• Steel and Composite Structures
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• 제26권1호
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• pp.1-15
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• 2018

This study reported, the effect of random variation in system properties on bending response of single wall carbon nanotube reinforced composite (SWCNTRC) plates subjected to transverse uniform loading is examined. System parameters such as the SWCNT armchair, material properties, plate thickness and volume fraction of SWCNT are modelled as basic random variables. The basic formulation is based on higher order shear deformation theory to model the system behaviour of the SWCNTRC composite plate. A C0 finite element method in conjunction with the first order perturbation technique procedure developed earlier by the authors for the plate subjected to lateral loading is employed to obtain the mean and variance of the transverse deflection of the plate. The performance of the stochastic SWCNTRC composite model is demonstrated through a comparison of mean transverse central deflection with those results available in the literature and standard deviation of the deflection with an independent First Order perturbation Technique (FOPT), Second Order perturbation Technique (SOPT) and Monte Carlo simulation.

• Asian-Australasian Journal of Animal Sciences
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• 제15권5호
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• pp.622-626
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• 2002

Growth records over six generations of 686 pigs in SD-II Swine Line were used to estimate the genetic and phenotypic covariance functions for body weight as longitudinal data. A random regression model with Legendre polynomials of age as independent variables was used to estimate the (co)variances among the regression coefficients, thus the coefficients of genetic and permanent environmental covariance functions by restricted maximum likelihood employing the average information algorithm. The results showed that, using litter effect as additional random effect, a reduced order of fit did not describe the data adequately. For all five orders of fit, however, the change trends of genetic and phenotypic (co)variances were very similar from ${\kappa}$=3 onwards.

• International Journal of Reliability and Applications
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• 제18권2호
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• pp.83-98
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• 2017

Stress-strength reliability problems arise frequently in applied statistics and related fields. In the context of reliability, the stress-strength model describes the life of a component, which has a random strength X and is subjected to random stress Y. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X > Y. The problem of estimation the reliability parameter in a stress-strength model R = P[Y < X], when X and Y are two independent two-parameter Lindley random variables is considered in this paper. The maximum likelihood estimator (MLE) and Bayes estimator of R are obtained. Also, different confidence intervals of R are obtained. Simulation study is performed to compare the different proposed estimation methods. Example in real data is used as practical application of the proposed procedure.

• Structural Engineering and Mechanics
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• 제64권4호
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• pp.413-426
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• 2017

Probabilistic methods are used in engineering where a computational model contains random variables. The proposed method under development: Direct Optimized Probabilistic Calculation (DOProC) is highly efficient in terms of computation time and solution accuracy and is mostly faster than in case of other standard probabilistic methods. The novelty of the DOProC lies in an optimized numerical integration that easily handles both correlated and statistically independent random variables and does not require any simulation or approximation technique. DOProC is demonstrated by a collection of deliberately selected simple examples (i) to illustrate the efficiency of individual optimization levels and (ii) to verify it against other highly regarded probabilistic methods (e.g., Monte Carlo). Efficiency and other benefits of the proposed method are grounded on a comparative case study carried out using both the DOProC and MC techniques. The algorithm has been implemented in mentioned software applications, and has been used effectively several times in solving probabilistic tasks and in probabilistic reliability assessment of structures. The article summarizes the principles of this method and demonstrates its basic possibilities on simple examples. The paper presents unpublished details of probabilistic computations based on this method, including a reliability assessment, which provides the user with the probability of failure affected by statistically dependent input random variables. The study also mentions the potential of the optimization procedures under development, including an analysis of their effectiveness on the example of the reliability assessment of a slender column.

