• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.11
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.1
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• pp.68-77
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• 1998

The purpose of this paper is to establish a method estimating the daily urban water demand using statistical analysis that is used for developing the efficient management and operation of the water supply facilities, and accurary of the model is verified by error rate and F-value. The data used in this study were the daily urban water use, the weather conditions such as temperature, precipitation, relative humidity, etc, and the day of The week. The case study was taken placed for the city of Namwon in Korea. The raw data used in this study were rearranged either by month or by season for analysis purpose, and the statistical analysis was applied to the data to obtain the regression model As a result of this study, the linear regression model was developed to estimate the daily urban water use with weather condition. The regression constant and coefficients of the model were determined for each month of a year. The accuracy of the model was within 3% of average error and within 11% of maximum error. The resulting model was found to he useful to the practical operation and management of the water supply facilities.

• Research in Community and Public Health Nursing
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• v.31 no.4
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• pp.459-471
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• 2020

Purpose: The purpose of this study is to construct and validate a posttraumatic growth structural model for firefighters based on Calhoun and Tedeschi's model (2006). Methods: The research data was collected from 200 firefighters working in Gyeongsang-do, Jeolla-do, and Gyeonggi-do. The participants completed an anonymous survey asking about ego-resilience, active coping, family support, organizational support, self-exposure, deliberate rumination, posstraumatic stress and posttraumatic growth. Results: The model selected as a final model was the one that supports 10 hypotheses out of 13 hypotheses. In the final model, deliberate rumination (β=.59, p<.001) had a significant effect in the posttraumatic growth of firefighters. Active coping, organizational support, self-exposure, ego-resilience and posttraumatic stress had a significant indirect effect. The explanatory power of these variables was 36.0%. Conclusion: The results of the survey show that it is important to develop a strategy to strengthen deliberate rumination. In addition, encouraging deliberate rumination through organizational support and self-exposure can promote posttraumatic growth of firefighters.

• Korean Journal of Adult Nursing
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• v.18 no.1
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• pp.115-124
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• 2006

Purpose: The purpose of this study was to propose a theoretical model of hope commonly held by the cancer patients just after surgery, under the assumptions that hope of those patients is not only realistic and disease oriented but in dialectical circulation. Method: A theoretical model was generated through 4 steps: exploring a hope structure by synthesizing the relevant hope structures expressed in Kim and Tae's studies, in-depth literature review, examining the meanings of the concepts consisted of the structure in use and their causal relations in logical adequacy, proposing a theoretical structure through synthesizing the causal relations, and diagramming the structure. Results: The proposed theoretical model involves concepts such as Cancer Related Uncertainty (CRU), Efforts to Find out the Possibility of Cure or Recovery (EFPCR), and Hopefulness or Hopelessness. The 'EFPCR' is stipulated as 'Behaviors Related to Looking for Evidences or Cues (BRLEC)' and 'Formation of Cognitive Schema (FCS)'. In the model, Hopefulness is directly influenced by 'CRU in low', which is affected by 'FCS in good' from the result of EFPCR started with 'CRU in increase' while 'CRU with increase' from the result from EFPCR has direct effect on Hopelessness. Conclusion: The theoretical model would be used to enhancing hope of the cancer patients in post-operation.

• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.709-724
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• 2013

Purpose: The purpose of this study is to examine five evaluation models constructed by different normalization and aggregation methods in terms of the volatility of rankings and rank reversals. We also explore how the volatility of rankings of the five models changes and how often the rank reversals occur when the outliers are removed. Methods: We used data published in the Complete University Guide 2014. Two universities with missing values were excluded from the data. The university rankings were derived by using the five models, and then each model's volatility of rankings was measured. The box-plot was used to detect outliers. Results: Model 1 has the lowest volatility among the five models whether or not the outliers are included. Model 5 has the lowest number of rank reversals. Model 3, which has been used by many institutions, appears to be in the middle among the five in terms of the volatility and the rank reversals. Conclusion: The university rankings vary from one evaluation model to another depending on what normalization and aggregation methods are used. No single model exhibits clear superiority over others in both the volatility and the rank reversal. The findings of this study are expected to provide a stepping stone toward a superior model which is both reliable and robust.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.865-876
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• 2018

