• 제목/요약/키워드: Principal components analysis

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보편적인 기저함수를 이용한 중앙면상의 머리전달함수 모델링 (Modeling of Median-plane Head-related Impulse Responses Using a Set of General Basis Functions)

  • 황성목;박영진;박윤식
    • 한국소음진동공학회논문집
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    • 제18권4호
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    • pp.448-457
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    • 2008
  • A principal components analysis (PCA) of the median-plane head-related impulse responses (HRIRs) in the CIPIC HRTF database reveals that the individual HRIRs in the median plane can be adequately reconstructed by a linear combination of 12 orthonormal basis functions. These basis functions can be used to model arbitrary median-plane HRIRs, which are not included in the process to obtain the basis functions. Memory size can be reduced up to 5-fold depending on the number of HRIRs to be modeled. To clarify whether these basis functions can be used to model other set of arbitrary median plane HRIRs, a numerical error analysis for modeling and a series of subjective listening tests were carried out using the measured and modeled HRIRs. The results showed that the set of individual HRIRs in the median plane, which were measured in our lab using different measurement conditions, techniques, and source positions, can be modeled with reasonable accuracy. All subjects, involved in the subjective listening test, reported not only the accurate vertical perception but also the front-back discrimination with the modeled HRIRs based on 12 basis functions.

간척지 농촌설계를 위한 표준농촌지역의 도출 (Extraction of Standard Rural Area for Design of Rural Settlement System in Reclaimed Land)

  • 최수명;고재군
    • 한국농공학회지
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    • 제28권2호
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    • pp.53-62
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    • 1986
  • An Idea of Standard Rural Area(SRA), the rural areas which have higher ruralities of the rice cropping region and also higher urban characteristics, was conceptualized to develop the tentative basic indices necessary for rural settlement design in reclaimed land. The SRA's were determined by a technique of the principal component analysis with relevant data from 81 counties or cities located in the west side of Korea(Chon-Nam,Chon-Buk, Chung-Nam, Kyung-Ki Do).By the definition of the SRA, the principal component analysis is seperately carried out by two subworks, analyses of rurality and urban characteristics. From the analysis, rurality of the SRA is characterized by four components which appears to describe the scale of farm management, intensive farming, soundness of farming and farming basis on rice cropping, while urban characteristics of the SRA by three components to describe the accessibility, keeping ratio of infrastructures and level of medical services. Through grouping and synthesizing two characteristics of all counties by each component score, 24 counties were classified as urban-rural harmonized region which is the same result as that obtained from the extraction index being more than 50% of available area to total area except 1 county. Therefore, SRA is defined as the group of counties having more than 50% of available area to total area.

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광화학측정망에서 측정한 휘발성유기화합물의 정도관리 방법 (Quality Assurance and Quality Control method for Volatile Organic Compounds measured in the Photochemical Assessment Monitoring Station)

  • 신혜정;김종춘;김용표
    • 한국입자에어로졸학회지
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    • 제7권1호
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    • pp.31-44
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    • 2011
  • The hourly volatile organic compounds(VOCs) concentrations between 2005 and 2008 at Bulgwang photochemical assessment monitoring station were investigated to establish a method for quality assurance and quality control(QA/QC) procedure. Systematic error, erratic error, and random error, which was manifested by outlier and highly fluctuated data, were checked and removed. About 17.3% of the raw data were excluded according to the proposed QA/QC procedure. After QA/QC, relative standard deviation for representing 15 species concentrations decreased from 94.7-548.0% to 63.4-125.8%, implying the QA/QC procedure is proper. For further evaluation about the adequacy of QA/QC procedure, principal components analysis(PCA) was carried out. When the data after QA/QC procedure was used for PCA, the extracted principal components were different from the result from the raw data and could logically explain the major emission sources(gasoline vapor, vehicle exhaust, and solvent usage). The QA/QC procedure based on the concept of errors is inferred to proper to be applied on VOCs. However, an additional QA/QC step considering the relationship between species in the atmosphere needs to be further considered.

