• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.83-103
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• 2004

The methodological framework of the Level 2 PSA appears to be currently standardized in a formalized fashion, but there have been different opinions on the way the sources of uncertainty are characterized and treated. This is primarily because the Level 2 PSA deals with complex phenomenological processes that are deterministic in nature rather than random processes, and there are no probabilistic models characterizing them clearly. As a result, the probabilistic quantification of the Level 2 PSA CET / APET is often subjected to two sources of uncertainty: (a) incomplete modeling of accident pathways or different predictions for the behavior of phenomenological events and (b) expert-to-expert variation in estimating the occurrence probability of phenomenological events. While a clear definition of the two sources of uncertainty involved in the Level 2 PSA makes it possible to treat an uncertainty in a consistent manner, careless application of these different sources of uncertainty may produce different conclusions in the decision-making process. The primary purpose of this paper is to characterize typical sources of uncertainty that would often be addressed in the Level 2 PSA and to provide a formal guidance for quantifying their impacts on the PSA Level 2 risk results. An additional purpose of this paper is to give a formal approach on how to combine random uncertainties addressed in the Level 1 PSA with subjectivistic uncertainties addressed in the Level 2 PSA.

• Educational Technology International
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• v.10 no.1
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• pp.1-23
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• 2009

Learners are often posited in a paradoxical situation where they are not fully involved in decision making processes on how to learn, in designing their tools. Cognitive artifacts in e-learning are supposed to effectively support learner-centered e-learning. The purpose of the study is to analyze cases of cognitive artifacts and to inquire those design principles for facilitating the learner-centered e-learning. Four research questions are suggested: First, it will be analyzed the characteristics of learners with respect to design of cognitive artifacts for supporting the learner-centered e-learning. Second, characteristics of four cases to design cognitive artifacts in learner-centered e-learning environment are analyzed. Third, it will be suggested the appropriate design principles of cognitive artifacts to facilitating learner-centered learning in e-learning environment. Four cases of cognitive artifacts design in learner-centered e-learning was identified as follows: Wiki software as cognitive artifacts in computer-supported collaborative learning; 'Play Around Network (PAN)' as cognitive artifact to monitor learning activities in knowledge community; Knowledge Forum System (KFS) as a cognitive artifact in knowledge building; cognitive artifacts in Courses-as-seeds applied meta-design. Five design principles are concluded as follows: Promoting externalization of cognitive artifacts to private media; Helping learners to initiate their learning processes; Encouraging learners to make connections with other learners' knowledge building and their cognitive artifacts; Promoting monitoring of participants' contributions in collaborative knowledge building; Supporting learners to design their cognitive artifacts.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.2
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• pp.89-94
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• 2014

Tidal generation has become one of environmentally friendly new and renewable future sources of energy. The Sihwa Tidal Power Plant in South Korea, which was imported from abroad by turnkey type in 2011, connected to the power system in 2012, and is currently under commercial operation. However, leading companies are reluctant to disclose their technologies associated with the control systems and are not cooperative in technology transfers, making it a high priority to develop core technologies in South Korea. In order to develop a start stop control system for tidal generation, this paper presents the optimal algorithm for decision making and prototype of hardware design. First, control systems in tidal power, such as plant operation control, data interfaces between systems, monitoring and control points of the control system, are analyzed. The software development and PC based emulator processes for optimization algorithm processing are described. Finally, verification of the algorithm implementation, hardware platform for start stop control device, and implementation of prototype control system were discussed.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.377-393
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• 2020

Freight management systems require a new business model for rapid decision making to improve their business processes by dynamically analyzing the previous experience data. Moreover, the amount of data generated by daily business activities to be analyzed for making better decisions is enormous. Online-to-offline or offline-to-online (O2O) is an electronic commerce (e-commerce) model used to combine the online and physical services. Data analysis is usually performed offline. In the present paper, to extend its benefits to online and to efficiently apply the big data analysis to the freight management system, we suggested a system architecture based on O2O services. We analyzed and extracted the useful knowledge from the real-time freight data for the period 2014-2017 aiming at further business development. The proposed system was deemed useful for truck management companies as it allowed dynamically obtaining the big data analysis results based on O2O services, which were used to optimize logistic freight, improve customer services, predict customer expectation, reduce costs and overhead by improving profit margins, and perform load balancing.

