• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.289-296
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• 2001

This paper proposes multivariate control chart for autocorrelated data which are common in chemical and process industries and lead to increase in the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a vector autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and therefore the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and Monte Carlo simulation is conducted to investigate the performances of the proposed control charts.

• Environmental Engineering Research
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• v.19 no.3
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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.

• 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.

• Journal of Environmental Science International
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• v.13 no.3
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• pp.233-244
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• 2004

This study was conducted to evaluate water quality in the Mankyung River using multivariate analysis. The analysis data which was surveyed from January 1996 to December 2002 in Mankyung river was aquired by the ministry of environment. Twelve water quality parameters were determined on each survey. The results were summarized as follow; Water quality in the Mankyung River could be explained up to 74.90% by four factors which were included in loading of organic matter and nutrients by the tributaries(43.28%), seasonal variation(10.40%), loading of pathogenic bacteria by domestic sewage of Gapcheon (12.41%) and internal metabolism in river(8.81%). The result of cluster analysis by station was classified into three group that has different water quality characteristics. Especially, Iksan river was appeared to considerable water quality characteristics against other station. In monthly cluster analysis, three group was classified by seasonal characteristics. Also, in yearly cluster analysis, three group was classified. It is necessary to control the pollutant loadings by domestic sewage and livestock waste for water quality management of Mankyung river.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.301-309
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• 2009

Multidimensional scaling(MDS) is a statistical multivariate analysis technique that is often used in information visualization for exploring similarities or dissimilarities in data. In order to analyse and visualize data, MDS measures the dissimilarities between objects and uses them or their mean if they are repeatedly measured. When there exist outliers or when the variation of data is too large, we can hardly get reliable results on the research using MDS. In this paper, we consider the MDS based on bootstrap method when the variation of data is large. Standardized residual sum of squares is considered as measuring goodness-of-fit of the model. A real data analysis is include to examine our approach.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.295-300
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• 1998

Recently graphical modelling is being studied as a useful process analysis tool for exploratory causal analysis. Graphical modelling is a presentation method that uses graphs to describe statistical models of the structures of multivariate data. This paper describes an application of this graphical modeling with two cases from the automotive parts industry. One case is the unbalance problem of the pulley, an automotive generator part. There is multivariate data of the product from each of the processes which are connected in the series. By means of exploratory causal analysis between the variables using graphical modeling, the key processes which causes the variation of the final characteristics and their mechanism of the causal relationship have become clear. Another case is, also, the unbalanced problem of automotive starter parts which consists of many parts and is manufactured by complex machinery and assembling process. By means of the similar technique, the key processes are obtained easily and the results are reasonable from technical knowledge.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.71-71
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• 2017

Stable stand establishment is pre-requisite in direct rice seeding system for obtaining optimal yield of rice crop in rain-fed and waterlogged areas. Anaerobic condition on waterlogged soil causes low germination which significantly reduces crop yield. Due to low availability of tolerant genetic material for anaerobic germination, there is urgent need to evaluate rice germplasm for better germinability under anaerobic conditions. Seeds of the 185 rice accessions were evaluated for germination vigor and coleoptile length under anaerobic conditions. The variation among germplasm was tested for significance using analysis of variance and various multivariate components. Significant level of variation was observed among all accessions for germination vigor and coleoptiles length. Although highest mean values for coleoptiles length (2.1cm) and germination rate (60%) were observed in japonica accessions but maximum coleoptile length (4.68cm) and germination rate (96%) was found in indica genotype CO18. A highly significant and positive correlation was also observed between germination vigor and coleoptiles length, which signify the importance of elongated coleoptile under anaerobic conditions. The PCA analysis illustrated that 97.24% variation was accounted by PC1 while PC2 and PC3 explained 2.54% and 0.24% variation for germination vigor and coleoptile length. PCA scattered plot divided the accessions in four various groups. All AG tolerant accessions were included in group I. Likewise in the case of cluster analysis, two major clades (I and II) were formed. All accessions showing >40% germination rate were included in clade I, whereas all other accessions with <40% germination rate were grouped in clade II. Further more highly tolerant accessions (>80% germination) were grouped in sub-cluster IA.

• Korean journal of applied entomology
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• v.34 no.1
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• pp.1-8
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• 1995

The relationships between aphids, plants, other organisms and some physical components of the environment are reviewed. Aspects considered include year cycles, polymorphism fecundity, relationship of different groups of aphids with particular groups of plants, honeydew, alarm pheromones, aposematic colouring, camouflage, colour variation within species, morphological variation within species, multivariate analysis and problems of its interpretation, parasitism, stridulating mechanisms, predators, coevolution of plants and aphids, plant galls, trapping aphids and the interpretation of trap catches, an curation of aphid collections. References are given to sources of information about aphids, with special reference to the Korean fauna.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.191-200
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• 2007

This paper introduces a tool for predicting potential cost overrun during project execution and for quantifying the uncertainty on the expected project cost, which is occasionally changed by the unknown effects resulted from project's complications and unforeseen environments. The model proposed in this stuff is useful in diagnosing cost performance as a project progresses and in monitoring the changes of the uncertainty as indicators for a warning signal. This model is intended for the use by project managers who forecast the change of the uncertainty and its magnitude. The paper presents a mathematical approach for modifying the costs of incomplete work packages and project cost, and quantifying reduced uncertainties at a consistent confidence level as actual cost information of an ongoing project is obtained. Furthermore, this approach addresses the effects of actual informed data of completed work packages on the re-estimates of incomplete work packages and describes the impacts on the variation of the uncertainty for the expected project cost incorporating Multivariate Probabilistic Analysis (MPA) and Bayes' Theorem. For the illustration purpose, the Introduced model has employed an example construction project. The results are analyzed to demonstrate the use of the model and illustrate its capabilities.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.303-303
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• 2022

The purpose of this study was to evaluate agronomic characteristics and identify the useful traits to utilize the wheat genetic resources for breeding programs by understanding the phenotypic variation among germplasm through multivariate analysis. In this study, a total of 394 wheat accessions were characterized for 15 agronomic traits using the National Agrobiodiversity Center (NAC) descriptor list, of which 31 accessions from 6 species and 363 unidentified accession (Triticum spp.) available at the NAC, Rural Development Administration (RDA), Korea. Growth characteristics such as leaf width, culm length, spike length, spikelet length, solid stemmed, days to heading, days to maturity, grain-filing period, and also seed characteristics such as width, height, area, perimeter, circle, solidity, and germination percent were studied. Among the 15 agronomic characteristics, the germination percent showed the smallest variation between resources (CV = 0.4%), and the spikelet length (CV = 66.5%) showed the highest variation. A strong positive correlation was found between seed traits such as seed height and seed area (r = 0.90), seed height and seed perimeter (r = 0.87) and seed length and width (r = 0.80). Principal component analysis (PCA) was conducted and the first five principal components comprised 76.7% of the total variance. Among the first five PCs, PCI accounted for 28.5% and PC2 for 20.0%. Wheat resources (394) were classified into four clusters based on cluster analysis, consisting of 215 resources(I), 117 resources(II), 48 resources(III), and 14 resources(IV). Among the clusters, the resources belonging to Cluster III showed the lowest seed width, height, area, and perimeter characteristics compared to other clusters. The wheat resources belonging to cluster IV had small seed width and low germination percent, but took longer to form heads and mature than resources in other clusters. These results will serve as the basis for further genetic diversity studies, and important agronomic characteristics will be used for improving wheat, including developing high-yielding and resistant varieties to biotic and abiotic stresses via breeding programs.