• Journal of Advanced Marine Engineering and Technology
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• v.40 no.2
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• Structural Engineering and Mechanics
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• v.60 no.3
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• pp.471-488
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• 2016

This study predicts the strength of rotary brace damper by analyzing a new set of probabilistic models using the usual method of multiple linear regressions (MLR) and advanced machine-learning methods of multivariate adaptive regression splines (MARS), Rotary brace damper can be easily assembled with high energy-dissipation capability. To investigate the behavior of this damper in structures, a steel frame is modeled with this device subjected to monotonic and cyclic loading. Several response parameters are considered, and the performance of damper in reducing each response is evaluated. MLR and MARS methods were used to predict the strength of this damper. Displacement was determined to be the most effective parameter of damper strength, whereas the thickness did not exhibit any effect. Adding thickness parameter as inputs to MARS and MLR models did not increase the accuracies of the models in predicting the strength of this damper. The MARS model with a root mean square error (RMSE) of 0.127 and mean absolute error (MAE) of 0.090 performed better than the MLR model with an RMSE of 0.221 and MAE of 0.181.

• Korean Journal of Community Nutrition
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• v.17 no.3
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• pp.329-340
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• 2012

Hypertension is a well-known risk factor for cardiovascular disease. Previous studies have shown that changes in diet and lifestyle factors can prevent the development of hypertension, but the combined effects of these modifiable factors on hypertension are not well established. The objective of this study is to investigate associations of diet and lifestyle factors, evaluated both individually and in combination, with prevalent hypertension among Korean adults. We analyzed data obtained from the 2007-2008 Korean National Health and Nutritional Examination Survey, a nationwide cross-sectional study using a stratified, multistage probability sampling design. The associations of 12 nutrient intakes and lifestyle factors with risk of hypertension were explored using restricted cubic spline regression and logistic regression models among 6,351 adults. Total energy and several nutrients and minerals, including, calcium, vitamin A, vitamin C, and sodium, showed non-linear relationships with the risk of prevalent hypertension. In multivariate logistic regression models, dietary score, obesity and alcohol intake were independently associated with the risk of prevalent hypertension, but smoking and physical activity were not. Overall, participants whose dietary habits and lifestyle factors were all in the low-risk group had 68% lower prevalence of hypertension (OR: 0.32, 95 CI: 0.14-0.74) compared to those who were at least one in the high-risk group of any dietary or lifestyle factors. The result suggests that combined optimal lifestyle habits are strongly associated with lower prevalence of hypertension among Korean adults.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.62-71
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• 2016

Food insecurity is associated with poor health outcomes. In particular, previous studies marked the adverse outcomes on mental health. This study examined the association of food insecurity and mental health in Korean adults using the data from the 2013 Korean National Health and Nutrition Examination Survey (KNHANES). The study population was 5,685 adults in Korea. Food insecurity was examined using 18-items. A diagnosis of depression was considered to be depression. Depressive symptoms were defined as more than 2 weeks of depression feelings. Multivariate logistic regression models examined the associations between food insecurity and depression and depressive symptom. The overall prevalence of depression was 3.8% in the participants. Food insecurity was associated significantly with depression and depressive symptom in the unadjusted and age and sex adjusted model. Food insecurity was associated with depression, depressive symptoms in the multivariate logistic regression model (OR:3.49, OR:3.70). Marginal food insecurity was not associated with depression in the multivariate logistic regression model. The results showed that food insecurity is associated with depression and depressive symptoms in adults. Multi-disciplinary interventions are needed including nutrition, health, health policy, and a healthy environment for the food insecurity group to achieve a better health outcome, especially mental health.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.80-90
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• 2001

The aim of this study is to develop the methodology which enables to identify the mechanical properties of element such as stress intensity factor by using the AE parameters. Considering the multivariate and nonlinear properties of AE parameters such as ringdown count, rise time, energy, event duration and peak amplitude from fatigue cracks of machine element the principal component regression(PCR) and artificial neural network(ANN) models for the estimation of stress intensity factor were developed and validated. The AE parameters were found to be very significant to estimate the stress intensity factor. Since the statistical values including correlation coefficients, standard mr of calibration, standard error of prediction and bias were stable, the PCR and ANN models for stress intensity factor were very robust. The performance of ANN model for unknown data of stress intensity factor was better than that of PCR model.

