• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.338-339
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• 2015

VTS Decision Support System can be defined a tool which assists VTS operator for decision-making at operational, planning and management level especially for the safety and efficiency of vessel traffic. This paper presents classification of VTS Decision Support System, detailed definition of alerts, and operational and functional requirements of VTS Decision Support System.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.886-891
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• 2004

The process of determining whether, when, where and how to intervene, of deciding on optimum allocation of resources and minimizing the cost is a very complex problem: different track sections tend to behave differently under the effects of loading; decision-making processes for maintenance work are closely interrelated technically and economically; decision-making for maintenance plans is based on a large quantity of technical and economic information, extensive knowledge and above all experience. For that reason, It is considered very important to develope objective and computer-aided decision-making support system for track maintenance plan. On this paper, we made a survey of the state-of-art of decision-making support systems for track maintenance which were developed and used abroad and reviewed requirements of system and present the plan of develope decision-making support system for track maintenance appropriate to local condition.

• Journal of Families and Better Life
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• v.30 no.4
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• pp.77-87
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• 2012

The purpose of this study is to analyze the effects of social support and, career decision-making self-efficacy on career maturity of adolescents of different gender and grades. Further, it aims to provide basic information for career maturity to create career educational program for adolescents. The participants of the study were 447 middle and high school students who were selected from second grade of five schools in Daegu. All participants were tested on social support, career decision-making self-efficacy and career maturity scale. The results were analyzed using two-way ANOVA, Pearson's Correlation Analysis, Regression Analysis with SPSS 18.0. The results of the present research are summarized as follows: first, the results of the ANOVA subscales revealed that there were significant gender and grade main effects and interaction effects of social support, career decision-making self-efficacy and career maturity. Second, the results of the correlation analysis among of the social support, career decision-making self-efficacy and career maturity showed a positive and negative correlation. Third, in terms of the influence of social support, career decision-making self-efficacy had a significant meaningful influence on career maturity. The results of this study can be used as a fundamental reference in career counseling at school for enhancing adolescent's career development and success.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.519-528
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• 2003

Container terminals need decisions in the course of daily-24 hour and 365 day - operations, and all these decisions are inter-related. The ultimate goal of Decision Support System is to minimize ship loading/unloading time, resources used to handle the workload, and congestion on the roads inside the terminal. It is also to make the best possible use of the storage space available. Therefore, the necessity of decision support tools are emphasized to enhance the operational efficiency of container shipping terminals more, because of limits and complexity of these decisions. So, in thia paper, we draw evaluation items for Decision Support Systems and suggest optimization strategy of evaluation items which have the greatest influence on Decision Support system, that is, yard stacking allocation, RTGC deployment among blocks, and YT allocation to QCs. We also estimate the efficiency of Decision Support System design by simulation using G2 language, comparing ship loading/unloading time.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.307-315
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• 2022

The review of known decision-making support systems and technologies regarding the possibility of donation and transplantation showed that currently there are no systems and technologies of decision-making support regarding the possibility of donation and transplantation considering civil law. The paper models the decision-making support process regarding the possibility of donation and transplantation, which is a theoretical basis for the development of rules, methods and technology of decision-making support regarding the possibility of donation and transplantation considering civil law. The paper also developed the technology of decision-making support regarding the possibility of donation and transplantation considering civil law as a component of the Unified State Information System for Organ and Tissue Transplantation, which automatically and free of charge determines the possibility/impossibility of donation and transplantation. In the case of the possibility of donation, the admissible type of donation is also determined - over-life or after-life donation - and data about potential donor is entered in the relevant Donor Register. In the case of the possibility of transplantation, if the recipient needs a transplant of one of the paired organs or a part of the organ/tissue, then data about potential recipient are entered in the Transplantation List from both over-life and after-life donor, otherwise, if the recipient needs a transplant of a non-paired organ or both paired organs, then data about potential recipient are entered only in the Transplantation List from after-life donor.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.352-357
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• 2001

This study presents an analysis of healthcare quality indicators using data mining for developing quality improvement strategies. Specifically, important factors influencing the inpatient mortality were identified using a decision tree method for data mining based on 8,405 patients who were discharged from the study hospital during the period of December 1, 2000 and January 31, 2001. Important factors for the inpatient mortality were length of stay, disease classes, discharge departments, and age groups. The optimum range of target group in inpatient healthcare quality indicators were identified from the gains chart. In addition, a decision support system was developed to analyze and monitor trends of quality indicators using Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. In the future, other quality indicators should be analyze to effectively support a hospital-wide continuous quality improvement (CQI) activity and the decision support system should be well integrated with the hospital OCS (Order Communication System) to support concurrent review.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.249-254
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• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.717-724
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• 2009

Most recent programs in and out of the country are related to urban renewal projects. Contemporary project management information systems have been developed was to manage single or multiple projects focusing on their construction phase, and those have limitations to apply to large-scale complicated mega projects. So, this study explain the core concept of decision support modules for iPMIS (Intelligent Program Management Information System) and its major functions to support project owner and participants by introducing ontology in the web environment. This study confined the scope of research to the planning phase of urban environment improvement projects. Ontological logic structure and relation about planning works is essential parts and three functions to implement decision support module are developed.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.239-250
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• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).