• The Journal of Fisheries Business Administration
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• v.15 no.1
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• pp.58-80
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• 1984

The classification of islands is prerequisite for establishing a development policy to vitalize many-sided function of islands. We try to classify the 440 inhabited islands which exist in Jeon-Nam area and Kyong-Nam area by means of PCA. PCA begins with making correlation matrix of orignal variables. From this matrix we can comprehend the rough relationships between two variables. Next, we look for the eigenvalues which are roots of characteristic equation of correlation matrix. The number of eigenvalues is equal to that of original variables. We choose the largest eigenvalue λ$_1$among them and then look for the eigenvector of correlation matrix corresponding to the largest eigenvalue. Linear combination of eigenvector obtained above and original variables is namely first Principal Component (PC). Using an eigenvalue criterion(λ$\geq$ 1), we choose 3 PCs in Jeon-Nam area and 2 PCs in Kyong-Nam area. But we decide to consider only two PCs in both areas to faciliate a comparative analysis. Now, loss of information is 31.7% in Jeon-Nam area and 26.64% in Kyong-Nam area. PCs extracted by preceding procedure have characteristics as follows. The first PC relates to aggregate size of islands in case of both areas. The second PC relates to income per household, factors of agricultural production and factors of fisheries production in Jeon-Nam area, but in Kyong-Nam area it means distance from island and income per household. A classification of islands can be attained by plotting component scores of each island in graph used two PCs as axes and grouping similiar islands. 6 groups are formed in Jeon-Nam area and 5 groups in Kyong-Nam area. The result of this study in kyong-Nam area accords with prior result of study.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.87-95
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• 1999

The min object of this study was to prove the effectiveness of PCA(principal component analysis) merged images produced by PCA method using high resolution IRS-1C PAN data and multispectral Landsat TM data A sample data which has ten classes was generated for evaluation of the overall classification accuracy. In result, merged sample image which TM13457 bands with IRS-1C PAN data by PCA method showed best result (95.1%). Especially, the largest improve (6.2%) in classification accuracy was resulted when IRS-1C PAN data was merged with TM123457 or TM13457 images. In addition, landuse classification accuracy of the PCA merged images was improved (5.16%) than original color composite images of Landsat TM data.

• Journal of Environmental Science International
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• v.32 no.4
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• pp.243-257
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• 2023

This study was conducted to investigate the distribution characteristics, source identification, and health risk of polycyclic aromatic hydrocarbons (PAHs) present in particulate matter 10 (PM-10), in Gwangju. PM-10 samples were collected from September 2021 to August 2022 from three sampling sites, one located in each of the following areas: green, residential, and industrial. The average concentrations of PAHs were found to be higher in the industrial area (9.75±6.51 ng/㎥) than in the green (6.90±2.41 ng/㎥) and residential (6.74±2.38 ng/㎥) areas. Throughout the year and across all sites, five-ring PAHs accounted for the largest proportion (29.8-34.5%) of all PAHs. The concentrations of PAHs showed distinct seasonal variations, with the highest concentration observed in winter, followed by autumn, spring, and summer. Source apportionment analyses were performed using diagnostic ratios and principal component analyses, which indicated that coal/biomass combustion and vehicle emissions were the primary sources of PAHs in PM-10. The incremental lifetime cancer risk was estimated for all age groups at all sampling sites, and the results revealed a much lower risk level than the standard acceptable risk level (1×10^-6).

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.393-401
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• 2007

Affective aspects of design attributes such as color, Pattern, and texture are important to the overall impression and the success of interior products. Among all the interior materials, wallpapers and flooring materials take up largest construction area and they are main components in creating affective impression for customers. This study aims to investigate the relationship between luxuriousness and related affective variables and design elements of wallpapers and flooring materials. The approach consists of 3 steps: (1) selecting related affective features and product design attributes through a literature survey, opinion of expert panel, and focus group interview, (2) conducting evaluation experiments, and (3) developing Kansei models using multivariate statistical analysis and analyzing critical attributes. Evaluation experiment was conducted using a questionnaire made up of 7-point scale and 100-point scale and 30 housewives and 20 interior designers participated in the evaluation experiment. The result of evaluation was analyzed through principal component regression and quantification I analysis. As a result of analyzing the survey data, the relationship between luxuriousness and related affective features and product design attributes was identified, moreover a optimal combination of the design component was identified. Consequently, it is expected that the results of the study would be a basis of the concept of emotion-based design by giving insights about how customers perceive the luxuriousness and suggesting the optimal combination, and providing specific quantitative design guidelines.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.2
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• pp.203-214
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• 1998

The purpose of this study is to classify the upper body of women into several kinds of somatotypes, using the method of Surgical Tape and making their shells. The subjects are 53 females 30 to 39 years-old. Fifty-three anthropometric data are measured per shell of bodysurface; six somatotype factors are obtained through principal component analysis and orthogonal rotation by the method of Varimax, Somatotype of women's upper body is achieved by cluster analysis, using the standardized factor score as an independent variable and the FASTCLUS of SAS by Kmeans. The results are as follows: 1. The number of the factors which explain the somatotype is six and those factors comprise 76.12 percent of total variance. Factor 1: related to the size of shape in the front of upper body Factor S: related to the size of shape in the back of upper body Factor 3: related to the type of the upper chest over the chest circumference line Factor 4: related to the length of·the upper body Factor 5: related to the part of the neck Factor 6: related to the type of the lower chest under the chest circumference line 2. Cluster analysis results in classification of upper body into five clusters. Cluster L: the length is the largest and the circumference is small. The part of waist is the largest and widest among surface areas. Cluster 2: Slender body line from chest to waist is characteristic. The length is longer. The part of upper and lower chest is larger among surface areas. Cluster S: the circumference is the smallest and armhole is small. The length and surface area are small. Cluster 4: the circumference and armhole is the largest. The length is the smallest. Cluster 5: the circumference is average and the length is a little long. The body line(silhouette) from chest to waist is curved slightly.

