• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.21-31
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• 2012

We focus on the issues of the non-linear return/risk relationship of IT investment and the balance between return and risk of IT portfolio. We develop an IT project selection model by integrating DEA models with Markowitz portfolio selection theory. The project data collected from a Fortune 100 company are used to illustrate the implementation of the model. In addition, computational experiments are conducted to demonstrate the validity of the proposed model.

• Journal of the Korean Society of School Health
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• v.28 no.1
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• pp.38-46
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• 2015

Purpose: The object of this study is to identify the reason why school health education act had not been enforced properly, and to find out implications for improving. Methods: The implementation process of school health education act was described and the imperatives of the process were analysed. M. Rein's Policy Implementation Model was used as an analysis framework. The sources of this study was based on the minutes of parliament, government reports, materials for the meetings of policy makers, the press, etc. Results: The school health education act clarified mandatory and systemic health education in it, but it did not clearly mentioned about 'the introduction of compulsory health education subject'. The bureaucrats of National Educational Ministry who are responsible for policy implementation, did not behave in a friendly manner toward the school health education act. What is more, the ways of mandatory and systemic school health education could not be discussed reasonably in the implementation process. Through this study it was found that the rational-bureaucratic imperative played the main role in the implementation process of school health education act due to the limitation of the legal imperative and the consensual imperative. Conclusion: The result of this study suggests the strong need to make up for the defect of the two imperatives, and to reform the rational-bureaucratic imperative.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.701-710
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• 2018

In the 4th Industrial Revolution, it is a time when all the devices and people interact to create new added value. Software education is necessary in elementary school because what is more important is software. However, until now there is a lack of teaching and learning methods for software education in elementary school. In this paper, IDOL model is proposed as a method to solve this problem. statements for elementary students. The idol model is learning through observe, to implement, to diversify. In the implementation, the elementary students are to make it quickly, In the diversification, it is variously changing the things that have been made, and observation how the changed things are different. A model is verified by a group of experts consisting of elementary school teachers.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.255-261
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• 2015

This paper aimed to analyze the factors affecting on the implementation of supply chain management (SCM) system of manufacturing company in Korea. For preparation of the data for this research, the Internet-based questionnaires with 5 Likert's scale were performed to the 125 manufacturing companies in Korea. The affecting factors on the implementation of SCM system were crystallized through factor analysis methods. And the correlations between factors were analyzed with structural equation model (SEM). The factors affecting on the implementation of SCM system are company's IT-competence and relationship with supply chains. This paper could contribute to show the guideline for the successful implementation of SCM system to the korean manufacturing company.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.131-141
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• 1998

Video data occurred in multimedia documents consist of a large scale of irregular data including audio-visual, spatial-temporal, and semantic information. In general, it is difficult to grasp the exact meaning of such a video information because video data apparently consist of unmeaningful symbols and numerics. In order to relieve these difficulties, it is necessary to develop an integrated manager for complex structures of video data and provide users of video digital libraries with easy, systematic access mechanisms to video informations. This paper proposes a generic integrated video information model(GIVIM) based on an extended Dublin Core metadata system to effectively store and retrieve video documents in digital libraries. The GIVIM is an integrated mo이 of a video metadata model(VMN) and a video architecture information model(VAIM). We also present design and implementation results of a video document management system(VDMS) based on the GIVIM.

• Korean Journal of Computational Design and Engineering
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• v.6 no.3
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• pp.157-168
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• 2001

The description of enterprise activities is the basis fur process improvement and information system building. To describe such activities, it is necessary to model the enterprise activities from the abstraction level to the implementation level in a stepwise and integrated form. For this reason, several modeling approaches have been proposed. However, most of them lacked the stepwise or integration aspects although some of them covered overall levels. This study proposes the hierarchical modeling approach for integrating the enterprise activity model from the abstraction level to the implementation level systematically. It is composed of five modeling levels such as function level, process level, task level, document workflow level, and event flow level. This study discusses the definition and characteristics of each level and compare our modeling frame with other modeling methodologies in case study.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.169-181
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• 2016

Organizations in some industries are still hesitant to adopt the Enterprise Resource Planning (ERP) system due to its high risk of failures. This study examined how industry classification affects the successful implementation of the ERP system. To achieve this goal, we reinvestigated the existing ERP Success Model that was developed by Chung with the data from various industry sectors, since Chung validated the model only in the engineering and construction industries. In order to test to see if the Chung model can be applicable outside the engineering and construction industries, the relationships between the ERP success indicators and the critical success factors in the Chung model and those in the sample data collected from ten different industry sectors were compared and investigated. The ten industry sectors were selected based on the Global Industry Classification Standard (GICS). We found that the impact of success factors on the success of implementing an ERP system varied across industry sectors. This means that the success of ERP system implementation can be industry-specific. Thus, industry classification should be considered as another factor to help IT decision makers or top-management avoid ERP system failures when they plan to implement a new ERP system.

• Safety and Health at Work
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• v.12 no.1
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• pp.42-50
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• 2021

Introduction: Despite huge investments in new technology and transportation infrastructure, terrible accidents still remain a reality of traffic. Methods: Severe traffic accidents were analyzed from four prevailing modes of today's transportations: sea, air, railway, and road. Main root causes of all four accidents were defined with implementation of the approach, based on Flanagan's critical incident technique. In accordance with Molan's Availability Humanization model (AH model), possible preventive or humanization interventions were defined with the focus on technology, environment, organization, and human factors. Results: According to our analyses, there are significant similarities between accidents. Root causes of accidents, human behavioral patterns, and possible humanization measures were presented with rooted graphs. It is possible to create a generalized model graph, which is similar to rooted graphs, for identification of possible humanization measures, intended to prevent similar accidents in the future. Majority of proposed humanization interventions are focused on organization. Organizational interventions are effective in assurance of adequate and safe behavior. Conclusions: Formalization of root cause analysis with rooted graphs in a model offers possibility for implementation of presented methods in analysis of particular events. Implementation of proposed humanization measures in a particular analyzed situation is the basis for creation of safety culture.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.31-42
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• 2010

GPM(Generic Product Model) developed by Hitachi in Japan is a common data model to integrate and share life cycle data of nuclear power plants. GPM consists of GPM core model, an abstract model, implementation language for the model and reference library written in the language. GPM core model has a feature that it can construct a semantic network model consisting of relationships among objects. Initial GPM developed and provided GPML as an implementation language to support the feature of the core model, but afterwards the GPML was replaced by GPM-XML based on XML to achieve data interoperability with heterogeneous applications accessing a GPM data model. However, data models written in GPM-XML are insufficient to be used as a semantic network model for lack of studies which support GPM-XML and enable the models to be used as a semantic network model. This paper proposes OWL as the implementation language for GPM core model because OWL can describe ontologies similar to semantic network models and has an abundant supply of technical standards and supporting tools. Also, OWL which can be expressed in terms of RDF/XML based on XML guarantees data interoperability. This paper uses OWL DL, one of three sublanguages of OWL, because it can guarantee complete reasoning and the maximum expressiveness at the same time. The contents of this paper introduce the way how to overcome the difference between GPM and OWL DL, and, base on this way, describe how to convert the reference library written in GPML into ontologies based on OWL DL written in RDF/XML.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.