• Title/Summary/Keyword: principal component score

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Face Recognition using 2D-PCA and Image Partition (2D - PCA와 영상분할을 이용한 얼굴인식)

  • Lee, Hyeon Gu;Kim, Dong Ju
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.2
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    • pp.31-40
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    • 2012
  • Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

Flavor Pattern Analysis of Imported Wines Using Electronic Nose System (포도주의 전자코(Electronic Nose)를 이용한 향기 패턴 분석)

  • Kim, Ji-Young;Jang, Ji-Sun;Lee, Ju-Woon;Lee, Ki-Teak
    • Journal of the East Asian Society of Dietary Life
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    • v.18 no.1
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    • pp.14-21
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    • 2008
  • Flavor is one of the most important factors for determining wine characteristics and quality. Flavor pattern of wines(brewed from America, France, Italy, Chile, and Australia) was analyzed by the electronic nose that is equipped with 12 metal oxide sensors. In the results, the flavor pattern of wines was discriminated according to their origins by the principal component analysis(PCA). Each proportion of the first principal component score in the PCA plot was 94.79%(America), 73.62%(France), 99.06%(Italy), 96.74%(Chile), and 96.53%(Australia), respectively. Consequently, the imported wines could be practically differentiated into one from the other origins by volatile properties, suggesting that electronic nose could be successfully used for easy screening and quality evaluation of wines.

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Efficiency Analysis for Major Ports in Korea and China using Boston Consulting Group and Data Envelopment Analysis Model

  • PHAM, Thi Quynh Mai;Choi, Kyoung-Hoon;Park, Gyei-Kark
    • Journal of Navigation and Port Research
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    • v.42 no.2
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    • pp.107-116
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    • 2018
  • Planning strategies to achieve higher competitiveness of ports are becoming increasingly important in business environment. Therefore, strategic competitive position and efficiency analysis needs to be performed to increase ports' effectiveness and competitiveness. This matches with one of targets of new concept e-Navigation to increase the agility and efficiency of ports. The purpose of this study was to apply Boston Consulting Group matrix to analyze competitive positioning of major ports in Korea and China in term of several main cargo types and then use a combination of Data Envelopment Analysis and Principal Component Analysis model to calculate efficiencies. Results show that, at the moment, Chinese ports are still on the top with high position and efficiency score for the representative-Shanghai port. However, result also points out that except container type, Korean ports have chance to compete in other cargo types. Moreover, Gwangyang port is regarded as efficient. It has better position time. It is believed that Gwangyang port together with Busan port can compete with Chinese port in the near future.

Factor Analysis of Uncertainty Experienced by Patients having Rheumatoid Arthritis (류마티스 관절염 환자가 지각하는 불확실성 개념의 요인분석)

  • Yoo, Kyoung-Hee;Lee, Eun-Ok
    • Journal of muscle and joint health
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    • v.4 no.2
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    • pp.238-248
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    • 1997
  • This study was conducted to identify the characteristics of uncertainty in patients having rheumatoid arthritis. Subjects of the study constituted 528 patients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. A self report questionnaire was used to measure the uncertainty. Reliability coefficients of this instrument was found Cronbach's ${\alpha}=.84$. In data analysis, SPSS PC 6.0 computer program was utilized for descriptive statistics and factor analysis. Three factors were appointed on the basis of literature review for the principal component factor analysis method and Varimax Orthogonal Rotation. The results of factor analysis were as follows ; 1) Three factors for uncertainty were identified through the principal component analysis and varimax rotation, and these contributed 37.4% of the valiance in the total score. Twenty six items among the whole items in the scale loaded above .39 on one of 3 factors. 2) The naming of each factor was as follows : Factor 1 was 'ambiguity' and has 12 items, factor 2 was 'lack of information' and has 8 items, factor 3 was 'unpredictability' and has 7 items. 3) Cronbach's alpha for internal consistency was .84 for the total items and .81, .80, .50 for each of three subscales in that order.

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A Study on Analyzing the Interest of the Youth to the Sea (靑少年의 海洋에 관한 關心度의 分析的 硏究)

  • Choi, Jong-Moon;Park, Chang-Ho;Lee, Cheol-Yeong
    • Journal of the Korean Institute of Navigation
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    • v.16 no.1
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    • pp.77-91
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    • 1992
  • How does the youth feel the sea affairs\ulcorner Concerning this question, this paper aims to measure the images of the youth toward the sea affairs - the sea, the ship and the seafarer and to examined the above subject. As sample 3, 250 students of middle and high school were selected by considering geographical environment. The data obtained using Semantic Differential Method were analyzed by principal component analysis, and the obtained factor scores were examined the significance of difference between sex, age and geographical environment. By introducing the principal component analysis, the authors extracted from each of the images, that is, factors of dynamics and affection to the image on these a and the former the factors and pleasure on the ship, and also the former two factors and factor of professional evaluation on the seafarer, The following results are obtained. 1) In the image of the sea, dynamic image of the student in high school were higher than the of the student in middle school in spite of geographic environment and affective image were opposite. 2) In the images of the ship, affective image of the student in middle school and high school in inland were high than the of the male and female student in near the sea. And also, male female students in middle school and male student s in high school of inland showed the highest score to the pleasure image. 3) In the image of the seafare, professional evaluation of the female student in middle school were higher than the others, but the students in high school showed the highest score to dynamic image. Especially, in the case of the majority of students in high school living in the city or town near the, their images of the seafarer were not so good in spite of their explorative experiences about the sea affairs.

