• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.3
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• pp.304-315
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• 2016

Purpose: The purpose of this study was to explore the relationships of critical thinking disposition (CT), nursing work environment (NWE), and clinical decision making ability among nurses. Methods: A cross-sectional, descriptive study design was conducted on 192 nurses who had worked for more than six months in five general hospitals. A self-reported questionnaire was used to collect data, which included demographics, CT, NWE, and clinical decision making ability. Results: The mean score of CT was 3.5. The highest score was on the objectivity of CT and the lowest on systematicity. The mean score of NWE was 2.3. The highest score was on the collegial nurse-physician relations of NWE and the lowest on the staffing and resource adequacy. The mean score of clinical decision making ability was 3.3. In hierarchical multiple regression, affecting factors on clinical decision making ability were CT and NWE. Conclusion: The findings showed that clinical decision making ability is associated with CT and NWE. To improve clinical decision making ability, it is important to improve CT. In addition, it should be considered to improve NWE where the nurses can make a decision with their job through critical thinking.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.3-8
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• 1998

The present work proposes the potential fuzzy framework, based on fuzzy set theory, for supporting decision-making problems, especially, selection problems of a best design in the area of nuclear energy system. The framework proposed is composed of the hierarchical structure module, the assignment module, the fuzzification module, and the defuzzification module. In the structure module, the relationship among decision objectives, decision criteria, decision sub-criteria, and decision alternatives is hierarchically structured. In the assignment module, linguistic or rank scoring approach can be used to assign subjective and/or vague values to the decision analyst's judgment on decision variables. In the fuzzification module, fuzzy numbers are assigned to these values of decision variables. Using fuzzy arithmetic operations, for each alternative, fuzzy preference index as a fuzzy synthesis measure is obtained. In the defuzzification module, using one of methods ranking fuzzy numbers, these indices are defuzzified to overall utility values as a cardinality measure determining final scores. According these values, alternatives of interest are ranked and an optimal alternative is chosen. To illustrate the applicability of the framework proposed to selection problem, as a case example, the best option choice of four design options under five decision criteria for primary containment wall thickening around large penetrations in an advanced nuclear energy system is studied.

• Journal of the Korean Home Economics Association
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• v.24 no.4
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• pp.163-177
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• 1986

The purpose of this study is to present basic data of clarifying the differences between employed and unemployed wives' family and comparing low classes with other classes for the more reasonable and successful home administration through investigating and analyzing decision-making patterns of the families of working women in the low income group. The questionnaires were distributed in September 1984 to 300 working women in the city of Seoul and Sung-Nam. Statistical methods such as frequency, percentage and the mean value were used for grasping general characteristics of the families and F-test, Pearson's Correlations were used for investigating the interrelation of the related variables. The results of this study were as follows; 1) Wife's participation indecision-making was increased while joint decision-making was decreased compared with those of unemployed wives' family and other classes. 2) Both of the degree of conjugal participation in decision-making and joint decision-making were influenced by wife's educational level, disparity in educations of couple, husbands' occupation, family income, wife's age. But duration of marriage affected only the degree of joint decision-making. Especially family income and husbands; occupations turned to be important variables in low income families. 3) In case of wife's satisfaction with her occupation, joint decision-making was well achieved or not according to certain decision items. Though wife and husband satisfied with their marriage, joint decision-making was not well performed in working wives' family with low income.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.91-96
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• 2019

Recently, it is expected for requirement for more scientific research of weapon systems acquisition alternatives with reliability and objectivity. For these needs, study on methodology of weapon systems acquisition alternatives is but on-going, but it is still in its early stages and is unprofessional. We compared general decision making methods, government development program decision making methods, methodologies of weapon systems acquisition alternatives research such as AHP, ANP, KAAM and proposed AHP as weapon acquisition analysis. This study guarantees objectivity and derives scientific research results reliability by analyzing and comparing comprehensive elements such as cost, effectiveness, deployment schedule, program management risk. Further study on AHP weight and other decision making methods is needed considering category of weapon systems and program characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4549-4567
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• 2016

To cope with the complex electromagnetic environment of wireless communication systems, anti-jamming decision methods are necessary to keep the reliability of communication. Basing on the rule-reduced genetic algorithm (RRGA), an anti-jamming decision method is proposed in this paper to adapt to the fast channel variations. Firstly, the reduced decision rules are obtained according to the rough set (RS) theory. Secondly, the randomly generated initial population of the genetic algorithm (GA) is screened and the individuals are preserved in accordance with the reduced decision rules. Finally, the initial population after screening is utilized in the genetic algorithm to optimize the communication parameters. In order to remove the dependency on the weights, this paper deploys an anti-jamming decision objective function, which aims at maximizing the normalized transmission rate under the constraints of minimizing the normalized transmitting power with the pre-defined bit error rate (BER). Simulations are carried out to verify the performance of both the traditional genetic algorithm and the adaptive genetic algorithm. Simulation results show that the convergence rates of the two algorithms increase significantly thanks to the initial population determined by the reduced-rules, without losing the accuracy of the decision-making. Meanwhile, the weight-independent objective function makes the algorithm more practical than the traditional methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.184-191
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• 2017