• The Journal of Health Technology Assessment
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• v.6 no.2
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• pp.81-87
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• 2018

With the recent change of healthcare environment including rapid technological development, evidences are more and more important and necessary to support relevant policies in health technology assessment to provide safe and effective health services, utilizing medical resources efficiently. Despite of the emphasis on the importance of real world data and real world evidence in health care research, current infrastructure supporting clinical research is considerably weak due to absence of legal and institutional basis. However, in accordance with the Article 26 of the Health and Medical Technology Promotion Act, there is a limited legal apparatus that can be used only in public data with other dataset for the purpose of healthcare technology assessment at the National Evidence-based Collaborating Agency. Although the use of linked data from various sources was often required in the field of clinical research, it was not yet working well due to insufficient environmental conditions. In order to support the decision-making of medical practice and health care policies, data-linking platform for clinical research is needed. If the legal system that can link up to the data of the private institutions without violating the significant value such as the protection of private informations is established, it will be a decisive foundation reinforcing the researches and policy making processes for the improvement of the national health care system.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.273-282
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• 2002

Although the influence of GIS has been proved in a variety of applications, there also have been some research issues about that the coupling of GIS with other mathematical or engineering tools is necessary to meet various needs of specialized problem domains. Linear Programming, a mathematical technique used in optimal distribution of given quantity, can enhance its usability by integrating with GIS since LP basically does not include means to deal with spatial data. The limitation of the traditional LP technique is that it requires explicitly defined conditions, which is impractical or impossible in such decision making processes as in land use problems that use less crisp decision factors. This study develops a method to incorporate such fuzzy situations by integrating Fuzzy-LP that employs fuzzy logic and GIS. The GIS provides data to or displays data from the Fuzzy-LP processes in the integrated system. This methodology is illustrated to solve a land use distribution problem.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.75-90
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• 2009

Improvement of productivity and efficient process management need to define the problem of the previous work. If it takes long time to gather necessary information, it becomes difficult to continuously manage processes to satisfy customers' needs and to enhance business efficiency. This paper proposes methods and a context awareness system for decision making to solve problems originated in management of manufacturing process through real-time information acquisition. We implement the context awareness by suggesting decision logics that automatically classify works with acquired information. And we also implement a system for case study which makes workers recognize problems and notifies instructions to them. Consistency between real object and stored data and continuous process monitoring with this system could find inefficient resources or delayed works, resolve them and improve processes efficiency.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.241-251
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• 2014

Mobile messenger services (MMSs), such as Kakaotalk, Wetalk, Line, and Whatsapp, are gaining popularity worldwide because of communicating with other people without any cost. We examined key antecedents of user loyalty to understand user's decision-making process in the MMS environment. To capture a long-term relationship with service providers, we posit relational commitment and user satisfaction as key predictors of user loyalty. Moreover, the effects of perceived usefulness, perceived enjoyment, and corporate image on user's decision-making processes were examined. The proposed model was tested by applying partial least squares to data from 220 experienced Kakaotalk users. The findings of this study found that both relational commitment and user satisfaction play an important role in enhancing user loyalty in the MMS context. The analysis results indicate that corporate image influences relational commitment and user loyalty through user satisfaction. The analysis results help MMS providers establish management or marketing strategies to effectively improve user loyalty.

• Korean Journal of Construction Engineering and Management
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• v.1 no.4 s.4
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• pp.74-81
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• 2000

The duration of construction in the construction works contains non-working days as well as working days. The duration is so relevant to climate that it should be calculated after fully considered about the regional climate in which construction processes. In most construction fields, however, there has been a frequent adjustment of duration because the field supervisor's experiences have decided non-working days indiscriminately without any accurate information about weather. Not only has that done great economic damages, but also caused many problems in interests among construction subject. So, in this study, we will analyse the elements of climate which has influences on the duration and implement the hypothetical weather simulation. By connecting the results of simulation with the duration of construction, we will propose the decision-making support model for the efficient calculation of duration when the field supervisor makes the projects schedule.