• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.136-152
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• 2017

The thermodynamic models, PC-SAFT (Perturbed-Chain Statistical Associated Fluid Theory) state equation and the Two-model approach liquid activity coefficient model NRTL (Non Random Two Liquid) + Henry + Peng-Robinson, for modeling the Rectisol process using methanol aqueous solution as the $CO_2$ removal solvent were compared. In addition, to determine the new binary interaction parameters of the PC-SAFT state equations and the Henry's constant of the two-model approach, absorption equilibrium experiments between carbon dioxide and methanol at 273.25K and 262.35K were carried out and regression analysis was performed. The accuracy of the newly determined parameters was verified through the regression results of the experimental data. These model equations and validated parameters were used to model the carbon dioxide removal process. In the case of using the two-model approach, the methanol solvent flow rate required to remove 99.00% of $CO_2$ was estimated to be approximately 43.72% higher, the cooling water consumption in the distillation tower was 39.22% higher, and the steam consumption was 43.09% higher than that using PC-SAFT EOS. In conclusion, the Rectisol process operating under high pressure was designed to be larger than that using the PC-SAFT state equation when modeled using the liquid activity coefficient model equation with Henry's relation. For this reason, if the quantity of low-solubility gas components dissolved in a liquid at a constant temperature is proportional to the partial pressure of the gas phase, the carbon dioxide with high solubility in methanol does not predict the absorption characteristics between methanol and carbon dioxide.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Convergence Security Journal
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• v.8 no.3
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• pp.83-92
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• 2008

In respect complication of group and period, the sales of retail trade is composed of various factors. This paper studies focus on estimating the determinants of the sales of retail trade. The volume of analysis consist of 7 groups. Analyzing period be formed over a 36 point(2005. 1$\sim$2007. 12). In this paper dependent variable setting up sales of retail trade, explanatory(independent) variables composed of composite stock price index, the number of the consumer's online buying behavior company, the coincident composite index, the index of trading price of APT, employment rate, an average of the rate of operation(the manufacturing industry), the consumer price index. The result of estimating the determinants of sales of retail trade provides empirical evidences of significance positive relationships between the coincident composite index, the index of trading price of APT, employment rate, an average of the rate of operation(the manufacturing industry). However this study provides empirical evidences of significance negative relationships between the consumer price index. The explanatory variables, that is, composite stock price and the number of the consumer's online buying behavior company, are non-significance variables. Implication of these findings are discussed for content research and practices.

• Journal of Animal Science and Technology
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• v.52 no.2
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• pp.91-96
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• 2010

The purpose of the study was to develop an optimum SNP marker set to be utilized for domestic pork traceability. The study tested 51 SNP markers analyzed for origin of farm to be determined from genotypes of offspring and parents in pigs. With the simulation data through random mating population (PI), half sib mating population ($PI_{half-sib}$) and full sib mating population ($PI_{sibs}$), probability of identical genotypes were analyzed as $5.63{\times}10^{-33}$, $4.35{\times}10^{-15}$ and $1.32{\times}10^{-15}$, respectively. The 51 SNP markers also had 100% accuracy for parental determination. These results suggest that if the pig breeding stock is genotyped with the 51 SNP markers, the genotype information of individual offspring can be checked for farm origins by tracing parental sow and sire. Therefore, these SNP markers will be useful to trace the pork from production to consumption in pigs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.153-160
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• 2010

It is necessary to determine accurate 3-dimensional coordinates of the building corner points that could be control or check points in order to verify the accuracy of 3D digital maps in the near future. The usual process of obtaining the coordinates of the building corner points is to set up the ground control points with a GPS and then to practice terrestrial survey such as distance or angle measurements. However, since an error in the ground control points can be propagated through the terrestrial survey into the final coordinates of the buildings, accurately should be considered as much as possible. The actual effect of the GPS-derived ground control point error on the estimates of the unknowns through the terrestrial survey is mathematically analyzed, and the simulation data is tested numerically. The error of the ground control points is tested in the cases of 1-4 cm for the horizontal components and 2-8 cm for the vertical component. The vertical component error is assigned twice the horizontal ones because of the characteristics of the GPS survey. The distance measurement is assumed for convenience and the precision of the estimated coordinates of the building corner points is almost linearly increased according to the errors of the ground control points. In addition, the final estimates themselves can vary by the simulated random errors depending on the precision of the survey instrument, but the precision of the estimates is almost independent of survey accuracy.

• Journal of dental hygiene science
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• v.7 no.4
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• pp.295-302
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• 2007

The purpose of this study is to make formulated examination and analysis about major two factors of dental hygienic students' satisfaction at clinical training, i.e. the contents of clinical training and their duties satisfaction, so that it can provide a basic reference material for more efficient clinical training and education. This study conducted a questionnaire survey for 427 students who were taken via simple random sampling from sophomore and junior dental hygienic students, who already experienced in clinical training courses, at some universities(and colleges) in Metropolitan and province areas. The data collected from this survey were analyzed using SPSS WIN 11.5, in parallel with t-test, one-way ANOVA and ${\chi}^2$(Chi-square) test. It was found that our students didn't feel so much satisfied at clinical training(satisfaction level = 3.34). Overall, they didn't show any significant satisfaction with the contents of training and the experiences in clinical training duties. Our dental hygiene students showed relatively low satisfaction with the contents of clinical training as well as satisfaction at clinical training duties, which ie that current clinical training in dental hygienics still remain at the level of simple assistance for dental treatment.

