• Journal of Digital Convergence
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• v.13 no.10
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• pp.121-133
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• 2015

This tutorial presents an approach to perform the covariance based structural equation modeling using the R. For this purpose, the tutorial defines the criteria for the covariance based structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "lavaan" which is the R package supporting the covariance based structural equation modeling. In this tutorial, a covariance-based structural equation modeling technique using the R and the R scripts targeting the example model were proposed as the results. This tutorial will be useful to start the study of the covariance based structural equation modeling for the researchers who first encounter the covariance based structural equation modeling and will provide the knowledge base for in-depth analysis through the covariance based structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the covariance based structural equation modeling.

• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• Structural Engineering and Mechanics
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• v.44 no.3
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• pp.379-403
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• 2012

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

• Structural Engineering and Mechanics
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• v.77 no.6
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• pp.765-777
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• 2021

Recently, the plate bending analysis has been interpreted in terms of the tensor's components of curvatures and bending moments by presenting the conceptual perspectives of the Hydrostatic Method of Analysis (HM) and theoretical formulations that combine the continuum mechanics with the graphical statics analysis, the theory of thin orthotropic and isotropic plates, and the elasticity theory. In pursuance of uncovering a genuine formulation of the plate's flexural differential equations, that possess the general-covariance and coordinates-independency. This study had then, tackled various natural and structural problems in both solid and fluid branches of the continuum mechanics in a description of such theoretical and conceptual attainment in uncovering the dimensional independent diffeomorphism covariant partial differential laws.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.751-760
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• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.

• Structural Engineering and Mechanics
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• v.56 no.4
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• pp.625-648
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• 2015

Modern super-tall buildings are more sensitive to strong winds. The evaluation of wind loads for the design of these buildings is of primary importance. A direct monitoring of wind forces acting on super-tall structures is quite difficult to be realized. Indirect measurements interpreted by inverse techniques are therefore favourable since dynamic response measurements are easier to be carried out. To this end, a Kalman filtering based inverse approach is developed in this study so as to estimate the wind loads on super-tall buildings based on limited structural responses. The optimum solution of Kalman filter gain by solving the Riccati equation is used to update the identification accuracy of external loads. The feasibility of the developed estimation method is investigated through the wind tunnel test of a typical super-tall building by using a Synchronous Multi-Pressure Scanning System. The effects of crucial factors such as the type of wind-induced response, the covariance matrix of noise, errors of structural modal parameters and levels of noise involved in the measurements on the wind load estimations are examined through detailed parametric study. The effects of the number of vibration modes on the identification quality are studied and discussed in detail. The made observations indicate that the proposed inverse approach is an effective tool for predicting the wind loads on super-tall buildings.

• Journal of the Korean Society of School Health
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• v.29 no.2
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• pp.63-70
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• 2016

Purpose: The purpose of this study was to find the factors influencing adolescents' adult media engagement. The study is based on Agnew's General Strain Theory (GST) and a micro-systemic perspective. Methods: The study examined 479 middle school freshmen who participated in the fourth wave of the Korean Children & Youth Panel Survey (KCYPS) conducted by National Youth Policy Institute. Data were analyzed through descriptive statistics, factor analysis, and reliability analysis using SPSS 22.0 Ver. Also, hypothesis testing was performed via covariance-based structure equation modeling (CB-SEM) using Amos 21.0 Ver. Results: Strain factors had positive effects on adolescent depression, and depression had a positive effect on adult media engagement. Also, cell-phone dependency had a positive mediation effect between depression and adult media engagement. Conclusion: The study's result identified the factors affecting adult media engagement. Therefore, we suggest intervention programs considering adolescents' strains, depression and cell-phone dependency to improve their health.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.555-562
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• 2021

This study aims to understand the effect of millennial transformational leadership (MTL) on organizational performance in Indonesian Fishery startups. The population of this study included select fishery startups in Indonesia based on the data released by the Ministry of Marine Affairs and Fisheries of the Republic of Indonesia and Digital Fishery Network. This study used the statistical method of PLS-SEM to analyze the data. The findings show that the MTL has no direct positive relationship with organizational performance; MTL has a direct positive relationship with organizational agility; MTL has a direct positive relationship with IT capability; IT capability has a direct positive relationship with organizational agility; organizational agility has a direct positive relationship with organizational performance in fishery startups in Indonesia during this pandemic era. It is suggested that future researches use covariance-based-structural equation modeling which is able to test the research model's feasibility. Roles of mediating variables in addition to the main variables-for example, organizational agility as a mediating variable on the relationship between MTL and organizational performance - are also suggested to be examined. In spite of the limitations, the model developed is still interesting to investigate and is expected to enhance the literature on transformational leadership.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.779-793
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• 2021

Water stress and environmental drivers are important factors to explain the variance of gross primary production (GPP). Environmental drivers are used to generate GPP in Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm and process-based model. However, MODIS algorithm only consider the vapor pressure deficit (VPD) data while the process-based biogeochemical model also uses limited data to express water stress. We compared the relationship between environmental drivers and GPP from eddy covariance method, MODIS algorithm, and Community Land Model 4 (CLM 4) simulation in normal years and drought years. To consider water stress specifically, we used VPD and evaporative fraction (EF). We evaluated the effects from environmental drivers and EF towards GPP products using the structural equation modeling (SEM) in South Korea. We found that GPP products from MODIS algorithm and model simulation results were not restricted from VPD data if VPD was underestimated. We also found that in the cropland area, irrigation effects can relieve VPD effects to GPP. However, GPP products derived from MODIS and CLM 4 had limitation to explain the irrigation effects to GPP. Overall, these results will enhance the understanding of GPP products derived from MODIS and CLM 4.