• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.63-70
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• 2013

The multimedia data of game affects the immersion of the game depending on its quality. It is difficult to design the evaluation criteria of artistic quality of the data. But, in a technical point of view, it is possible to evaluate its quality. Thus, the design of evaluation standard can ensure the reliability and objectivity of quality. However, multimedia data quality evaluation metrics had not yet been designed. Therefore, in this study, we extracted quality evaluation elements of Game Multimedia Data, and verified the reliability of the elements. And we defined detailed evaluation items of each element, developed Multimedia Data Quality Evaluation Metrics. We expect that the results of this study will serve as a guide in the development of high-quality games, have a positive impact on the growth of the game industry.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.301-312
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• 2017

Quality evaluation and control represent increasingly important concerns for construction quality management. There is an evident need for a standard data model to be used as the basis for computer-aided quality management. This study focuses on how to realize evaluation of construction quality based on BIM and database technology. In this paper, the reinforced concrete main structure is taken as an example, and the BP neural network evaluation model is established by inquiring current construction quality acceptance specification and evaluation standard. Furthermore, IFC standard is extended to integrate quality evaluation information and realize the mapping of evaluation information in BIM model, contributing to the visualization and transfer sharing of evaluation information. Furthermore, the conceptual entity model is designed to build quality evaluation database, and this paper select MySQL workbench system to achieve the establishment of the database. This study is organized to realize the requirement of visualization and data integration on construction quality evaluation which makes it more effective, convenient, intuitive, easy to find quality problems and provide more comprehensive and reliable data for the quality management of construction enterprises and official construction administratiors.

• Journal of Information Technology Applications and Management
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• v.10 no.4
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• pp.103-118
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• 2003

This study presents a database quality evaluation framework. As a way to build a framework, this study expands data quality management to include data transformation processes as well as data. Further, an information structure graph is applied to represent data transformations processes. An information structure graph is absed on a relational database scheme. Thus, data transformation processes may be stored in a relational database. This kind of integration of data transformation metadata with technical metadata eases evaluation of database qualities and their causes.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.123-136
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• 1996

Lately, the demand for data standardization become increased to obtain various data jointly along with development of information technology and diversity of society. Thus the research on tile definition and evaluation of data quality indicating accuracy and confidence of geospatial data, is required for this standardization. In this study, by virtue of comparison of definitions and evaluation methods of data quality element being selected from representative countries, the following results were obtained: (1) Application of ISO/TC211's Draft having accepted evaluation standard to KSDTS(Korea Spatial Data Transfer Standard) is desirable for definitions of data quality elements. (2) This study presented the quality evaluation of much more resonable geospatial data accompaning with quality element. Furthermore, this study suggests that this evaluation be applicable to KSDTS and be contained in the digital map product specification of National Geography Institute with more clearness of a report form of data quality evaluation result. (3) Studies on various sampling methods, establishment of AQL(Acceptable Quality Level) suitable for our country, and computer programming which can rapidly and automatically evaluate mass much of data are required.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.119-128
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• 2007

In this paper, We study on the Data Quality Model of ISO/IEC 25012 among the Software product Quality Requirements and Evaluation(SQuaRE) in ISO/IEC 25000 Series. Because of the increasing data, user require the accuracy data, recent data, suitable data for used tools, complied security and not open to be public. We research the data quality management in the point of application of be affect influenced low quality in business. We propose the testing items and we propose the method of the evaluation proposed testing items. We study on the basis international Standards ISO/IEC 25012 and ISO/IEC 9126-2 and we proposed the testing method quantitatively on the basis of ISO/IEC 25000.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.109-116
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• 2008

The rapid change of computer and Internet environments produces a lot of data of various quality, Because this fact affects enterprise and organization, it demands the level evaluation on data quality, Thus, we propose mathematical model for quality evaluation on the base of data quality in this paper. And we propose the analysis model(web evaluation model, DQnA)) that analyzes and maintains data quality.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.533-545
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• 2014

According to the evolving of IT technologies, the amount of data we are facing increasing exponentially. Thus, the technique for managing and analyzing these vast data that has emerged is a distributed processing system of big data. A quality evaluation for the existing distributed processing systems has been proceeded by the structured data environment. Thus, if we apply this to the evaluation of distributed processing systems of big data which has to focus on the analysis of the unstructured data, a precise quality assessment cannot be made. Therefore, a study of the quality evaluation model for the distributed processing systems is needed, which considers the environment of the analysis of big data. In this paper, we propose a new quality evaluation model by deriving the quality evaluation elements based on the ISO/IEC9126 which is the international standard on software quality, and defining metrics for validating the elements.

• Asian Journal for Public Opinion Research
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• v.7 no.1
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• pp.57-74
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• 2019

Researchers usually examine the quality of survey data by several conventional measures of reliability and validity. However, those measures are mainly designed to examine the quality of an individual measurement, rather than the quality of a data set as a whole. There is a relative lack of methods for evaluation of the overall data quality. This paper attempts to fill this gap. We propose using interviewers' assessments as one of criteria for evaluating the overall data quality. Interviewers are the ones who literally conduct and thus directly observe interviews. Taiwan's Election and Democratization Studies (TEDS) have required interviewers to assess how trustworthy the responses of each of their interviewees are, and to provide several descriptions about the process and environment of the interviews. We use this information to evaluate the data quality of TEDS surveys and compare it with the results from the conventional test-retest method. The findings are that the interviewer assessment is a fair indicator of the overall reliability of attitudinal questions but not a good indicator when factual questions are examined. Regarding the evaluation of data validity, more data is required to see whether or not interviewers' assessment is informative in terms of data quality.

• ETRI Journal
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• v.28 no.2
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• pp.191-204
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• 2006

Many previous studies of data quality have focused on the realization and evaluation of both data value quality and data service quality. These studies revealed that poor data value quality and poor data service quality were caused by poor data structure. In this study we focus on metadata management, namely, data structure quality and introduce the data quality management maturity model as a preferred maturity model. We empirically show that data quality improves as data management matures.

• Korea Journal of Hospital Management
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• v.13 no.3
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• pp.69-93
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• 2008

Rising healthcare cost is a global phenomenon that justifies governments' introduction of 'incentive regulation' plan for the improvement of hospital efficiency. A number of previous studies tried to evaluate the efficiency of healthcare organization by using Data Envelopment Analysis(DEA), a common efficiency benchmarking method. However, there is a concern that this kind of efficiency evaluation could induce "quantity-quality trade-off". Moreover, as quality aspect is especially important in terms of 'effectiveness' of health care, it should be considered in efficiency evaluation of healthcare organization. A number of different models were tried so far to incorporate quality aspect into DEA, however, none is universally recognized as a standard. Thus, in this study, previous quality-incorporating DEA models were categorized into 6 types according to the way of incorporating quality aspect, and strengths and limitations of each type were reviewed with a set of artificial data as an example. Based on this review, a new quality-incorporating efficiency evaluation model, named Quality-adjusted output DEA(QAO-DEA), was suggested. As an exploratory empirical analysis, technical efficiency of human resource were measured with different quality-incorporating DEA models, using 2004 data from National University Hospitals. In conclusion, Quality-adjusted output DEA(QAO-DEA) model seems to be one of the most desirable alternatives to incorporate quality aspect in efficiency evaluation of hospital, and deserves the consideration as a policy tool to induce simultaneous improvement of both efficiency and quality.