• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.430-432
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• 1993

In this paper, an algorithm for the fault diagnosis using simple FCM(Fuzzy Cognitive Map) is proposed FCMs which store uncertain causal knowledges are fuzzy signed graphs with feedback. The algorithm allows searching the origin of fault and the ways of propagating the abnormality throughout the process simply and has following characteristics. First, it can distinguish the cause of soft failure which can degenerate the process as well as hard failure. Second, it is proper for the processes which have difficulties to establish the exact quantative model. Finally, it has short amputation time in comparison with the fault tree or the other AI methods. The applicability of the proposed algorithm for the fault diagonosis to a tank or pipeline system is demonstrated

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3D
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• pp.239-245
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• 2012

The necessity of professional construction management has been increased as a construction project is getting larger, more complex and specialized. Thus, the CM market has steadily expanded since 1996 in Korea. Despite the external expanding of the CM market, experts claim that domestic CM regulations and infrastructures should be revised. Therefore, this paper developed a causal map which consists of elements vitalizing CM market. Then, the simulation model using NUMBER (Normalized Unit Modeling by Elementary Relationships) to predict the size of the CM market is established. As a result, in the case of more regulation related CM, the quantity of CM projects could not reach of construction supervision until 2020. This paper can be used as a baseline providing a prospection of the change of CM market according to causal relation between the improvement as well as the base of revitalization research of CM market based on non-institutional factors change.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.158-168
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• 2017

As the big data technologies advance, there is an increasing interest in systematic methodologies for data-based policy determination especially in the public health area. This study proposes a method to develop an issue detection model through the collaboration with domain experts in order to intelligently detect major socio-national issues on infectious diseases based on data. At first, the factors influencing the 'domestic inflow of foreign infectious diseases' are determined and variables representing the factors are set. Thereafter, by using system dynamics methods, the causal analysis is made to find causal map indicating main influential factors. In this process, an empirical modeling is conducted through collaboration between data analysts and experts in the infectious disease domain. The proposed issue detection approach based on domain knowledges will make it possible to make a decision on policies more efficiently if the detection system is capable of continuos monitoring of the related issues.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.502-512
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• 2019

To examine the problem structure of balanced regional development policy and identify the causes of the gap between the capital and non-capital areas, this study examined the causal structure in terms of the concentration and distribution of functions in the metropolitan area and non-capital area and explored the policy leverage. As a research method, the causal map was drawn using System Dynamics techniques and policy leverage was derived through an exploration of the feedback structure. In particular, the causes of the problems in balanced regional development policies were approached by system accidents rather than by single-circuit accidents, and causality analysis was performed among the variables constituting balanced regional development policies based on system accidents. In particular, it singled out 31 variables, developed 13 feedback loops, and confirmed four major policy leverages, including relocation of the capital function, local decentralization policies, consistent development, and investment practices centered on the Non­Capital Area. Subsequently, a follow-up study by computer simulation is needed by modeling the structure of the system to identify the ripple effect of the policies of the Capital Area on the Non­Capital Area.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.87-106
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• 2002

The behavioral and dynamic implications of an ERP implementation/installation are, to say the least, not well understood. Getting the switches set to enable the ERP software to go live is becoming straightforward. The really difficult part is understanding all of the dynamic interactions that accrue as a consequence. Dynamic causal and connectionist models are employed to facilitate an understanding of the dynamics and to enable control of the information-enhanced processes to take place. The connectionist model ran be analyzing (behind the scenes) the information accesses and transfers and coming If some conclusions about strong linkages that are getting established and what the behavioral implications of those new linkages and information accesses we. Ultimately, the connectionist model will come to an understanding of the dynamic, behavioral implications of the larger ERP implementation/installation per se. The underlying connectionist model will determine information transfers and workflow. Once a map of these two infrastructures is determined by the model, it becomes a relatively easy job for an analyst to suggest improvements in both. Connectionist models start with analog object structures and then use learning to produce mechanisms for managerial problem diagnoses. These mechanisms are neural models with multiple-layer structures that support continuous input/output. Based on earlier work performed and published by the author[10][11], a Connectionist ReasOning and LEarning System(CROLES) is developed that mimics the real-world reasoning infrastructure. Coupled with an explanation subsystem, this system can provide explanations as to why a particular reasoning structure behaved the way it did. Such a system operates in the backgmund, observing what is happening as every information access, every information response coming from each and every intelligent node (whether natural or artificial) operating within the ERP infrastructure is recorded and encoded. The CROLES is also able to transfer all workflows and map these onto the decision-making nodes of the organization.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.89-101
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• 2008

