• Journal of Environmental Science International
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• v.7 no.5
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• pp.591-598
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• 1998

This study was conducted to evaluate water quality in the Keum River estuary using principal component analysis. The results was summarized as follow; Water quality in the Keum River estuary could be explained up to 70.40% by three factors which were included in the inffluent loading by the Keum River and Kyungpo cheon(38.99%), seasonal variation and organic matter pollution(19.05%), sediment resuspension and internal metabolism(12.35%). For spatial variation of factor score, artificial pollutant loading is highest at st.1, below Keum River barrage, and decreases toward the outer sea. For annual variation of factor score, factor 1 was highly related to artificial pollutant leading, and it was gently increased in 1994. Also, organic matter pollution, sediment resuspension and internal metabolism were increased to every year. It is necessary to control the nutrient leading by Keum river and Kyongpo cheon for Water quality management of estuary.

• International Journal of Quality Innovation
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• v.4 no.2
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• pp.16-31
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• 2003

A reducing variation of quality characteristics is a typical example of quality improvement. In such a case, we treat the quality characteristic, as a response variable and need to find active factors affecting the response from many candidate factors since reducing the variation of the response will be achieved by reducing variation of the active factors. In this paper, we first derive a method of selecting an active factor by linear regression. It is well known that correlation between factors deteriorates the precision of estimators. We, therefore, examine robustness of the selecting method against the correlation in the data set and derive an evaluation method of the deterioration brought by the correlation. Furthermore, some examples of selecting and evaluation methods are shown to demonstrate practical usage of the methods.

• Korean journal of food and cookery science
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• v.32 no.3
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• pp.353-362
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• 2016

Purpose: This study examined the influence of restaurant quality attributes on customers' satisfaction and their intention to revisit by investigating the moderating effects of customers' electronic word of mouth evaluation about ethnic restaurants. The study was based on a total of 215 samples obtained from social networking service users in a metropolitan area from July 10 to 25, 2015. The major findings are as follows. Methods: The data were analysed using frequency, factor analysis, regression analysis and hierarchical regression analysis. Results: According to the results of factor analysis, quality attributes were separated into three factors: food, service, and atmosphere. According to the results, food attributes, service attributes and atmosphere attributes had an affect on customers' satisfaction, between quality attributes and revisit intention, only food attribute had an affect on revisit intention. It showed also that customers' satisfaction had an affect on revisit intention. Customers' electronic word of mouth (eWOM) evaluation was found to moderate the relationships between service quality attributes and satisfaction. Conclusion: Implications and future research were also discussed.

• Journal of Korean Society on Water Environment
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• v.23 no.1
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• pp.161-168
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• 2007

The main aim of this work is focus on the Geum river water quality evaluation of pollution data obtained by monitoring measurement during the period 2001-2005. The complex data matrix 19 (entire monitoring stations)*13 (parameters), 60 (month)*13 (parameters) and 20 (season)*13 (parameters) were treated with different multivariate techniques such as factor analysis/principal component analysis (FA/PCA). FA/PCA identified two factor (19*13) classified pollutant Loading factor (BOD, COD, pH, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P, Chl-a), seasonal factor (water temp, SS) and three Factor (60*13, 20*13) classified pollutant Loading factor (BOD, COD, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P), seasonal factor (water temp, SS) and metabolic factor (Chl-a, pH). Loadings of pollutant factor is potent influence main factor in the Geum river which is explained by loadings of pollutant factor at whole sampling stations (71.16%), month (52.75%) and season (56.57%) of main water quality stations. Result of this study is that pollutant loading factor is affected at Gongju 1, 2, Buyeo 1, 2, Gangkyeong, Yeongi stations by entire stations and entire month (Gongju 1, Cheongwon stations), April, May, July and August (buyeo 1) by month. Also the pollutant Loading factor is season gives an influence in winter (Gongju 1, buyeo 1) from main sampling stations, but Cheongwon characteristic is non-seasonal influenced. This study presents necessity and usefulness of multivariate statistic techniques for evaluation and interpretation of large complex data set with a view to get better information data effective management of water sources.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.17-30
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• 2015