• Journal of Fashion Business
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• v.10 no.5
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• pp.93-104
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• 2006

The main purpose of this research is to examine what are the factors that affect consumer attitude by the types of clothing window display, and find if there is any difference by gender of consumer group. Total 357 data from random sample of 347 adults(156 male and 191 female) who were between 19 to 49 years of age were analyzed. Sources for the sample were companies and apartment complexes and several colleges in Seoul and Chonan to diversify by such demographics as age and social status. Factors were measured by respondents' rating of 9 statements using a 5-point Likert-type scale. SPSS(Statistical Package for Social Science) Version 10.0, is used for factor analysis in order to comprehend the factors of consumer attitude and Cronbauch's ${\alpha}$ in order to measure the credibility of questions in each factor. The main findings are as follows: First, three dimensions of consumer attitude to two types of window-display of product centered display and image centered display were identified as interest, information, and impression and theses are same to both male and female consumer group. Second, for both male and female consumer group, three dimensions of consumer attitude toward two types of window-display were same, however, included sub categories in each dimension showed a little difference. In product centered display, both male and female consumer group showed high interest in the sub categories of 'fashion' and 'informations related to the product' and they were considered same factor. Otherwise, In image centered display, two sub categories of 'having some interests in the display' and 'recognize the display that projects the image or impression of clothing well' were showed high relationship each other and they were also considered same factor. Third, Cronbauch's ${\alpha}$ of three dimensions of consumer attitude demonstrated high credibility from 0.75 to 0.91. Mean score of subcategories of attitudes toward the type of display by the gender of consumer showed high scores of 'interest' and 'impression' categories in image centered display and showed high scores of 'information' category in product centered display for both gender.

• Journal of Korean Public Health Nursing
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• v.11 no.1
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• pp.66-81
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• 1997

This study examined the experience of health education and assessed the needs for health education in the students attending a university located in Inchon. The primary subjects were 749. who were selected from each college by using systematic random sampling. Of these students. 457 subjects responded to the self-reported questionnaire. revealing the response rate of $61.01\%$. As for the analysis of the data. percentages. chi-square test. and correlation and regression analyses were adopted. The experience rate of health education was 39.02% and the rate was higher in women than in men. The students experienced the education about smoking and first-aid most frequently. whereas they experienced stress management much less frequently. Stress management was given the highest priority among the subjects of health education which they proposed to need. Physical health states of the students were better than their mental health states. The women tended to eat meals irregularly compared to men. Those students living not with their family nor with their relatives were more likely to eat meals twice a day compared to those who live at their homes. Those who recognized the need for health education showed the willingness to join health education to be given. The willingness was, also observed in those who had better self-evaluated mental health. regardless of the recognition of the need for health education. These findings revealed both objective and subjective needs for educating management of mental health. Education on healthy eating habit should be given particularly to woman students and those who do not live with family nor with relatives. When educating for the management of mental health. there should be strategies to facilitate the participation of the students who do not have good mental health.

• Journal of Periodontal and Implant Science
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• v.47 no.5
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• pp.264-272
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• 2017

Purpose: This study evaluated trends in tooth extraction due to acute and chronic periodontal disease (PD) using data from the National Health Insurance Service-National Sample Cohort for 2002-2013. Methods: A random sample of 1,025,340 individuals was selected as a representative sample of the population, and a database (DB) of diagnostic and prescription codes was followed up for 12 years. We used multivariate logistic regression analysis to assess the incidence of total extraction (TE), extraction due to periodontal disease (EPD), and immediate extraction due to periodontal disease (IEPD) according to sociodemographic factors (sex, age, household income, health status, and area of residence). Results: The incidence of tooth extraction was found to be increasing, and at a higher rate for TE in PD patients. In 2002, 50.6% of cases of TE were caused by PD, and this increased to 70.8% in 2013, while the number of cases of IEPD increased from 42.8% to 54.9% over the same period. The incidence rates of extraction due to acute and chronic PD increased monotonically. We found that the incidence rates of TE, EPD, and IEPD were all 2-fold higher among patients with high income levels and those who were not beneficiaries of health insurance. Conclusions: The rates of TE, EPD, and IEPD have been steadily increasing despite dental healthcare policies to expand public health insurance coverage, increasing the accessibility of dental clinics. Moreover, the effects of these policies were found to vary with both income and education levels. Consistent patient follow-up is required to observe changes in trends regarding tooth extraction according to changes in dental healthcare policies, and meticulous studies of such changes will ensure optimal policy reviews and revisions.