• Korean Journal of Clinical Laboratory Science
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• v.43 no.1
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• pp.12-18
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• 2011

The purpose of this study was to evaluate the significance of higher than normal mean corpuscular volume (MCV) and lower than normal mean corpuscular hemoglobin concentration (MCHC) in 20 patients. The hemoglobin (Hb), red blood cell indices (MCV, MCH, MCHC,), red cell distribution width (RDW), serum ferritin, serum iron (Fe) and total iron binding capacity (TIBC) were measured and the transferrin saturation were calculated. 18 (90.0%) cases were categorized as chronic diseases. Chronic renal failure, malignancy, and bleeding were all related to the cases. The mean values of hemoglobin was $9.5{\pm}2.14g/dL$; the MCV was $29.0{\pm}2.8fL$; the MCH was $30.9{\pm}1.0pg$; the MCHC was $31.2{\pm}0.5%$; the RDW was $17.0{\pm}3.6%$; serum Fe was $39{\pm}21{\mu}g/dL$; the TIBC was $219.7{\pm}108.8{\mu}g/dL$; transferrin saturation was $19.2{\pm}9.9%$ and ferritin was $445.5{\pm}499.6{\mu}g/L$ in the patients. The WHO criteria for hemoglobin of patients confirms anemia in 18 of the 20 (90.0%) cases. Anemia of chronic disease was shown in 11 (73.3%) cases; acute gastric ulcer with hemorrhage in 1 (6.7%) case; iron deficiency anemia in 1 (6.7%) case; 2 patients (13.3%) were of normal cases. There were changes in the baseline Hb level results of the 19 (95.0%) cases while no change was shown in 1 case. As a result, diseases associated with anemia and bleeding where the MCV is higher than the normal range and MCHC is lower than normal range are considered relevant findings.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.185-195
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• 2018

In the Seoul Metropolitan City, the PM(pariculate matter) application used by the citizens provides the PM concentration of the nearest monitoring stations located on the PM monitoring stations. Currently, the selecting method of the PM monitoring network considered by the Ministry of Environment is based on considering the monitoring station distribution and population density only. In this study, we analyzed the distance between PM monitoring station and the administrative center point in addition to the above considerations. The number of test sites was verified and the range of coverage of each monitoring stations was indicated by using the Voronoi algorithm and hexagon grid. The spatial position problem of the PM monitoring station was suggested by spatial data analysis. The variables of spatial data analysis are single-family houses, apartments, $1^{st}$ class neighborhood, $2^{nd}$ class neighborhood, garbage disposal plant, hazardous material disposal facility, factory, and the density map. The analysis result of the selection criterion considering the additional variables for new PM monitoring stations was presented, in addition to the selection criteria provided by the Ministry of Environment.

• Journal of Wind Energy
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• v.14 no.2
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• pp.26-33
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• 2023

In this study, the global response characteristics of floater and mooring for floating offshore wind turbine with a detachable mooring system are performed. Global motion and structural response result extracted from the coupled motion analysis of 10MW DTU floating offshore wind turbine with detachable mooring system modeled by high-order boundary element model and finite element mesh, were used to study the characteristics of tension on mooring lines subjected to three different types of ocean loads. Breaking limit of mooring line characterized by wind, current and wave load has a major effect on the distribution of mooring tension found in time domain analysis. Based on the numerical results of coupled motion analysis, governing equation for calculating the motion response of a floater under ocean loads, and excitation force and surge motion and tension respectively are presented using excursion curve. It is found that the response of floater is reliable and accurate for calculating the tension distributions along the mooring lines under complex loadings. This means that the minimun breaking limit of mooring system satisfied a design criteria at ultimate ocean environmental loading condtions.

