• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.83-102
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• 2008

Ubiquitous computing requires timely supply of contextual information in order to upgrade decision quality. In this sense, this study is aimed at proposing a multi-dynamic decision support system for highly ill-structured problems. Especially, it is very important for decision makers in the ubiquitous computing to coordinate conflicts among local goals and global goal harmoniously. The proposed Multi-Dynamic Decision Support System (MDDSS) is basically composed of both central structure and distributed structure, in which central structure supports multi objects decision making and distributed structure supports individual decision making. Its hybrid architecture consists of decision processor, multi-agent controller and intelligent knowledge management processor. Decision processor provides decision support using contexts which come from individual agents. Multi-agent controller coordinates tension among multi agents to resolve conflicts among them. Meanwhile, intelligent knowledge management processor manages knowledge to support decision making such as rules, knowledge, cases and so on. To prove the validity of the proposed MDDSS, we applied it to an u-fulfillment problem system in which many kinds of decision makers exist trying to satisfy their own objectives, and timely adjustment of action strategy is required. Therefore, the u-fulfillment problem is a highly ill-structured problem. We proved its effectiveness with the aid of multi-agent simulation comprising 60 customers and 10 vehicles under three experimental modes.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.557-567
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• 2005

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 are, 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 multiperson 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 interaction 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.

• Informatization Policy
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• v.27 no.4
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• pp.47-66
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• 2020

The rapid development of artificial intelligence technologies such as machine learning and deep learning is expanding its impact in the public administrative and public policy sphere. This paper is an exploratory study on policy decision-making in the age of artificial intelligence to design automated configuration and operation through data analysis and algorithm development. The theoretical framework was composed of the types of policy problems according to the degree of problem structuring, and the success and failure cases were classified and analyzed to derive implications. In other words, when the problem structuring is more difficult than others, the greater the possibility of failure or side effects of decision-making using artificial intelligence. Also, concerns about the neutrality of the algorithm were presented. As a policy suggestion, a subcommittee was proposed in which experts in technical and social aspects play a professional role in establishing the AI promotion system in Korea. Although the subcommittee works independently, it suggests that it is necessary to establish governance in which the results of activities can be synthesized and integrated.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.77-104
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• 1995

Intelligent Decision System support the decision analysis process in the managerial problems with decision analytic knowledge as well as domain specific knowledge. Influence Diagram has been one of the major knowledge representation in the intelligent decision system. In the development of intelligent decision system, knowledge acquisition is also known to be difficult. This paper suggests a developing tool using an influence diagram and Verbal Protocol Analysis which facilitates knowledge acquision for intelligent decision system. An ennvironmental decision making problem is used as an illustrative example and validation of the suggested developing tool is discussed. The suggested tool is very flexible to be expanded or applied to similar problems.

• Journal of Korean Academy of Nursing
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• v.29 no.4
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• pp.880-891
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• 1999

The purpose of this study was to describe nursing decision tasks, their characteristics, and problems associated with decision making. The subjects were 32 nurses who had at least one-year nursing experience and worked on medical-surgical units or intensive care units(ICU). They were asked to describe their decision making experiences in patient care situations and to identify the characteristics of each decisions. They were also asked to describe perceived problems associated with decision making in nursing. The responses on nursing decision tasks and problems were analyzed with content analysis and the decision characteristics were identified by statistical analysis of variance. It was found that there were 16 nursing decisions which are as follows : decisions related to interpreting and selecting appropriate strategies for pain management(6.6%) ; decisions related to providing emotional support (0.7%) ; decisions related to explaining the patient's condition and rationale for procedures(1.1%) ; decisions related to assisting patients to integrate the implications of illness and recovering into their lifestyles(2.9%) ; decisions related to detecting significant changes In patients and selecting appropriate intervention strategies (17.2%) ; decisions related to anticipating problems and selecting preventive measures(4.2%) ; decisions related to identifying emergency situations(0.4%) ; decisions related to effective management of patient crisis until physician assistance becomes available(2.8%) ; decisions related to starting and maintaining intravenous therapy(2.6%) ; decisions related to administering medications(8.1%) ; decisions related to combating the hazards of immobility(7.3%) : decisions related to treating wound management strategies(5.5%) ; decisions related to relieving patient discomfort(13.9) ; decisions related to selecting appropriate strategy according to the changing situation of the patient(18.2%) ; decisions related to selecting the best strategy for patient management(5.3%) ; and decisions related to coordinating, ordering, and meeting the various needs of the patient (3.1%). The nurses reported the fellowing problems in decision making : difficulties due to lack of knowledge and experience (18.6%) ; uncertainty and complexity of decision tasks(15.2%) ; lack of time to make decisions(2.9%) ; personal values which conflict with other staff(15.7%) ; lack of selection autonomy(30.0%) ; and organizational barriers(7.6%). Continuing education programs and decision support systems for frequent nursing decision tasks can be established on the basis of these results. Then decision ability in nurses will increase through the education programs and decision support systems, and then quality of nursing service will be better.