• 한국전산구조공학회논문집
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• 제33권6호
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• pp.401-409
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• 2020

확률론적 지진취약도 평가는 구조물 혹은 기기의 손상확률을 각 취약도 변수별 조합을 통해 이루어진다. 지진취약도로부터 구해지는 2개 이상 기기의 동시손상확률 계산은 기존에는 각 기기의 손상확률을 독립으로 가정해 왔다. 하지만 기기별 손상확률에 상관성이 있으며, 이를 평가한 결과 상관성에 따라 동시손상확률이 변화할 수 있는 결과를 보였다. 이 지진상관성을 무시하면 비보수적인 결과가 나오고 따라서 이를 고려해서 계산되어야 한다. 이 연구에서는 지진상관계수를 해석적으로 평가하기 위해 몇 가지 확률 변수를 선정하여 각 변수별로 혹은 통합하여 평가하고 그 차이를 비교했다. 그리고 단순화된 모델과, 복잡한 모델에 대한 상관계수 차이도 비교하였다. 이들 방법에 따른 상관계수의 결과와 차이를 분석했다. 그 결과 각 변수별로 평가하는 것과 통합하여 평가할 때 변수별 영향의 차이에 따라 상관성이 변화함을 확인하였고, 모델이 단순할수록 상관성이 높아짐을 확인하였다.

• 산경연구논집
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• 제11권7호
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• pp.29-40
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• 2020

Purpose: In modern society, many urban problems are occurring, such as aging, hollowing out old city centers and polarization within cities. In this study, we intend to apply big data and machine learning methodologies to predict depression symptoms in the elderly population early on, thus contributing to solving the problem of elderly depression. Research design, data and methodology: Machine learning techniques used random forest and analyzed the correlation between CES-D10 and other variables, which are widely used worldwide, to estimate important variables. Dependent variables were set up as two variables that distinguish normal/depression from moderate/severe depression, and a total of 106 independent variables were included, including subjective health conditions, cognitive abilities, and daily life quality surveys, as well as the objective characteristics of the elderly as well as the subjective health, health, employment, household background, income, consumption, assets, subjective expectations, and quality of life surveys. Results: Studies have shown that satisfaction with residential areas and quality of life and cognitive ability scores have important effects in classifying elderly depression, satisfaction with living quality and economic conditions, and number of outpatient care in living areas and clinics have been important variables. In addition, the results of a random forest performance evaluation, the accuracy of classification model that classify whether elderly depression or not was 86.3%, the sensitivity 79.5%, and the specificity 93.3%. And the accuracy of classification model the degree of elderly depression was 86.1%, sensitivity 93.9% and specificity 74.7%. Conclusions: In this study, the important variables of the estimated predictive model were identified using the random forest technique and the study was conducted with a focus on the predictive performance itself. Although there are limitations in research, such as the lack of clear criteria for the classification of depression levels and the failure to reflect variables other than KLoSA data, it is expected that if additional variables are secured in the future and high-performance predictive models are estimated and utilized through various machine learning techniques, it will be able to consider ways to improve the quality of life of senior citizens through early detection of depression and thus help them make public policy decisions.

• Smart Structures and Systems
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• 제9권6호
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• pp.505-534
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• 2012

The present work deals with second order statistics of post buckling response of piezoelectric laminated composite cylindrical shell panel subjected to hygro-thermo-electro-mechanical loading with random system properties. System parameters such as the material properties, thermal expansion coefficients and lamina plate thickness are assumed to be independent of the temperature and electric field and modeled as random variables. The piezoelectric material is used in the forms of layers surface bonded on the layers of laminated composite shell panel. The mathematical formulation is based on higher order shear deformation shell theory (HSDT) with von-Karman nonlinear kinematics. A efficient $C^0$ nonlinear finite element method based on direct iterative procedure in conjunction with a first order perturbation approach (FOPT) is developed for the implementation of the proposed problems in random environment and is employed to evaluate the second order statistics (mean and variance) of the post buckling load of piezoelectric laminated cylindrical shell panel. Typical numerical results are presented to examine the effect of various environmental conditions, amplitude ratios, electrical voltages, panel side to thickness ratios, aspect ratios, boundary conditions, curvature to side ratios, lamination schemes and types of loadings with random system properties. It is observed that the piezoelectric effect has a significant influence on the stochastic post buckling response of composite shell panel under various loading conditions and some new results are presented to demonstrate the applications of present work. The results obtained using the present solution approach is validated with those results available in the literature and also with independent Monte Carlo Simulation (MCS).

