• Korean Journal of Adult Nursing
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• v.17 no.5
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• pp.762-771
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• 2005

Purpose: The purpose of this study was to identify characteristics of patients who were recipients of decision-making DNR, to describe the situations of DNR, and to analyze the APACHE III and MOF scores. Method: Data collection was conducted through reviews of medical records of 51 patients and through interviews with families of patients who were decision-makers for DNR at C university K Hospital located in Seoul from April to September 2002. Results: The men's APACHE III and MOF scores were higher than the women's and the non cancer patients were higher than cancer patients. Some 80.4% of DNR orders was by communication, while 11.8% of consents were written. Each of APACHE III and MOF scores of patients in the intensive care unit was higher than the patients in general ward at both points of admission and decision-making of DNR. APACHE III and MOF scores positively correlated statistically with each other. Conclusions: The findings of this study suggest that APACHE III and MOF scores be useful for decision-making of DNR as a tool measuring severity.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.855-861
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• 2005

Every public agency governing infrastructure has to plan effectively for rehabilitation of existing facilities within the constraints of the capital program. Numerous technical, social, political, financial, and management constraints govern the decision to rehabilitate a facility. However, without a systematic procedure for selecting facilities for rehabilitation, within the prevailing constraints, it is possible that the funds available for rehabilitation might be suboptimized. Therefore, a decision support system that assists the user in selecting facilities for rehabilitation while considering the technical, social, financial, and political and management constraints will be useful in the decision-making process. This paper compares the Analytical Hierarchy Process (AHP) with the Swing Weight method used to prioritize functional criteria for suburban station rehabilitation. This paper also contains a brief discussion about the relevance of the Multi Attribute utility theory in developing a decision model for the problem at hand. The results of this paper provides the user with a decision support system that would prioritize the stations in order of their weights obtained by a systematic evaluation of various criteria and sub-criteria involved in the decision making process

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.15-32
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• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.147-153
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• 2017

The Korean government has implemented various policies to introduce the cloud to the public sector. The objectives of the paper are to develop a decision-making model and to propose the roadmap for cloud introduction in the public sector. To achieve these objectives, we analyze the characteristics of public services and types of cloud service. Then we develope a cloud introduction method using fuzzy AHP based convergence decision-making model. As a result of this study, we decided to prioritize the cloud service candidates and proposed a three-step roadmap. The results are expected to contribute to cloud introduction and transition in the public sector and establishment of the cloud policy. In the future, it will be necessary to develop budget plans as well as additional decision-making factors for cloud adoption.

• Fire Science and Engineering
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• v.33 no.5
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• pp.86-93
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• 2019

Previous studies related to evacuation guidance systems are focused on the system construction, and research on manual of the standard evacuation map is insufficient. Therefore, this research is a basic study to establish the standard evacuation map, and analyzed the decision-making time according to the type and size for each component of the evacuation map. Experimental elements were derived through the review of previous studies and legal regulations. After that, decision-making time was analyzed according to the type and size of the component display method. An experiment was conducted to analyze the decision-making time according to the type and size of the component display method. Afterwards, through the statistical test, the evacuation map guidelines for smartphones were proposed.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.502-509
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• 2013

In Information age, The academic liberal art computer education course set up goals to promote computer literacy and develop the ability to cope with changes in information society and improve productivity and national competitiveness. In this paper, we analyze on discovering of decisive variable and satisfaction index to have a influence on computer education on university students. As a preprocessing course, the proposed method selects optimum variable using correlation based feature selection(CFS) of machine learning tool based on Java and we calculate weighted value for each variable and then, we generate the optimal variable using weighted value based on fuzzy decision making method. we proposed Fuzzy decision making method in analysis of the academic liberal art computer education satisfaction index data and checked the accuracy of the satisfaction evaluation by using recall and precision.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.828-833
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• 2009

WWW which is an applicable massive set of document on the Web is a thesaurus of various information for users. However, Search engines spend a lot of time to retrieve necessary information and to filter out unnecessary information for user. In this paper, we propose the EFAM(the Extended Fuzzy AHP Method) model to manage the Web resource efficiently, and to make a decision in the problem of specific domain definitely. The EFAM model is concerned with the emotion analysis based on the domain corpus information, and it composed with systematic common concept grids by the knowledge of multiple experts. Therefore, The proposed the EFAM model can extract the documents by considering on the emotion criteria in the semantic context that is extracted concept from the corpus of specific domain and confirms that our model provides more efficient decision-making through an experiment than the conventional methods such as AHP and Fuzzy AHP which describe as a hierarchical structure elements about decision-making based on the alternatives, evaluation criteria, subjective attribute weight and fuzzy relation between concept and object.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.5-17
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• 1996

There are various cases that we vote for making a decision or combining ideas (i.e. human being's opinions) in group meetings. Group Decision Support System(GDSS) provides us with a number of voting methods for decision making or aggregation of the ideas. It is generally difficult to select a voting method appropriate for given a meeting situation, without any aid of experts or computers having a knowledge on voting. In this paper we propose a supporting system for selecting an appropriate voting method. Since the selected method is recommended to the facilitator of GDSS, a part of time and effort related with the voting would be reduced. The knowledge in the system is represented as rules that are inductively generated from examples of voting. We used UNiK-INDUCE with ID3 algorithm so as to learn, which is a tool of developing expert systems.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.93-103
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• 1997

LHR(Landfill Site Hazard Ranking Model) was developed for ranking the relative hazard of landfill sites by using the method of value-structured approach. LHR consists of combining a multiattribute decision-making method with a Qualitative risk assessment approach. A pairwise com parisian method was applied to determine weights of landfill site factors related. To determine the hazard of landfill site, hydrogeological factors, waste characteristics factors and receptors factors were evaluated by LHR. LHR can help decision-makers prioritization of remediation of landfill sites through the relatively convenient and concise evaluation method of landfill site features related. LHR focuses mainly on pathways of groundwater and surfacewater for evaluating landfill hazard to receptors including humans. To validiate the applicability of LHR, Nanjido Landfill site, Metropolitan Landfill site, and Hwasung Landfill site were evaluated.