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The Analysis of Children's Torso using Photographic Anthropometry(II):A Classification of Clusters by Principal Component Score (사진 계측에 의한 아동의 동체 형상 분석(II): 주성분 점수에 의한 군집 유형의 분류)

  • Jeon, Eun-Kyung;Kwon, Sook-Hee
    • Korean Journal of Human Ecology
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    • v.8 no.2
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    • pp.313-325
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    • 1999
  • This study aimed to classify the data of children's bodies into several clusters by principal component scores that were extracted through the factor analysis in the former study, and to describe the distribution and body characteristics of the clusters. The sample was 308 elementary school children aged from 6 to 8 and the anthropometric measurements were performed indirectly from the photographs of the subjects, which was the same as the first analysis. The data were analysed statistically using SPSSWIN Ver. 8.0. Through the statistical analysis, 3 clusters were obtained from the data. The first cluster distributed more in the children aged 7 and 8 than in the children aged 6. The somatotype of this group was the tallest among the three groups, and they were the most developed group compared to the two other groups in lateral component as well as in linear component. The second cluster group wasn't well developed in lateral components, and had lowest level in Rohrer Index, so this group had thin figures compared to the other groups. The third cluster revealed dominant distribution in the group aged 6, and the group had the least developed linear components but higher level in Rohrer Index. Each cluster group revealed peculiar somatotype that was dominant in one group but rarely in other cluster groups. Lateral views of these characteristics were showed using the average of the measurements of clusters.

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A Study on Somatotype and Body Shape Variation of Female in the Twenties (20대(代) 여성(女性)의 소마토타입과 체형변화(體型變化)에 관(關)한 연구(硏究))

  • Jung, Myoung Sook;Lee, Soon Won
    • Journal of the Korean Society of Clothing and Textiles
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    • v.17 no.1
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    • pp.119-128
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    • 1993
  • This paper is to show the difference in body shape between 2 female groups; one group of 129 subjects is from 18 to 24 years old and the other group of 49 subjects from 25 to 29. Anthropometric somatotyping method by Heath-Carter and descriptive classification method by Sheldon are applied to classify somatotype. There is no difference in somatotype between 2 groups. The average somatotype is 443, which is the balanced type. By comparing the results of T-test, principal component analysis, and factor score, detailed differences in body shape between 2 groups are shown. The results of factor score for obesity factor of both groups are almost same and agree to somatotype results.

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Establishment of Strategy for Management of Technology Using Data Mining Technique (데이터 마이닝을 통한 기술경영 전략 수립에 관한 연구)

  • Lee, Junseok;Lee, Joonhyuck;Kim, Gabjo;Park, Sangsung;Jang, Dongsik
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.2
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    • pp.126-132
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    • 2015
  • Technology forecasting is about understanding a status of a specific technology in the future, based on the current data of the technology. It is useful when planning technology management strategies. These days, it is common for countries, companies, and researchers to establish R&D directions and strategies by utilizing experts' opinions. However, this qualitative method of technology forecasting is costly and time consuming since it requires to collect a variety of opinions and analysis from many experts. In order to deal with these limitations, quantitative method of technology forecasting is being studied to secure objective forecast result and help R&D decision making process. This paper suggests a methodology of technology forecasting based on quantitative analysis. The methodology consists of data collection, principal component analysis, and technology forecasting by logistic regression, which is one of the data mining techniques. In this research, patent documents related to autonomous vehicle are collected. Then, the texts from patent documents are extracted by text mining technique to construct an appropriate form for analysis. After principal component analysis, logistic regression is performed by using principal component score. On the basis of this result, it is possible to analyze R&D development situation and technology forecasting.

Estimation of Genetic Variance Components of Body Size Measurements in Hanwoo (Korean Cattle) Using a Multivariate Linear Model

  • Lee, Jung-Jae;Kim, Nae-Soo
    • Journal of Animal Science and Technology
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    • v.52 no.3
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    • pp.167-174
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    • 2010
  • The objectives of this study were to quantify the combination values of the principal components and factors calculated using body measurements of Hanwoo (Korean Cattle) and estimate their heritabilities. The technique of multivariate analysis was used to reduce a large number of variables to a smaller number of new variables and characterize cattle according to body shape. The analyses were performed using 1,979 cattle at 12 months of age and 936 cattle at 24 months of age. The data for the analyses was obtained from progeny tests performed on Korean Cattle for 6 years from 2003 to 2008. The phenotypic correlations among these traits were estimated to range from 0.32 to 0.90 at 12 months of age and from 0.21 to 0.82 at 24 months of age. The first principal components (PC1s) indicated a weighed average of overall body measurements, accounting for 99.91% of the total variation for both periods of test. The two first PCs had positive coefficients for all body measurements. The major sources of PC, such as chest girth (CG), body length (BL), rump height (RH), and wither height (WH) were similar for both test periods. The heritabilities for PC1, the first factor score (FS1), and the second factor score (FS2) were estimated by multivariate REML method. The estimated heritabilities for PC1, FS1, and FS2 were 0.33, 0.38, and 0.40, respectively, at 12 months of age and 0.26, 0.76, and 0.58 at 24 months of age. Further studies are needed to determine whether the heritabilities of FS1 and FS2 at 24 months of age were overestimated.

