• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.1029-1042
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• 2018

Purpose: The purpose of this study is to explore the health care decision making of Ethiopian women at household level. Moreover it is to understand the factors that influence to potential customers in healthcare industry from the social quality level perspective. Methods: We used Ethiopia Demographic Health Survey (EDHS) 2005 & 2016, which provided data about currently married women aged 15-49 years (N=2003, N=2017, respectively). We performed a chi-square test, and a Pearson correlation and a logistic regression. Andersen model is considered as well. Results: This study revealed that the mobility decision making has an association with health care decision making of women. Furthermore, there is a moderate effect of an economic decision making of women. Lastly, the women's decision making empowerment level increase year by year. Conclusion: Health care industry has to consider potential costumers among women like in Ethiopia, whose decision making empowerment will enhance on their own healthcare in future. It is very important to figure out factors from the social quality management domain. It helps finding a new market from downstream approach. From this point, the impact of decision making of women empowerment has a significant implication from the holistic perspective.

• Journal of Korean society of Dental Hygiene
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• v.22 no.1
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• pp.73-79
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• 2022

Objectives: This study aimed to analyze the correlation among dental hygiene students' life stress, grit, and career decisionmaking self-efficacy, and to identify the factors influencing career decision-making self-efficacy. Methods: Data were collected through a survey from October 19 to November 7, 2020, targeting 196 students enrolled in dental hygiene departments in Daejeon and Daegu. Life stress, grit, and career decision-making self-efficacy were measured. For data analysis, the descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple regression analysis were performed using SPSS/WIN 24.0. Results: Life stress was 2.12 points, grit was 3.07 points, and career decision-making self-efficacy was 3.43 points. Career decision-making self-efficacy was influenced by satisfaction with the course department, as well as life stress and grit; the most influential factor was found to be grit. These variables could explain career decision-making self-efficacy by 23.8%. Conclusions: For students to advance successfully into society as dental hygienists, a career decision-making self-efficacy promotion program that can help students achieve self-confidence and establish career goals should be developed. additionally, a program that can enhance grit should be included in this development.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2
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• pp.75-79
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• 2008

In this paper, we propose a novel speech enhancement technique using global soft decision (GSD) based on the probabilistic outputs of support vector machine (SVM). Generally, speech enhancement algorithms applied soft decision gain modification and noise power estimation have bettor performance than those employing hard decision. Especially, global speech absence probability (GSAP), which is known as an effective measure of the speech absence in each frame, has been adopted to SD-based speech enhancement methods. For this reason, we introduce a new GSAP estimated from the probabilistic output of SVM using sigmoid function. The performance of the proposed algorithm is evaluated by the PESQ and MOS test under various noise environments and yields better results compared with the conventional GSD scheme.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.156-172
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• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• Journal of Korean Critical Care Nursing
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• v.13 no.1
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• pp.27-43
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• 2020

Purpose : This integrative review aimed to synthesize studies on intensive care unit (ICU) nurses' attitude, perceptions, and experiences toward end-of-life care decision-making. Methods : Using Whittermore and Knafl (2005)'s methods, we identified and synthesized research articles published in domestic journals between the years 2003 and 2019 and evaluated the quality of selected articles using the Mixed Methods Appraisal Tool. Results : In the 13 studies reviewed, 12 were published prior to enactment of the "The Act for Hospice and Palliative Care and Decision-Making about Life-Sustaining Treatment (2018)." All nine quantitative studies identified were based on cross-sectional descriptive survey. In four qualitative studies, content analysis (n=2) and phenomenology (n=2) were used. Overall, ICU nurses were well-aware of the necessity of communicating and limiting life-sustaining treatments. Many ICU nurses had positive attitude towards limiting life-sustaining treatments to promote patients' comfort and dignity. Although nurses were willing to take active roles, they also reported having experienced high stress in the process of decision-making and implementation. Conclusions : It is important to prepare ICU nurses with proper knowledge and attitude regarding the topic area. It is also equally important to develop systems to support nurses' emotional stress and moral distress during communication, decision-making, and implementation.

• Nuclear Engineering and Technology
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• v.35 no.4
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• pp.318-335
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• 2003

Expert judgment is frequently employed in the search for the solution to various engineering and decision-making problems where relevant data is not sufficient or where there is little consensus as to the correct models to apply. When expert judgments are required to solve the underlying problem, our main concern is how to formally derive their technical expertise and their personal degree of familiarity about the related questions. Formal methods for gathering judgments from experts and assessing the effects of the judgments on the results of the analysis have been developed in a variety of ways. The most important interest of such methods is to establish the robustness of an expert's knowledge upon which the elicitation of judgments is made and an effective trace of the elicitation process as possible as one can. While the resultant expert judgments can remain to a large extent substantiated with formal elicitation methods, their applicability however is often limited due to restriction of available resources (e.g., time, budget, and number of qualified experts, etc) as well as a scope of the analysis. For this reason, many engineering and decision-making problems have not always performed with a formal/structured pattern, but rather relied on a pertinent transition of the formal process to the simplified approach. The purpose of this paper is (a) to address some insights into the balanced use of formally structured and simplified approaches for the explicit use of expert judgments under resource constraints and (b) to discuss related decision-theoretic issues.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.255-264
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• 2006

The auxiliary reinforcement method is normally applied to prevent a possible collapse of the tunnel face where the ground condition is not favorable or geologic information is not sufficient. Recently, several engineering approaches have been made to choose the effective reinforcement methods using expert system such as neural network and fuzzy theory field, among others. Even if the expert system has offered many decision aid tools to properly select the reinforcement method, the quantitative assessment items are not easy to estimate and this is why the data mining technique, widely used in the field of social science, medical treatment, banking and agriculture, is introduced in this study. Using decision tree together with PDA, the decision aids for reinforcement method based on field construction data are created to derive the field rules and future study will be concentrated on the application of the proposed methods in a variety of underground development cases.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.471-478
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• 2003

In this paper, we reconsider the Kolmogorov-Smirnoff distance as a split criterion for binary decision trees and suggest an algorithm to obtain the Kolmogorov-Smirnoff distance more efficiently when the input variable have more than three categories. The Kolmogorov-Smirnoff distance is shown to have the property of exclusive preference. Empirical results, comparing the Kolmogorov-Smirnoff distance to the Gini index, show that the Kolmogorov-Smirnoff distance grows more accurate trees in terms of misclassification rate.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.3
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• pp.381-395
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• 1998

The purpose of this study is to determine the optimal gas turbine system for special purpose ships. First we generate critical evaluation criteria an construct their hierarchical structure. The criteria consist of qualitative ones as well as the economic factor. Then AHP is applied to solve the decision making problem AHP gibes good results different from those only by the economic evaluation methods. And during the analysis, the procedure produces many useful informations to the decision making. The results shows that AHP is an appropriate method for these kinds of problems such as the system selection.