This study focuses on the operating requirements of multi-resolution modeling(MRM) in training war-game model and proposes solutions for major issues of multi-resolution interoperation between Combat21 model and tank multi-purpose simulator(TMPS). We study the operating requirements of MRM through interviews with defense M&S experts and literature surveys and report the various issues that could occur with low-resolution model Combat21 and high-resolution model TMPS linked, for example, when to switch objects, what information to exchange, what format to switch to, and how to match data resolutions. This study also addresses the purpose and concept of training using multi-resolution interoperation, role of each model included in multi-resolution interoperation, and issue of matching damage assessments when interoperated between models with different resolutions. This study will provide the common goals and directions of MRM research to MRM researchers, defense modeling & simulation organizations and practitioners.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.223-224
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• 2021

The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.163-189
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• 2010

The purpose of this research is to develop a decision-making model for the calculation of the National Disaster Management System's standard prevention workforce quota. The final purpose of such model is to support in arranging a rationally sized prevention workforce for local authorities by providing information about its calculation in order to support an effective and efficient disaster management administration. In other words, it is to establish and develop a model that calculates the standard disaster prevention workforce quota for basic local governments in order to arrange realistically required prevention workforce. In calculating Korea's prevention workforce, it was found that the prevention investment expenses, number of prevention facilities, frequency of flood damage, number of disaster victims, prevention density, and national disaster recovery costs have positive influence on the dependent variable when the standard prevention workforce was set as the dependent variable. The model based on the regression analysis-which consists of dependent and independent variables-was classified into inland mountainous region, East coast region, Southwest coastal plain region to reflect regional characteristics for the calculation of the prevention workforce. We anticipate that the decision-making model for the standard prevention workforce quota will aid in arranging an objective and essential prevention workforce for Korea's basic local authorities.

• Journal of Korean Library and Information Science Society
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• v.49 no.3
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• pp.331-359
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• 2018

The purpose of this study is to analyse the Big6 model and the Big6 modification model to find out the characteristics of the Big6 model and to derive implications for applying the Big6 model in the field. For this purpose, the information literacy standards of the AASL and the ACRL were compared with the Big6 model. The Big6 model, influenced by Bloom's taxonomy was analyzed alongside the Big6+3 model, the Big8 model and the modified Big6 model, provided by LG Science Land. As a result, the Big6 model could be used as an information problem-solving model, metacognitive activation strategy, and scaffolding to improve students' information literacy. In addition, it could be used as a model for constructivism, inquiry-based learning, the integration of curriculum, collaborative education, and ICT technology. How teacher-librarians or librarians apply the Big6 model is related to the improvement of critical thinking skills. Teacher-librarians and librarians need to plan situations, subjects, topics, and methods in a systematic and specific way when applying the Big6 model to the information literacy curriculum.

• Korean Journal of Adult Nursing
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• v.28 no.5
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• pp.585-594
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• 2016

Purpose: The purpose of this study was to develop and test a predictive model on the male nurses' turnover intention. Methods: This study utilized the model-testing design based on the Price's causal model of turnover. This study collected data from 306 male nurses on a national scale with structured questionnaires measuring job opportunity, kinship responsibility, positive emotion, work autonomy, role conflict, work satisfaction, organizational commitment, and turnover intention. The data were analyzed using SPSS/WIN 22.0 program and AMOS 20.0 program. Results: As the outcomes satisfied the recommended level, the hypothetical model appeared to fit the data. Twenty-seven of the 38 hypotheses selected for the hypothetical model were statistically significant. 54.2% of turnover intention was explained by job opportunity, kinship responsibility, positive emotion, work autonomy, role conflict, work satisfaction and organizational commitment. Conclusion: The hypothetical model of this study was confirmed to be adequate in explaining and predicting male nurses' turnover intention. Findings from this study can be used to design appropriate strategies to decrease the male nurse's turnover intention.