• The Journal of Industrial Distribution & Business
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• v.11 no.7
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• pp.29-40
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• 2020

Purpose: In modern society, many urban problems are occurring, such as aging, hollowing out old city centers and polarization within cities. In this study, we intend to apply big data and machine learning methodologies to predict depression symptoms in the elderly population early on, thus contributing to solving the problem of elderly depression. Research design, data and methodology: Machine learning techniques used random forest and analyzed the correlation between CES-D10 and other variables, which are widely used worldwide, to estimate important variables. Dependent variables were set up as two variables that distinguish normal/depression from moderate/severe depression, and a total of 106 independent variables were included, including subjective health conditions, cognitive abilities, and daily life quality surveys, as well as the objective characteristics of the elderly as well as the subjective health, health, employment, household background, income, consumption, assets, subjective expectations, and quality of life surveys. Results: Studies have shown that satisfaction with residential areas and quality of life and cognitive ability scores have important effects in classifying elderly depression, satisfaction with living quality and economic conditions, and number of outpatient care in living areas and clinics have been important variables. In addition, the results of a random forest performance evaluation, the accuracy of classification model that classify whether elderly depression or not was 86.3%, the sensitivity 79.5%, and the specificity 93.3%. And the accuracy of classification model the degree of elderly depression was 86.1%, sensitivity 93.9% and specificity 74.7%. Conclusions: In this study, the important variables of the estimated predictive model were identified using the random forest technique and the study was conducted with a focus on the predictive performance itself. Although there are limitations in research, such as the lack of clear criteria for the classification of depression levels and the failure to reflect variables other than KLoSA data, it is expected that if additional variables are secured in the future and high-performance predictive models are estimated and utilized through various machine learning techniques, it will be able to consider ways to improve the quality of life of senior citizens through early detection of depression and thus help them make public policy decisions.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.1
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• pp.72-82
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• 2008

Benzene is a very harmful and toxic compound known as human carcinogen by all routes of exposure. Owing to the risky feature of benzene, several countries such as Japan, UK and EU have established the ambient air quality standard and protect from that risk of it. Korea also has designated it as one of the criteria air pollutants and established the concentration limit ($5\;{\mu}g/m^3$) in the air and is going to apply the standard from 2010. Benzene is emitted from various sources such as combustion plants, production processes, waste treatment facilities and also automobiles. Mobile source is known as one of the major emission sources of benzene. In this study, we estimated the domestic emissions of benzene from mobile source and compared the results with those of advanced countries. Mobile source was divided into 2 categories, Le., on-road source and non-road source. The total emissions of benzene from mobile source were estimated as 3,106 tons/yr and 1,612 tons/yr was emitted from on-road source and 1,494 tons/yr was from non-road source. Emission ratio of benzene from on-road source showed that 80.0% was from passenger cars, 10.1% was from taxis, 7.2% was from light-duty vehicles, 2.5% was from heavy-duty vehicles and 0.2% was from buses. In the case of non-road source, the distribution showed that 66.3% was from construction machineries, 14.5% was from locomotives, 11.7% was from ships, 7.1% was from agriculture equipments and 0.5% was from aircrafts. The cold-start emissions were estimated as 942 tons/yr and this value was almost 1.5 times greater than that for hot engine emissions (608 tons/yr). In addition, the fuel-based distribution was 65.9%, 31.1% and 2.8% from gasoline, LPG and diesel vehicles, respectively. The emission ratio from mobile source occupied 65% and 30% of total benzene emissions in USA and UK, respectively. In case of Korea, the emission ratio of benzene from mobile source occupied 29% (15% from on-road source, 14% from non-road source) which showed similar value with UK.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.795-814
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• 2021

With the development of science and technology in recent years, various types of unstructured buildings have begun to be implemented by combining traditional architectural styles with digital tools, which are significantly different from conventional formal buildings. Designers will use various methods or digital tools to complete the unstructured and freer architectural forms when building an unstructured building. Based on this background, the need for research on the criteria for evaluating the characteristics of unstructured architectural forms is raised. First, the text was reconstructed by considering and integrating the elements of the unstructured exterior form based on prior research, with the external form of the unstructured building as the main research object. Second, the purpose of this study was to classify various types of unstructured forms and to provide important basic data for designing digital processes of unstructured architectural forms.Third, from 2000 to 2020, the text focused on the study of unstructured buildings and conducted in-depth analysis of the characteristics of their form expressions. While providing a case basis for the study of related fields, distribution laws and presence values related to the characteristics of unstructured buildings were sought. In addition, the analysis was conducted in combination with the distribution of functional use of buildings, and this study is differentiated from the existing research in that the atypical form is applied to the buildings by use, and the application trend of this type is understood to enhance understanding of the atypical form of buildings.