The most used tool for quality control is control chart in manufacturing industry. But it has limitations at current situation where most of manufacturing facilities are automated and several manufacturing processes have interdependent relationship such as CCM assembly line. To Solve problems, we propose quality management system based on data mining that are consisted of monitoring system where it monitors flows of processes at single window and feature extraction system where it predicts the yield of final product and identifies which processes have impact on the quality of final product. The quality management system uses decision tree, neural network, self-organizing map for data mining. We hope that the proposed system can help manufacturing process to produce stable quality of products and provides engineers useful information such as the predicted yield for current status, identification of causal processes for lots of abnormality.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.410-427
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• 2009

This study aims to rethink the meaning of graphicacy, discuss the possible criteria to evaluate the level of graphicacy, and show how the graphicacy differs through different grades. First, it finds that as school grades advance, implicit information processing abilities, and conceptual information processing abilities were more required comparing to explicit information processing abilities, when interpreting graphic data. Secondly, the percentage of items which examinee showed a proficient level, decreased as school grades advanced. Thirdly, the graphicacy level of sixth graders was the status of being able to derive explicit information from pictorial maps and read implicit information in simple contour map or line graphs. Ninth graders were able to infer causal relationship between geographic phenomenons by utilizing graphic materials. Tenth graders could read graphic materials by utilizing simple knowledge and experience.

• Journal of Information Technology Applications and Management
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• v.29 no.4
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• pp.1-16
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• 2022

This study analyzed the policy dilemma for ICT SMEs venture companies that changed after COVID-19 based on the results of the cognitive map analysis for ICT SMEs venture policies. First, as a result of analyzing the cognitive map of ICT SMEs venture companies that have changed since COVID-19, ICT venture companies are expanding support for ICT venture companies due to the threat of COVID-19. However, in order to convert COVID-19 into an opportunity factor, it also shows a policy direction to achieve innovative growth by creating a new market through non-face-to-face industry revitalization based on digital transformation (digital new deal). As a result of the study, the policy measures of supporting DNA-centered convergence innovation technology, digital transformation (digital new deal), fostering ICT startups (K-Global project), and expanding support for ICT SMEs did not have a policy dilemma. However, although many support has been expanded for ICT SMEs due to COVID-19, it is difficult to find and foster ICT start-up companies, and globalization problems are occurring due to the decrease in exports to COVID-19, making it difficult to create new markets. There is a negative (-) perception of causality that ICT SMEs venture companies may face risks as jobs decrease and innovative growth cannot be led to the revitalization of the non-face-to-face industry. Therefore, it was found that both the flow of causal relationship between the expansion of support for ICT SMEs and the high growth of ICT SMEs is not + and has a policy dilemma in part.

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.431-447
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• 2014

Demand of spectrum resource is tremendously increasing and this trend will continue as more IT services such as cloud computing, smart devices, Internet of Things are provided through wireless network. Recent development of spectrum sharing technology has drawn attention to spectrum policy makers as a promising way to overcome the expected spectrum shortage problem. However, technology-based solution to spectrum shortage problem may not be sustainable since the solution affect only one aspect of spectrum sharing ecosystem. To understand the whole picture of spectrum shortage problem, policies to vitalize spectrum sharing ecosystem were proposed based on the analysis of System Dynamics causal map in the previous study. This study compares and analyzes the effect of those proposed vitalization policies by using System Dynamics simulation. Among seven alternative policies, combined application of demand acceleration policy and technology development policy was found to be more effective for better utilization of spectrum. The effect of demand acceleration policy was offset when other policies are applied together except supply acceleration policy which shows better spectrum sharing.

• Journal of Korean Academy of Nursing
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• v.35 no.2
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• pp.323-335
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• 2005

Purpose: The purpose of this study was to examine the problems and relevant variables for effective Organizational Socialization of new nurses, to produce a causal map, to build up a simulation model and to test its validity. Method: The basic data was collected from Sep. 2002 to July 2003. The Organizational Socialization process of new nurses was analyzed through a model simulation. The VENSIM 5.0b DSS program was used to develop the study model. Result: This Model shows interrelation of these result variables: organizational commitment, job satisfaction, job performance, intention of leaving the work setting, decision making ability, and general results of Organizational Socialization. The model's factors are characteristic of organization and individual values, task-related knowledge and skills, and emotion and communication that affects new nurses' socialization process. These elements go through processes of anticipatory socialization, encounter, change and acquisition. The Model was devised to induce effective Organizational Socialization results within 24 months of its implementation. The basic model is the most efficient and will also contribute to the development of knowledge in the body of nursing. Conclusion: This study will provide proper direction for new Nurse's Organizational Socialization. Therefore, developing an Organizational Socialization Process Model is meaningful in a sense that it could provide a framework that could create effective Organizational Socialization for new nurses.