• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.256-257
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• 2023

This paper aims to propose optimal method to assess and cumulate the daily profit for liner shipping to support the shipping lines in making optimal decision with the highest average daily profit. This paper not only explains the actual calculated results align with decision-makers' behavior from concepts indicated in cumulative prospect theory but also contributes to an easy-to-apply method for liner shipping network predictability in and provides optimal decision-making is helpful for shipping managers for the best effective selection of the most appropriate alternative under uncertainties.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.530-532
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• 2006

In this paper, we propose stable walking algorithm using ZMP for the biped robot in the slope-way. At first, we define discrete state variables that classified stable area and unstable area by center of mass from ZMP during slope-way walking. For the stable walking gait, the discrete state controller for determining the high-level and low-level decision making are designed. The high-level decision making is composed of the discrete state variables; left foot support phase, right foot support phase, flat-way, and slope-way. Then the continuous state controller is implemented for the low-level decision making using ZMP.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.1-16
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• 2012

This paper is aimed to present a fuzzy decision-making approach to deal with disaster recovery priority decision problem in information system. We derive an evaluation approach based on TOPSIS(Technique for Order Performance by Similarity to Ideal Solution), to help disaster recovery priority decision of total information system for port logistics in a fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by trapezoidal fuzzy numbers. This study applies the fuzzy multi-criteria decision-making method to determine the importance weight of evaluation criteria and to synthesize the ratings of candidate disaster recovery system. Aggregated the evaluators' attitude toward preference, then TOPSIS is employed to obtain a crisp overall performance value for each alternative to make a final decision. This approach is demonstrated with a real case study involving 4 evaluation criteria(system dependence, RTO, loss, alternative business support), 7 information systems for port logistics assessed by 5 evaluators from Maritime Affairs and Port Office.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7143-7147
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• 2013

Background: The survival outcomes for women presenting with early breast cancer are influenced by treatment decisions. In Malaysia, survival outcome is generally poor due to late presentation. Of those who present early, many refuse treatment for complementary therapy. Objective: This study aimed to explore the decision making experiences of women with early breast cancer. Materials and Methods: A qualitative study using individual in-depth interviews was conducted to capture the decision making process of women with early breast cancer in Malaysia. We used purposive sampling to recruit women yet to undergo surgical treatment. A total of eight participants consented and were interviewed using a semi-structured interview guide. These women were recruited from a period of one week after they were informed of their diagnoses. A topic guide, based on the Ottawa decision support framework (ODSF), was used to facilitate the interviews, which were audio recorded, transcribed and analysed using a thematic approach. Results: We identified four phases in the decision-making process of women with early breast cancer: discovery (pre-diagnosis); confirmatory ('receiving bad news'); deliberation; and decision (making a decision). These phases ranged from when women first discovered abnormalities in their breasts to them making final surgical treatment decisions. Information was vital in guiding these women. Support from family members, friends, healthcare professionals as well as survivors also has an influencing role. However, the final say on treatment decision was from themselves. Conclusions: The treatment decision for women with early breast cancer in Malaysia is a result of information they gather on their decision making journey. This journey starts with diagnosis. The women's spouses, friends, family members and healthcare professionals play different roles as information providers and supporters at different stages of treatment decisions. However, the final treatment decision is influenced mainly by women's own experiences, knowledge and understanding.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.101-104
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• 1997

Providing information on corporate level decision making for multiple decision makers in a consistent way is essential in Decision Support Systems. However, since the decision makers have different background and knowledge, the models used by them are also different in representation models. This makes the decision makers require a lot of efforts for model integration in an integrated decision making. The purpose of this paper is to propose an integration mechanism for synthetic use of multi-abstraction level decision making models. The proposed integration mechanism consists of model interpretation phase, model transformation phase and model integration phase. Specifically, the model transformation phase is divided into model tightening mode which gather information to makes a model transformed into upper level model, and model relaxing mode which makes lower level model.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.435-440
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• 2004

Most of our GIS implementation activities have been focussed on the management of urban information in local municipalities. Management of urban facilities has been the major issue of concern and has little role in providing the decision maker with alternatives from which one can analyse and choose the optimum solution. For this reason, the spatial decision support system is in need. Business analysis software is effectively used for site analysis of new stores, customer prospecting and other issues of decision making for business purposes, The same geoprocessing module of business analysis software would be useful if put to use for the management of disaster management especially for storm surge management. Application of the business analysis model for disaster management has been reviewed. Specially in case of storm surge, where quick response is crucial, the spatial decision support system will be most effective.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.310-312
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• 2003

This paper discusses a GIS based decision support system that provides functions of prospect screening and evaluation in both technical aspects (Volume, structure, trap, reservoir and charge, etc.) and economic aspects (Net present value, Profit / investment Ratio, etc.). The decision support system has been tested in a virtual offshore exploration prospect to facilitate and improve the decision making process. The study represents a test bed for decision makers at all levels to establish prospect screening and evaluation guidelines that may be applicable to other related prospect investment issues.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1187-1192
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• 2008

In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• 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.