• Journal of Educational Research in Mathematics
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• v.23 no.4
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• pp.467-490
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• 2013

Correlation is a basic statistical concept which is necessary for understanding the relationship between two variables when they change values. In the middle school curriculum of Korea, only informal definition of correlation is taught with two-way data representations such as scatter plots and contingency tables. In this study, we investigated Korean high school students' understanding of correlation using a test consisting of 35 items about interpretation of scatter plot, contingency table, and text in realistic situation. 216 students from a high school in Seoul took the test for 20 minutes. From the results, we could observe the following: First, students did not have right criteria for determining the strength of correlation presented in scatter plots. Most of students could determine if there is correlation/no correlation and if the correlation is positive/negative by seeing the data presented in scatter plots. However, they did not judge by the closeness to the regression line but rather judged by the closeness between data points. Second, when statements about comparing the strength of correlation in the context of real life situation were given in text, the students had difficulty in understanding the distribution-related characteristic of the bi-variate data. Students had difficulty in figuring out the local distribution characteristic of data, which cannot be guessed merely based on the expression 'The correlation is strong' without statistical knowledge of correlation. Third, a large number of students could not judge the association between two variabels using conditional proportions when qualitative data are given in 2-by-2 tables. They made judgement by the absolute cell count and when the marginal sum of two categories are different for explanatory variable they thought the association could not be determined. From these results, we concluded that educational measures are required in order to remove such misconceptions and to improve understanding of correlation. Considering that the current mathematics curriculum does not cover the concept of correlation, we need to improve the curriculum as well.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.4
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• pp.661-669
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• 2000

This research was carried out to evaluate effect of metallic release and change of water corrosive indices by the pH and alkalinity adjustment using the SDLS (Simulated Distribution Loop System) which consist of six types of pipe loop with DCIP, PVC, PE, STS304, CP, GSP, respectively, and its effects on water quality changes which were microbes quality(SPC), residual chlorine. THMs and other parameters. And it was to propose optimal criteria of water quality control for the field application. According to the results, water control system by pH and alkalinity adjustment showed the changing of corrosive water and reducing of metallic release rate and it was not affects of THMs formation, microbes regrowth and variation of other parameters. Water quality stability and corrosion control were due to calcium carbonate precipitation film formation of pipe inner by water quality control. Therefore, corrosive water control system by pH and alkalinity adjustment can be attributed to effective water quality management in water distribution system according to water quality stability of pH and TIC(Total Inorganic Carbonate concentration) that affect the precipitation and dissolution of solids.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.167-176
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• 2005

This paper describes how the state tying model based on the decision tree which is one of Acoustic models used for speech recognition optimizes the model by reducing the number of mixture Gaussians of the output probability distribution. The state tying modeling uses a finite set of questions which is possible to include the phonological knowledge and the likelihood based decision criteria. And the recognition rate can be improved by increasing the number of mixture Gaussians of the output probability distribution. In this paper, we'll reduce the number of mixture Gaussians at the highest point of recognition rate by clustering the Gaussians. Bhattacharyya and Euclidean method will be used for the distance measure needed when clustering. And after calculating the mean and variance between the pair of lowest distance, the new Gaussians are created. The parameters for the new Gaussians are derived from the parameters of the Gaussians from which it is born. Experiments have been performed using the STOCKNAME (1,680) databases. And the test results show that the proposed method using Bhattacharyya distance measure maintains their recognition rate at $97.2\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. And the method using Euclidean distance measure shows that it maintains the recognition rate at $96.9\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. Then the methods can optimize the state tying model.