• Korean Journal of Community Nutrition
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• v.19 no.2
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• pp.163-175
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• 2014

Objectives: We aimed to evaluate dietary intake among female breast cancer survivors in a cross-sectional study. Methods: A total of 127 women who had breast cancer surgery at least 6 months before baseline were included. Dietary intake of female breast cancer survivors was assessed through self-reported 3 day-dietary records. To compare dietary intake between breast cancer survivors and general female population without cancer, we selected the 1:4 age matched women from the 2011 Korean National Health and Nutrition Examination Survey (KNHANES). In the KNHANES, participants were asked about their dietary intake using the 24-hour dietary recalls. We also examined whether dietary intake varied by age group, cancer stage, or time since surgery among breast cancer survivors. We used the generalized linear model to compare their dietary intakes. Results: Intakes of total energy, beta-carotene, folate, vitamin C, plant iron and fruits were lower among breast cancer survivors with longer time since surgery compared to those with shorter time (p<0.05). Breast cancer patients with higher stage at diagnosis tended to consume less legumes (p=0.01) than those with lower stage. When we compared dietary intake between breast cancer survivors and the general female population without cancer, breast cancer survivors were more likely to consume most of macro- and micro-nutrients in larger quantity (p<0.05) and adhere to healthier diet characterized by higher intakes of legumes, seed and nuts, vegetables and fishes and shells than the general female population who never had been diagnosed with cancer (p<0.05). Conclusions: Our study results suggested that the intakes of nutrients and foods varied by time since surgery and cancer stage among breast cancer survivors and dietary intakes among breast cancer survivors differed from that in the general population. Further prospective studies are warranted to explore the association between dietary intakes of specific food items and survival among Korean breast cancer survivors.

• The Korean Journal of Physiology and Pharmacology
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• v.16 no.3
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• pp.175-180
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• 2012

Yoga has been known to have stimulatory or inhibitory effects on the metabolic parameters and to be uncomplicated therapy for obesity. The purpose of the present study was to test the effect of an 8-week of yoga-asana training on body composition, lipid profile, and insulin resistance (IR) in obese adolescent boys. Twenty volunteers with body mass index (BMI) greater than the 95th percentile were randomly assigned to yoga (age $14.7{\pm}0.5$ years, n=10) and control groups (age $14.6{\pm}1.0$ years, n=10). The yoga group performed exercises three times per week at 40~60% of heart-rate reserve (HRR) for 8 weeks. IR was determined with the homeostasis model assessment of insulin resistance (HOMA-IR). After yoga training, body weight, BMI, fat mass (FM), and body fat % (BF %) were significantly decreased, and fat-free mass and basal metabolic rate were significantly increased than baseline values. FM and BF % were significantly improved in the yoga group compared with the control group (p<0.05). Total cholesterol (TC) was significantly decreased in the yoga group (p<0.01). HDL-cholesterol was decreased in both groups (p<0.05). No significant changes were observed between or within groups for triglycerides, LDL-cholesterol, glucose, insulin, and HOMA-IR. Our findings show that an 8-week of yoga training improves body composition and TC levels in obese adolescent boys, suggesting that yoga training may be effective in controlling some metabolic syndrome factors in obese adolescent boys.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.5 no.1
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• pp.62-67
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• 2002

Purpose: The aim of this study was to investigate the age of onset and the prevalence of lactose malabsorption in early childhood in Korea. Methods: We conducted a study of lactose malabsorption by breath hydrogen test in healthy children aged between 25~96 months old. Standard lactose loading (2 g lactose/kg, maximum 40g) test was done in 129 children and cow's milk (10 mL/kg) loading in 126 children followed by breath sampling of 60 and 120 minutes after the loading. An increase above baseline of 20 ppm or more was used as a criteria for positive responses. Results: The prevalence of lactose malabsorption was 7% in 25~36 months old, 19% in 37~48 months old, 35% in 49~60 months old, 55% in 61~72 months old, 82% in 72~84 months old, 80% in 85~96 months old children. Only 1% of the children showed positive result in breath hydrogen test after the cow's milk challenge. Conclusion: The prevalence of lactose malabsorption was increased between 37 months and 60 months of age, reached to adult level of prevalence after 72 months of age. When physiological dose of lactose was used as the challenge, the number of lactose malabsorbers become clinically insignificant.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.416-416
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• 2015

