• 한국디지털정책학회:학술대회논문집
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• 2004.11a
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• pp.375-387
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• 2004

The paper presents an Integrated E-Community System (IECS) for management, decision and service, designed for the e-government project of Haishu District of Ningbo, Zhejiang, China. The project need is to promote the integration of management information and service information of communities, providing a unified platform on which different departments of the district government can share and exchange community information, government officers can analyze information and make decisions, and the outside users can access and request services. To meet the project need, the IECS consists of five parts: 1) The Central DataBase (CDB) that stores all information related with management, decision and service of communities: 2) Information Extracting Subsystem (IES) that provides functions of extracting data from data sources, transforming and loading them into the CDB for system administrators; 3) Information Management Subsystem (IMS) that provides functions of querying and sharing of information for government users, and functions of information maintenance, rights and log management for system administrators: 4) Intelligent Analysis Subsystem (IAS) that provides functions of extracting analysis related data from the CDB and loading them into the DW, and functions of multi-dimensional analysis and decision-making based on the DW and OLAP for government users; 5) Information Service Website (ISW) that provides functions of promulgating and collecting of information for government users and system administrators, and functions of browsing, querying and requesting of service information for outside users. The IECS supports management, decision and service of a government based on a unified data platform--the CDB, and ensures data security by providing different workplaces and rights for different users. In the real application, the system works well.

• Journal of the military operations research society of Korea
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• v.16 no.1
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• pp.18-34
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• 1990

In light of the recent developments of transitory nature, it is likely that national defense decision-making will be more difficult to make for years to come. In other words, sudden changes in security environment would call into question the basic assumptions on which we have built our national defense planning and increase the number of the uncertain factors in the decision-making process; the subdivision and ramification of national defense management would increase the factors for decision-making and complicate even further the mutual interactions among these factors; the accelerated pace of sophistication and diversification of weapon systems and military technology would increase the risk of failure and system costs geometrically; and the reduced level of acceptance among the people on the sanctification of national defense in proportion to the rapid progress toward a more democratic and industrial society would engender an increased criticism or checking role by the National Assembly or by the mass media. As the changes in national defense environment and conditions create an innumerable number of new tasks, this paper intends to suggest a few core policy measures to improve the quality of national defense decision-making. More specifically, it proposes to 1) eradicate entirely the bureaucratic behavior and tendencies; 2) utilize actively the brain staff for quality assurance of decision-making; 3) and introduce and apply as a whole set, a total system, or an incorporated pack age the PPBEES(Planning-Programming-Budgeting-Executing-Evaluating-System)/LCMM (Life-Cycle Management Model for System Acquision), the OR/SA(Operations Research/Systems Analysis), and DMIS (Defense Management Information System).

• Journal of Trauma and Injury
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• v.23 no.2
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• pp.113-118
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• 2010

Purpose: Prolonged stay in the emergency department (ED), which is closely related with the time interval from the ED visit to a decision to admit, might be associated with poor outcomes for trauma patients and with overcrowding of the ED. Therefore, we examined the factors affecting the delay in the decision to admit severe trauma patients. Also, a multidisciplinary department system was preliminarily evaluated to see if it could reduce the time from triage to the admission decision. Methods: A retrospective observational study was conducted at a tertiary care university hospital without a specialized trauma team or specialized trauma surgeons from January 2009 to March 2010. Severe trauma patients with an International Classification of Disease Based Injury Severity Score (ICISS) below 0.9 were included. A multivariable logistic regression analysis was used to find independent variables associated with a delay in the decision for admission which was defined as the time interval between ED arrival and admission decision exceeded 4 hours. We also simulated the time from triage to the decision for admission by a multidisciplinary department system. Results: A total of 89 patients were enrolled. The average time from triage to the admission decision was $5.2{\pm}7.1$ hours and the average length of the ED stay was $9.0{\pm}11.5$ hours. The rate of decision delay for admission was 31.5%. A multivariable regression analysis revealed that multiple trauma (odds ratio [OR]: 30.6, 95%; confidence interval [CI]: 3.18-294.71), emergency operation (OR: 0.55, 95%; CI: 0.01-0.96), and treatment in the Department of Neurosurgery (OR: 0.07, 95%; CI: 0.01-0.78) were significantly associated with the decision delay. In a simulation based on a multidisciplinary department system, the virtual time from triage to admission decision was $2.1{\pm}1.5$ hours. Conclusion: In the ED, patients with severe trauma, multiple trauma was a significant factor causing a delay in the admission decision. On the other hand, emergency operation and treatment in Department of Neurosurgery were negatively associated with the delay. The simulated time from triage to the decision for admission by a multidisciplinary department system was 3 hours shorter than the real one.