An Analytical Study on the Stem-Growth by the Principal Component and Canonical Correlation Analyses (주성분(主成分) 및 정준상관분석(正準相關分析)에 의(依)한 수간성장(樹幹成長) 해석(解析)에 관(關)하여)

  • Lee, Kwang Nam
    • Journal of Korean Society of Forest Science
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    • v.70 no.1
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    • pp.7-16
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    • 1985
  • To grasp canonical correlations, their related backgrounds in various growth factors of stem, the characteristics of stem by synthetical dispersion analysis, principal component analysis and canonical correlation analysis as optimum method were applied to Larix leptolepis. The results are as follows; 1) There were high or low correlation among all factors (height ($x_1$), clear height ($x_2$), form height ($x_3$), breast height diameter (D. B. H.: $x_4$), mid diameter ($x_5$), crown diameter ($x_6$) and stem volume ($x_7$)) except normal form factor ($x_8$). Especially stem volume showed high correlation with the D.B.H., height, mid diameter (cf. table 1). 3) (1) Canonical correlation coefficients and canonical variate between stem volume and composite variate of various height growth factors ($x_1$, $x_2$ and $x_3$) are ${\gamma}_{u1,v1}=0.82980^{**}$, $\{u_1=1.00000x_7\\v_1=1.08323x_1-0.04299x_2-0.07080x_3$. (2) Those of stem volume and composite variate of various diameter growth factors ($x_4$, $x_5$ and $x_6$) are ${\gamma}_{u1,v1}=0.98198^{**}$, $\{{u_1=1.00000x_7\\v_1=0.86433x_4+0.11996x_5+0.02917x_6$. (3) And canonical correlation between stem volume and composite variate of six factors including various heights and diameters are ${\gamma}_{u1,v1}=0.98700^{**}$, $\{^u_1=1.00000x_7\\v1=0.12948x_1+0.00291x_2+0.03076x_3+0.76707x_4+0.09107x_5+0.02576x_6$. All the cases showed the high canonical correlation. Height in the case of (1), D.B.H. in that of (2), and the D.B.H, and height in that of (3) respectively make an absolute contribution to the canonical correlation. Synthetical characteristics of each qualitative growth are largely affected by each factor. Especially in the case of (3) the influence by the D.B.H. is the most significant in the above six factors (cf. table 2). 3) Canonical correlation coefficient and canonical variate between composite variate of various height growth factors and that of the various diameter factors are ${\gamma}_{u1,v1}=0.78556^{**}$, $\{u_1=1.20569x_1-0.04444x_2-0.21696x_3\\v_1=1.09571x_4-0.14076x_5+0.05285x_6$. As shown in the above facts, only height and D.B.H. affected considerably to the canonical correlation. Thus, it was revealed that the synthetical characteristics of height growth was determined by height and those of the growth in thickness by D.B.H., respectively (cf. table 2). 4) Synthetical characteristics (1st-3rd principal component) derived from eight growth factors of stem, on the basis of 85% accumulated proportion aimed, are as follows; Ist principal component ($z_1$): $Z_1=0.40192x_1+0.23693x_2+0.37047x_3+0.41745x_4+0.41629x_5+0.33454x_60.42798x_7+0.04923x_8$, 2nd principal component ($z_2$): $z_2=-0.09306x_1-0.34707x_2+0.08372x_3-0.03239x_4+0.11152x_5+0.00012x_6+0.02407x_7+0.92185x_8$, 3rd principal component ($z_3$): $Z_3=0.19832x_1+0.68210x_2+0.35824x_3-0.22522x_4-0.20876x_5-0.42373x_6-0.15055x_7+0.26562x_8$. The first principal component ($z_1$) as a "size factor" showed the high information absorption power with 63.26% (proportion), and its principal component score is determined by stem volume, D.B.H., mid diameter and height, which have considerably high factor loading. The second principal component ($z_2$) is the "shape factor" which indicates cubic similarity of the stem and its score is formed under the absolute influence of normal form factor. The third principal component ($z_3$) is the "shape factor" which shows the degree of thickness and length of stem. These three principal components have the satisfactory information absorption power with 88.36% of the accumulated percentage. variance (cf. table 3). 5) Thus the principal component and canonical correlation analyses could be applied to the field of forest measurement, judgement of site qualities, management diagnoses for the forest management and the forest products industries, and the other fields which require the assessment of synthetical characteristics.

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