• Asia pacific journal of information systems
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• v.9 no.3
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• pp.75-92
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• 1999

Executive information systems (EIS) developers are faced with an increasingly difficult choice problem in the evaluation and selection of software packages. For many reasons, they frequently must depend on identification and evaluation of features of packages. When EIS software evaluation is regarded as an unstructured or semi-structured group decision making problem, the most appropriate decision-aiding methods are needed to help effective group interaction. This paper examines evaluation criteria of full-featured EIS packages and considers the priority of these criteria using the Analytic Hierarchy Process (AHP). Two exploratory phases are presented. In the first phase, an approach combining the AHP with the linear weighted attribute method is presented to computer qualities of some packages. In the second phase, the decision making group includes EIS developers, users, and vendors to prioritize evaluation criteria.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.359-367
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• 2009

Trust-based solutions provide some form of payment to peers to encourage good behavior. The problem with trust management systems is that they require prior knowledge to work. In other words, peers are vulnerable to attack if they do not have knowledge or correct knowledge of other peers in a trust management system. Therefore, considering only trust is inadequate when a decision is made to identify the best set of peers to utilize. In order to solve the problem, we propose a distributed decision-making mechanism for wireless peer-to-peer (P2P) networks based on game theory and relevant trust mechanisms in which we incorporate the element of trust and risk into a single model. The main idea of our mechanism is to use utility function to express the relationship between benefits and costs of peers, and then make the decision based on expected utility as well as risk attitude in a fully distributed fashion. The unique feature of our mechanism is that it not only helps a peer to select its partners, but also mitigates vulnerabilities in trust-based mechanisms. Through analysis and experiments, we believe our approach is useful for peers to make the decision regarding who to interact with. In addition, it is also a good starting point for exploring tradeoffs among risk, trust and utility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.555-565
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• 2018

This study was conducted to investigate factors influencing career maturity in nursing students. A convenience sample of 230 nursing student was selected from S city, between 20 October and 10 November 2017. Data were collected using a structured questionnaire and analyzed using descriptive statistics, t-test, one-way ANOVA, Pearson's correlation, and multiple regression analysis with the SPSS/WIN 21.0 program. Factors that influenced career maturity included gender(t=2.117, p=.035), age(t=-2.572, p=.011), grade(F=4.716, p=.010), education at the time of admission(t=-2.695, p=.008) and perceived academic achievement(F=11.127, p<.001). Career maturity showed a positive correlation with career decision-making self-efficacy(r=.585, p<.001) and problem solving ability(r=.407, p <.001), but a negative correlation with job-seeking stress(r=-.424, p<.001). Regression analysis revealed that significant factors influencing career maturity were career decision-making self-efficacy, problem solving ability and job-seeking stress. This regression model explained 42.8% of the variance in the career maturity. Based on these findings, it is necessary to develop and test programs to ensure an improvement in career decision-making self-efficacy, problem solving ability and job-seeking stress among nursing students to increase their career maturity.

• Korean Journal of Occupational Health Nursing
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• v.18 no.2
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• pp.141-152
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• 2009

Purpose: The purpose of this research was to describe the decision making of nurses in a VIP ward. Method: The methodology of collecting and analyzing the data was based on the grounded theory of Strauss and Corbin (1998). The data were collected through an in-depth interview, which were audio-taped and transcribed. The data were collected from 10 nurses from July to November 2007. Results: The core category on VIP ward nurses' decision making was named as "adjusting with flexibility and deepened insight". The causal condition was established by 'the patients who wanted to be treated specially'. The contextual conditions included 'caring patients from various departments', 'differences depending on the nurses' clinical experience', and 'client-centered atmosphere in the VIP ward'. The intervening conditions included 'problem solving styles of nurses', 'attitudes of patients and family members', 'nurse-doctor relationships', and 'accessibility to information'. It was confirmed that nurses changed their action-interaction strategies depending on the intervening conditions, thus resulted in the nurses' role conflict and the need to expand their consciousness. Conclusion: The result of this study indicates that nurse's decision making depends on their experiences and the nature of social context in which nursing occurs.