• Title/Summary/Keyword: Principle component analysis

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Application of Regression Analysis Model to TOC Concentration Estimation - Osu Stream Watershed - (회귀분석에 의한 TOC 농도 추정 - 오수천 유역을 대상으로 -)

  • Park, Jinhwan;Moon, Myungjin;Han, Sungwook;Lee, Hyungjin;Jung, Soojung;Hwang, Kyungsup;Kim, Kapsoon
    • Journal of Environmental Impact Assessment
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    • v.23 no.3
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    • pp.187-196
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    • 2014
  • The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

A Study on the Consumer's Purchasing Motives toward Casual Hanbok - in the areas of Pusan - (생활한복의 구매동기에 관한 연구 -부산지역을 중심으로-)

  • 최은경
    • Journal of the Korean Society of Costume
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    • v.45
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    • pp.71-84
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    • 1999
  • This study was to identify the dimensions of consumer's purchasing motives and purchasing delay reasons toward casual hanbok. Other objective was to examine relationship between these variables and future purchasing intention. Th 22 purchasing motive questions and 19 purchasing delay reasons were selected through the result of self-questionnaire analysis. 302 purchaser and 297 consumers who delay for particular reasons in Pusan responsed to the second questionnaire of purchasing motives and purchasing delay reasons toward casual Hanbok. The results as follows: 1. For factor analysis 22 purchasing motive questions were subjected to the principle component analysis with orthogonal rotation after extraction of 6 major factors. Six dimensions are consciousness of nation goodness of design conformity with fashion charming apperance relaxation fo body and mind nation goodness of design conformity with fashion charming appearance relaxation of body and mind and pursuit of individuality. These factors explained 62.0% of total variables. 2. Consumer's purchasing motives such as consciousness of nation goodness of design charming appearance and relaxation of body and mind has predicting power to the re-purchasing intention of casual hanbok 3. For factor analysis 19 delay reason question were subjected to the principle component analysis with orthogonal rotation after extraction of 5 major factors. Five dimensions are non-fitness for occasion and body shape unsatisfaction with design unsatisfaction with price need of information search for better product and preference for traditional hangok. These factors explained 60.4% of total variables. 4. Delay reasons of unsatisfaction with design and price were positively related to the future purchasing intention. This delay reason is caused by forces external to the consumer and the consumer has engaged in information search. This result explained this type of consumer has the strong future purchasing intention.

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Sleep Disturbance Classification Using PCA and Sleep Stage 2 (주성분 분석과 수면 2기를 이용한 수면 장애 분류)

  • Shin, Dong-Kun
    • The Journal of the Korea Contents Association
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    • v.11 no.4
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    • pp.27-32
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    • 2011
  • This paper presents a methodology for classifying sleep disturbance using electroencephalogram (EEG) signal at sleep stage 2 and principal component analysis. For extracting initial features, fast Fourier transforms(FFT) were carried out to remove some noise from EEG signal at sleep stage 2. In the second phase, we used principal component analysis to reduction from EEG signal that was removed some noise by FFT to 5 features. In the final phase, 5 features were used as inputs of NEWFM to get performance results. The proposed methodology shows that accuracy rate, specificity rate, and sensitivity were all 100%.

An Improved Multiplicative Updating Algorithm for Nonnegative Independent Component Analysis

  • Li, Hui;Shen, Yue-Hong;Wang, Jian-Gong
    • ETRI Journal
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    • v.35 no.2
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    • pp.193-199
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    • 2013
  • This paper addresses nonnegative independent component analysis (NICA), with the aim to realize the blind separation of nonnegative well-grounded independent source signals, which arises in many practical applications but is hardly ever explored. Recently, Bertrand and Moonen presented a multiplicative NICA (M-NICA) algorithm using multiplicative update and subspace projection. Based on the principle of the mutual correlation minimization, we propose another novel cost function to evaluate the diagonalization level of the correlation matrix, and apply the multiplicative exponentiated gradient (EG) descent update to it to maintain nonnegativity. An efficient approach referred to as the EG-NICA algorithm is derived and its validity is confirmed by numerous simulations conducted on different types of source signals. Results show that the separation performance of the proposed EG-NICA algorithm is superior to that of the previous M-NICA algorithm, with a better unmixing accuracy. In addition, its convergence speed is adjustable by an appropriate user-defined learning rate.

Gesture Recognition Using Higher Correlation Feature Information and PCA

  • Kim, Jong-Min;Lee, Kee-Jun
    • Journal of Integrative Natural Science
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    • v.5 no.2
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    • pp.120-126
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    • 2012
  • This paper describes the algorithm that lowers the dimension, maintains the gesture recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.

An intelligent sun tracker with self sensor diagonosis system (자기 센서진단기능을 가진 지능형 태양추적장치)

  • 최현석;현웅근
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.452-456
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    • 2002
  • The sensor based control system has some sensor fault while operating in the field. In this paper, a sensor fault detection and reconstruction system for a sun tracking controller has been researched by using polynomial regression and principle component analysis approach. The developed sun tracking system controls tow actuators with sensor based mechanism as on-line control and sun orbit information as off-line control, alternatively. To show the validity of the developed system, several experiments were illustrated.

