• Journal of the Korea Institute of Building Construction
• /
• v.11 no.1
• /
• pp.91-99
• /
• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.11
• /
• pp.5449-5464
• /
• 2018

Recent works have validated the possibility of reducing the energy consumption in wireless heterogeneous networks, achieved by switching on/off some base stations (BSs) dynamically. In this paper, to realize energy conservation, the discrete time Markov Decision Process (DTMDP) is developed to match up the BS switching operations with the traffic load variations. Then, an asynchronous decision-making algorithm, which is based on the Bellman equation and the on/off priorities of the BSs, is firstly put forward and proved to be optimal in this paper. Through reducing the state and action space during one decision, the proposed asynchronous algorithm can avoid the "curse of dimensionality" occurred in DTMDP frequently. Finally, numerical simulations are conducted to validate the effectiveness and advantages of the proposed asynchronous on/off strategies.

• International conference on construction engineering and project management
• /
• 2007.03a
• /
• pp.642-652
• /
• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• Health Policy and Management
• /
• v.24 no.2
• /
• pp.181-190
• /
• 2014

Background: Demands are recently rising for the securement of procedural justification of policy decision-making. This study aims to improve the procedure of making a decision to expand health insurance benefit package from the perspective of building a social consensus. Methods: Major priority principles were firstly derived through literature search. Weights for such principles were calculated through an analytic hierarchy process, based upon the survey conducted for the health policy experts. Priority for 11 non-covered services was assessed by applying the weights as above to the results of the questionnaire survey targeted at people including members of related committees or societies. Results: Weights for priority principles were in the order of 'severity/urgency (0.428)', 'cost-effectiveness (0.318)', 'substitutability (0.164),' and 'accountability (0.090)'. What was obtained by applying these weights to the results of the questionnaire survey was considerably in line with what health experts classified those items into 3 groups depending on their own judgement of service necessity (consistent with 9 services out of 11). Conclusion: Results of the study are suggestive as to how far a brief assessment by experts could be utilized in case there are constraints on time and expenses in implementing all the process to secure procedural justification. Various attempts and endeavors need to be made to secure procedural justification that will not mar efficiency of decision-making in the days to come.

• The Journal of Society for e-Business Studies
• /
• v.18 no.3
• /
• pp.17-43
• /
• 2013

This research is to assess the relationship Big Data attributes and disaster response process. The hypothesis are designed to form decision making between situation awareness and disaster response by defining major attribute of Big Data(Volume, Variety, Velocity, Complexity). It is proved whether there is a moderating effect in cause-and-effect relationship by visualizing Big Data. To test the hypotheses, it was conducted a questionnaire survey of civil servants in charge of disaster-related government employees, and collected 320 data(without 12 undependable responses). The research findings are suggested the attributes of accumulation, expandability, flexibility, real-time, analytical, combination of Big Data have a strong effect on disaster manager's situation awareness.

• Journal of Digital Convergence
• /
• v.14 no.10
• /
• pp.173-181
• /
• 2016

The objective of this study is to subdivide the tactical considerations (METT+TC; Mission, Enemy, Terrain & Weather, Troops available, Time available, Civil considerations) through Delphi method and prioritize those via AHP (Analytic Hierarchy Process). Though it has been taken for granted that the tactical considerations were inevitable for decision making relating to military operations, their segmentation and priority have not been studied sufficiently in military. The data for Delphi method and AHP were based on interview with military experts and questionnaires answered by those. Six tactical considerations were segmented into 34 sub-considerations by Delphi, and Six tactical considerations and 34 sub-ones were prioritized through AHP in attack and defense aspects. If the research results will be embedded into database of automatic command and control system (e.g. ACTIS; Army Tactical Command Information System), effective decision-making process will get easier and faster.

• The Journal of Korean Academy of Prosthodontics
• /
• v.55 no.4
• /
• pp.444-450
• /
• 2017

Prosthetic decision-making is complex because of various factors, and involves a combination of the individual dentist's interpretation of the objective clinical data and his or her interaction with the patient. Increasing therapeutic options and emerging outcome data demand the constant re-evaluation of our decision-making process. In this case, fixed prosthetic restorations were selected as a treatment method to reconstruct the occlusal plane of a patient with disharmonious occlusal plane. And the occlusal plane was re-established by establishing a treatment plan through diagnostic wax-up. Provisional restorations obtained by continuous re-evaluation for a sufficient period of time was replicated to definitive restorations using CAD/CAM technology. The results were satisfactory when they were observed through clinical follow-up for 3 months after the end of treatment.

• International Journal of Highway Engineering
• /
• v.8 no.3 s.29
• /
• pp.1-19
• /
• 2006

Researches on method for quantitative analysis applied with decision-making in consideration of variation in risk factors based on GIS(Geographic Information System) concluded as follows. Firstly, by way of decision-making in consideration of variation in risk factors, quantitative analysis performed for the existing route was applied to the new route, which would bring about reliable criteria in route planning and basic design stage. Secondly, horizontal and vertical alignment were easily available out of GIS for relatively speedy design and analysis with three dimensional alignment by decision-making in route planning. Thirdly, automation of route alignment is possible by utilizing quantitative evaluation system established in this research so that a risk analysis can be carried out in a relatively short time. Therefore it will eventually contribute to further development of road design technology.

• Journal of the Korea Computer Graphics Society
• /
• v.22 no.5
• /
• pp.37-47
• /
• 2016

This study evaluate user feedback such as physiological response and facial expression when subjects play a social decision making game with interactive virtual agent partners. In the social decision making game, subjects will invest some of money or credit in one of projects. Their partners (virtual agents) will also invest in one of the projects. They will interact with different kinds of virtual agents which behave reciprocated or unreciprocated behavior while expressing socially affective facial expression. The total money or credit which the subject earns is contingent on partner's choice. From this study, I observed that subject's appraisal of interaction with cooperative/uncooperative (or friendly/unfriendly) virtual agents in an investment game result in increased autonomic and somatic response, and that these responses were observed by physiological signal and facial expression in real time. For assessing user feedback, Photoplethysmography (PPG) sensor, Galvanic skin response (GSR) sensor while capturing front facial image of the subject from web camera were used. After all trials, subjects asked to answer to questions associated with evaluation how much these interaction with virtual agents affect to their appraisals.

• The Journal of Information Systems
• /
• v.17 no.3
• /
• pp.205-233
• /
• 2008

This study suggests the dynamic value chain model, that will be able to not only show changing processes to organization's significant capital by integrating an individual, implicit, and explicit knowledge which affect organizational decision making, but also distinguish the key driver for raising organizational competitive power because it makes possible to analyze sensitivity of performance along with decision making alternatives and policy changes from dynamic view by connecting knowledge management capability, knowledge management activity, and relations with organizational performance with specific strategic map. Recently, a lot of organizations show interest in measuring and evaluating their performance synthetically. In organizations taking knowledge management, they introduce effective value chain model like a dynamic balanced scorecard (DBSC), and therefore they can reflect their knowledge management condition as well as show their changes by checking performance of established vision and strategy periodically. Furthermore, they can ask for their inner members' understanding and participation by communicating with and inspiring their members with awareness that members are one of their group, present a base of benchmarking, and offer significant information for later decision making. The BSC has been a successful framework for measuring an organization's performance in various perspectives through translating an organization's vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, this study employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC would serve as a useful strategic teaming tool for facilitating an organization's communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, this study applied the DBSC model to Prototype of Korea manufacturing and service firm.