• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.689-699
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• 2013

During extreme ionospheric storms, anomalous ionospheric delays and gradients could cause potential integrity threats to users of GNSS (Global Navigation Satellite System) augmentation systems. GNSS augmentation ground facilities must monitor these ionospheric anomalies defined by a threat model and alarm the users of safely-of-life applications within time-to-alerts. Because the ionospheric anomaly threat model is developed using data collected from GNSS reference stations, the use of poor-quality data can degrade the performance of the threat model. As the total number of stations increases, the number of station with poor GNSS data quality also increases. This paper analyzes the quality of data collected from Korean GPS reference stations using comprehensive GNSS data quality check algorithms. The results show that the range of good and poor qualities varies noticeably for each quality parameter. Especially erroneous ionospheric delay and gradients estimates are produced due to poor quality data. The results obtained in this study should be a basis for determining GPS data quality criteria in the development of ionospheric threat models.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.439-447
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• 2020

Public data refers to all data or information created by public institutions, and public information that leads to communication and cooperation among all people. Public data is an important method to lead the next generation of new industries such as artificial intelligence and smart cities, Korea is continuously ranked high in the international evaluation related to public data. However, despite the continuous efforts, the use of public data or industrial influence is insufficient. Quality issues are continuously discussed in the use of public data, but the criteria for quantitatively evaluating data are insufficient. This paper reviews indicators for public data quality evaluation and performs quantitative evaluation on selected public data. In particular, the quality of open standard data constructed and opened based on public data management guidelines is examined to determine whether government guidelines are appropriate. The data quality assessment includes the metadata and data values of open standard data, and is reviewed based on completeness and accuracy indicators. Based on the data analysis results, this paper proposes policy and technical measures for quality improvement.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.3
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• pp.56-65
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• 2001

In interpreting stream water quality data, scientific or statistical mehtods should be employed. Classical parametric statistical methods may not be adopted in analyzing water quality data, due to the violation of normality. In this study, nonparametric statistical methods, such as Kruskal-Wallis test and Mann-Whitney test, were used in comparing water quality data from several monitoring stations. Water quality data used are those collected Bokha watershed, located in Ichon-city, Kyonggi province. Based on the test results, domestic sewage is the major pollution source. A couple of sub-watersheds with a large number of livestock do not show significant differences in water quality parameters. It should be noted that comparison of mean values of water quality parameters is difficult to relate water quality with watershed characteristics. The results also indicate that livestock farming does not significantly affect the water quality.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.582-587
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• 2007

ERP system is a good one because it provides required data to the Board of Directors at the right time, but needs to collect many data in this system. Nevertheless, increase in data leads to the system's quality deterioration which makes companies to carry out quality improvement. In order to solve quality deterioration problem, a company's quality improvement director must execute under acknowledgement of the relationships between sectors to be improved, which are DBMS, Application, System, Data Management, Archiving, and Reorganization. But in many cases, these relationships are ignored due to massive size of each of the sectors, resulting fragmental quality improvement operation. This case paper proposes a solution to effectively solve quality deterioration problem created by the massive data produced while operating ERP System(constructed by SAP package and web). First, it defines the sectors where quality improvements are vital, and lists out things to be considered. Then, by analysing the working process of these sectors, proposes the most efficient order of the improvement process. This case will eventually help the company's quality improvement director to execute quality improvement most effectively without trials and errors, which is this paper's ultimate goal.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.363-370
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• 1999

Remotely sensed data is regarded as a potentially effective data source for the measurement of water quality and for the environmental change of water bodies. In this study, we measured the spectral reflectance by using multi-spectral image of low resolution camera(LRC) which will be loaded in the OSMI multi-purpose satellite(KOMPSAT) scheduled to be launched on 1999 to use the data in analyzing water pollution. We also investigated the possibility of extraction of water quality factors in water bodies by using remotely sensed low resolution data such as NOAA/AVHRR. In this study, Shiwha-District and Sang-Sam Lake was set up as the subject areas for the study. In this part of the study, we measured the spectral reflectance of the water surface to analyze the radiance of the water bodies in low resolution spectral band and tried to analyze the water quality factors in water bodies by using radiance feature from another remotely sensed data such as NOAA/AVHRR. As the method of this study, first, we measured the spectral reflectance of the water surface by using SFOV( Single Field of View) to measure the reflectance of water quality analysis from every channel in LRC spectral band(0.4~O.9${\mu}{\textrm}{m}$). Second, we investigated the usefulness of ground truth data and the LRC data by measuring every spectral reflectance of water quality factors. Third, we analyzed water quality factors by using the radiance feature from another remotely sensed data such as NOAA/AVHRR. We carried out ratio process of what we selected Chlorophyll-a and suspended sediments as the first factors of the water quality. The results of the analysis are below. First, the amount of pollutants of Shiwha-Lake has been increasing every you since 1987 by factors of eutrophication. Second, as a result of the reflectance, Chlorophyll-a represented high spectral reflectance mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and turbidity represented high spectral reflectance at 0.57${\mu}{\textrm}{m}$. But suspended sediments absorbed high at 0.8${\mu}{\textrm}{m}$. Third, Chlorophyll-a and suspended sediments could have a distribution chart as a result of the water quality analysis by using NOAA/AVHRR data.

• Journal of Korean Society for Quality Management
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• v.11 no.2
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• pp.25-31
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• 1983

Often arrangement for effective product assessment and audit have not been completely satisfactory. The underlying reasons are: (a) The lack of early evidence of new unit quality. (b) The collection and processing of data. (c) Ineffective data analysis techniques. (d) The variability of information on which decision making is based. Because of the nature of the product the essential outputs from an affective QA organization would be: (a) Confirmation of new unit quality. (b) Detection of failures which are either epidemic or slowly degradatory. (c) Identification of failure cases. (d) Provision of management information at the right time to effect the necessary corrective action. The heart of an effective QA scheme is the acquisition and processing of data. With the advent of data processing for quality monitoring becomes feasible in an automotive testing environment. This paper shows how the method enables us to use Automotive Testing data for the cost benefits of QA management.

• 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 Korean Society for Quality Management
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• v.23 no.1
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• pp.64-73
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• 1995

At the time of internationalization, it is inevitable to improve the quality of products to survive the international competition. ISO 9000 series have been recognized by most companies as the quality assurance system. However, it was known to require quite many records and data which need to be controlled and analyzed. The objective of this paper is to present the procedure in establishing the quality information data base which enables a company to easily handle the required records and data for the ISO 9000 series. Examples using the quality information data base are also presented.

• 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.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.142-148
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• 2006

Data mining is a useful tool for analyzing data from different perspectives and for summarizing them into useful information. Recently, the data mining methods are applied to solving quality problems of the manufacturing processes. This paper discusses the problems of construction of a quality mining system, which is based on the various data mining methods. The quality mining system includes recipe optimization, significant difference test, finding critical processes, forecasting the yield. The contents and system of this paper are focused on the TFT-LCD manufacturing process. We also provide some illustrative field examples of the quality mining system.