• Smart Structures and Systems
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• v.21 no.1
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• pp.123-137
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• 2018

Structural monitoring is the most important part of the construction and operation of the embankment dams. Appropriate instruments selection for dams is vital, as inappropriate selection causes irreparable loss in critical condition. Due to the lack of a systematic approach to determine adequate instruments, a framework based on three comparable Multi-Attribute Decision Making (MADM) methods, which are VIKOR, technique of order preference by similarity to ideal solution (TOPSIS) and Preference ranking organization method for enrichment evaluation (PROMETHEE), has been developed. MADM techniques have been widely used for optimizing priorities and determination of the most suitable alternatives. However, the results of the different methods of MADM have indicated inconsistency in ranking alternatives due to closeness of judgements from decision makers. In this study, 9 criteria and 42 geotechnical instruments have been applied. A new method has been developed to determine the decision makers' importance weights and an aggregation method has been introduced to optimally select the most suitable instruments. Consequently, the outcomes of the aggregation ranking correlate about 94% with TOPSIS and VIKOR, and 83% with PROMETHEE methods' results providing remarkably appropriate prioritisation of instruments for embankment dams.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.69-78
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• 2007

In real world, the project managers handle conflicting goals that govern the use of resources within the stipulated time and budget with required quality and safety. These conflicting goals are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The fuzzy linear programming model proposed herein helps project managers to minimize total project costs, completion time, and crashing costs considering indirect costs, contractual penalty costs etc by practically charging them in terms of direct cost of the project. A case study of bituminous pavement under construction is considered to demonstrate the feasibility of applying the proposed model for optimization of project parameters. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with multiple fuzzy goal values. Additionally, the proposed model provides a systematic decision-making framework, enabling decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model with other models include, flexible decision-making process, multiple objective functions, and wide-ranging decision information.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• The Journal of Information Systems
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• v.18 no.3
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• pp.135-154
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• 2009

As the knowledge is recognized as a core factor of organization's competitiveness and creation of value added, the importance of knowledge management is also increased. To achieve the successful knowledge management, it is important to establish strategy that consider essential purpose of knowledge management such as creating and sharing of knowledge resource, improving performance, and continuing organizational innovation within the organization and influence factor inside and outside of organization. Until now, however, the research for knowledge management strategy was mostly limited to the statistical analysis based on the unilinear causality model, and systematic access and analysis that consider interaction and feedback structure between factors. In this paper, we developed the novel decision-making framework for successful strategy establishment by applying the analytic network process(ANP). Specifically. we derive clusters and components to decide the interaction and feedback structure between the elements of knowledge management by literature studies. And we produced relative importance and preference of clusters, components and alternatives dealing with feedback structure through the survey of experts in the field or related one of knowledge management. In result of this study, we expect that it will help the knowledge officer to decide establishing knowledge management strategy.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.148-156
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• 2015

Increased competitive challenges are forcing companies to find better ways to bring their applications to market faster. Distributed development environments can help companies improve their time-to-market by enabling parallel activities. Although, such environments still have their limitations in real-time communication and real-time collaboration during the product development process. This paper describes a web-based collaborative framework which has been developed to support the decision making on a 3D design developing process. The paper describes 3D design file for the discussion that contains all relevant annotations on its surface and their visualization on the user interface for design changing. The framework includes a native CAD data converting module, 3D data based real-time communication module, revision control module for 3D data and some sub-modules such as data storage and data management. We also discuss some raised issues in the project and the steps underway to address them.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.269-275
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• 2004

Geographic data have widely been applied in different areas including landuse, city planning and management, environment, disaster management and even daily use of citizens. Since geographic data have been built individually using different methods, many problems such as data inconsistency, duplicated investment, and confusion in decision making have arisen. Thus, the necessity of national framework database that can be shared by different areas has increased. As a result, eight fields of the framework database were defined by NGIS Law and 19 detailed items were selected. This study used the AHP (Analytical Hierarchy Process) and the decision tree to evaluate the relative importance of the items (eg. roads, railroads, coastline, surveying control points, and etc.) and presented the groups classified according to the priorities of the items. The result of this study is believed to contribute to effective budget planning for building national framework database.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2473-2478
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• 2011

The asset management of railway facilities is a total framework for finally supporting a safe and comfortable train service, which includes functions of supporting evaluation of condition and performance of infrastructures, making the decision method of repair or rehabilitation of deteriorated facilities, and lengthening the life cycle of structure through the decision of adequate cost and time of repair or reinforcement. In the range of the asset management, organization, human, the target, and information & data of company are included. Therefore, in this paper, appling the method of asset management analysis to the railway structures, the process of the risk assesment using BRE(Business Risk Exposure) and the basis of consisting optimized renewal decision-making are expressed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.385-405
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• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• Asia Marketing Journal
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• v.26 no.1
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• pp.1-10
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• 2024

This study explores incomplete decision-making dynamics on reward-based crowdfunding platforms, focusing on temporal and social factors influencing backers' decisions. Utilizing the temporal aspect (i.e., pledging campaign phase) and social aspect (i.e., current pledged amount ratio) as stimuli within the stimulus-organism-response framework, our findings reveal that nearly 50.9% of respondents change their initial decisions, highlighting widespread incomplete information processing. Backers are more prone to altering decisions under heightened time pressure and display herding behaviors. Furthermore, backers exhibit an increased likelihood of changing decisions under heightened time pressure, coupled with a greater chance that the pledged goal amount will not be achieved. The study discusses theoretical and practical implications.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1220-1227
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• 2003

To perform rational decision-making, autonomous agents need considerable computational resources. When other agents are present in the environment, these demands are even more severe. In these settings, it may be difficult for the agent to decide what to do in an acceptable time in multiagent situations that involve many agents. These problems motivate us to investigate ways in which the agents can be equipped with flexible decision-making procedures that enable them to function in a variety of situations in which decision-making time is important. The flexible decision-making methods explicitly consider a tradeoff between decision quality and computation time. Our framework limits resources used for agent deliberation and produces results that are not necessarily optimal, but provide autonomous agents with the best decision under time pressure. We validate our framework with experiments in a simulated anti-air defense domain. The experiments show that compiled rules reduce computation time while offering good performance.