• The Journal of Advanced Prosthodontics
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• v.10 no.5
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• pp.367-373
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• 2018

PURPOSE. To evaluate the fit of a crown produced based on a 3D printed model and to investigate its clinical applicability. MATERIALS AND METHODS. A master die was fabricated with epoxy. Stone dies were fabricated from conventional impressions (Conventional stone die group: CS, n=10). Digital virtual dies were fabricated by making digital impressions (Digital Virtual die group: VD, n=10). 3D data obtained from the digital impression was used to fabricate 3D printed models (DLP die group: DD, n=10, PolyJet die group: PD, n=10). A total of 40 crowns were fabricated with a milling machine, based on CS, VD, DD and PD. The inner surface of all crowns was superimposed with the master die files by the "Best-fit alignment" method using the analysis software. One-way and 2-way ANOVA were performed to identify significant differences among the groups and areas and their interactive effects (${\alpha}=.05$). Tukey's HSD was used for post-hoc analysis. RESULTS. One-way ANOVA results revealed a significantly higher RMS value in the 3D printed models (DD and PD) than in the CS and DV. The RMS values of PD were the largest among the four groups. Statistically significant differences among groups (P<.001) and between areas (P<.001) were further revealed by 2-way ANOVA. CONCLUSION. Although the fit of crowns fabricated based on the 3D printed models (DD and PD) was inferior to that of crowns prepared with CS and DV, the values of all four groups were within the clinically acceptable range (<$120{\mu}m$).

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1333-1342
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• 2013

New & renewable energy becomes a crucial subject to solve the problems inherent in the current energy resources, which results in the fast development of the new & renewable energy industry worldwide. However, not only its base is still weak but the high initial investment for technology development and certain scale of an energy market are required in many cases. For this reason, many countries in the world, including Korea, run the energy policies to foster the new & renewable energy industry such as RSP and FIT. In general, a policy should be established to take various, intertwined interests as well as a number of variables related to economic, social, environmental, and international matters into comprehensive consideration. For new & renewable energy industry, there are many variables to be considered and indexes necessary for evaluation but it is hard to take all of them into account. Even though they were considered, no criteria are available for use in a consistent manner. Therefore, this study plans to develop an evaluation model for the Korean new & renewable energy policy.

• Journal of Korean Academy of Nursing Administration
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• v.11 no.4
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• pp.371-384
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• 2005

Purpose: The aim of this study was to analysis path model of the research variables. Methods: The subjects of this study were 647 nurses who were working in the 8 general hospitals located in Seoul and Incheon area. The data were collected by self-reporting questionnaires. The data were analyzed using descriptive statistics and path analysis. Results: In the modified path model, overall fitness indexes were $X^2$= 223.27, goodness of fit index=0.90, root mean square residual=0.039, root mean square error of approximation=0.12, non-normed fit index=0.96, and normed fit index=0.90. From the model, among research variables that influence organizational effectiveness motivator, job satisfaction and organizational identification affected directly work performance. In internal marketing factors, paid-leave, communication and reward affected directly motivator. Motivator and hygiene factors affected directly job satisfaction, organizational commitment and organizational identification. Conclusion: With these findings, paid-leave, communication, reward, motivator, job satisfaction and organizational identification were direct or indirect predictors of the work performance. Therefore nursing managers ought to develop internal marketing strategies and motivation enhancing system for nurses based on this path model in order to improve the nursing organizational effectiveness.

• Journal of Welding and Joining
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• v.19 no.4
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• pp.384-390
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• 2001

There have been many problems due to deformation in industry field. Especially, it is severe in parts with small size and thin thickness and in products that must have excellent airtightness and anti-noise. The countermeasures for this deformation in field have mainly been dependent on the rule of trial and error by operator's experience because of productivities. Systematic study about this product with deformation is also insufficient that deformation is complex problem with shape, size, material of product, joining method and conditions, etc.. It is efficient to apply CAE technique without influence on productivity to this problem. There is, however much difference between the result analyzed by CAE and appearances in working field because of the insufficiency of communication between simulator and worker and of sensing data for boundary condition in analysis. In this study, to solve this deformation problem, we intend to make a simulation model that is adapted from working conditions by tuning and feedback between sensing data and simulation results. This paper include temperature monitoring and make a heat transfer model using sensing data in product as previous step for deformation analysis. The heat transfer analysis of shrinkage fit process is considerably difficult due to contact heat transfer between case and core. To solve this contact problem, gap element is used in present study.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.773-782
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• 2014

The general path model (GPM) is one approach for performing degradation-based, or Type III, prognostics. The GPM fits a parametric function to the collected observations of a prognostic parameter and extrapolates the fit to a failure threshold. This approach has been successfully applied to a variety of systems when a sufficient number of prognostic parameter observations are available. However, the parametric fit can suffer significantly when few data are available or the data are very noisy. In these instances, it is beneficial to include additional information to influence the fit to conform to a prior belief about the evolution of system degradation. Bayesian statistical approaches have been proposed to include prior information in the form of distributions of expected model parameters. This requires a number of run-to-failure cases with tracked prognostic parameters; these data may not be readily available for many systems. Reliability information and stressor-based (Type I and Type II, respectively) prognostic estimates can provide the necessary prior belief for the GPM. This article presents the Bayesian updating framework to include prior information in the GPM and compares the efficacy of including different information sources on two data sets.

