• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.659-666
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• 2011

The absence of present accurate geospatial information can cause us to undergo severe problems in controlling the complicate and multiplicate disaster. Our country is trying to build the Disaster Spatial Data Infrastructure (DSDI), and the key information is the national framework data. This study aims to investigate the characteristics of disaster spatial data, and analyze the present conditions and problems of national framework data, and suggest the way to improve for the GIS application system. In order to provide a wide range of services through the national geospatial data integration system, the data management authority should be established to maintain the consistency of quality and data accuracy of the entire national spatial data infrastructure. In addition, the step-by-step update plan of the national geospatial data should be determined by means of the framework data. And the basic data (lowest common denominator) should be formulated to maintain the data consistency of national spatial information infrastructure.

• The Journal of Information Systems
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• v.26 no.2
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• pp.105-121
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• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.248-255
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• 2016

The amount and diversity of information is increasing, as is the information integration connecting data among the related institutions. In the defense field, DTAQ, which is in charge of the quality of military supplies, is attempting to collect and analyze the information which is related with it. In addition, the object of information integration is to expand civil data as well as defense data. There are many ways to integrate data in various environments. In the defense field, which needs enhanced security, it is necessary to establish and apply the information integration methods which are enhanced with more security. In this study, the framework and architecture of information integration was designed by considering task requirements and security conditions. As a result of example application of this framework for information systems to the selected 4 institutions, it was confirmed that the task can be performed through data connections. From the study result, integration architecture which can be applied securely in defense field was suggested. The data accumulated by using this framework with strengthened security are expected to be utilized for the quality improvement of military supplies.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.91-112
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• 2019

The IoT environment has led to explosive growth of existing enterprise data, and how to utilize such big data is becoming an important issue in the management field. In this paper, major factors affecting the decisions of companies to utilize big data have been studied. And also, the effect of big data utilization on the management quality is studied empirically. During this process, we have studied the difference according to the award of Korean national quality award. As a result of the study, we confirmed that the five factors such as cost from technology, organization and environment perspective, compatibility, company size, chief officer support, and competitor pressure are key factors influencing big data utilization. Also, it was confirmed that the use of big data for management activities has an important influence on the six management quality factors based on MBNQA, and that the management quality level of Korean national quality award companies is relatively high. This paper provides practical implications for companies' use of big data because it demonstrates for the first time that big data utilization has an impact on management quality improvement.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.601-610
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• 2017

Purpose: Authors observe the digital twin enabled smart factory and/or digital manufacturing processes where Industry 4.0 technologies and quality management principles intersect. In this regard, this study reviews existing research regarding digital twins from the perspective of quality management. Methods: Initially, attention was given to how digital twins are manifested in the Industry 4.0 environment. Then, authors identify quality management elements amongst digital twin models, to align the concept of quality with the functional purpose of digital twins. After introducing specific examples of quality management tools applied to digital twins, the authors extend the domain of quality management into the analysis of multimedia format quality data obtained through machine vision. Results: Inspired by cases on the quality management application to digital twins, the authors suggest a framework for Industry 4.0 quality management. The envisioned suggested framework encompasses 4 dimensions, namely, 4M&1E, an application time window, new methodologies, and enabling technologies. Conclusion: Finally, the authors unfold the emerging trend of digital twin enabled smart factories, while emphasizing the necessity of quality management in conjunction with the introduction of digital twins.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.193-200
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• 2019

Accruals-Quality(AQ) is an important proxy for evaluating the quality of accounting information disclosures. High-quality accounting information will provide high predictability and precision in the disclosure of earnings and will increase the response to stock prices. And high Accruals-Quality, such as mitigating heterogeneity in accounting information interpretation, provides information usefulness in capital markets. The purpose of this study is to suggest how AQ, which represents the quality of accounting information disclosure, is transformed into digitized data in real-time in combination with IT information technology and provided to financial analyst's information environment in real-time. And AQ is a framework for predictive analysis through big data log analysis system. This real-time information from AQ will help financial analysts to increase their activity and reduce information asymmetry. In addition, AQ, which is provided in real time through IT information technology, can be used as an important basis for decision-making by users of capital market information, and is expected to contribute in providing companies with incentives to voluntarily improve the quality of accounting information disclosure.

• Journal of Engineering Education Research
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• v.21 no.6
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• pp.90-98
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• 2018

This paper proposes a framework of engineering education for product development processes based on product data management (PDM) software and 3D printing. The PDM software supports the product development process-oriented educational coursework, collaborative team projects and project-based learning environment. The 3D printing supports the prototyping step in the product development process and helps participants consider physical realization of their designs during the product design and development phases. The framework was implemented in an introductory course for engineering students to product design and development, and author found that it is important to support rich communication among participants including lecturers, teaching assistants and students to enhance the quality of education and to overcome the burden of learning various computer-aided tools and 3D printing techniques needed for the framework.

• Quality Improvement in Health Care
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• v.22 no.1
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• pp.11-26
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• 2016

The Organization for Economic Cooperation and Development, which has continuously evaluated the performance of healthcare systems, has recently invested much effort into hospital performance measurement. The purpose of this paper is to introduce the hospital performance measurement programs operated by international organizations or at the national level based on the OECD's hospital performance project. Health Insurance Review & Assessment service (HIRA)'s quality assessment was analyzed based on the analytical framework of the OECD's hospital performance project. The hospital performance measurement programs of WHO, Canada, Australia, United States and United Kingdom are briefly explored, in view of the conceptual framework, key performance dimensions and indicators that are currently in use. The OECD suggested seven key dimensions of hospital performance: timeliness, efficiency, continuity, effectiveness and appropriateness, staff orientation, patient orientation and safety. The analysis of the quality assessment program of HIRA, which operates 36 diseases and procedures and 347 indicators, shows that the numbers of indicators are relatively small in the areas of safety, patient centeredness and efficiency. Continuity of care and staff orientation are not fully developed also, but the situations are similar in other countries. In conclusion, hospital performance measurement using stable and comprehensive data should be developed to improve overall system performance, and discussions on a conceptual framework that can lay out directions and key performance domains need to take into place.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1533-1556
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• 2017

The concept of trust in vehicular ad hoc networks (VANETs) is usually utilized to assess the trustworthiness of the received data as well as that of the sending entities. The quality of safety applications in VANETs largely depends on the trustworthiness of exchanged data. In this paper, we propose a self-organized distributed trust computing framework (DTCF) for VANETs to compute the trustworthiness of each vehicle, in order to filter out malicious nodes and recognize fully trusted nodes. The proposed framework is solely based on the investigation of the direct experience among vehicles without using any recommendation system. A tier-based dissemination technique for data messages is used to filter out non authentic messages and corresponding events before even going farther away from the source of the event. Extensive simulations are conducted using Omnet++/Sumo in order to investigate the efficiency of our framework and the consistency of the computed trust metrics in both urban and highway environments. Despite the high dynamics in such networks, our proposed DTCF is capable of detecting more than 85% of fully trusted vehicles, and filtering out virtually all malicious entities. The resulting average delay to detect malicious vehicles and fraudulent data is showed to be less than 1 second, and the computed trust metrics are shown to be highly consistent throughout the network.