• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.121-131
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• 2022

The goal of the study was to see how quality management (QMA), strategy (STR), and innovative capability (INC) influence the competitive advantage of a Thai information communication technology (ICT) firm (COA). The researchers collected 431 surveys from Thailand's owners and managers employed in ICT enterprises from the beginning of June 2021 to the end of September 2021using diverse sample strategies. A questionnaire with an index of item-objective congruence (IOC) value of 0.60-1.00 and a reliability value of 0.92-0.96 was used as the research tool. Participants in the survey were requested to fill out a seven-level opinion survey posted on Google Forms. A latent variable structural equation model (SEM) path analysis using LISREL 9.1 was used for the four latent variables, 31 manifest variables, and the five hypotheses testing. The analysis showed that all three causal variables positively affected COA, which had a total effect (TE) R² value = 80% when combined with the other latent variables. Moreover, the values for the latent variables when ranked by total effect (TE) were STR, QMA, and INC with TE values of 0.95, 0.89, and 0.25, respectively. Finally, there were very strong influences from COA to STR (0.95), INC to QMA (0.86), and STR to QMA (0.71).

• Journal of Families and Better Life
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• v.19 no.6
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• pp.145-155
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• 2001

The purposes of this study were first to construct statistical and econometric models based on Amemiya\`s Type I Tobit mainly addressing the issue of statistical efficiency; second to explore income, price, and curvilinear age effects on the explained variable in order to illustrates its statistical marginal effects related to econometric issues; finally to provide invaluable insight for graphical simulations as a new interpretation approach using Tobit analysis. Results indicated that interpretation for the mean marginal effects of three possible cases of dependent variable was more likely to be evident to understand Tobit results compared to conventional analysis only using latent variable, beta. Results also revealed that prediction value of dependent variable can be possibly and easily projected by the independent variable changed whereas only beta value can not illustrate its projection as independent variables'changes.

• Journal of Wetlands Research
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• v.18 no.2
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• pp.166-172
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• 2016

Accurate understanding of land surface is essential to analyze energy exchanges between earth surface and atmosphere. For the quantization of energy fluxes, the various researches about Land Surface Model(LSM) have been progressed. Among the various LSMs, the researches using Common Land Model(CLM) and Variable Infiltration Capacity(VIC) model are performed briskly. The CLM which is advanced LSM can calculate realistic results with few user defined parameters. The VIC model which is also typical LSM is widely used for estimation of energy fluxes and runoff in various fields. In this study, the energy fluxes which are net radiation, sensible heat flux, and latent heat flux were estimated using CLM and VIC model at Southern Sierra-Critical Zone Observatory(SS-CZO) site in California, United States. In case of net radiation and sensible heat flux, both models showed good agreement with observations, however, the CLM showed underestimated patterns of net radiation and sensible heat flux during precipitation period. In case of latent heat flux, the CLM represented better estimation of latent heat flux than VIC model which underestimated the latent heat flux. Through the estimation of energy fluxes and analysis of models' pros and cons, the applicability of CLM and VIC models and need of multi-model application were identified.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.175-182
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• 2013

Lately, customers think highly of the emotional satisfaction and as a result, issues on odor are matters of concern. The cases are odor of interior material and air-conditioner of vehicles. In particualar, with respect to the odor of air-conditioner, customers strongly claimed defects with provocative comments : "It smells like something rotten," "It smells like a foot odor," "It stinks like a rag." Generally, it is known that mold of evaporator core in the air-conditioning system decays and this produce VOCs which causes the odor to occur. In this study, partial least squares regression model is applied to predict the strength of the odor and select of important VOCs which affect car air conditioning smell. The PLS method is basically a particular multilinear regression algorithm which can handle correlated inputs and limited data. The number of latent variable is determined by the point which is stabilized mean absolute deviations of VOCs data. Also multiple linear regression is carried out to confirm the validity of PLS method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.12
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• pp.1657-1668
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• 1998

In the analysis of a mushy solidification system with natural convection using a fixed grid method, the enthalpy method has been used to account for the release of latent heat. The variable viscosity, Darcy source, and hybrid methods have been employed for the velocity suppression in a mushy region. The choice of the values of solid viscosity and permeability constant in conjunction with the Darcy source term plays an important role in forming the location and shape of the phase boundaries. In this work the effects of these major parameters related to steady-state behavior in the system of mushy solidification are investigated through a simple test problem. The effective specific heat based on the spatial gradients of the enthalpy and temperature is adopted for the treatment of the release of latent heat. The effects of the Prandtl and Rayleigh numbers on the shape of mushy region are examined using the hybrid method.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.83-87
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• 2012

This study is aimed to identify latent classes which are based the change patterns in assistive technology device use among worker with disabilities and to test the effects of independent variables(gender, education, disability type, disability density, activity and participation of ICF: ICF, subjective socioeconomic status: SES, job satisfaction, life satisfaction) on determining latents classes. This study applied Nagin's(1999) semi-parametric group based approach to the panel survey of employment for the disabled. Because dependant variable has dichotomous scale, logit model was used. The results identified three latent classes, which could be defined based on the patterns as follows; assistive device continued use group, assistive device mid-level use group, assistive device sharp decline use group. The effects of the independent variables on the latent classes was tested by multinomial logit analysis. The results showed that education, disability type, ICF, SES, and life satisfaction were significant determinants of the latent classes. Finally, the implications based on analysis results were suggested.

• Korean Chemical Engineering Research
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• v.48 no.4
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• pp.475-482
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• 2010

In this work, soft sensor based on image anlaysis is proposed for quantitatively estimating the visual appearance of manufactured products and is applied to quality monitoring. The methodology consists of three steps; (1) textural feature extraction from product images using wavelet transform, (2) numerical estimation of the product appearance through projection of the textural features on subspace, and (3) use of latent variables of textural features (i.e., numerical estimates of product appearance). The focus of this approach is on the consistent and quantitative estimation of continuous variations in visual appearance rather than on classification into discrete classes. This approach is illustrated through the application to the estimation and monitoring of the appearance of engineered stone countertops.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.60-65
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• 2021

Human error is often in part in the cause of accidents and the result of various factors in an organization. Accidents should be investigated to elucidate all causes. Therefore, to reduce accidents, it is necessary to identify which factors affect human error within the organization. In this study, five groups of influencing factors on human error were selected using previousresearch, and operational definitions were made based on them. In addition, a questionnaire for measuring latent variables by operational definition was developed as an observation variable, and responses were received from employees of chemical companies in Ulsan. Based on SEM (structural equation modeling) analysis, 1) confirmatory factor analysis of variables in the human error model, 2) reliability and validity of latent variables, 3) correlations among latent variables, 4) influencing coefficients among influence factors, and 5) the verification results of the paths that these influencing factors have on human error are introduced in this study.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.35 no.12
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• pp.41-48
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• 2006

For the Designing a Dedicated Outdoor Air System with Ceiling Radiant Cooling Panels the concept of a dedicated outdoor air system(DOAS) with parallel sensible cooling was born from the decoupled system concept, which can be summarized as decoupling of ventilation and air-conditioning functions, or decoupling of sensible and latent load functions. First , remove the latent loads from the outside air(OA) intake and generated in spaces using a 100% OA ventilation system(i.e., DOAS). Second, remove the space sensible loads using a parallel mechanical cooling system, such as fan coil units, conventional variable air volume , and ceiling radiant cooling panel(CRCP) independent of the ventilation system.