This paper presents cluster based hybrid spectrum sensing system for M2M services. For each cluster, secondary nodes within the transmission radius of the primary node use hard decision method through local spectrum sensing to determine whether the primary node exists. And the other secondary nodes and the secondary nodes having poor radio channel conditions judge the existence of the primary node through the soft decision method of the values obtained by performing the cooperative spectrum sensing. In the proposed hybrid spectrum sensing system, the performance according to the number of secondary nodes is analyzed with the conventional system over Rayleigh fading channel. As the number of cooperative sensing users increased to 2, 3 and 4, the cluster error probability decreased to 0.5608, 0.5252 and 0.4001 at SNR of -10[dB] respectively. Since the proposed system uses less overhead traffic, it is found that it is more effective in terms of frequency usage than the conventional system using soft decision-soft decision and soft decision-hard decision methods.

• The Journal of Korean Society for School & Community Health Education
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• v.15 no.1
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• pp.45-59
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• 2014

Objectives: This study is designed to evaluate the influential factors of career decision-making self-efficacy and career identity by health science college students on their job preparation beaviors. Methods: The total 714 questionnaires were distributed to juniors and seniors of health science college, and the result was statistically analyzed through IBM SPSS statistics 20.0. Results: 1. There was no significant difference of job preparation behavior between male students and female students, and while seniors showed highly active job preparation behaviors, those who had high satisfaction level toward their major studies, high academic achievement, and outgoing personality had highly active job preparation behaviors. 2. Students with high satisfaction level toward their major studies, high academic achievement, outgoing personality, and high expected salaries showed high career decision-making self-efficacy level. 3. Students with high satisfaction level toward their major studies, high academic achievement and highly outgoing personality showed high level of career identity. 4. Subsidiary factors of career decision-making self-efficacy were collection of job information, goal setting, planning, and self-assessment, and all of them showed correlation with job preparation behaviors. 5. Among subsidiary factors of career decision-making self-efficacy, "self-understanding" and understanding of job information showed correlation with job preparation behaviors. Conclusion: For improvement on career decision-making self-efficacy and career identity of health science college students, individual support, psychological support, educational support and other supports regarding job employment to provide wide paths and methods for job preparation behaviors are essential, and through various job employment education program and graded counseling, job preparation behaviors shall be promoted as a great strategy.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• Journal of Korean Academy of Nursing
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• v.48 no.5
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• pp.578-587
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• 2018

Purpose: This study aimed to understand the mechanisms of decision regret and stress of family surrogates' end-of-life decision making using an exploratory path model. In particular, the research identified the direct effects of perceptions of uncertainty and effective decisions on decision regret and stress, and examined the indirect effects of being informed, having clear values, and being supported for decision regret and the stress of end-of-life decision making through the mediating variables of perceptions of uncertainty and effective decisions. Methods: Data were collected from 102 family surrogates who had participated in end-of-life decision making for patients with terminal cancer in a tertiary hospital. Results: Perception of effective decisions was a significant direct predictor of decision regret, and uncertainty was a significant predictor of stress among the participants. Being informed, having clear values, and being supported had a significant indirect influence on decision regret through the perception of effective decisions among family surrogates. However, only having clear values had a significant indirect influence on stress through the perception of uncertainty. The model explained 63.0% of decision regret and 20.0% of stress among the participants and showed a good fit with the data, ${\chi}^2=12.40$ (df=8, p=.134), TLI=.97, and RMSEA=.07. Conclusion: Nurses can support family surrogates in end-of-life decision-making processes to decrease their decision regret by providing information about end-of-life care choices, clarifying personal values, and supporting the decision-making process, and to relieve their stress by facilitating the clarification of personal values.

• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.161-172
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• 2006

This study aims to compare and contrast the Kansei modeling methods for building a luxuriousness model that people feel about appearance of mobile phones. For the evaluation based on Kansei engineering approaches, 15 participants were employed to evaluate 18 mobile phones using a questionnaire. The results of evaluation were analyzed to build luxuriousness models through quantification I method, neural network, and decision tree method, respectively. The performance of Kansei modeling methods was compared and contrasted in terms of accuracy and predictability. The result of comparison of modeling methods indicated that model accuracy and predictability was closely related to the number of variables and data size. It was also revealed that quantification I method was the best in terms of model accuracy while decision tree method was the best modeling method with small variance in terms of predictability. However, it was empirically found that quantification I method showed extremely unstable predictability with small number of data. Consequently, it is expected that the research findings of this study might be utilized as a guideline for selecting proper Kansei modeling method.