• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1180-1190
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• 2013

This study is to analyze femoral necks and lumbar spine bone mineral density in Korean men aged 60 or older 2,736 people, as well as to research in its relation to anthropometry, life style, diet, fracture history, family history of osteoporosis and medical history using data from Korea National Health and Nutrition Examination Survey (KNHANES)(the 2nd(2008) and 3rd(2009) year at the 1st survey, and the 1st(2010) year at the 5th survey). To express the strength of the associations, percent differences were calculated from multiple linear regression models using the formula ${\beta}{\times}$(unit/mesnBMD). Unit for continuous variables were chosen to approximate 1 standard deviation(SD). Prevalence of osteoporosis for 60-69, 70-79 and >80 old men were 6.7%, 15.8% and 31.4% respectively. The proportion of osteoporosis calculated for each age group in the femoral neck group was: 60-69 years old, 2.6%, 70-79years old, 8.2%, >80years old, 24.8%. For the lumbar spine group, the values were: 60-69 years old, 5.5%, 70-79years old, 11.3%, >80years old, 15.4%. In men aged 60 or older, lean mass greatly influenced bone density in the femoral neck and lumbar spine. Thus, to increase the lean mass would be an effective way to prevent osteoporosis in elderly men.

• Journal of Preventive Medicine and Public Health
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• v.39 no.4
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• pp.302-308
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• 2006

Objectives: This study aims to examine if a garbage dumping site has real and negative influence on the quality of life (QOL) for the nearby residents. The net effects of the residential distance from the garbage dumping site and from the garbage truck route were investigated for five domains of the QOL. Methods: Two hundred fifty seven Shin-dong Myeon residents, Chun-cheon Si, participated in a self-administrated survey. The Shin-dong Myeon garbage dumping site began operating in 1996. ANCOV A with generalized linear models and multiple regression analysis were performed. Results: Descriptive analyses show that a residence nearby a garbage dumping site is negatively associated with the physical and environmental domains of the QOL. The residential distance from the garbage truck route does not exert any significant effect on various domains of QOL, except for the environmental domain. On the multivariate analysis, the residents living near the garbage dumping site tended to have a significantly negative QOL in the physical and environmental domains. However, the distance from the garbage truck route did not show a significant nor substantial effect on the QOL. The demographic and socioeconomic control variables are associated with a number of the QOL domains, and their patterns are consistent with the general expectations. Conclusions: The results indicated that a garbage dumping site is considered to be an environmental hazard among the nearby residents according to the lower scores on the physical and environmental domains of the QOL. The findings from this study provide comprehensive understanding on the residents' QOL, and they may help politicians and policy makers make decisions for appropriate interventions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.93-100
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• 2008

The parameters of lens such as focal length, focus, and aperture stop changes while shooting the scenes with zoom lens. Especially, zooming action dramatically changes the geometry of lens system that causes significant change of lens model. We investigated how the lens model changes while zooming in general shooting condition. Each parameters of lens model was estimated and checked whether they can be modeled well in the condition of auto-controlling focus, aperture and vibration reduction. In order to do this, calibration images were taken, modeled in different fecal length setting. And changing patterns of models were inspected to find out if there is some elements that have some particular pattern in changing with respect to focal length. The result showed us that although we didn't control the focus and aperture setting, there's specific changing patterns in radial and do-centering distortion. Especially, the strong linear correlation was found between coefficient of $r^2$ and focal length. It is expected that many parts of distortion can be eliminated without additional self calibration even if zoom operation is done when shooting the scenes if we know its fecal length and model of this coefficient.

• Journal of Nutrition and Health
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• v.52 no.6
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• pp.552-558
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• 2019

Purpose: Although vitamin D deficiency is common among Korean adolescent girls and young women, few studies have explored the potential health effects of vitamin D deficiency in this vulnerable population. This study examined the association between vitamin D deficiency and anemia in Korean adolescent girls and young women. Methods: The data from the Korea National Health and Nutrition Examination Survey 2008 ~ 2014 were used. A total of 3,643 girls and adult women aged 12 to 29 who provided all the information (including serum 25-hydroxy vitamin D, hemoglobin, and/or serum ferritin) needed for the analysis were included in the analysis. Demographic, lifestyle, and health data were obtained through survey questionnaires. Anemia and iron deficiency anemia were defined according to the World Health Organization cut-offs. Multivariable logistic regression, and restricted cubic spline regression were used in the analysis. Results: In fully adjusted logistic regression models, the vitamin D deficiency was significantly associated with higher prevalences of anemia (odds ratio (OR): 1.61, 95% confidence interval (CI): 1.04 ~ 2.49) and iron deficiency anemia (OR: 1.43, 95% CI: 1.01 ~ 2.03). In a cubic spline regression model, we observed a dose-response relationship between serum 25(OH)D concentration and anemia, and this linear relationship was also clearly observed between serum 25(OH)D concentration and iron deficiency anemia. Conclusion: Vitamin D deficiency may be associated with a higher prevalence of iron deficiency anemia and anemia in adolescent girls and young women. Alternatively, vitamin D deficiency may be a concurrent event for patients with anemia, which we cannot distinguish in this cross-sectional study. Further studies are needed to verify the causality in this population of low vitamin D levels.