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Protein and Amino-acid Contents in Backtae, Seoritae, Huktae, and Seomoktae Soybeans with Different Cooking Methods (콩의 종류 및 조리방법에 따른 단백질·아미노산 함량 변화)

  • Im, Jeong Yeon;Kim, Sang-Cheon;Kim, Sena;Choi, Youngmin;Yang, Mi Ran;Cho, In Hee;Kim, Haeng Ran
    • Korean journal of food and cookery science
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    • v.32 no.5
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    • pp.567-574
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    • 2016
  • Purpose: The objective of this study was to provide nutritional information (protein and amino-acid contents) of soybeans (Baktae, Seoritae, Huktae, and Seomoktae) with different cooking methods. Methods: Raw, boiled (in $100{\pm}15^{\circ}C$ of water for 4 hr), and fried (in a pan at $110{\pm}15^{\circ}C$ for $20{\pm}5min$) soybean samples were prepared. Contents of protein and amino acids were determined. Results: Protein content in raw Baktae, Seoritae, Huktae, and Seomoktae soybeans ranged from 361.0 to 386.8 mg/g. Protein contents differed according to cooking methods. They were higher in pan-fried beans (107.9-113.5%) than in raw or boiled soybeans (48.2-49.5%). A total of 18 amino acids were analyzed. Amino acid data sets were subjected to principle component analysis (PCA) to understand their differences according to soybean types and cooking methods. Bean samples could be distinguished better according to cooking method in comparison with bean types by principle component (PC1) and PC2. In particular, fried soybeans contained much higher levels of cystein. Other amino acids were the dominant in raw and boiled ones. On the other hand, the amounts of threonine, histidine, proline, arginine, tyrosine, lysine, tryptophan, and methionine were higher in raw bean samples than in cooked ones. Conclusion: The contents of amino-acids and proteins are more effected by different cooking methods in comparison with soybean types.

The Evaluation of Water Quality Using a Multivariate Analysis in Changnyeong-Haman weir section (다변량 통계분석을 이용한 낙동강 창녕함안보 구간의 수질 특성 평가)

  • Gwak, Bo-ra;Kim, Il-kyu
    • Journal of Korean Society of Water and Wastewater
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    • v.29 no.6
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    • pp.625-632
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    • 2015
  • The study of water environment system using a multivariate analysis in Changnyeong-Haman weir section has been conducted. The purpose of this study is to establish better understanding related water qualities in the Changnyeong-Haman weir section which can provide useful information. The data were consisted of water quality data and algae data including WT(water temperature), pH, DO, EC, COD, SS, T-N, $NH_3-N$, T-P, $PO_4-P$, Chl-a, TOC, d-silica, t-silica, Cyanobacteria, Diatoms, and Green algae. Statistical analyses used in this study were correlation analysis, principal components, and factor analysis. According to correlation analysis on COD and TOC, it revealed that the each value of correlation coefficient was 0.843. On the other result, a negative correlation was observed between diatoms and d-silica. Furthermore, the results of principal component analysis to the overall water quality were classified into four main factors with contribution rate 81.071%.

Morphological characterization of Korean and Turkish watermelon germplasm

  • Huh, Yun Chan;Choi, Hak Soon;Solmaz, Ilknur;Sari, Nebahat;Kim, Su
    • Korean Journal of Agricultural Science
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    • v.41 no.4
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    • pp.309-314
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    • 2014
  • A total of 67 watermelon accessions which include 37 accessions from Korean and 27 accessions from Turkish germplasm and 3 accessions of other related species from USA were investigated for morphological characteristics. The UPOV descriptor list for 56 characters (6 seedlings, 4 plants, 11 leaves, 5 flowers, 23 fruits and 7 seeds) was used in characterization. In addition, eight quantitative characters, hypocotyl length, cotyledon width, cotyledon length, fruit weight, fruit length, fruit width, thickness of outer layer of pericarp and soluble solid content were also measured. The 56 qualitatively scored characters were analyzed by principle coordinate analysis (PCoA) while the eight quantitative ones were subjected to principle component analysis (PCA). Morphological characterization result demonstrated that the accessions displayed high morphological diversity(how much percent?). A high level of phenotypic diversity was observed from the results of morphological characterization. However, plant growth habit and leaf blade flecking showed constant characters for all of the accessions. The Korean and Turkish watermelon genotypes are diverse groups and can be separated by both multivariate analysis of morphological characters although the grouping was more apparent in PCoS results.

Progressive collapse analysis of steel frame structure based on the energy principle

  • Chen, Chang Hong;Zhu, Yan Fei;Yao, Yao;Huang, Ying
    • Steel and Composite Structures
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    • v.21 no.3
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    • pp.553-571
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    • 2016
  • The progressive collapse potential of steel moment framed structures due to abrupt removal of a column is investigated based on the energy principle. Based on the changes of component's internal energy, this paper analyzes structural member's sensitivity to abrupt removal of a column to determine a sub-structure resisting progressive collapse. An energy-based structural damage index is defined to judge whether progressive collapse occurs in a structure. Then, a simplified beam damage model is proposed to analyze the energies absorbed and dissipated by structural beams at large deflections, and a simplified modified plastic hinges model is developed to consider catenary action in beams. In addition, the correlation between bending moment and axial force in a beam during the whole deformation development process is analyzed and modified, which shows good agreement with the experimental results.