• 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.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.63-69
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• 1999

The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.763-774
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• 2006

The purpose of this study is to identify relationship among service quality, service value and customer satisfaction of food service industries. The respondents included 120 customers of K-restaurant in the survey. Data were analyzed by confirmatory factor analysis and cause-effect analysis among the constructs. After research model testing, the following results was obtained : Service Value was influenced directly and positively by the service quality. And customer satisfaction was influenced directly and positively by the service value. But customer satisfaction was not influenced directly and positively by the service quality.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2107-2111
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• 2013

Objectives: To investigate data agreement of cancer registries and medical records as well as the quality of care and assess their relationship in a 5-year period from 2006 to 2011. Methods: The present cross-sectional, descriptive-analytical study was conducted on 443 cases summarized through census and using a checklist. Data agreement of Nemazi hospital-based cancer registry and the breast cancer prevention center was analyzed according to their corresponding medical records through adjusted and unadjusted Kappa. The process of care quality was also computed and the relationship with data agreement was investigated through chi-square test. Results: Agreement of surgery, radiotherapy, and chemotherapy data between Nemazi hospital-based cancer registry and medical records was 62.9%, 78.5%, and 81%, respectively, while the figures were 93.2%, 87.9%, and 90.8%, respectively, between breast cancer prevention center and medical records. Moreover, quality of mastectomy, lumpectomy, radiotherapy, and chemotherapy services assessed in Nemazi hospital-based cancer registry was 12.6%, 21.2%, 35.2%, and 15.1% different from the corresponding medical records. On the other hand, 7.4%, 1.4%, 22.5%, and 9.6% differences were observed between the quality of the above-mentioned services assessed in the breast cancer prevention center and the corresponding medical records. A significant relationship was found between data agreement and quality assessment. Conclusion: Although the results showed good data agreement, more agreement regarding the cancer stage data elements and the type of the received treatment is required to better assess cancer care quality. Therefore, more structured medical records and stronger cancer registry systems are recommended.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.295-306
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• 2016

The purpose of this paper is both to analyze research trends and to predict industrial flows using the meta-data from the previous studies on data quality. There have been many attempts to analyze the research trends in various fields till lately. However, analysis of previous studies on data quality has produced poor results because of its vast scope and data. Therefore, in this paper, we used a text mining, social network analysis for time series network analysis to analyze the vast scope and data of data quality collected from a Web of Science index database of papers published in the international data quality-field journals for 10 years. The analysis results are as follows: Decreases in Mathematical & Computational Biology, Chemistry, Health Care Sciences & Services, Biochemistry & Molecular Biology, Biochemistry & Molecular Biology, and Medical Information Science. Increases, on the contrary, in Environmental Sciences, Water Resources, Geology, and Instruments & Instrumentation. In addition, the social network analysis results show that the subjects which have the high centrality are analysis, algorithm, and network, and also, image, model, sensor, and optimization are increasing subjects in the data quality field. Furthermore, the industrial connection analysis result on data quality shows that there is high correlation between technique, industry, health, infrastructure, and customer service. And it predicted that the Environmental Sciences, Biotechnology, and Health Industry will be continuously developed. This paper will be useful for people, not only who are in the data quality industry field, but also the researchers who analyze research patterns and find out the industry connection on data quality.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.87-98
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• 2014

Generally there is a technical gap for the image data quality between from the satellite requirement values and from the users. After Cal/Val for KOMPSAT-3 had been done by Dec. 31, 2012, all requirements for KOMPSAT-3 image data quality have been validated, and then the normal operation of it started from Jan. 2013. In the normal period, the image data quality for the users has been defined and managed, and according to the result of it, the additional Cal/Val items have been doing. Cal/Val team and Processing team in KARI made the quality report (QR) for KOMPSAT-3 image data quality for the users, and have determined the quality level of KOMPSAT-3 product generated by Processing system (PMS; Product Management System) and managed the quality report for it. According to the result of the quality report, Cal/Val team defined six additional Cal/Val items, and has done five items of them and has been implementing the result of them into the Processing system.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7985-7987
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• 2014

Introduction: Khon Kaen Cancer Registry (KKCR) was established in 1984. KKCR aims to collect all cancer cases in Khon Kaen Province. The poorly qualified data may lead to distort the cancer burden and misinterpretation of policy maker. Objective: To assess data quality in childhood cancer between 1990 and 2007 in Khon Kaen Province, Thailand. Materials and Methods: Data of childhood cancer cases aged less than 20 years diagnosed during 1990-2007 were retrieved from the population-based data set of KKCR. All childhood cancer data were verified before data entry. Internal consistency, percentage of morphological verification (MV%) and cancer cased of the basis of diagnosis by death certificate only (DCO%) were evaluated. The age-adjusted rate (ASR) was calculated by standard method. Results: The data of childhood cancer from KKCR is acceptably qualified which reflects the quality of the whole registration.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.885-890
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• 2007

This study is to investigate factors that affect usage change in mobile data service (MDS). In the first, an exploratory study based on 378 survey responses was conducted to learn about important decision factors of MDS usage. It revealed discrepancy between the influencing forces of usage increase and those of usage decrease. Based on the findings from the exploratory study and the two-factor theory, we postulated information quality as the motivator and system quality as the de-motivator (or hygiene) of MDS. Then, a confirmative study was undertaken on their respective role in encouraging and discouraging the usage of mobile data service. A research model was proposed and subsequent hypotheses were empirically tested with partial least square (PLS) based on 478 responses from the users of mobile data service. It was learned that information quality (as a motivator) was positively associated with usage increase in mobile data service, but system quality (as a de-motivator) was not. Also, system quality was negatively associated with usage decrease, but information quality was not. Lastly, their association strength was partially moderated by the type of motivation for using MDS.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.509-522
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• 2018

Purpose: The purpose of this study was to propose more accurate mathematical model which can represent result of government quality assurance activity, especially corrective action and flaw. Methods: The collected data during government quality assurance activity was represented through histogram. To find out which distributions (Poisson distribution, Zero-Inflated Poisson distribution) could represent the histogram better, this study applied Pearson's correlation coefficient. Results: The result of this study is as follows; Histogram of corrective action during past 3 years and Zero-Inflated Poisson distribution had strong relationship that their correlation coefficients was over 0.94. Flaw data could not re-parameterize to Zero-Inflated Poisson distribution because its frequency of flaw occurrence was too small. However, histogram of flaw data during past 3 years and Poisson distribution showed strong relationship that their correlation coefficients was 0.99. Conclusion: Zero-Inflated Poisson distribution represented better than Poisson distribution to demonstrate corrective action histogram. However, in the case of flaw data histogram, Poisson distribution was more accurate than Zero-Inflated Poisson distribution.