• Journal of Animal Science and Technology
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• v.59 no.2
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• pp.3.1-3.7
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• 2017

Background: The modelling of lactation curve provides guidelines in formulating farm managerial practices in dairy cows. The aim of the present study was to determine the suitable non-linear model which most accurately fitted to lactation curves of five lactations in 134 Gir crossbred cows reared in Research-CumDevelopment Project (RCDP) on Cattle farm, MPKV (Maharashtra). Four models viz. gamma-type function, quadratic model, mixed log function and Wilmink model were fitted to each lactation separately and then compared on the basis of goodness of fit measures viz. adjusted $R^2$, root mean square error (RMSE), Akaike's Informaion Criteria (AIC) and Bayesian Information Criteria (BIC). Results: In general, highest milk yield was observed in fourth lactation whereas it was lowest in first lactation. Among the models investigated, mixed log function and gamma-type function provided best fit of the lactation curve of first and remaining lactations, respectively. Quadratic model gave least fit to lactation curve in almost all lactations. Peak yield was observed as highest and lowest in fourth and first lactation, respectively. Further, first lactation showed highest persistency but relatively higher time to achieve peak yield than other lactations. Conclusion: Lactation curve modelling using gamma-type function may be helpful to setting the management strategies at farm level, however, modelling must be optimized regularly before implementing them to enhance productivity in Gir crossbred cows.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.143-151
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• 2006

This paper presents the comparison of the goodness-of-fit test of analytical bond models between concrete and steel or GFRP reinforcements. Bond test specimens were prepared in accordance with the CSA codes and the rebars used in the test were steel and two types of commercial GFRP rebar products. Using the test data, a bond model was proposed, and comparison of goodness-of-fit test for existing bond models and proposed bond model was carried out by the least squares method. The result indicates that the proposed bond model has better goodness-of-fit test than the existing ones.

• Journal of Distribution Science
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• v.20 no.5
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• pp.85-96
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• 2022

Purpose: This study aims to dissemination a new concept based on empirical research on enhancing entrepreneurship intention (EI) in the theory of planned behavior (TPB) through entrepreneurship mindset (EM) and task technology fit (TTF). The TTF is a moderating variable in strengthening the relationship between EM and EI. Research design, data, and methodology: This research design was quantitative research. The respondents were 202 students from Malaysia and Indonesia who had filled out and collected an online questionnaire in Microsoft form. Three hypotheses examined the direct influence and the indirect impact of EM on EI through antecedent variables of TPB, and the effect of TTF as moderating variable to enhance the relationship between EM and EI. The data was analyzed using the WarpPLS version 7.0. Results: The result showed that EM had a significant impact on the students' EI. The interaction of EM and TTF was significantly able to improve EI. Conclusions: The findings contributed new ideas to develop the theoretical framework of the TPB model and were able be utilized by lecturers to consider the integration of EM and TTF in the model. The novelty of this study elaborated the EM and TTF variables as an extended model of the TPB.

• Journal of Korean Academy of Nursing
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• v.28 no.2
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• pp.344-357
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• 1998

This study was designed to construct a model that predicts the quality of life of family caregivers with a chronically ill patient. The hypothetical model was developed based on the findings from past studies on quality of life and on the family with a chronically ill patient. Data were collected by self-reported questionnaires from 200 family caregivers in Seoul & Kyung Gi-Do, from May 1 to July 21, 1997. Data were analyzed using descriptive statistics and correlation analysis. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which predicts causal relationships among variables. The results are as follows : 1. The overall fit of the hypothetical model to the data was moderate [X$^2$=31.54(df=23, p=.11), GFI=.96, AGFI=.91, RMR=.04]. 2. Paths of the model were modified by considering both its theoretical implication and the statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data expect chi-square value(GFI=.95, AGFI=.91, RMR=.04). 3. Some of predictive factors, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support and fatigue revealed indirect effects on the quality of life of family caregivers with a chronically ill patient. 4. The factors, burden and role satisfaction revealed significant direct effects on the quality of life of family caregivers with a chronically ill patient. 5. All predictive variables of quality of life of family caregivers with a chronically ill patient, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support, fatigue, burden and role satisfaction explained 38.0% of the total variance in the model. In conclusion, the derived model in this study is considered appropriate in explaining and predicting quality of life of family caregivers with a chronically ill patient. Therefore it can effectively be used as a reference model for further studies and suggests direction in nursing practice.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.274-275
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• 2007

The investigation of the equivalent circuit models for the electrode/electrolyte interface has been pursued for a long time by several researchers. Previous circuit models fit the experimental results in limited conditions such as frequency range, type of electrode, or electrolyte. This paper describes a new electrical circuit model and its capability of fitting the experimental results. Electrochemical impedance spectroscopy was used to characterize the interface for Au, Pt, and stainless steel electrode in 0.9% NaCl solution. Both the proposed model and the previous model were applied to fit the measured impedance results for comparison. The proposed model fits the experimental data more accurately than other models especially at the low frequency range, and it enables us to predict the impedance at very low frequency range, including DC, using the proposed model.