• The Journal of Economics, Marketing and Management
• /
• v.8 no.1
• /
• pp.29-35
• /
• 2020

Purpose - In this study, among the various stresses experienced by single-family senior citizens, we will focus on economic and financial stress and help to comprehend it generally, examine the differences in economic and financial stress and coping behaviors caused by the background variables in the aged group, and verify the variables that affect economic and financial stress, response behavior, and life satisfaction. Research design, data, and methodology - First of all, frequency analysis and technical statistics were conducted to identify the general characteristics of the elderly (characteristics of demographic sociology, social relationships) and the satisfaction level of life. Secondly, Hierarchical Multiple Regression Analysis was conducted to analyse influential factors on life satisfaction. Results - looking at the demographic characteristics of the elderly showed that in case the spouse exists, the level of satisfaction in life was shown to be higher. Next, looking at the characteristics of economic stress showed that the lower the economic stress was, the higher the satisfaction level of life was shown. Conclusions - Since stress has been identified as the most influential variable in life satisfaction through this study, we believe that economic and financial stress should be studied together as a parameter to find out which factors influence life satisfaction, or studies to reduce stresses for experts and senior party members altogether is also needed.

• Advances in nano research
• /
• v.10 no.2
• /
• pp.101-114
• /
• 2021

An analytical investigation has been performed on the mechanical performance of waves propagated in a Single-Layered Graphene Sheet (SLGS) when an In-plane Varying Bending (IVB) load is interacted. It has been supposed that the Graphene Sheet (GS) is located on an elastic medium. Employing a two-parameter elastic foundation, the effects of elastic substrate on the GS behavior are modeled. Besides, the kinematic equations are derived by the means of a trigonometric two-variable refined plate theory. Moreover, in order to indicate the size-dependency of the SLGS, a Nonlocal Strain Gradient Theory (NSGT) was considered. The nonlocal governing differential equations are achieved in the framework of Hamilton's Principle (HP). Also, an analytical approach was used to detect the unknowns of the final eigenvalue equation. Finally, the effects of each parameters using some dispersion charts were determined.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.1
• /
• pp.1-8
• /
• 2021

As a nation experiencing rapid economic growth, South Korea and its government have made a continuous effort toward efficient research investments to achieve transformation of the Korean industry for the fourth industrial revolution. To achieve the maximum effectiveness of the research investments, it is necessary to evaluate its funding's worth and default risk. Thus, incorporating the concepts of the Black-Scholes-Merton model and the Greeks, this study develops a default-risk evaluation model in the foundation of a system dynamics methodology. By utilizing the proposed model, this study estimates the monetary worth and the default risks of research funding in the public and private sectors of Information and Communication technologies, along with the sensitivity of the R&D economic worth of research funding to changes in a given parameter. This study finds that the public sector has more potential than the private sector in terms of monetary worth and that the default risks of three types of research funding are relatively high. Through a sensitivity analysis, the results indicate that uncertainty in volatility, operation period, and a risk-free interest rate has trivial impacts on the monetary worth of research funding, while volatility has large impacts on the default risk among the uncertain factors.

• Geomechanics and Engineering
• /
• v.23 no.6
• /
• pp.535-546
• /
• 2020

The stress environment of deep rock masses is complex. Under the action of earthquakes or blasting, the strength and stability of anchored rock masses in fracture zones or faults are affected. To explore the variation in anchored rock masses under creep-fatigue loading, shear creep comparative testing of anchored marble specimens with or without fatigue loading is performed. Considering the damage variable of rock under fatigue loading, a rheological model is established to characterize the whole shear creep process of anchored rock masses under creep-fatigue loading. The results show that (1) the overall deformation of marble under creep-fatigue loading is larger than that under only shear creep loading, and the average deformation is increased by 18.3%. (2) By comparing the creep curves with and without fatigue loading, the two curves basically coincide when the first level stress is applied, and the two curves are stable with the increase in stress level. The results show that the strain difference among the specimens increases gradually in the steady-state stage and reaches the maximum at the fourth level. (3) The shear creep is described by considering the creep mechanical properties of anchored rock masses under fatigue loading. The accuracy of this creep-fatigue model is verified by laboratory tests, and the applicability of the model is illustrated by the fitting parameter R2. The proposed model provides a theoretical basis for the study of anchored rock masses under low-frequency earthquakes or blasting and new methods for the stability and reinforcement of rock masses.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.4
• /
• pp.257-265
• /
• 2021

Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in comparison with the rain-flow counting method as an exact solution. A step-by-step study was carried out to develop new approximate spectral moments that are close to the rain-flow counting moment, which can be used for the development of a fatigue damage model. Using the special parameters and bandwidth parameters, four kinds of parameter-based combinations were constructed and estimated using the R-squared values from regression analysis. Based on the results, four candidate empirical formulas were determined and compared with the rain-flow counting moment, probability density function, and root mean square (RMS) value for relative distance. The new approximate spectral moments were finally decided through comparison studies of eight response spectra. The new spectral moments presented in this study could play an important role in improving the accuracy of fatigue damage model development. The present study shows that the new approximate moment is a very important variable for the enhancement of Gaussian wide-band fatigue damage assessment.

• Journal of Korean Society of Water and Wastewater
• /
• v.35 no.6
• /
• pp.507-516
• /
• 2021

In this study, the machine learning which has been widely used in prediction algorithms recently was used. the research point was the CD(chudong) point which was a representative point of Daecheong Lake. Chlorophyll-a(Chl-a) concentration was used as a target variable for algae prediction. to predict the Chl-a concentration, a data set of water quality and quantity factors was consisted. we performed algorithms about random forest and gradient boosting with Python. to perform the algorithms, at first the correlation analysis between Chl-a and water quality and quantity data was studied. we extracted ten factors of high importance for water quality and quantity data. as a result of the algorithm performance index, the gradient boosting showed that RMSE was 2.72 mg/m³ and MSE was 7.40 mg/m³ and R² was 0.66. as a result of the residual analysis, the analysis result of gradient boosting was excellent. as a result of the algorithm execution, the gradient boosting algorithm was excellent. the gradient boosting algorithm was also excellent with 2.44 mg/m³ of RMSE in the machine learning hyperparameter adjustment result.

• Steel and Composite Structures
• /
• v.41 no.6
• /
• pp.787-803
• /
• 2021

The size-dependent nonlinear thermomechanical vibration analysis of pre- and post-buckled tapered two-directional functionally graded (2D-FG) microbeams is presented in this study. In the context of the modified couple stress theory, the formulations are derived based on the parabolic shear deformation beam theory and von Karman nonlinear strains. Different thermomechanical material properties are assumed to be temperature-dependent and smoothly vary in both length and thickness directions using the power law and the physical neutral axis concept is employed. The nonlinear governing equations are derived using the Hamilton principle and the resulting variable coefficient equations of motion are solved using the differential quadrature method (DQM) and iterative Newton's method for clamped-clamped and simply supported boundary conditions. Comparison studies are presented to validate the derived model and solution procedure. The impacts of induced thermal moments, temperature power index, two gradient indices, nonuniform cross-section, and microstructure length scale parameter on the frequency-temperature configurations are explored for both clamped and simply supported microbeams.

• Journal of Fashion Business
• /
• v.26 no.6
• /
• pp.32-46
• /
• 2022

The purpose of this study is to explore a three-dimensional (3D) simulation of skirt shape concepts by manipulating circumferences and lengths via parametric design in the fashion design concept stage. This study also intends to propose a modeling method that can judge and transform the shape through immediate parameter adjustment. We looked at cases that utilized parametric design in other fields of fashion design, reviewed and analyzed the variables used in each study, and constructed parameters suitable to implement skirt fashion design. The traditional design elements required for skirt design, namely waist and hip circumferences, were set as variables in this study. The parametric design was developed to generate ideas of two skirt silhouettes (tight and flared) and three lengths (mini, knee-length, and maxi). To apply the skirt design implemented through variables to the actual 3D human shape, the shape data of women in their 20s and 30s were randomly selected from the 5th human data of Size Korea. Skirt design silhouette modeling was performed by adjusting the variable values according to body type. Parametric design has the potential to help develop design ideas in the field of fashion design, considering the method and characteristics of parameters of the variety of variables and rapid modification. Furthermore, if systematic research on variables and options among fashion design elements is conducted, the possibility of converging them into customization or co-design fashion design processes could be confirmed.

• Communications for Statistical Applications and Methods
• /
• v.29 no.1
• /
• pp.65-83
• /
• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4567-4583
• /
• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.