• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• 산업기술연구
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• 제36권
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• pp.71-76
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• 2016

In this study, we determined the precise coordinates of TBMs (Tidal Bench Marks), which used as the national reference points in coastal area of Korea, using a GPS data analysis SW for the academic and scientific applications, GAMIT/GLOBK. For accurate 3-D positioning of TBM locations, we performed the GPS point surveying according to the national surveying policy and also acquired the GPS data for 48 TBMs located in the western and southern coastal part of Korea. Considering the results of baseline analysis to each observation session obtained from GAMIT module, the baseline analysis was realized to be done precisely because the values of Normalized RMS (NRMS) were mostly less than ${\pm}0.20mm$. Before the network adjustment using GLOBK module, we evaluated the suitability of observations for each session by applying the chi-squared test (${\chi}^2$ test) to the degree of freedom in observed session. An overall distributions of ${\chi}^2$ test were less than 1.0 for all sessions, and the statistical of ${\chi}^2$ test showed the average, 0.267 with minimum and maximum value, 0.063 and 0.653, respectively. Finally, we analyzed the network adjustment for 48 TBMs to reduce the residuals of baseline analysis on each point by connecting with 42 permanent GPS stations in Korea. In the network adjustment procedure, we set up the weighted values of each permanent station to be allocated between 0.9 and 1.14, and also removed the observed points having residual exceeds 4-times of standard deviation ($4{\sigma}$).

• 지역사회간호학회지
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• 제28권4호
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• pp.513-523
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• 2017

Purpose: We evaluated the psychometric properties of a questionnaire on the acceptance of the quality improvement information system (QIIS) among long-term care workers (mostly nurses). Methods: The questionnaire composes of 21 preliminary questions with 5 domains based on the Technology Acceptance Model and related literature reviews. We developed a prototype web-based comprehensive resident assessment system, and collected data from 126 subjects at 75 long-term care facilities and hospitals, who used the system and responded to the questionnaire. A priori factor structure was developed using an exploratory factor analysis and validated by a confirmatory factor analysis; its reliability was also evaluated. Results: A total of 16 items were yielded, and 5 factors were extracted from the explanatory factor analysis: Usage Intention, Perceived Usefulness, Perceived Ease of Use, Social Influence, and Innovative Characteristics. The five-factor structure model had a good fit (Tucker-Lewis index [TLI]=.976; comparative fit index [CFI]=.969; standardized root mean squared residual [SRMR]=.052; root mean square error of approximation [RMSEA]=.048), and the items were internally consistent(Cronbach's ${\alpha}=.91$). Conclusion: The questionnaire was valid and reliable to measure the technology acceptance of QIIS among long-term care workers, using the prototype.

• 한국측량학회지
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• 제29권1호
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• pp.1-9
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• 2011

본 논문의 목적은 KOMPSAT-2 영상과 함께 제공되는 RPC를 이용하여 계산된 3차원 지형정보의 정확도를 향상시키는 것이다. 본 논문에서는 보정된 RFM 알고리즘을 제안하였고, 이러한 알고리즘을 이용하여 정확도를 향상시킬 수 있었다. 또한, 지상기준점의 수에 따른 정확도의 변화도 실험하였다. 실험에는 9개의 GCP와 24개의 CP가 사용되었다. 24개의 CP를 이용하여 실험한 결과, 수평방향의 RMSE는 2.20(m)를 나타냈으며, X방향 1.72(m), Y방향 1.37(m), Z방향 2.20(m)의 RMSE를 나타냈다.

• Asian-Australasian Journal of Animal Sciences
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• 제19권7호
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• pp.915-921
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• 2006

Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to predict future milk yield of Holstein cows in Korea. A total of 257,908 test-day (TD) milk yield records from a total of 28,135 cows belonging to 1,090 herds were considered for estimating (co)variance of the random covariate coefficients using an expectation-maximization REML algorithm in an animal mixed model. The variances did not change much between the models, having different order of Legendre polynomial, but a decreasing trend was observed with increase in the order of Legendre polynomial in the model. The R-squared value of the model increased and the residual variance reduced with the increase in order of Legendre polynomial in the model. Therefore, a model with $5^{th}$ order of Legendre polynomial was considered for predicting future milk yield. For predicting the future milk yield of cows, 132,771 TD records from 28,135 cows were randomly selected from the above data by way of preceding partial TD record, and then future milk yields were estimated using incomplete records from each cow randomly retained. Results suggested that we could predict the next four months milk yield with an error deviation of 4 kg. The correlation of more than 70% between predicted and observed values was estimated for the next four months milk yield. Even using only 3 TD records of some cows, the average milk yield of Korean Holstein cows would be predicted with high accuracy if compared with observed milk yield. Persistency of each cow was estimated which might be useful for selecting the cows with higher persistency. The results of the present study suggested the use of a $5^{th}$ order Legendre polynomial to predict the future milk yield of each cow.

• 한국전산유체공학회지
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• 제10권2호
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• pp.38-47
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• 2005

Substructuring methods are often used in finite element structural analyses. In this study a multi-level substructuring(MLSS) algorithm is developed and proposed as a possible candidate for finite element fluid solvers. The present algorithm consists of four stages such as a gathering, a condensing, a solving and a scattering stage. At each level, a predetermined number of elements are gathered and condensed to form an element of higher level. At the highest level, each sub-domain consists of only one super-element. Thus, the inversion process of a stiffness matrix associated with internal degrees of freedom of each sub-domain has been replaced by a sequential static condensation of gathered element matrices. The global algebraic system arising from the assembly of each sub-domain matrices is solved using a well-known iterative solver such as the conjugare gradient(CG) or the conjugate gradient squared(CGS) method. A time comparison with CG has been performed on a 2-D Poisson problem. With one domain the computing time by MLSS is comparable with that by CG up to about 260,000 d.o.f. For 263,169 d.o.f using 8 x 8 sub-domains, the time by MLSS is reduced to a value less than $30\%$ of that by CG. The lid-driven cavity problem has been solved for Re = 3200 using the element interpolation degree(Deg.) up to cubic. in this case, preconditioning techniques usually accompanied by iterative solvers are not needed. Finite element formulation for the incompressible flow has been stabilized by a modified residual procedure proposed by Ilinca et al.[9].

