• Journal of Korean Society for Quality Management
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• v.12 no.2
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• pp.11-14
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• 1984

Some statistics are presented for construction of confidence intervals of variance components for the unbalanced twofold nested classification model and they are shown to be approximated by chi-square distributions.

• Korean Management Science Review
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• v.24 no.1
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• pp.147-160
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• 2007

Six Sigma's concept has long been used as an effective way of restructuring the management process of a firm. In literature regarding Six Sigma, a number of successful cases were reported, where Six Sigma based management activities could enhance firm's strategic performance dramatically for year. However, there exist very few researches investigating the effect of Six Sigma on process innovation and quality improvement. Therefore this study propose a research model testing whether Six Sigma innovation could improve process innovation and quality improvement by industrial classification. We collected 332 valid questionnaires from expert in Six Sigma activities, and applied PLS. Empirical results showed that Six Sigma activities could contribute to process innovation and quality improvement.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.126-139
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• 1995

We describe a formal approach to the construction of optimal classification rule for the two-group normal classification with equal population mean problem. Based on the utility function of Bernardo, we suggest a balanced design for the classification and construct the optimal rule under the balanced design condition. The rule is characterized by a constrained minimization of total risk of misclassification, the constraint of which is constructed by the process of equation between expected utilities of the two group conditional densities. The efficacy of the suggested rule is examined through numerical studies. This indicates that, in case little is known about the relative population sizes, dramatic gains in accuracy of classification result can be achieved.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.709-716
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• 2017

Purpose: NCS(National Competency Standards) is a systematic organization of knowledge, skills, and literacy required for performing tasks in industrial settings. This research aims to search for keywords that are important to us and to present key directions of education for the fourth industrial age in the future. Methods: The systematic classification system of NCS was investigated and the classification code structure was analyzed. Among them, the frame and structure analysis of the classification code of quality was analyzed using R-program. Results: This study grasped the quality classification situation of NCS and suggested improvement plan from the operational aspect of the fourth industrial revolution era. Conclusion: In conclusion, this study suggested the idea of education direction of SMEs(Small and Medium-sized Enterprises) in the era of the 4th industrial revolution by understanding NCS which reflects Korean characteristics.

• The Journal of Bigdata
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• v.3 no.2
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• pp.11-18
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• 2018

This study is a study on domain automatic classification for domain - based quality diagnosis which is a key element of big data quality diagnosis. With the increase of the value and utilization of Big Data and the rise of the Fourth Industrial Revolution, the world is making efforts to create new value by utilizing big data in various fields converged with IT such as law, medical, and finance. However, analysis based on low-reliability data results in critical problems in both the process and the result, and it is also difficult to believe that judgments based on the analysis results. Although the need of highly reliable data has also increased, research on the quality of data and its results have been insufficient. The purpose of this study is to shorten the work time to automizing the domain classification work which was performed from manually to using machine learning in the domain - based quality diagnosis, which is a key element of diagnostic evaluation for improving data quality. Extracts information about the characteristics of the data that is stored in the database and identifies the domain, and then featurize it, and automizes the domain classification using machine learning. We will use it for big data quality diagnosis and contribute to quality improvement.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1491-1499
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• 2019

Insufficient sleep time and bad sleep quality causes many illnesses and it's research became more and more important. The most common method for measuring sleep quality is the polysomnography(PSG). The PSG is a test used to diagnose sleep disorders. The most common PSG data is obtained from the examiner, which attaches several sensors on a body and takes sleep overnight. However, most of the sleep stage classification in PSG are low accuracy of the classification. In this paper, we have studied algorithm for sleep level classification based on machine learning which can replace PSG. EEG, EOG, and EMG channel signals are studied and tested by using CNN algorithm. In order to compensate the performance, a mixed model using both CNN and DNN models is designed and tested for performance.

