• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1628-1636
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• 2017

Such as closed caption, ancillary data, electronic program guide(EPG), data broadcasting, and etc, increased data for service convenience cause to degrade video quality of high definition contents. This article propose a method to transfer the closed caption data of video contents without video quality degradation. Video quality degradation does not cause in video compression by the block image insertion of caption data in DTV essential hidden area. Additionally the proposed methods have advantage to synchronize video, audio, and caption from preinserted script without time delay.

• Atmosphere
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• v.24 no.1
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• pp.77-87
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• 2014

The radar reflectivity is significantly affected by ground clutter, beam blockage, anomalous propagation (AP), birds, insects, chaff, etc. The quality of radar reflectivity is very important in quantitative precipitation estimation. Therefore, Weather Radar Center (WRC) of Korea Meteorological Administration (KMA) employed two quality control algorithms: 1) Open Radar Product Generator (ORPG) and 2) fuzzy quality control algorithm to improve quality of radar reflectivity. In this study, an occurrence of AP echoes and the performance of both quality control algorithms are investigated. Consequently, AP echoes frequently occur during the spring and fall seasons. Moreover, while the ORPG QC algorithm has the merit of removing non-precipitation echoes, such as AP echoes, it also removes weak rain echoes and snow echoes. In contrast, the fuzzy QC algorithm has the advantage of preserving snow echoes and weak rain echoes, but it eliminates the partial area of the contaminated echo, including the AP echoes.

• Journal of Korean Society on Water Environment
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• v.21 no.6
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• pp.651-658
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• 2005

The Non-parametric Analysis is powerful in data test especially for the non- normality water quality data. The data at three monitoring stations of the Tam-Jin River were evaluated for their normality using Skewness, Q-Q plot and Shapiro-Willks tests. Various constituent of water quality data including temperature, pH, DO, SS, BOD, COD, TN and TP in the period of January 1994 to December 2004 were used as dataset. Shapiro-Willks normality test was carried out for a test 5% significance level. Most water quality data except DO at monitoring stations 1 and 2 showed that data does not normally distributed. It is indicating that non-parametric method must be used for a water quality data. Therefore, a homogeneity was conducted by Mann-Whitney U test (p<0.05). Two stations were paired in three pairs of such stations. Differences between stations 1, 2 and stations 1, 3 for pH, BOD, COD, TN and TP were meaningful, but Tam-Jin 2 and 3 stations did not meaningful. In addition, a narrow gap of the water quality ranges is not a difference. Categories in which all three pairs of stations (1 and 2, 2 and 3, 1 and 3) in the Tam-Jin River showed difference in water quality were analyzed on TN and TP. The results of in this research suggest a right analysis in the homogeneity test of water quality data and a reasonable management of pollutant sources.

• Journal of the Ergonomics Society of Korea
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• v.28 no.4
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• pp.117-124
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• 2009

To inspect the quality of data collected from a large-scale body measurement and investigation project, it is necessary to establish a proper data editing process. The three-dimensional body measurement may have measuring errors caused from measurer's proficiency or changes in the subject's posture. And it may also have errors caused in the process of algorithm expressing the information obtained from the three-dimensional scanner into numerical values, and in the course of data-processing dealing with numerous data for individuals. When those errors are found, the quality of the measured data is deteriorated, and they consequently reduce the quality of statistics which was conducted on the basis of it. Therefore this study intends to suggest a new way to improve the quality of the data collected from the three-dimensional body measurement by proposing a working procedure identifying data errors and correcting them from the whole data processing procedure-collecting, processing, and analyzing- of the 2004 Size Korea Three-dimensional Body Measurement Project. This study was carried out into three stages: Firstly, we detected erroneous data by examining of logical relations among variables under each edit rule. Secondly, we detected suspicious data through independent examination of individual variable value by sex and age. Finally, we examined scatter-plot matrix of many variables to consider the relationships among them. This simple graphical tool helps us to find out whether some suspicious data exist in the data set or not. As a result of this study, we detected some erroneous data included in the raw data. We figured out that the main errors are not because of the system errors that the three-dimensional body measurement system has but because of the subject's original three-dimensional shape data. Therefore by correcting some erroneous data, we have enhanced data quality.

