• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Advances in Computational Design
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• v.5 no.2
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• pp.195-207
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• 2020

The present study focuses on the application of artificial neural network (ANN) and Multiple linear Regression (MLR) analysis for developing a model to predict the unconfined compressive strength (UCS) and split tensile strength (STS) of the fiber reinforced clay stabilized with grass ash, fly ash and lime. Unconfined compressive strength and Split tensile strength are the nonlinear functions and becomes difficult for developing a predicting model. Artificial neural networks are the efficient tools for predicting models possessing non linearity and are used in the present study along with regression analysis for predicting both UCS and STS. The data required for the model was obtained by systematic experiments performed on only Kaolin clay, clay mixed with varying percentages of fly ash, grass ash, polypropylene fibers and lime as between 10-20%, 1-4%, 0-1.5% and 0-8% respectively. Further, the optimum values of the various stabilizing materials were determined from the experiments. The effect of stabilization is observed by performing compaction tests, split tensile tests and unconfined compression tests. ANN models are trained using the inputs and targets obtained from the experiments. Performance of ANN and Regression analysis is checked with statistical error of correlation coefficient (R) and both the methods predict the UCS and STS values quite well; but it is observed that ANN can predict both the values of UCS as well as STS simultaneously whereas MLR predicts the values separately. It is also observed that only STS values can be predicted efficiently by MLR.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.64-71
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• 2013

Purpose: The purpose of this study was to select standing posture parameters that have a significant difference according to the severity of spinal deformity, and to develop a novel Cobb angle prediction model for adolescent girls with idiopathic scoliosis. Methods: Five normal adolescents girls with no history of musculoskeletal disorders, 13 mild scoliosis patients (Cobb angle: $10^{\circ}-25^{\circ}$), and 14 severe scoliosis patients (Cobb angle: $25^{\circ}-50^{\circ}$) participated in this study. Six infrared cameras (VICON) were used to acquire data and 35 standing parameters of scoliosis patients were extracted from previous studies. Using the ANOVA and post-hoc test, parameters that had significant differences were extracted. In addition, these standing posture parameters were utilized to develop a Cobb-angle prediction model through multiple regression analysis. Results: Twenty two of the parameters showed differences between at least two of the three groups and these parameters were used to develop the multi-linear regression model. This model showed a good agreement ($R^2$ = 0.92) between the predicted and the measured Cobb angle. Also, a blind study was performed using 5 random datasets that had not been used in the model and the errors were approximately $3.2{\pm}1.8$. Conclusions: In this study, we demonstrated the possibility of clinically predicting the Cobb angle using a non-invasive technique. Also, monitoring changes in patients with a progressive disease, such as scoliosis, will make possible to have determine the appropriate treatment and rehabilitation strategies without the need for radiation exposure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.543-553
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• 2020

This study analyzed secondary data using the results of the 7th Korea National Health and Nutrition Survey in 2018. The aim of this study was to identify and compare the effects of physical activity, body mass index, and depression on the health-related quality of life of elderly women. Specifically, the sample consisted of 550 women with hypertension and 375 women without hypertension. The data were analyzed using descriptive statistics, chi-square test, t-test, and multiple linear regression with the IBM SPSS/WIN 22.0 program. Multiple linear regression analysis showed that age, education, physical activity, body mass index, and depression accounted for 26.9% of the health-related quality of life (HRQOL) in the hypertension group (F=14.30, p<.001), followed by physical activity (t=3.02, p=.003), body mass index (t=-3.12, p=.002), and depression (t=-7.69, p<.001). Education and depression accounted for 31.7% of the QoL in the non-hypertension group (F=4.42, p<.001), followed by depression (t=-5.53, p<.001). Based on these results, a physical activity intervention program will be needed to reduce depression and obesity in older women. Moreover, further research comparing the characteristics of other specific physical activities in elderly women with hypertension is recommended.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.77-86
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• 2021

