiler increase substantically while market shares of electric and gas boilers decrease dramatically. The market share of oil boiler did not change significantly. Meanwhile, as people are more rich, more educated, and exposed to advertisement on pellet boilers, the likelihood of choosing the pellet boiler increases.

• Journal of Korean Academy of Nursing Administration
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• v.4 no.1
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• pp.193-214
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• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein. 1967: Fishbein & Ajzen. 1975). the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances. continuing education opportunity. rigidity of the administration. paticipative decision making, latitude, group support, role conflict, work load, need for achievement. experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however. that path analysis can not count measurment errors: measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%), pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment, the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support, role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention, The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment', 'Rigidity of the administration' and latitude were also found to have important roles in predictingr the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of Korean Academy of Nursing Administration
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• v.4 no.1
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• pp.183-214
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• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein, 1967;Fishbein & Ajzen. 1975), the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances, continuing education opportunity, rigidity of the administration, paticipative decision making, latitude, group support, role conflict, work load, need for achievement, experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however, that path analysis can not count measurement errors; measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%). pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment. the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support. role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention. The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment'. 'Rigidity of the administration' and latitude were also found to have important roles in predictor for the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of the Korean earth science society
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• v.31 no.4
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• pp.301-312
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• 2010

Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.737-743
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• 2014

This experiment was conducted to compare heterogeneity for the variance in dairy cattle population and to induce homogeneity of variance using 502,228 performance test records of dairy cattle. The estimates of heritability for milk yields, fat yields and protein yields were 0.28, 0.26 and 0.24, respectively and the estimate of average breeding value by birth year was lower in HV (heterogenous variance) model than in animal model, collectively. The average breeding values of milk yields, fat yields and protein yields for 545 sire bulls applicable to the criteria of interbull MACE programme were 453.54kg, 10.75kg and 14.33kg, respectively and when the heterogeneity was adjusted they were 432.06kg, 10.15kg and 13.40kg, respectively, which were lower in all milk traits collectively. In animal model, coefficients of phenotypic correlation between dataset I and II were 0.839 in milk yields, 0.821 in fat yields, and 0.837 in protein yields, while in HV model, they were 0.841 in milk yields, 0.820 in fat yields, and 0.836 in protein yields, showing similar results in 2 models. When compared using animal model and HV model, the regression coefficient for ratio of number of daughters by calving year of milk yields increased from 15.157 to 16.105 and that of fat yields increased from =0.227 to =0.196, but that of protein yields decreased from 0.630 to 0.586.

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.405-422
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• 2014

Two important issues in hedonic model are to specify accurate model and delineate submarkets. While the former has experienced much improvement over recent decades, the latter has received relatively little attention. However, the accuracy of estimates from hedonic model will be necessarily reduced when the analysis does not adequately address market segmentation which can capture the spatial scale of price formation process in real estate. Placing emphasis on improvement of performance in hedonic model, this paper tried to segment real estate markets in Gangnam-gu and Jungrang-gu, which correspond to most heterogeneous and homogeneous ones respectively in 25 autonomous districts of Seoul. First, we calculated variable coefficients from mixed geographically weighted regression model (mixed GWR model) as input for clustering, since the coefficient from hedonic model can be interpreted as shadow price of attributes constituting real estate. After that, we developed a spatially constrained data-driven methodology to preserve spatial contiguity by utilizing the SKATER algorithm based on a minimum spanning tree. Finally, the performance of this method was verified by applying a multi-level model. We concluded that submarket does not exist in Jungrang-gu and five submarkets centered on arterial roads would be reasonable in Gangnam-gu. Urban infrastructure such as arterial roads has not been considered an important factor for delineating submarkets until now, but it was found empirically that they play a key role in market segmentation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3721-3729
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• 2014

Background: Cancer is becoming the most important public health burden around the globe. As per the GLOBOCAN 2008 estimates, about 12.7 million cancer cases and 7.6 million cancer deaths were estimated to have occurred in 2008. The burden of cancer cases for India in the year 2020 is calculated to be 1,148,757 (male 534,353; female 614,404) compared to 979,786 in 2010. The pattern of cancer incidence is varying among geographical regions, esophageal cancer for example being high in China, lung cancer in USA, and gallbladder cancer in Chile. The question remains why? Is it due to the diversity in genome pool, food habits, risk factor association and role of genetic susceptibility or some other factors associated with it? In India, the North East (NE)-India region is seeing a marked increase in cancer incidence and deaths, with a very different cancer incidence pattern compared to mainland India. The genome pool of the region is also quite distinct from the rest of India. Northeastern tribes are quite distinct from other groups; they are more closely related to East Asians than to other Indians. In this paper an attempt was made to see whether there is any similarity among the pattern of cancer incidence cases for different sites of NE-India region to South or East-Asia. Materials and Methods: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Pearson Correlation coefficient test was assessed to evaluate the linkage of North-East India region to other regions. A p value <0.05 was considered as statistically significant. Results: The results clearly shows that there are similarities in occurrence of cancer incidence patterns for various cancer sites of NE-India with South and East-Asian regions, which may lead to the conclusion that there might be a genetic linkage between these regions.