• 유기물자원화
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• 제21권2호
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• pp.88-96
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• 2013

본 연구의 목적은 고형폐기물의 메탄발생 특성을 나타내기 위한 1차 반응식과 S형태 식들의 적합성을 평가하는 것이다. S형태 식은 수정 Gompertz와 Logistic 식을 사용하였다. 모델의 적합성을 평가하기 위해 잔차제곱합, 표준제곱근 오차, Akaike's information criterion 등의 통계분석을 실시하였다. AIC (Akaike's information criterion)는 모델의 변수 개수 차이에 따른 모델 적합성을 비교하기 위하여 적용하였다. 1차 반응식의 경우 지체기를 고려하지 않을 때보다 고려하였을 경우 잔차제곱합과 표준제곱근 오차는 감소하는 것으로 나타났다. 그러나 1차 반응식의 경우 S형태 식보다 AIC가 상대적으로 높게 나타났다. 이는 S형태 식이 1차 반응식보다 메탄발생특성을 나타낼 때에 더욱 적합한 것으로 사료된다.

• 수산경영론집
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• 제42권2호
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• pp.69-83
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• 2011

This paper estimates demand functions of oyster as Kimchi's ingredients of capital area, other areas excluding a capital area, and a whole area in Korea to forecast its demand quantities in 2011~2015. To estimate oyster demand function, this paper uses pooled data produced from Korean housewives over 30 years old in 2009 and 2010. Also, this paper adopts several econometrics methods such as Ordinary Least Squares and Feasible Generalized Least Squares. First of all, to choose appropriate variables of oyster demand functions by area, this paper carries out model's specification with joint significance test. Secondly, to remedy heteroscedasticity with pooled data, this paper attempts residual plotting between estimated squared residuals and estimated dependent variable and then, if it happens, undertakes White test to care the problem. Thirdly, to test multicollinearity between variables with pooled data, this paper checks correlations between variables by area. In this analysis, oyster demand functions of a capital area and a whole area need price of the oyster, price of the cabbage for Gimjang, and income as independent variables. The function on other areas excluding a capital area only needs price of the oyster and income as ones. In addition, the oyster demand function of a whole area needed White test to care a heteroscedasticity problem and demand functions of the other two regions did not have the problem. Thus, first model was estimated by FGLS and second two models were carried out by OLS. The results suggest that oyster demand quantities per a household as Kimchi's ingredients are going to slightly increase in a capital area and a whole area, but slightly decrease in other areas excluding a capital area in 2011~2015. Also, the results show that oyster demand quantities as kimchi's ingredients for total household targeting housewives over 30 years old are going to slightly increase in three areas in 2011~2015.

• Journal of Preventive Medicine and Public Health
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• 제55권6호
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• pp.578-585
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• 2022

Objectives: This study aimed to adapt the survey questionnaire designed by Moens et al. (2021) and determine the validity and reliability of the Arabic version of the survey in a sample of the Saudi population experiencing teleworking. Methods: The questionnaire includes 2 sections. The first consists of 13 items measuring the impact of extended telework during the coronavirus disease 2019 (COVID-19) crisis. The second section includes 6 items measuring the impact of the COVID-19 crisis on selfview of telework and digital meetings. The survey instrument was translated based on the guidelines for the cultural adaptation of self-administrated measures. Results: The reliability of the questionnaire responses was measured by Cronbach's alpha. The construct validity was checked through exploratory factor analysis followed by confirmatory factor analysis (CFA) to further assess the factor structure. CFA revealed that the model had excellent fit (root mean square error of approximation, 0.00; comparative fit index, 1.0; Tucker-Lewis index, 1; standardized root mean squared residual, 0.0). Conclusions: The Arabic version of the teleworking questionnaire had high reliability and good validity in assessing experiences and perceptions toward teleworking. While the validated survey examined perceptions and experiences during COVID-19, its use can be extended to capture experiences and perceptions during different crises.

• 한국지진공학회논문집
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• 제28권4호
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• pp.193-203
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• 2024

Existing reinforced concrete (RC) building frames constructed before the seismic design was applied have seismically deficient structural details, and buildings with such structural details show brittle behavior that is destroyed early due to low shear performance. Various reinforcement systems, such as fiber-reinforced polymer (FRP) jacketing systems, are being studied to reinforce the seismically deficient RC frames. Due to the step-by-step modeling and interpretation process, existing seismic performance assessment and reinforcement design of buildings consume an enormous amount of workforce and time. Various machine learning (ML) models were developed using input and output datasets for seismic loads and reinforcement details built through the finite element (FE) model developed in previous studies to overcome these shortcomings. To assess the performance of the seismic performance prediction models developed in this study, the mean squared error (MSE), R-square (R²), and residual of each model were compared. Overall, the applied ML was found to rapidly and effectively predict the seismic performance of buildings according to changes in load and reinforcement details without overfitting. In addition, the best-fit model for each seismic performance class was selected by analyzing the performance by class of the ML models.