A method of constructing a war simulation based on Bayesian Inference was proposed as a method of constructing heterogeneous historical war data obtained with a time difference into a single model. A method of applying a linear regression model can be considered as a method of predicting future battles by analyzing historical war results. However it is not appropriate for two heterogeneous types of historical data that reflect changes in the battlefield environment due to different times to be suitable as a single linear regression model and violation of the model's assumptions. To resolve these problems a Bayesian inference method was proposed to obtain a post-distribution by assuming the data from the previous era as a non-informative prior distribution and to infer the final posterior distribution by using it as a prior distribution to analyze the data obtained from the next era. Another advantage of the Bayesian inference method is that the results sampled by the Markov Chain Monte Carlo method can be used to infer posterior distribution or posterior predictive distribution reflecting uncertainty. In this way, it has the advantage of not only being able to utilize a variety of information rather than analyzing it with a classical linear regression model, but also continuing to update the model by reflecting additional data obtained in the future.

• Korean Journal of Ecology and Environment
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• v.48 no.2
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• pp.95-107
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• 2015

In order to identify long-term trends of water quality parameters in Lake Kyeongpo, Mann-Kendall test, Sen's slope estimator and linear regression were applied on data, with 15 parameters from three different sites and rainfall, monitored once in every two months from March to November during 1998~2013. Seasonal variation analysis only used Mann-Kendall test and Sen's slope estimator. Analysis result showed that salinity, transparency and nutrient variables (total phosphorus, dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen, ammonia nitrogen) were only parameters having statistically significant trend. In linear regression analysis, salinity (surface and bottom layer of all sites) and transparency (only at site 1), were figured out with statistically significant increasing trend, while in non-parametric statistical method, salinity and transparency in all sites (surface, middle, deep) were figured out with statistically significant increasing trend. Water quality parameters showing statistically significant decreasing trends were dissolved oxygen (surface layer of site 1 and bottom layer of sites 2 and 3), total phosphorus (sites 1 and 2), dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen and ammonia nitrogen in the linear regression analysis and, dissolved oxygen (bottom layer of all sites), total phosphorus, dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen and ammonia nitrogen in the non-parametric method. Seasonal trend analysis result showed that salinity, turbidity, transparency and suspended solids in spring, salinity, transparency, nitrate nitrogen and suspended solids in summer and temperature, salinity, transparency and suspended solids in fall were the variables depending on the season with increasing trends. In general, rainfall during the research period showed decreasing trend. The significant reduction trends of nutrients in Lake Kyeongpo were believed to be related to lagoon restoration and water management project run by Gangneung city and under-water wear removal, but further detailed studies are needed to know the exact causes.

• Anxiety and mood
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• v.8 no.2
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• pp.86-92
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• 2012

Objective : This study investigated the relationship between the resilience and posttraumatic stress symptoms, as well as comorbid symptoms in firefighters. Methods : We collected 764 firefighters, who worked at six fire department stations in Gangwon-do. We investigated the impact of event scale-revised (IES-R), the life events checklists (LEC), Connor-Davidson resilience scale (CD-RISC), Beck depression inventory (BDI), state trait anxiety inventory (STAI) and alcohol use disorder identification test (AUDIT). Full PTSD groups, partial PTSD groups and non-PTSD groups, which were classified by IES-R scores, were compared in the LEC, CD-RISC, BDI, STAI and AUDIT, ; multiple linear regression analyses were done for independent predictors of variables. Results : Of the 764 firefighters, there were significant differences in LEC (p<0.001), CD-RISC (p<0.001), BDI (p<0.001), and AUDIT (p=0.001) among the full PTSD groups, partial PTSD groups and non-PTSD groups. However, STAI did not show significant difference among three groups. In multiple regression analysis, CD-RISC (${\beta}=-0.168$, p<0.001), LEC (${\beta}=0.211$, p<0.001) and AUDIT (${\beta}=0.115$, p=0.001) were significant predictors for IES-R. Conclusion : The results of the present study suggested that resilience might be a protective factor in PTSD and comorbid symptoms of PTSD.

