• Clinical and Experimental Pediatrics
• /
• v.48 no.10
• /
• pp.1082-1089
• /
• 2005

Purpose : Abdominal obesity is encountered as a risk factor for cardiovascular diseases. However, the anthropometric cut-off value to estimate the cardiovascular risk, has not been suggested. This study was designed to find the relationship between the abdominal fat and various parameters of obesity to find the cardiovascular risk factors related to abdominal obesity and to establish practical methods to measure them. Methods : Twenty seven obese Korean adolescents of moderate to severe degree and 22 healthy adolescents were enrolled. The body mass index(BMI), arm circumference and skinfold thickness were measured. Furthermore, blood lipid, sugar, insulin and four different cytokines' levels were checked and the distribution of body composition was measured by bioelectrical impedance analysis. The subcutaneous and intra-abdominal fat thickness by abdominal ultrasonography(US) and the total and intra-abdominal fat area by abdominal computerized tomography(CT) were measured in the obese group. Results : The most accurate method to measure abdominal fat in children is abdominal CT and the fat mass measured by bioelectrical impedance was strongly correlated with it(r=0.954). It was also correlated with arm circumference, fat thickness measured by abdominal US, BMI, aspartate aminotransferase(AST), alanine aminotransferase(ALT) and triglyceride level. Conclusion : Abdominal CT is the most accurate method to measure intra-abdominal fat, and it can be replaced by abdominal US for cost effectiveness. The screening methods that can be used at school or in outpatient basis include bioelectrical impedance, waist/hip ratio, and arm circumference. The cardiovascular risk factors include leptin, triglyceride and insulin level.

• Restorative Dentistry and Endodontics
• /
• v.33 no.6
• /
• pp.507-517
• /
• 2008

There are considerable in vitro and in vivo evidences for remineralization and demineralization occurring simultaneously in incipient enamel caries. In order to "heal" the incipient dental caries, many experiments have been carried out to determine the optimal conditions for remineralization. It was shown that remineralization is affected by different pH, lactic acid concentrations, chemical composition of the enamel, fluoride concentrations, etc. Eighty specimens from sound permanent teeth without demineralization or cracks, 0.15 mm in thickness, were immersed in lactic acid buffered demineralization solutions for 3 days. Dental caries with a surface zone and subsurface lesion were artificially produced. Groups of 10 specimens were immersed for 10 or 12 days in lactic acid buffered remineralization solutions consisting of pH 4.3 or pH 6.0, and 100, 50, 25, or 10 mM lactic acid. After demineralization and remineralization, images were taken by polarizing microscopy (${\times}100$) and micro-computed tomography. The results were obtained by observing images of the specimens and the density of the caries lesions was determined. 1.As the lactic acid concentration of the remineralization solutions with pH 4.3 was higher, the surface zone of the carious enamel increased and an isotropic zone of the subsurface lesion was found. However, the total decalcification depth increased at the same time. 2.In the remineralization solutions with pH 6.0, only the surface zone increased slightly but there was no significant change in the total decalcification depth and subsurface zone. In the lactic acid buffer solutions with the lower pH and higher lactic acid concentration, there were dynamic changes at the deep area of the dental carious lesion.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.32 no.2
• /
• pp.82-94
• /
• 2014

This study aims to comprehend that Gwanghalluwon for aspects of landscape change in terms of construction garden(樓園). Transformation focused on the spatial structure is divided into four periods based on literature. And reflect of landscape elements in defunct or unattributable records from tale and novel. The results were as follows. First, The beginning of Gwanghanllu pavilion(廣寒樓) was the composition of the Gwangtongnu Pavilion(廣通樓). The pavilion is located amid beautiful scenery such as the close-range view of a small stream, and distant view Jiri Mountain. Analysis of literature shows that Gwanghallu pavilion was in succession to Gwangtongnu Pavilion's landscape. Secondly, Gwanghallu(廣寒樓) pavilion represents the characteristic of the garden since 1582. Built the Samsinsan(三神山), Construct Lake and bridge that represents the galaxy for realization of utopia reflect in Taoist ideology. Thirdly, Gwanghalluwon garden was recovered when from Jeong-yu-jae-ran(丁酉再亂) to the Japanese Ruling Era. It took Gwanghalluwon garden a long while to recover from original form. According to records, Gwanghalluwon garden is still being likened to the landscape of fairyland by inheriting landscape in the previous of Jeong-yu-jae-ran(丁酉再亂). Fourth, By the modern times, Gwanghalluwon Garden has personality of tourist attractions. Until now, the area of the Gwanghalluwon garden has been expended during the processes of three times. Fifth, Aspect of landscape change of Gwanghalluwon is wide-spreading mainly Gwanghallu pavilion. But elements of external expansion in garden by introduced into the facility irrelevant to the authenticity of the garden. Sixth, Comprehension the cultural landscape of the garden are limited by deficient records. But, the main elements in the Gwanghalluwon garden are commonly appeared on imaginary environment within a tale and a novel. In addition, culture of garden at the time was depicted in tale and novel. In this sense, cultural landscape in garden was able to estimate through imaginary environment within novel.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.14 no.3
• /
• pp.148-157
• /
• 1981

This experiment was carried out to evaluate the sanitary quality of sea water at popular swimming beaches such as Haeundae, Kwanganri and Songjeong which are located in the suburbs of Busan Korea. One hundred and seventy five sea water samples were collected from the 25 stations during the both summer seasons in 1979 and in 1980. The sampling stations were established in the above 3 swimming beaches and the estuary of Suyeong river (See Fig.1.). To evaluate the sanitary quality, coliform group, fecal coliform, viable cell count and Vibrio parahaemolyticus were observed. The median value of coliform group MPN of the samples ranged 2,300 to 6,500/100m1 in Kwanganri, 670 to 910/100m1 in Haeundae and 430 to 460/100m1 in Songjeong swimming beach. Geometric mean of fecal coliform MPN was 3,200/100m1 in Kwanganri, 500/100m1 in Haeundae and 360/100m1 in Songjeong swimming beach. Composition of coliform was $23\%$ Escheri-chia coli group, $20\%$ Citrobacter freundii group, $41\%$ Klebsiella aerogenes group and $16\%$others. The density of Vibrio parahaemolyticus in Kwanganri was much higher than those of in other beaches by 5 to 6 times. Plate count of the samples in the estuary of Suyeong river was varied from 300 to $8.5\times10^6/ml$ during the study period. No remarkable difference was observed in bacterial density by tide in swimming beaches but the bacterial density of sea water at ebb tide was obviously higher than those of the samples at flood tide in the estuary of Suyeong river.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.23-45
• /
• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.