• Journal of Korean Society on Water Environment
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• v.29 no.4
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• pp.504-513
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• 2013

Water quality trends for major tributaries (66 sites) in the Yeongsan River basin of Korea were examined for 12 parameters based on water quality data collected every month over a period of 12 months. The complex data matrix was treated with multivariate analysis such as PCA, FA and CA. PCA/FA identified four factors, which are responsible for the structure explaining 78.2% of the total variance. The first factor accounting 27.3% of the total variance was correlated with BOD, TN, TP, and TOC, and weighting values were allowed to these parameters for grade classification. CA rendered a dendrogram, where monitoring sites were grouped into 5 clusters. Cluster 2 corresponds to high pollution from domestic wastewater, wastewater treatment and run-off from livestock farms. For grade classification of tributaries, scores to 10 indexes were calculated considering the weighting values to 3 parameters as BOD, TN and TP which were categorized as the first factor after FA. The highest-polluted group included 10 tributaries such as Gwangjucheon, Jangsucheon, Daejeoncheon, Gamjungcheon, Yeongsancheon. The results indicate that grade classification method suggested in this study is useful in reliable classification of tributaries in the study area.

• Water Engineering Research
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• v.3 no.4
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• pp.259-267
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• 2002

South Africa has developed a policy and law that calls and provides for the equitable and sustainable use of water resources. Sustainable resource use is dependent on effective resource protection. Rivers are the most important freshwater resources in the country, and there is a focus on developing and applying methods to quantify what rivers need in terms of flow and water quality. These quantified and descriptive objectives are then related to specified levels of ecological health in a classification system. This paper provides an overview of an integrated and systematic methodology, where, fer each river, and each river reach, the natural condition and the present ecological condition are described, and a level/class of ecosystem health is selected. The class will define long term management goals. This procedure requires each ecosystem component to be quantified, starting with the abiotic template. A modified flow regime is modelled for each ecosystem health class, and the resultant fluvial geomorphology and hydraulic habitats are described. Then the water chemistry is described, and the water quality changes that are likely to occur as a consequence of altered flows are predicted. Finally, the responses to the stress imposed on the biota (fish, invertebrates and vegetation) by modified flow and water quality are predicted. All of the predicted responses are translated into descriptive and/or quantitative management objectives. The paper concludes with the recognition of active method development, and the enormous challenge of applying the methods, implementing the law, and achieving river protection and sustainable resource-use.

• Journal of Soil and Groundwater Environment
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• v.18 no.2
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• pp.19-26
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• 2013

This study developed the classification of National Soil Quality Monitoring Network (NSQM) and its site selection criteria to meet the recently established purposes of the NSQM. The NSQM were suggested by this study to classify into the six-purposes site groups from the current classification of land uses. The six purposes site groups were 1) intensive observation sites, 2) contaminant loading sites, 3) human activity sites, 4) background sites, 5) river soil sites, and 6) sites near the groundwater quality monitoring wells. Furthermore, this study developed the site selection criteria of NSQM utilizing the accumulated NSQM data, road traffic data, chemical emission data, census, soil information, and the literature related to soil quality variation due to contaminant loads. For selecting suitable sites for NSQM, this study used road traffic, chemical emission, the distance from the contaminant sources, and population information as specific criteria. The suggested site classification and criteria were appled for the current 100 NSQM sites for evaluation. Forty sites were met to the criteria suggested by this study, but sixty sites were not met to the criteria. However, some of the sixty sites also included the obscure sites that their addresses were not apparent to find them.

• Journal of the Korea Safety Management & Science
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• v.19 no.4
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• pp.221-230
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• 2017

Recently, service quality must reflect several demands of customers who show rapid and various changes so as to be compared with the past. So, objective and rapid methods for them are necessary more. For them, first of all, service company must calculate their standard of service quality accurately by measuring service quality exactly. To measure service quality accurately, this researcher collected and analyzed data by survey for customers who are customers of logistics services, grasped potential satisfaction standard(P) by 5 point Likert scale and one survey for accurate classification of quality attributes through weighted customer satisfaction coefficient changing quality attributes by developing the study on Kano model and Timko's customer satisfaction coefficient, and suggested Potential Customer Satisfaction Improvement index(PCSI) for examining the improvement of customer satisfaction so as to utilize them as an index of differentiated and concrete measurement of service quality.