• Korean Journal of Occupational Health Nursing
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• v.22 no.4
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• pp.324-333
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• 2013

Purpose: This study was conducted to compare the changes in the levels of liver enzymes after providing health education to workers. Methods: Among 909 electronics-manufacturing workers, 96 (10.6%) workers had abnormal liver functions. Of these, male workers were randomly assigned into either the health education experimental group (48 [52.2%]) or the control group (44 [47.8%]). Depending on the level of participation in the health education, workers in the experimental group were classified into the participation (32 [34.8%]) and non-participation groups (16 [17.4%]). Changes in the levels of liver enzymes were compared among three groups. Results: The changes in the levels of gamma-glutamyltransferase (r-GTP) in the participation, non-participation, and control groups were $-25.3{\pm}54.5$ IU/L, $-4.4{\pm}24.1$ IU/L, and $-5.3{\pm}38.8$ IU/L, respectively (p=.036). Aspartate transaminase, alanine transaminase, waist circumference, body mass index, daily alcohol consumption, weekly exercise, and changes in smoking habits in the 3 groups did not differ significantly. In the multiple linear regression analysis, the variable of education participation revealed a significant regression coefficient of -25.10 when the change in r-GTP levels was the dependent variable. Conclusion: A brief health education targeted towards the management of liver disease among workers improved r-GTP levels.

• Nutrition Research and Practice
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• v.10 no.1
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• pp.67-73
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• 2016

BACKGROUND/OBJECTIVES: This study was aimed at examining the association between dietary flavanones intake and lipid profiles according to the presence of metabolic syndrome (MetS) in Korean women with type 2 diabetes mellitus (T2DM). SUBJECTS/METHODS: A cross-sectional analysis was performed among 502 female T2DM patients (non-MetS group; n = 129, MetS group; n = 373) who were recruited from the Huh's Diabetes Clinic in Seoul, Korea between 2005 and 2011. The dietary intake was assessed by a validated semi-quantitative food frequency questionnaire (FFQ) and the data was analyzed using the Computer Aided Nutritional Analysis program (CAN-Pro) version 4.0 software. The intake of flavanones was estimated on the basis of the flavonoid database. RESULTS: In the multiple linear regression analysis after adjustment for confounding factors, daily flavanones intake was negatively associated with CVD risk factors such as total cholesterol, LDL-cholesterol, and apoB and apoB/apoA1 ratio only in the MetS group but not in the non-MetS group. Multiple logistic regression analysis revealed that the odds ratio for a higher apoB/apoA1 ratio above the median (${\geq}0.74$) was significantly low in the $4^{th}$ quartile compared to that in the $1^{st}$ quartile of dietary flavanones intake [OR: 0.477, 95% CI: 0.255-0.894, P for trend = 0.0377] in the MetS group. CONCLUSIONS: Dietary flavanones intake was inversely associated with the apoB/apoA1 ratio, suggesting a potential protective effect of flavanones against CVD in T2DM women with MetS.

• The Korean Journal of Pain
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• v.34 no.4
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• pp.417-426
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• 2021

Background: Non-cardiac chest pain (NCCP) is a common patient complaint imposing great costs on the healthcare system. It is associated with psychological factors such as depression. The aim of the present study is determining depression predictors in NCCP patients. Methods: The participants of this cross-sectional study were 361 NCCP patients. Patients filled out questionnaires concerning their sociodemographic, lifestyle, and clinical factors (severity of pain, type D personality, somatization, cardiac anxiety, fear of body sensations, and depression). Results: Based on multiple ordinal logistic regression, lack of physical activity (odds ratio [OR], 1.78; 95% confidence interval [CI], 1.09-2.87), sleep quality (OR, 2.98; 95% CI, 1.15-7.69), being a smoker (OR, 1.33; 95% CI, 2.41-4.03), present pain intensity (OR, 1.08; 95% CI, 1.05-1.11), type D personality (OR, 2.43; 95% CI, 1.47-4.03), and somatization (OR, 1.22; 95% CI, 1.15-1.3) were significant predictors of depression in NCCP patients. Additionally, multiple linear regression showed that being unmarried (β = 1.51, P = 0.008), lack of physical activity (β = 1.22, P = 0.015), sleep quality (β = 2.26, P = 0.022), present pain intensity (β = 0.07, P = 0.045), type D personality (β = 1.87, P < 0.001), somatization (β = 0.45, P < 0.001), and fear of bodily sensation (β = 0.04, P = 0.032) increased significantly depression scores in NCCP patients. Conclusions: Physicians should consider the predictors of depression in NCCP patients which can lead to receiving effective psychological consultations and reducing the costs and ineffectual referrals to medical centers.