기후변화는 미래 강수량 변동을 야기하여 하천유량 관리에 큰 영향을 미칠 것으로 예상하고 있다. 이에 본 연구에서는 기후변화에 따른 중장기 하천유량 관리를 위하여 금호강 유역을 대상으로 SWAT 모형을 이용하여 중장기 하천유량을 예측하였다. 임하댐 상류지역의 2008~2012년 유량자료에 대하여 보정 완료된 SWAT 모형을 기반으로, 지역기후모형(RCM)인 HadGEM3-RA모형을 활용한 IPCC 제5차 보고서 RCP 4.5, RCP 8.5 시나리오를 적용하였다. 금호강 표준유역별 기후변화에 의한 영향을 모의하기 위하여 편이보정(Bias Correction)방법을 적용하였으며, 금호강 유역 내 과거 30년(1975~2005년, Baseline) 기상자료와 비교하여 통계적인 유사성을 가지도록 보정을 실시하였다. 기후변화 시나리오 적용결과는 S1(2011~2040년), S2(2041~2070년), S3(2071~2099년)으로 분할하여 월별, 계절별, 연도별 미래 강수량과 기온을 분석하였다. 분석 결과, RCP 4.5 시나리오의 경우 봄철(3~5월)의 강수량은 기준년도에 비해 약 57%가 증가하였으나, 가을철(6~8월)에는 7.9% 감소하였으며, 첨두 강수시기는 8~9월에서 6~7월로 이동하였다. 평균기온은 각 구분 시기별 $0.2^{\circ}C$, $1.1^{\circ}C$, $1.8^{\circ}C$ 정도 상승할 것으로 예측되었다. RCP 8.5 시나리오에서는 기준년도 대비 강우량은 봄철에 61% 증가, 가을철에는 14.9% 감소하는 것으로 모의되었다. 평균기온은 약 $0.4^{\circ}C$, $2.1^{\circ}C$, $4.2^{\circ}C$ 정도 상승하는 것으로 나타났다. 기후변화에 따른 유출량 결과 비교는 2001~2010년을 기준으로 하였으며, RCP 4.5 시나리오에서는 S1, S2, S3 시기별 각각 -10.9%, -7%, -3.6% 감소하였으며, RCP 8.5 시나리오에서는 약 -12.3%, 4.9%, -1.2% 변동하는 것으로 나타냈다. 금호강 유역 전반에 걸쳐 유출량이 감소하는 추세를 보였으며, 특히 본류에 비해 지류유역의 건천화가 심해지는 양상을 보였다. 또한 현재에 비해 여름철 유출패턴 시기가 앞당겨져 봄철 유량이 증가하고 겨울철에 감소하는 경향을 보이고 있다. 기후변화로 인한 수문패턴의 변화로 현재 하천유량관리의 변화가 필요할 것으로 판단되며, 향후 본 연구결과를 바탕으로 물수지 분석을 추가하여 유지유량 만족을 위한 해당유역의 이수기 유량관리 방안 연구를 수행할 예정이다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.197-205
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• 2013

In this study, we developed a program of optimizing stand-level carbon stock using a stand-level yield model and the Simulated Annealing (SA) heuristic method to derive a optimized forest treatment solution. The SA is one of the heuristic algorithms that can provide a desirable management solution when dealing with various management purposes. The SA heuristic algorithm applied 'thermal equilibrium test', a thresholds approach to solve the phenomenon that does not find an optimum solution and stays at a local optimum value during the process. We conducted a sensitivity test for the temperature reduction rate, the major parameter of the thermal equilibrium test, to analyze its influence on the objective function value and the total iteration of the optimization process. Using the developed program, three scenarios were compared: a common treatment in forestry (baseline), the optimized solution of maximizing the amount of harvest(alternative 1), and the optimized solution of maximizing the amount of carbon stocks(alternative 2). As the results, we found that the alternative 1 showed provide acceptable solutions for the objectives. From the sensitivity test, we found that the objective function value and the total iteration of the process can be significantly influenced by the temperature reduction rate. The developed program will be practically used for optimizing stand-level carbon stock and developing optimized treatment solutions.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.25 no.4
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• pp.45-56
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• 2012