• Journal of Nutrition and Health
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• v.46 no.5
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• pp.410-417
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• 2013

Caloric restriction is recognized as one of the best treatment options for obesity, and is associated with changes in body composition. The purpose of this study was to determine the influence of age in caloric restriction in overweight and obese women. In this caloric restriction study, nutrient intake of 61 women was evaluated using food records written by subjects for three days. Body composition and metabolic risk factors were assessed before and after caloric restriction. Blood levels of lipids, glucose, leptin, and adiponectin were measured. Visceral fat and subcutaneous fat were evaluated using bioimpedance analysis. General linear models (GLM) identified the independent effects of age after co-varying baseline weight and difference of energy intake. Weight, fat mass, visceral fat, subcutaneous fat, and blood pressure showed a significant decrease by caloric restriction of 452 kcal/day. The percent changes in weight, visceral fat, and subcutaneous fat were -4.5%, -12.0%, and -8.2%, respectively, after caloric restriction. The percent changes of weight, visceral fat, and subcutaneous fat showed an independent association with age co-varying baseline weight and difference of energy intake. Decreased change in percent of leptin by caloric restriction also showed an association with age. Changes in body composition and leptin by caloric restriction showed an independent association with age. This may indicate greater difficulty in achievement of change of body composition as well as greater obesity-related metabolic risk with aging. Therefore, caloric restriction considering age should be recommended for effective dietary treatment in overweight or obese women.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.

• Journal of Sasang Constitution and Immune Medicine
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• v.32 no.3
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• pp.33-45
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• 2020

Object Although Taeeum and Soyang constitutional types have bigger body shapes and higher body mass index values than those with the Soeum, the relationship between the Sasang constitutional type and bone mass density is controversial and the association of osteopenia and osteoporosis remains unknown. Therefore, we investigated the relationship between bone mineral density, osteopenia, and osteoporosis according to Sasang constitutional type. Methods A total of 2,508 participants were included in this study. Among the study participants, 1,396 had Taeeum type, 276 had Soeum type, and 836 had Soyang type, respectively. The relationships to bone mass density, osteopenia, and osteoporosis in those with Sasang constitutional type were estimated using logistic and linear regression models. Results Bone mass density was significantly higher in the order of Taeeum, Soyang, and Soeum group (p < 0.01). Soeum group in comparison with Taeeum or Soyang group was significantly associated with a high odds ratio for osteopenia and osteoporosis except in the hip and femoral neck in the comparison of Taeeum and Soeum group (p < 0.01). Moreover, the bone mass density of Soeum group decreased more rapidly as the age increased when compared with Taeeum and Soyang group. Conclusions Our findings may contribute to the early prevention and management of high-risk individuals with poor bone mass density, osteopenia, and osteoporosis using Sasang constitution medicine.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.26-33
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• 2005

Inversion of multi-mode surface-wave phase velocity for shallow engineering site investigation has received much attention in recent years. A sensitivity analysis and inversion of both synthetic and field data demonstrates the greater effectiveness of this method over employing the fundamental mode alone. Perturbation of thickness and shear-wave velocity parameters in multi-modal Rayleigh wave phase velocities revealed that the sensitivities of higher modes: (a) concentrate in different frequency bands, and (b) are greater than the fundamental mode for deeper parameters. These observations suggest that multi-mode phase velocity inversion can provide better parameter discrimination and imaging of deep structure, especially with a velocity reversal, than can inversion of fundamental mode data alone. An inversion of the theoretical phase velocities in a model with a low velocity layer at 20 m depth can only image the soft layer when the first higher mode is incorporated. This is especially important when the lowest measurable frequency is only 6 Hz. Field tests were conducted at sites surveyed by borehole and PS logging. At the first site, an array microtremor survey, often used for deep geological surveying in Japan, was used to survey the soil down to 35 m depth. At the second site, linear multichannel spreads with a sledgehammer source were recorded, for an investigation down to 12 m depth. The f-k power spectrum method was applied for dispersion analysis, and velocities up to the second higher mode were observed in each test. The multi-mode inversion results agree well with PS logs, but models estimated from the fundamental mode alone show f large underestimation of the depth to shallow soft layers below artificial fill.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.