Technology-oriented national R&D programs produce intellectual property as their final result. Patents, as typical industrial intellectual property, are therefore considered an important factor when evaluating the outcome of R&D programs. Among the main components of patent evaluation, in particular, the patent right quality is a key component constituting patent value, together with marketability and usability. Current approaches for patent right quality evaluation rely mostly on intrinsic knowledge of patent attorneys, and the recent rapid increase of national R&D patents is making expert-based evaluation costly and time-consuming. Therefore, this study defines a hierarchy of patent right quality and then proposes how to quantify the evaluation process of patent right quality by combining text mining and regression analysis. This study will contribute to understanding of the systemic view of the patent right quality evaluation, as well as be an efficient aid for evaluating patents in R&D program assessment processes.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1995.11a
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• pp.41-47
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• 1995

This research suggests a criterion, security quality, which is a unifying principle in computer network security that has the lack of a unifying principle. The security quality includes secrecy, integrity, recording, and availability among the factors that represent the security evaluation of the computer system. So, we defined the security quality, which is a basis for determining the security level, as the grand total of evaluation about each factor.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.108-116
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• 2010

The maintenance of a deteriorating system is often imperfect. Previous studies have shown that the imperfect preventive maintenance (PM) can reduce the wear out and aging effects of deteriorating systems to a certain level between the conditions of as good as new and as bad as old. In this paper, we employ the concept of the improvement factor in investigating two optimal PM policies; failure limit policy and periodic PM policy. We redefine the improvement factor model as a function of the cost of PM, using this concept, we derive the conditions of optimal PM policies and formulate expressions to compute the expected cost rate. Based on this information, the determination of the maintenance policies which minimize the cost rate is examined. Numerical examples for the Weibull distribution case are also given.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.814-821
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• 2007

This study was estimated water quality to raw water quality management of the Maeri intake station in the Nakdong River using Multivariate Analysis. The results of Principle Component Analysis was explained up to 76.9% of total water quality by three principle components. The 1st, 2nd was explained 44.7%, 17.9% and third was explained 14.3%. Also, the three factors was derived from Factor Analysis. The 1st factor was estimated as the matabolism and organic matter pattern related to algal growth. The 2nd factor was judged as the pollution of pattern related to the discharge from stream of the Nakdong River and 3rd factor was viewed as the hydrological variation pattern related to particle matter. The results of Cluster Analysis were classified into three groups.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.76-84
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• 2002

The conventional database evaluation method is carried out by the way in which the person in charge of each specialty database(DB manager) composes the evaluation sheets for corretionㆍrevision on the already-constructed database in a manual method and carries out the measurement and re-education of DB workers based upon it. As a result, that way consumes much time on career information and measurement works about DB workers, causing low time and cost efficiency and lack of systematic management of DB workers, resulting in becoming the hindrance factor of databases quality improvement. This research provides on-line, red-time results of measurements about the efficiency of DB production and DB workers by combining the static measurement with dynamic measurement by DB manager, both of which utilize the System. Therefore, the DB manager can contribute to the improvement of DB quality by determining the continuation of DB production by DB workers or carrying out the re-education of DB workers without being affected by time or spacial constraints.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.916-925
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• 2018

The academic research performance is often quantitatively measured by means of using citation frequency. The citation frequency-based indicators, such as h-index and impact factor, are commonly used reflecting the citation quality to some extent. However, these frequency-based indicators are usually carried out based on the assumption that all citations are equal. This may lead to biased evaluations in that, the attributes of the citing objects and cited objects are significant. A high-accuracy evaluation method is needed. In this paper, we review various citation quality-based evaluation indicators, and categorize them considering the algorithms being applied. We discuss the pros and cons of these indicators, and compare them from four dimensions. The outcomes will be useful for our further research on distinguishing citation quality.