Objective : This study was done to investigate the correlation between general quality of life(QOL) and disease specific QOL of tinnitus patients. Methods : 2009 National health and nutrition survey(NHNS) data were employed for analyzing the mean estimates of total population and tinnitus sub-group patients, and predicting the regression equation of mapping between EQ-5D and disease severity. Baseline statistical analyses and normality tests were done by using Student t-test, Chi-square test, Shapiro-Wilk test and ladder test. Hierarchial regression analyses were performed using related variables and predicted the optimal regression equations. Statistical significance was achieved if the probability was less than 5%. Results : Firstly, the standardized prevalence of tinnitus patient in South Korea was 18.69% and over 90th age-group was relatively higher than other groups. Mean value of domestic QOL measured by EQ-5D was estimated as 0.9486 and QOL of tinnitus subgroup(0.9169) was lower than the non-tinnitus subgroup(0.9559), significantly. Stratified by age and sex, QOLs of all sub-groups with tinnitus were lower than without tinnitus sub-groups significantly. Regression equations from 2009 NHNS data were developed using hierarchial regression analysis which is as follows. $$Y_{EQ-5D}=0.9224-0.0079{\times}T1-0.0261{\times}T2-0.0951{\times}T3+\sum_{i=1}^{n}{\beta}_i{\times}X_i\\{\hspace{95}}(0.0106){\hspace{3}}(0.0037){\hspace{30}}(0.0072){\hspace{30}}(0.0038)$$ ($X_i$=Other explanatory variables except Tinnitus QOL1, 2, 3, ${\beta}$= Regression Coefficient of Model 4) Conclusion : We confirmed the correlation among THI and EQ-5D and HUI-III, and developed the inference for regression equation of EQ-5D.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.7
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• pp.191-198
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• 2021

Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distributed deep learning is proposed to reduce the training time by distributing computation across multiple nodes. In this study, we propose hybrid allreduce strategy that considers the characteristics of each layer and communication and computational overlapping technique for synchronization of distributed deep learning. Since the convolution layer has fewer parameters than the fully-connected layer as well as it is located at the upper, only short overlapping time is allowed. Thus, butterfly allreduce is used to synchronize the convolution layer. On the other hand, fully-connecter layer is synchronized using ring all-reduce. The empirical experiment results on PyTorch with our proposed scheme shows that the proposed method reduced the training time by up to 33% compared to the baseline PyTorch.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.1
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• pp.13-24
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• 2019

Objectives : The goals of the study are how to establish the cohort systems for the children and adolescents victims with sexual abuse in Korea and to identify the risk and protective factors that influence mental health in child sexual abuse (CSA). This is initial assessment data based on the analysis of cohort variables for baseline evaluation of subjects. Methods : We constructed the cohort systems for CSA victims recruited by Seoul Sunflower Children Center, CSA victims protection center. The initial assessment data which consisted of demographic and psychological inventories of CSA victims and their parents/families, psychiatric diagnoses were the results of statistical analysis of 65 subjects under 19 years old for 3 years 7 months. Results : The initial data were followings : female participants, N=56; mean age, 11.6 (SD=4.5); the most sexual assault, molestation 71.8%; victims, family and acquaintance 87.1%; 61.5% of the subjects diagnosed with psychiatric disorder; 29.2% diagnosed with PTSD and 23.1% diagnosed with depression. Mean duration for abuse to report is 1.5 years. Mean score of IES-R-K, TSCYC-avoidant and CBCL-problematic behavior were increased above clinical cut-off. Conclusions : CSA victims tend to have high risks in mental health problem. The cohort study could provide the risk and protective factors of CSA in mental health, and construct the predictive model for mental illness in Korea.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.855-865
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• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.71-82
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• 2019

The purpose of this study is to analyze the Mekong River streamflow alteration due to climate change. The future climate change scenarios were produced by bias corrections of the data from East Asia RCP 4.5 and 8.5 scenarios, given by HadGEM3-RA. Then, SWAT model was used for discharge simulation of the Kratie, the main point of the Mekong River (watershed area: $646,000km^2$, 88% of the annual average flow rate of the Mekong River). As a result of the climate change analysis, the annual precipitation of the Kratie upper-watershed increase in both scenarios compared to the baseline yearly average precipitation. The monthly precipitation increase is relatively large from June to November. In particular, precipitation fluctuated greatly in the RCP 8.5 rather than RCP 4.5. Monthly average maximum and minimum temperature are predicted to be increased in both scenarios. As well as precipitation, the temperature increase in RCP 8.5 scenarios was found to be more significant than RCP 4.5. In addition, as a result of the duration curve comparison, the streamflow variation will become larger in low and high flow rate and the drought will be further intensified in the future.