• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.84-93
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• 2012

The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• Journal of Fashion Business
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• v.15 no.1
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• pp.145-157
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• 2011

The purposes of this study were to investigate the impacts of empowerment, job satisfaction, and organizational commitment on service quality. So, this research attempted to test the hypothesized relationships between service quality and its determinants such as job satisfaction, organizational commitment, and customer orientation. To measure these hypotheses, total 200 questionnaires were handed out and 185 were collected. Finally 163 questionnaires were used for the analysis, while 22 were found to be invalid. The frequency analysis, factor analysis, reliability analysis, and multiple regression were conducted after coding and cleaning by SPSS 18.0 The result of this study are as follow. As a result of multiple regression, it shows that empowerment have an effect on job satisfaction, organizational commitment, and service quality. And it shows that job satisfaction and organizational commitment have an effect on service quality.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.444-448
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• 2007

The purpose of this research is to test the effects of employee perceived job characteristics on service quality. Empirical analysis was based on the data of 692 hotel employees from Seoul and Gyung-gi province. To test the relationship between job characteristics and service quality, multiple regression analysis was applied, and hierarchial regression analysis(Cohen & Cohen, 1983) applied to test the moderating effects of gender and tenure. Multiple regressional analysis showed that job importance, job variety, and feedback had an affirmative impact on tangibility, reliability, responsiveness, assurance, empathy, but autonomy had a negative impact on tangibility, reliability, responsiveness, assurance.

• Bulletin of the Korean Chemical Society
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• v.29 no.7
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• pp.1391-1394
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• 2008

Polymer materials are very difficult to decompose for the purpose of chemical analysis. Nondestructive analysis without pretreatment provides a suitable solution that will overcome this obstacle. In this study, CRM candidate samples that contained toxic elements such as As, Cd, Cr and Zn in a polypropylene (PP) were analyzed using instrumental neutron activation analysis (INAA). The analytical results were obtained from ten samples selected by random sampling at two different concentration levels (low and high). Particular attention was paid to reducing analytical errors and evaluating the associated uncertainty.

• 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.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.21-25
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• 2014

Now, almost enterprise is applying data analysis method using the information systems on based information technology. The data analysis is focusing on the Quality of the data affecting the decision-making of various companies. This is the result of the data quality is due to the important role in the various parts as well as the effective operation of the enterprise. In this study, we describe about the data quality assessment models that are currently being studied. Based on this, we describe about the adaptive DQnA model being utilized for data quality analysis, and discuss about the quality analysis using this method.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.127-130
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• 2002

Recently, with the increasing use of power semiconductors and microprocessors which are very sensitive to little change of power quality and for coping positively with anticipating power quality disputes between power providers and consumers which are possible to occur by of power market being formed, the power quality problem has gained preponderance among the contemporary research areas. To serve these purposes, the integrated system has been researched and developed for power quality analysis and monitoring, which provides speedy and powerful functions by the growth of computer hardware and information technology. But the advent of fast and lower price hardware make little difference in an application on many systems. As a result, the key issues of constructing power quality monitoring system are in the management of data obtained, accurate algorithms, graphic representation and user-friendly-environment for easy and clear analysis results. So, in this paper it will be introduced that the standard of user-friendly-GUI(Graphic User Interface) and analysis graphic representation for intuitive understanding of results from power quality analysis based on consideration of several systems currently being in use.

• Journal of the Korea Safety Management & Science
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• v.14 no.2
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• pp.193-204
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• 2012

This paper deals with an empirical analysis of the structural relationship among the factors such as quality management activities, organizational learning and firm performance of manufacturing corporations. The findings of the analysis are expected to make lots of contribution to manufacturing corporations establishing strategies for quality management activities and organizational learning. From the analysis, following conclusions and suggestions could be drawn: First, an analysis of the relationship between quality management activities and organizational learning showed that most activities of quality management turned out to exercise great influence upon the factors of organizational learning. This means that the activities of quality management will prompt the members of an organization to actively engage in learning activities individually, by team and organizationally, motivating them to spread such activities across the whole organization, leading ultimately to fundamental renovation of the very organization. Second, from an analysis of the relationship between organizational learning and firm performance, that is, financial and non-financial performances of a company, it was found that most factors of organizational learning have tremendous impact upon financial and non-financial performances of the company. Such result implies that decision and management of the things to be performed in the process of organizational performances are essential to determining firm performance because firm performance depend largely on the outcomes of organizational learning.