• Membrane and Water Treatment
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• v.13 no.5
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• pp.245-257
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• 2022

Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.

• IE interfaces
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• v.21 no.2
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• pp.237-246
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• 2008

In today's competitive global environment, technological innovation is an important issue. Many countries are devising national level strategies to further strengthen industrial capacity in support of innovative companies. South Korea is no exception, and multiple strategies are in place to aid innovative development in the private sector. This study postulates that such national level strategies are applied differently depending on the innovation goal pursued by the service sector in Korea. We use data mining methods to test such research hypothesis. Factor analysis is used for clustering of various service companies, while association rule is used in finding the relationship per each cluster. The results show that national level strategies are underutilized and unequally distributed. This may be attributed to the disparity between the demand and needs of the private sector and the opinion of the government, which lead to underutilized and indistinguishable strategies.

• Proceedings of the ESK Conference
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• 1993.04a
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• pp.64-68
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• 1993

The idia of modern product design is translated from the concept of functional importance as the basic function to that of emotional importance as the supplement function. In other words, the interests of the emotion in human performance side based on psychological factors of human are increased as well as the function in technical performance side based on physical factors of product. The standard emotional works for understanding the human's emotion are arranged in this paper. The standard emotional words are composed of words expressing the humaa's emotion. The adjectives adaptable to human's emotional works are collected from Korean dictionaries and arranged in the semantic differential(SD) scale. Next, the words with great marks evaluated by SD method are analyzed by factor analysis(FA) method and characterized as emotional words for understanding the human's emotion. The standard emotional words arranged in this paper are important because they are basic information for the development of product or technology as well as for the matter of emotional measurement technical development.

• Journal of Environmental Science International
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• v.24 no.6
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• pp.743-753
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• 2015

In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and $COD_{Mn}$ (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable $BOD_5$ and $COD_{Mn}$. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).

• Journal of Digital Convergence
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• v.11 no.8
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• pp.119-125
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• 2013

The Recently many companies have tried to implement the Business Intelligence (BI) system to enhance the competitive edge in the rapid change of business environment. The BI system is implemented on the basis of current Management Information System, like Enterprise Resource Planning (ERP) system. For the successful implementation of BI system, many critical factors, like maturity and satisfaction level of current Information System, should be considered. The goal of this paper is to analyze which factors influence on the implementation intention of BI system, and how is the relationship among these factors. To achieve this goal, the empirical research has been carried out with factor analysis and Structural Equation Model (SEM). The result of this paper could be usefully referred in decision making process for the successful implementation of the BI system, and show the guideline to the management of the companies, which have the plan for the implementation of BI system.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.454-462
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• 2014

Retention of possible churning customer is one of the most important issues in customer relationship management, so companies try to predict churn customers using their large-scale high-dimensional data. This study focuses on dealing with large data sets by reducing the dimensionality. By using six different dimension reduction methods-Principal Component Analysis (PCA), factor analysis (FA), locally linear embedding (LLE), local tangent space alignment (LTSA), locally preserving projections (LPP), and deep auto-encoder-our experiments apply each dimension reduction method to the training data, build a classification model using the mapped data and then measure the performance using hit rate to compare the dimension reduction methods. In the result, PCA shows good performance despite its simplicity, and the deep auto-encoder gives the best overall performance. These results can be explained by the characteristics of the churn prediction data that is highly correlated and overlapped over the classes. We also proposed a simple out-of-sample extension method for the nonlinear dimension reduction methods, LLE and LTSA, utilizing the characteristic of the data.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.353-366
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• 2018