• IE interfaces
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• v.14 no.3
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• pp.310-317
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• 2001

The purpose of this study is to investigate and to develop a decision support system for supporting the outworn facility replacement analysis in shipbuilding. This paper also provides an information system which can be effectively applied to various criteria in decision making. The modelbase of decision support system uses the concepts of the analytic hierarchy process along with an appropriate scoring methods. The AHP represents an improvement over other well-known scoring approaches since the criteria weights of priorities established by the AHP are not based on arbitrary scales, but use a ratio scale for human judgements. The proposed methodology in this research enables the decision maker to evaluate the investment alternatives based on qualitative data and quantitative data in a systematic way.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.214-217
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• 1996

Early decision support systems (DSS) were the "passive" decision support systems in the sense that the systems only able to do what the users explicitly direct them to do. But some researchers such as Raghav Rao et al. [51 showed architectures to suggest general idea of the innovative DSS systems which offer active form of decision support, say, "active Intelligent Decision Support Systems(active IDSS)". The system can perform not only what the users want to do but some voluntary (or involuntary) intelligent works. This paper presents the issues in the design of the active IDSS in the domain of investment evaluation, a domain area where few researchers have suggested frameworks or architectures to discriminate good investment from bad one. We propose a new paradigm, by utilizing historical investment results using neural network and Multivariate Discriminant Analysis(MDA), to identify goodness of investment. A new active IDSS architecture which consists of neural network, expert system and three components of the traditional passive DSS is suggested with some scenario based results.nario based results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.8
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• pp.580-586
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• 2011

In this study, 3 cooling systems of apartment which are air-cooled air conditioner with indoor unit, water-cooled air conditioner with indoor unit and small capacity absorption chiller-heater with FCU have been evaluated by Multi-Criteria Decision Making Analysis. Weights of 7 selected factors which are economics, space, billing, constructability, human comfort, visibility and reliability are determined by expert group of 30 system designers and 30 construction engineers. Final weights were derived for 101 and 166 $m^2$ apartments. Analysis shows that small capacity absorption chiller-heater with FCU is the most favorable system for apartment cooling system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.287-294
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• 2012

The spread of infectious diseases in the event of livestock is getting faster and the route of spread gets more varied. It is important for the responsible agency to detect early and establish a prevention and surveillance system. If the spread cannot be contained effectively, great damage and loss will be inevitable in terms of social, environment and economic aspects as well as the welfare of the farmers. At present in Korea, a web-based Infectious Livestock Diseases Statistics System (AIMS: Animal Infectious Disease Data Management System) has been already implemented for this purpose and the service is available to the general public. But this system does not provide geospatial information and does not provide support for decision making and does not provide multi-dimensional information. In this study, an open source-based SOLAP (Spatial On-Line Analytical Processing) technology is applied to enable many diverse forms of data analysis from many aspects to support decision making. The SOLAP system was designed to integrate geospatial information and the analysis of information has been largely divided into map-based analysis and table-based analysis.

• Journal of Korean Society of Rural Planning
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• v.11 no.2 s.27
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• pp.1-8
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• 2005

This study is to develop a web-based integrated system for flow of agricultural products based on recent researches with engineering approach. The system stands on the basis of web for accessibility and usability. Three parts of the system consist of analysis of regional shipping characteristics using tank model, estimation of pallet load efficiency with Monte Carlo Simulation, a long term prediction of market price with reliability analysis. Besides a decision support module for selecting optimal shipping market is added through synthesizing techniques and spatial analysis using GIS and applied to Chinese cabbage of Pyeongchang in 2004.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.107-119
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• 2003

Expectation and interest about e-CRM are rising for more efficient customer management in on-line including electronic commerce. The decision-making tree can be used usefully as the data mining technology for e-CRM. In this paper, the representative decision making techniques, CART, C4.5, CHAID analyzed the differences in personalization point of view with actuality customer data through an experiment. With these analysis data, it is proposed a new decision-making tree system that has big advantage in personalization techniques. Through new system, it can get following advantage. First, it can form superior model more qualitatively in personalization by adding individual's weight value. Second it can supply information personalized more to customer. Third, it can have high position about customer's loyalty than other site of similar types of business. Fourth, it can reduce expense that cost marketing and decision-making. Fifth, it becomes possible that know that customer through smooth communication with customer who use personalized service wants and make from goods or service's quality to more worth thing.