• International Journal of Contents
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• v.6 no.3
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• pp.1-4
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• 2010

The national management and retrieval service of the national scholar Content DB are very important. High quality content can improve the user's utilization and satisfaction and be a strong base for both the citation index creation and the calculation of journal impact factors. Therefore, the system is necessary to check data quality effectively. We have closely studied and developed a webbased data quality checking system that will support anything from raw digital data to its automatic validation as well as hands-on validation, all of which will be discussed in this paper.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.118-124
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• 2023

Many recent studies have reported that the quality of input learning data was vital to the detection of regions of interest. However, due to a lack of research on the quality of learning data on lesion detetcting using gastroscopy, we aimed to quantify the impact of quality difference in endoscopic images to lesion detection models using Image Quality Assessment (IQA) algorithms. Through IQA methods such as BRISQUE (Blind/Referenceless Image Spatial Quality Evaluation), Laplacian Score, and PSNR (Peak Signal-To-Noise) algorithm on 430 sheets of high quality data (HQD) and 430 sheets of low quality data (PQD), we showed that there were significant differences between high and low quality images in lesion detecting through BRISQUE and Laplacian scores (p<0.05). The PSNR value showed 10.62±1.76 dB on average, illustrating the lower lesion detection performance of PQD than HQD. In addition, F1-Score of HQD showed higher detection performance at 77.42±3.36% while F1-Score of PQD showed 66.82±9.07%. Through this study, we hope to contribute to future gastroscopy lesion detection assistance systems that involve IQA algorithms by emphasizing the importance of using high quality data over lower quality data.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.128-141
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• 1996

The advent of the quality-improvement movement caused a great expansion in the use of statistically designed experiments in industry. The regression method is often used for the analysis of data from such experiments. However, the data for a quality characterstic often takes the form of counts or the ratio of counts, e.g. fraction of defectives. For such data the analysis using generalized linear models is preferred to that using the simple regression model. In this paper we introduce the generalized linear model and show how it can be used for the analysis of non-normal data from quality-improvement experiments.

• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.72-85
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• 2002

Advances in computer and sensor technology have made it possible to obtain superlarge manufacturing process data in real time, letting us extract meaningful information from these superlarge data sets. We propose a systematic data analysis procedure which field engineers can apply easily to manufacture quality products. The procedure consists of data cleaning and data analysis stages. Data cleaning stage is to construct a database suitable for statistical analysis from the original superlarge manufacturing process data. In the data analysis stage, we suggest a graphical easy-to-implement approach to extract practical information from the cleaned database. This study will help manufacturing companies to achieve six sigma quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.127-134
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• 2021

Recently, acquisition of high quality data has become an important issue as the expansion of the big data industry. In order to acquiring high quality data, accurate evaluation of data quality should be preceded first. The quality of data can be evaluated through meta-information such as statistics on data, and the task to extract such meta-information is called data profiling. Until now, data profiling software has typically been provided as a component or an additional service of traditional data quality or visualization tools. Hence, it was not suitable for utilizing directly in various environments. To address this problem, this paper presents the development result of data profiling software based on a microservice architecture that can be serviced in various environments. The presented data profiler provides an easy-to-use interface that requests of meta-information can be serviced through the restful API. Also, a proposed data profiler is independent of a specific environment, thus can be integrated efficiently with the various big data platforms or data analysis tools.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.11-18
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• 2010

GNSS(Global Navigation Satellite System) Ground Station performs GNSS signal acquisition and processing. This system generates error correction information and distributes them to GNSS users. GNSS Ground Station consists of sensor station which contains receiver and meteorological sensor, monitoring and control subsystem which monitors and controls sensor station, control center which generates error correction information, and uplink station which transmits correction information to navigation satellites. Monitoring and control subsystem acquires and processes navigation data from sensor station. The processed data is transmitted to GNSS control center. Monitoring and control subsystem consists of data acquisition module, data formatting and archiving module, data error correction module, navigation determination module, independent quality monitoring module, and system maintenance and management module. The independent quality monitoring module inspects navigation signal, data, and measurement. This paper introduces independent quality monitoring and performs the analysis using measurement data.