• 한국환경과학회지
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• 제7권2호
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• pp.171-176
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• 1998

This study was conducted to evaluate water quality utilizing principal component analysis in the Nakdong River Estuary. From the results of analysis, water quality in the Nakdong River Estuary could be explained up to 65.3 Percente by three factors which were Included In river loadlnwastes from the Nakdong River and rainfalls : 39.1%1, sediment resuspension(13.7BS) and metabolism(12.5%). In the eastern part of estuary In flowing the Nakdong River, river loading factor score(factor 1 Pas higher than that In western part. Sediment resuspension factor score(factor 2) was high in shallow water, while metabolism factor score(factor 3) was high in deeper water. For seasonal variations of factors score, factor 1 was h19h- 1y related to rainfall season.

• 품질경영학회지
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• 제21권2호
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• pp.121-130
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• 1993

In this paper, we relate the reliability of the system to the reliabilities of the components or subsystems. We discussed the basic concept of system reliability and present a method to determine probabilities of failure of coherent system components under various conditions, especially forcused on probability of component or subsystem failure before system failure. Several examples illustrate the procedure.

• 품질경영학회지
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• 제17권1호
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• pp.1-10
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• 1989

In general, the characteristics of components which consist of multi-component system can not be the same. This paper proposes a maintenance model of multi-component system considering the characteristics of each component. In this paper, multi-component system is divided into three components-critical unit, major unit and minor unit, respectively. This paper determines the optimal replacement time of the system which minimizes total maintenance cost, optimal replacement period of major unit and initial stock quantity of minor unit within this optimal replacement time. Numerical examples are shown when the failure times of each unit have gamma distribution.

• Asian Pacific Journal of Cancer Prevention
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• 제15권2호
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• pp.695-701
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• 2014

The main objective of palliative treatment for cancer patients has been to maintain, if not improve, the quality of life (QoL). There is a lack of local data on satisfaction and QoL among cancer patients receiving palliative treatment in Malaysia. This study covers patients with incurable, progressive cancer disease receiving palliative treatment in a teaching hospital in Kuala Lumpur, comparing the different components of QoL and correlations with patient satisfaction. A cross-sectional survey using Malay validated SF36 QoL and PSQ-18 (Short Form) tools was carried out between July 2012 -January 2013 with 120 cancer patients receiving palliative treatment, recruited into the study after informed consent using convenient sampling. Results showed that highest satisfaction were observed in Communication Aspect ($50.6{\pm}9.07$) and the least in General Satisfaction ($26.4{\pm}5.90$). The Mental Component Summary ($44.9{\pm}6.84$) scored higher when compared with the Physical Component Summary ($42.2{\pm}7.91$). In this study, we found that patient satisfaction was strongly associated with good quality of life among cancer patients from a general satisfaction aspect (r=0.232). A poor significant negative correlation was found in Physical Component (technical quality, r=-0.312). The Mental Component showed there was a poor negative correlation between time spent with doctor (r=-0.192) and accessibility, (r=-0.279). We found that feeling at peace and having a sense of meaning in life were more important to patients than being active or achieving good physical comfort. More studyis needed to investigate patients who score poorly on physical and mental component aspects to understand their needs in order to achieve better cancer care.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.349-357
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• 2005

Principal component analysis(PCA) was carried out to evaluate the water quality with the monitering data collected from 1997 to 2003 along the coastal area of Ulsan, Korea. To enhance evaluation and to complement descriptive power of traditional PCA, optimal scaling was applied to transform the original data into optimally scaled data. Cluster analysis was also applied to classify the monitering stations according to their characteristics of water quality.

• Environmental Engineering Research
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• 제19권3호
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• pp.197-203
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• 2014

This study estimated spatial and seasonal variation of water quality to understand characteristics of Nakdong river basin, Korea. All together 11 parameters (discharge, water temperature, dissolved oxygen, 5-day biochemical oxygen demand, chemical oxygen demand, pH, suspended solids, electrical conductivity, total nitrogen, total phosphorus, and total organic carbon) at 22 different sites for the period of 2003-2011 were analyzed using multivariate statistical techniques (cluster analysis, principal component analysis and factor analysis). Hierarchical cluster analysis grouped whole river basin into three zones, i.e., relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) based on similarity of water quality characteristics. The results of factor analysis/principal component analysis explained up to 83.0%, 81.7% and 82.7% of total variance in water quality data of LP, MP, and HP zones, respectively. The rotated components of PCA obtained from factor analysis indicate that the parameters responsible for water quality variations were mainly related to discharge and total pollution loads (non-point pollution source) in LP, MP and HP areas; organic and nutrient pollution in LP and HP zones; and temperature, DO and TN in LP zone. This study demonstrates the usefulness of multivariate statistical techniques for analysis and interpretation of multi-parameter, multi-location and multi-year data sets.