The purpose of this study was assessment the quality of water by using the statistical analysis technique of the Water flow and water quality from January 2012 to December 2016 at the unit basin for total pollutant load management system (TPLMS) in the Imjin River. Water flow and water quality were monitored at an average of 8 day intervals, 11 parameters were used for correlation analysis, principal component analysis (PCA), factor analysis (FA), and cluster analysis (CA). The Hierarchical CA was classified into three according to the change of space, such as natural rivers, urban rivers, point with large influence of point pollution source, it was found that the type of contamination source the similarity of water quality affected the classification of cluster. Using one-way analysis of variance (ANOVA) and post-hoc Analysis, there were statistically significant differences between mean values among the clusters. Correlation analysis showed the correlation coefficient between $COD_{Mn}$ and TOC was 0.951 (p<0.01) and the correlation was statistically significantly higher. According to the result PCA and FA, 3 principal components can explaining 72% of the total variations in water quality characteristics and main factor was EC, $BOD_5$, $COD_{Mn}$, TN, TP and TOC indirect indicators of organic matter and nutrients were influenced. This study presented the regression equation obtained by applying the factor scores to the multiple linear regression analysis and concluded that the management Indirect indicators of organic matter and nutrients is important for water quality management in the Imjin River basin.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.263-288
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• 2012

This study aims to define which factors will contribute to vitalization of Saemangeum New Port to secure international competitiveness in order to attract international shipping companies, shippers and forwarders in constructing Saemangeum New Port, and to propose subsequent implications. For research methods of the current study, a factor analysis and a decision making method of analytic hierarchy process(AHP) were used. Through precedent studies, total 11 measuring variables were selected including short entrance and exit channels, main infrastructure development project, tax cut and deregulation, and through a factor analysis, total 3 high rank evaluation factors including 'location and facilities', 'surrounding infrastructure and hydrophile property', and 'local policy and environment'. Analysis results summarizing a test of reliability of measuring variables in this study indicate that as Cronbach alpha coefficient of total 11 measuring variables were turned out to be over 0.8, it is surpassing general average 0.6, which means there is reliability.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.159-178
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• 2012

Recently, Global network expansion strategy of GTOs(Global Terminal Operator) coupled with each country's port policy, plays huge role for the evolution of modern container port. The Chinese ports can be regarded as the major markets to the GTOs. However, there are scant of researches for finding the key success factors of GTOs' strategies when they consider to invest in overseas. In this respect, the aims of this study were to draw out the evaluation variables for successful investment strategies of GTOs, and to calculate the selected target ports. The 14 variables are selected including the variable named 'development potentiality of a port' through literature reviews. Using the Factor Analysis (FA) based on selected variables, four principal factors were extracted such as 'ability for port operating and cargo generating', 'the trade route and volume', 'the calling potentiality for large vessels' and 'the possibility of utilization of existing infrastructure'. In addition, the weights of factors and variables are evaluated through Fuzzy AHP method. As a result, 'ability for port operating and cargo generating' is chosen as the most important factor among principal factors as scored 0.343, and 'the development potentiality of a port' (0.107) is represented as the most important variable among 14 detailed variables. In overall, from the Global Terminal Operator's point of view, Shanghai is ranked as most suitable port for operating new terminal among the top 5 Chinese ports.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2583-2589
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• 2013

Purpose: Studies have indicated that diabetes mellitus (DM) is a risk factor for bladder cancer; however, not all evidence supports this conclusion. The aim of this meta-analysis was to collate and evaluate all primary observational studies investigating the risk of bladder cancer associated with DM. Methods: The PubMed and Google Scholar databases were searched to identify studies that estimated the association of DM and bladder cancer. Summary effect estimates were derived using a random-effects meta-analysis model. Results: A total of 23 studies (8 case-control studies, 15 cohort studies) including 643,683 DM and 4,819,656 non-DM cases were identified. Analysis of all studies showed that DM was associated with an increased risk of bladder cancer compared with non-DM overall (OR=1.68, 95% CI 1.32-2.13). Analysis of subgroups demonstrated this to be the case in both case-control studies (OR=1.59, 95% CI 1.28-1.97, $I^2$=58%) and cohort studies (RR=1.70, 95% CI 1.23-2.33, $I^2$=96%). There was no gender difference in DM-associated bladder cancer risk. Bladder cancer risk was increased in Asia and the North America region, but not in Europe. Furthermore, DM-associated bladder cancer risk was obviously higher in Asia than North America and Europe or in those with Caucasian ethnicity. With extension of follow-up time, the bladder cancer risk was not increased for the patients with DM. Conclusions: This meta-analysis provided further evidence supporting theDM association with a significantly higher risk of bladder cancer obtained from observational studies.