• Journal of Korean Society of Forest Science
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• v.76 no.4
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• pp.338-347
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• 1987

The research was carried out to investigate the related phenomena, the latent structures and synthetical characteristics in various growth factors of Phyllostachys bambusoides Sieb. et Zucc. growing at Damyang gun, Chollanamdo, using multivariate analysis. 1. By synthetical characteristics in canonical correlation between height-growth factor group and diameter-growth factor group, the former was determined by the culm height ($x_1$), and the latter by the. diameter of the largest internode($x_7$). And for those between quantitative growth factor group and qualitative growth factor group, the former was determined by the surface area($x_{10}$), and the latter by the diameter of the largest internode ($x_7$). 2. The ten growth factors of bamboo culm were simplified by two principal components on the basis of accumulated proportion aimed at 90%. The first principal component($Z_1$) as a "size factor" showed high correlation with growth factors except eye-height diameter($x_5$). The second principal component($Z_2$) as a "shape factor" showed high correlation only with $x_5$. 3. The bamboo culm, and the latent phenomenon between their growth factors could be determined by two common factors showing high communality(94.16%). The ten growth factors can be grouped into two attribute factors: quantity and quality. 4. The bamboo culms can be classified into five types: total, volume, shape-quality, inferior and middle.

• The Plant Pathology Journal
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• v.24 no.3
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• pp.337-351
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• 2008

Host-pathogen interaction in rice bacterial blight pathosystem was analyzed for a better understanding of their relationship and recognition of stable pathogenicity among the populations of Xanthomonas oryzae pv. oryzae. A total number of 52 bacterial strains isolated from diseased leaf samples collected from 12 rice growing states and one Union Territory of India, were inoculated on 16 rice varieties, each possessing known genes for resistance. Analysis of variance revealed that the host genotypes(G) accounted for largest(78.4%) proportion of the total sum of squares(SS), followed by 16.5% due to the pathogen isolates(I) and 5.1% due to the $I{\times}G$ interactions. Application of the Additive Main effects and Multiplicative Interaction(AMMI) model revealed that the first two interaction principal component axes(IPCA) accounted for 66.8% and 21.5% of the interaction SS, respectively. The biplot generated using the isolate and genotypic scores of the first two IPCAs revealed groups of host genotypes and pathogen isolates falling into four sectors. A group of five isolates with high virulence, high absolute IPCA-1 scores, moderate IPCA-2 scores, low AMMI stability index '$D_i$' values and minimal deviations from additive main effects displayed in AMMI biplot as well as response plot, were identified as possessing stable pathogenicity across 16 host genotypes. The largest group of 27 isolates with low virulence, small IPCA-1 as well as IPCA-2 scores, low $D_i$ values and minimal deviations from additive main effect predictions, possessed stable pathogenicity for low virulence. The AMMI analysis and biplot display facilitated in a better understanding of the host-pathogen interaction, adaptability of pathogen isolates to specific host genotypes, identification of isolates showing stable pathogenicity and most discriminating host genotypes, which could be useful in location specific breeding programs aiming at deployment of resistant host genotypes in bacterial blight disease control strategies.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.19-27
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• 2005

As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.

• Journal of the Korean Magnetics Society
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• v.4 no.2
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• pp.184-187
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• 1994

Nuclear magnetic resonance of $^{133}Cs$ in a $CsMnCl_{3}$ single crystal grown by the Czochralski method has been investigated by employing a Bruker FT NMR spectrometer. The $^{133}Cs$ resonance of two different groups were recorded. Various transitions belonging to two cesium spectra of a different intensity ratio are analyzed. The quadrupole coupling constant of Cs(I) is $0.15{\pm}0.01$ MHz, and that of Cs(II) is $0.21{\pm}0.01$ MHz. The anisotropy parameter is zero for both. The principal axes of the EFG tensors for these two sites are found to be the same. The Z axis, conventionally the largest component of the EFG tensor, is parallel to the crystallographic c-axis.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.52 no.6
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• pp.740-744
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• 2019

Pacific white-sided dolphins Lagenorhynchus obliquidens inhabit cool temperate waters; in Korean waters, they concentrate near the coast of Gangwon and Gyeongbuk from late autumn to early spring. We collected 15 individuals from Yeongduk, Gyeongju, Ulsan, and Busan between December 2018 and February 2019 and analyzed their stomach contents. Fresh prey items were identified to the species level, and residual stomach contents that were unidentified due to digestion were filtered through a sieve to find fish otoliths and cephalopod beaks. The most important prey items of Pacific white-sided dolphins were cephalopods, composing 68.0% of the diet by occurrence. Fishes were the second largest dietary component, making up 32.0% of the diet by occurrence. Of the cephalopod species consumed, Watasenia scintilans was the principal prey item.