• Journal of agriculture & life science
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• v.46 no.1
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• pp.113-121
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• 2012

A total of 150,624 records of Holstein milk production collected from 2005 to 2009 were analyzed to investigate the effects of two different contemporary group definitions, parity and somatic cell score (SCS). The first definition (H BY S) of contemporary group was milking cows and heifers born in the same year and season. And the second thing (H CY S) was milking cow and heifers that delivered calves in the same year and season. Effects of contemporary group, parity and regression effect on SCS from two models were highly significant sources of variation. Coverage of variation ($R^2$) was somewhat higher in models with H BY S as contemporary group. From multivariate models with H BY S, phenotypic correlation coefficients of milk components were estimated high and positive. However, the phenotypic correlation coefficient between milk yield and SCS was -0.09, which was low enough to evidence no correlation between them. Phenotypic correlation between SCS and butter fat or between SCS and protein were also negligible but negative. From multivariate models with H CY S as contemporary group, phenotypic correlation among milk traits and SCS were similar to the estimates from models with H BY S. However, SCS in these models were lowly but negatively correlated with milk yield, milk protein, butter fat or SNF, and the phenotypic correlation coefficients of which were -0.10, -0.08, -0.08, -0.11, respectively.

• Water for future
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• v.26 no.4
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• pp.117-125
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• 1993

A flood -flow management system model of river basin has been developed in this study. The system model consists of the observation and telemetering system, the rainfall forecasting and data-bank system, the flood runoff simulation system, the dam operation simulation system, the flood forecasting simulation system and the flood warning system. The Multivariate model(MV) and Meterological-factor regression model(FR) for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood-flow management. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, streamflow and other hydrological data during the past flood periods. The flood-flow management system model with SSARR model(FFMM-SR,FFMM-SR(FR) and FFMM-SR(MV)), in which the integrated operation of dams and rainfall forecasting in the basin are considered, is then suggested and applied for flood-flow management and forecasting. The results of the simulations done at the base stations are analysed and were found to be more accurate and effective in the FFMM-SR and FFMM0-SR(MV).

• Journal of Families and Better Life
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• v.22 no.6 s.72
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• pp.191-199
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• 2004

The main purpose of this study was to examine the impact of religious participation on the depression of elder adults in USA. Specifically, this study examined how the influence of religious participation varied according to continuity or discontinuity of participation. Data from N=1,658 adults aged 65-90 who were respondents to two waves of the U.S. National survey of Families and Households 1987-1993 were used for these analyses. Depression was measured with a 12-item (of the original 20) modified version of the CES-D (Center for Epidemiological Studies-Depression). Multivariate regression models controlling for several demographic variables were estimated. Some clear evidence was found supporting activity theory and continuity theory That is, participating in a religious organization role at Time 2 but not Time 1 (T1 No - T2 Yes) and being continuously involved in religious organizations both at Time 1 and Time 2 (T1 Yes -T2 Yes) were associated with reduced depression, compared to continuous nonparticipation in religious organizations (71 No -72 No).

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.48-60
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• 1995

A flood - flow forecasting system model of river basins has been developed in this study. The system model consists of the data management system(the observation and telemetering system, the rainfall forecasting and data-bank system), the flood runoff simulation system, the reservoir operation simulation system, the flood forecasting simulation system, the flood warning system and the user's menu system. The Multivariate Rainfall Forecasting model, Meteorological factor regression model and Zone expected rainfall model for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood - flow forecasting. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, 7 streamfiow and other hydrological data during the past flood periods.

• Korean Journal of Health Education and Promotion
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• v.32 no.5
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• pp.53-62
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• 2015

Objectives: The purpose of this study was to examine the associations among self-rated health and socioeconomic status. Methods: Analyses were conducted based on cross-sectional data obtained from the Korea Youth Risk Behavior Web-based Survey. A total of 79,202 students aged 12 to 18 years participated in the study and there was a response rate of 95.5%. Separate logistic regression analyses were performed on each gender group based on a set of independent variables. Those being: the level of parental education level; family affluence scale; subjective household economic status; and subjective school achievement with SRH as the dependent variable. Results: Multivariate analyses revealed significant associations between each SES and adolescent SRH after controlling for other covariates. However, in the models that included all SES indicators, subjective household economic status and subjective school achievement remained significant in boys and girls. Conclusions: The findings demonstrated that subjective SES indicators are more closely related to adolescent SRH when compared with objective indicators.