• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.281-285
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• 2004

This paper aims to describe how the decision making capability and context-aware computing are jointly used to establish ubiquitous applications. An amended DSS paradigm: CKDDM is proposed in this paper. Under the CKDDM paradigm, a framework of ubiquitous decision support systems (ubiDSS) is addressed with the description of the subsystems within.

• Journal of Information Technology Applications and Management
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• v.21 no.2
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• pp.81-98
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• 2014

Recently, due to external environment like the changes in health policy and various healthcare accreditations, along with hospital's internal efforts to improve the quality of medical services, demands for the development of medical information systems are increasing. Some examples are clinical information like DUR (Drug Utilization Review), CVR (Critical Value Report), and automatic benefit processing by treatment purposes, or hospital DSS (Decision Support System) on overall medical practice. Such systems act as a guide in making clinic judgments during practice or in other medical practice, and their effects on the medical treatment improvements are being proven by previous studies. In the reality of increasing attention in the effects of medical treatment improvement, studies related to hospital DDS were mostly focused on clinical, technical, and engineering points of view, and studies focusing on the user viewpoint are very limited. In order to verify the effects of DSS on practice improvements and hospital's management performance, this study used a research model constructed to verify how SERVQUAL of hospital DSS affects hospital management performance in BSC (Balanced Score Card) point of view. To empirically verify the research model, a questionnaire was conducted on the basis of "K-University Hospital's DSS" on clinicians and hospital employees related to system development, and the relationships between the factors were analyzed through path analysis. As a result of path analysis, excluding reactivity, tangibility, confidence, reliability, empathy among service qualities, had partially significant effects on management performance factors (learning and growth, internal process, financial affairs). This study is to prepare the theoretical ground on the management performance analysis of hospital DSS, and suggest the service quality of the system that should be considered in the planning and development stages for improved system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.140-145
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• 2008

In this paper, we constructed the advanced cargo monitoring system for liquid cargo tankers which embedded the Decision Support System (DSS) based on the International Ship Management Code (ISM Code). To make this system, we first organized a base of expert's knowledge concerning liquid tanker operations that largely affect ocean accidents. We can find out the knowledge via inference method which simply imitates the fuzzy inference method. Based on this expert's knowledge, we constructed the DSS that provides a code of conduct for operating cargo tanks safely. The proposed monitoring system could eliminate human error when confronting dangerous situations, so the system will help sailors to operate cargo tanks safely.

• Environmental Engineering Research
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• v.14 no.2
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• pp.111-119
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• 2009

A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.52-57
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• 2011

Bridges are essential and valuable elements in road and rail transportation networks. Bridge remediation is a top priority for asset managers, but identifying the nature of true defect deterioration and associated remediation treatments remains a complex task. Nowadays Decision Support Systems (DSS) are used extensively to assist in decision-making across a wide spectrum of unstructured decision environments. In this paper a requirements-driven framework is used to develop a risk based decision support model which has the ability to quantify the bridge condition and find the best remediation treatments using Multi Attribute Utility Theory (MAUT), with the aim of maintaining a bridge within acceptable limits of safety, serviceability and sustainability.

• IE interfaces
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• v.7 no.2
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• pp.121-132
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• 1994

Despite extensive research on various factors affecting the effectiveness of decision support systems (DSS), considerable ambiguity still exists regarding the role and influence of the experience on the given task and the decision support system. Although researchers have advocated DSS effectiveness as a multi-dimensional construct, specific results regarding the effect of the familiarity in the task and the DSS on the problem-solving time is still lacking. The study reported here attempts to find the effect of the peculiarity of the problem-solving process on the problem-solving time. The results of the study highlight that the expertise in both the task and the DSS have made the shortage of the problem-solving time. However, more research about the generalized performance measure on the DSS is required.

• Smart Structures and Systems
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• v.21 no.2
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• pp.249-255
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• 2018

Many studies in risk management have been focused on management process, contract relation, and risk analysis in the past decade, but very few studies have addressed project risks from the perspective of risk efficiency. This study started with using Fault Tree Analysis to develop a framework for the decision-making support system of risk management from the perspective of risk efficiency, in order for the support system to find risk strategies of optimal combination for the project manager by the trade-off between project risk and cost of project strategies. Comprehensive and realistic risk strategies must strive for optimal decisions that minimize project risks and risk strategies cost while addressing important data such as risk causes, risk probability, risk impact and risk strategies cost. The risk management in the construction phase of building projects in Taiwan upon important data has been analyzed, that provided the data for support system to include 247 risk causes. Then, 17 risk causes were extracted to demonstrates the decision-making support system of risk management from the perspective of risk efficiency in building project of Taiwan which could reach better combination type of risk strategies for the project manager by the trade-off between risk cost and project risk.

• 한국공간정보시스템학회:학술대회논문집
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• 2000.06a
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• pp.93-105
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• 2000

GIS is a powerful toolbox in managing spatial data associated with attribute data. However GIS is short of spatial analysis function and graphic user interface(GUI) function in dealing with dynamic planning problems. Decision Support Systems(DSS) make up for the shortage of GIS by providing GUI function, modeling function and database function. Spatial Decision Support Systems(SDSS), a new kind of DSS, incorporate display function, basic spatial analysis function and manipulation function of spatial data and attribute data of GIS and GUI function, modeling function and database function of DSS in dealing with spatial planning problems. Planning Support Systems(PSS) add more advanced spatial analysis function and intertemporal function to the functions of SDSS. This study focuses on the modeling of a PSS for capacity expansion of water-distribution network depending upon land use planning by using GIS, value engineering(VE) and life cycle costing(LCC). The PSS shows a guideline about the investment of water-distribution networks related to urban growth management through generating certain numbers of dynamic alternatives to supply the amount of water caused by land use planning.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.129-151
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• 1994

Recently, Decision Support Systems (DSS) research has seen a more to combine Artificial Intelligence (AI) including neural network techniques with traditional DSS concepts and technologies to build an intelligent DSS or a knowledge-based DSS. This article proposes a Management Evaluation and its Support System (MESS) as a knowledge-based DSS. The management evaluation of a firm means the performance of all managerial operations is appraised by considering the situations of the firm. A neural network is used to represent the management evaluation structure as a suitable means of management knowledge representation. Finally a case study in a telecommunication corporation is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.73-82
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• 1993

Over the last decades, interest in the application of decision support systems(DSS) in organizations has increased rapidly. Desipte the growing number of investigations examining decision support system, relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study examined, using a computer simulation technique, the effect of recursion in problem-solving processes about the problem-solving time. Results indicate that the recursion at the early stage of problem-solving processes scarcely influenced the problem-solving time, which is contrasted with the case of the recursion at the final stage.