• 한국산학기술학회논문지
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• 제15권5호
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• pp.2603-2609
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• 2014

기계시스템의 신뢰성 해석을 위해서는 기계시스템에 성능을 미치는 변수의 확률 분포와 파라미터를 결정하는 통계적 모델링은 반드시 필요하다. 하지만, 신뢰성 해석에서 상당수의 변수는 상관관계가 있음에도 불구하고 독립변수로 취급되거나 실험데이터 수가 부족하다는 이유로 통계 모델에 대한 잘못된 가정을 하는 경우가 많다. 본 연구에서는 베이지안 방법을 이용하여 상관관계를 갖는 데이터의 결합분포함수를 copula를 이용하여 모델링함으로써 적은 수의 데이터로부터 정확한 입력모델을 산정하는 방법을 제안하였으며, 방법의 검증을 위해 다양한 상관계수와 데이터 수에 대해 통계 시뮬레이션을 수행하였다. 그 결과 Bayesian방법은 상관계수가 낮아 후보함수가 유사하거나 샘플수가 적어 정확한 모델을 산정하기 어려운 경우에도 후보 copula 중 실제 copula와 가장 근사한 후보 copula를 선정하였다. 이러한 근사 후보 copula는 신뢰성 해석결과 역시 실제 copula 함수를 이용한 신뢰성 해석 결과와 유사한 결과를 가짐을 확인할 수 있으므로 베이지안 방법은 신뢰성 해석을 위해 정확한 통계모델링을 제공함을 알 수 있다.

• 대한간호학회지
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• 제54권2호
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• pp.193-210
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• 2024

Purpose: The objective of this study was to develop a predictive model for the sexual experiences of adolescents using the random forest method and to identify the "variable importance." Methods: The study utilized data from the 2019 to 2021 Korea Youth Risk Behavior Web-based Survey, which included 86,595 man and 80,504 woman participants. The number of independent variables stood at 44. SPSS was used to conduct Rao-Scott χ² tests and complex sample t-tests. Modeling was performed using the random forest algorithm in Python. Performance evaluation of each model included assessments of precision, recall, F1-score, receiver operating characteristics curve, and area under the curve calculations derived from the confusion matrix. Results: The prevalence of sexual experiences initially decreased during the COVID-19 pandemic, but later increased. "Variable importance" for predicting sexual experiences, ranked in the top six, included week and weekday sedentary time and internet usage time, followed by ease of cigarette purchase, age at first alcohol consumption, smoking initiation, breakfast consumption, and difficulty purchasing alcohol. Conclusion: Education and support programs for promoting adolescent sexual health, based on the top-ranking important variables, should be integrated with health behavior intervention programs addressing internet usage, smoking, and alcohol consumption. We recommend active utilization of the random forest analysis method to develop high-performance predictive models for effective disease prevention, treatment, and nursing care.

• 가정과삶의질연구
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• 제15권4호
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• pp.201-220
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• 1997

The purpose of this study is to investigate communication style & communication in the family and marital satisfaction. This study focuses on the following aspects: 1) to find out which variables of background variables(oe, sociodemographic variables & communication styles) have effect on communica-tion and marital satisfaction in the family. 2) to find out the relationships between communication in the family and marital satisfaction. 3) to find out the independent influence of background variables on marital satisfaction. In order to clarify the above problems the data were obtained from questionaires with 72 items. The selected sample is composed of 365 housewives in chong Joo city. SAS pc program was used for th statistical analysis of the data. Data was analyzed by frequency percentage mean F-test Duncan's multiple range test regression analysis path analysis pearson's correlation coefficient. Major findings are as follows: first age of couples education of couples durati n of marriage family life cycle number of children income were variables to have influence on communication in the family, And communication styles were variables to have influence on communication in the family. Second age of couple education of couple duration of marriage family life cycle number of children were variables to have influence on marital satisfaction. And communication styles were variables to have influence on marital satisfaction. Third there were positive relation between communication in the family and marital satisfaction. The higher communication about clothing food housing skill health affection money, time and infstitutional facilities the higher marital satisfaction. Fourth influential variables related to marital satisfaction were communication about clothing affection & money and communication styles(ie, random style, morphogenic style, mophostatic style)