• Advances in environmental research
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• 제6권1호
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• pp.53-65
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• 2017

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of river pollution due to natural or anthropogenic inputs of point and non-point sources. In this study, surface water quality data for 15 physico-chemical parameters collected from 7 monitoring stations in a river during the years from 2014 to 2016 were analyzed. The principal component analysis technique was employed to evaluate the seasonal correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing seasonal variations of river water quality. Analysis shows that a parameter that is most important in contributing to water quality variation for one season may not be important for another season except alkalinity, which is always the most important parameters in contributing to water quality variations for all three seasons.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권7_8호
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• pp.618-641
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• 2003

소프트웨어 제품의 품질을 평가하기 위한 방법으로써 품질 요소, 품질 항목 및 여러 가지 메트릭을 이용한 품질 모델들이 제시되어 왔다. 하지만, 소프트웨어의 품질을 보다 정확하게 평가하기 위해서는 각각의 특징에 맞는 특화된 모델이 필요하다. 본 논문에서는 소프트웨어 컴포넌트 개발에 있어서 개발이 진행중인 상태의 소프트웨어 내부 속성에 적절한 메트릭을 적용시킨 결과를 이용하여 개발 완료 후의 소프트웨어가 가지게 되는 외부 품질을 어떻게 추정하는지에 대한 외부 품질 추정 모델을 제시한다. 소프트웨어 품질을 측정하기 위한 메트릭을 적용한 결과로써 품질 자체를 측정하는데 한정하지 않고, ISO 9126에서 제시하는 소프트웨어의 내부 속성을 이용하여 소프트웨어 컴포넌트 개발의 각 산출물에 어떻게 적용시키는지에 대한 모델을 예제를 통하여 제시한다.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2189-2196
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• 2015

Stereo matching algorithm is usually used to obtain a disparity map from a pair of images. However, the disparity map obtained by using stereo matching contains lots of noise and error regions. In this paper, we propose a virtual-view synthesis algorithm using disparity refinement in order to improve the quality of the synthesized image. First, the error region is detected by examining the consistency of the disparity maps. Then, motion information is acquired by applying optical flow to texture component of the image in order to improve the performance. Then, the occlusion region is found using optical flow on the texture component of the image in order to improve the performance of the optical flow. The refined disparity map is finally used for the synthesis of the virtual view image. The experimental results show that the proposed algorithm improves the quality of the generated virtual-view.

• 한국물환경학회지
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• 제35권1호
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• pp.19-27
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• 2019

The purpose of this study is to evaluate the water quality and phytoplankton community in Bukhan River which account for 44.4 % of the total inflow into Lake Paldang, using multivariate statistical techniques (i.e., correlation analysis, principal component analysis (PCA)/factor analysis (FA)). Water samples were collected from March to November 2015 and the following parameters measured; water temperature, pH, DO, EC, SS, BOD, Chl-a, COD, TN, $NO_3-N$, $NH_3-N$, TP, DTP, $PO_4-P$, and phytoplankton community. The water quality of the main stream and the tributaries were not significantly different apart from the relatively high concentration of BOD, COD and nutrients recorded in MH. The highest cell density of Stephanodiscus hantzschii and Merismopedia glauca dominated phytoplankton was observed in PD. Based on the correlation analysis, total phytoplankton and cyanophyceae were highly correlated with BOD, COD and nutrients. PCA/FA resulted in four main factors accounting for 82.240 % of the total variance in the water quality dataset. The group of component 1 (TN, DTN, DO, $NO_3-N$, water temperature) and component 2 ($PO_4-P$, T-P, DTP, SS) were classified as nutrient element factor whereas component 3 (Chl-a, COD, BOD, $NH_3-N$, pH) was related to organic substances. Hence, the identification of the main potential environmental pollution factors in Bukhan River will help policy makers make better and more informed decisions on how to improve the water quality.