PCA에 기반을 둔 인공신경회로망을 이용한 온실의 습도 예측 (Predicting the Greenhouse Air Humidity Using Artificial Neural Network Model Based on Principal Components Analysis)

  • 오우라비압둘하메드바바툰데;이종원;메쓰캄카남즈사니카닐란가니자야세카라;이현우
    • 한국농공학회논문집
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    • 제59권5호
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    • pp.93-99
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    • 2017
  • A model was developed using Artificial Neural Networks (ANNs) based on Principal Component Analysis (PCA), to accurately predict the air humidity inside an experimental greenhouse located in Daegu (latitude $35.53^{\circ}N$, longitude $128.36^{\circ}E$, and altitude 48 m), South Korea. The weather parameters, air temperature, relative humidity, solar radiation, and carbon dioxide inside and outside the greenhouse were monitored and measured by mounted sensors. Through the PCA of the data samples, three main components were used as the input data, and the measured inside humidity was used as the output data for the ALYUDA forecaster software of the ANN model. The Nash-Sutcliff Model Efficiency Coefficient (NSE) was used to analyze the difference between the experimental and the simulated results, in order to determine the predictive power of the ANN software. The results obtained revealed the variables that affect the inside air humidity through a sensitivity analysis graph. The measured humidity agreed well with the predicted humidity, which signifies that the model has a very high accuracy and can be used for predictions based on the computed $R^2$ and NSE values for the training and validation samples.

주성분분석과 지구통계법을 이용한 제주도 지하수의 수리지화학 특성 연구 (Hydrogeochemical Characterization of Groundwater in Jeju Island using Principal Component Analysis and Geostatistics)

  • 고경석;김용제;고동찬;이광식;이승구;강철희;성현정;박원배
    • 자원환경지질
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    • 제38권4호
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    • pp.435-450
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    • 2005
  • 본 연구는 다변량 통계분석을 이용하여 수리지화학적 특성을 분석하고, 주성분 분석을 통해 얻어진 변수를 설명하는 수리지화학적 과정에 대한 해석, 그리고 각 성분과 주성분을 이용한 공간정보에 대하여 지구통계기법을 적용하여 연구지역 지하수의 유동 및 순환 과정을 해석하고자 하였다. 제주도 지하수의 수질에 가장 많이 영향을 미치는 성분은 Cl과 $NO_3$이었으며, 특히 농업활동에 의해 증가되는 $NO_3$는 지하수 성분 중 가장 큰 변동을 보여주었다. 다변량 통계분석법인 주성분 분석(PCA)에 의한 수리지화학적 특성 분석 결과, 초기 3개의 주성분은 전체 분산의 $73.9\%$를 설명하였다. 주성분 1은 용존 이온의 증가를 나타내며, 주성분 2는 탄산염 광물의 용해와 질산염 오염의 영향, 주성분 3은 양이온 교환반응과 규산염광물의 용해과정을 지시한다. 실험적 반베리오그램 유형 분석 견과 지하수 성분은 크게 두 그룹으로 분류되며 각각의 그룹에는 EC, Cl, Na, $NO_3$$HCO_3,\;SiO_2,$ Ca, Sr이 속한다 지하수 성분의 공간분포 특징을 조사한 결과, 전기전도도(EC), Cl, Na는 해수의 영향을 받는 해안가로 갈수록 증가하는 경향을 보여주며, $NO_3$는 농경지의 분포와 밀접한 상관관계를 가진다. 이들 성분은 또한 지형과도 상관성을 가지며 이는 지하수 함양과의 관련성을 나타낸다. 요인 크리깅 수행 결과 PCI은 Cl, Na, EC의 공간분포와는 다른 양상을 보여주는데 이는 pH, Ca, Sr, $HCO_3$가 PCI에 미치는 영향 때문인 것으로 분석되었다 서부지역에서는 PC2의 이상대가 길게 나타나며 이는 탄산염 광물의 용해와 관련이 있는 것으로 사료된다. 이상의 결과로부터 연구지역 지하수에 대한 다변량 통계분석 및 지구통계 분석 기법의 적용은 수질에 대한 복합적 정보의 정량화와 공간 특성을 해석하는데 사용될 수 있다.

A Model-based Collaborative Filtering Through Regularized Discriminant Analysis Using Market Basket Data

  • Lee, Jong-Seok;Jun, Chi-Hyuck;Lee, Jae-Wook;Kim, Soo-Young
    • Management Science and Financial Engineering
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    • 제12권2호
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    • pp.71-85
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    • 2006
  • Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.

인공신경망을 이용한 목재건조 중 발생하는 음향방출 신호 패턴분류 (Pattern Classification of Acoustic Emission Signals During Wood Drying by Artificial Neural Network)

  • 김기복;강호양;윤동진;최만용
    • Journal of Biosystems Engineering
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    • 제29권3호
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    • pp.261-266
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    • 2004
  • This study was Performed to classify the acoustic emission(AE) signal due to surface cracking and moisture movement in the flat-sawn boards of oak(Quercus Variablilis) during drying using the principal component analysis(PCA) and artificial neural network(ANN). To reduce the multicollinearity among AE parameters such as peak amplitude, ring-down count event duration, ring-down count divided by event duration, energy, rise time, and peak amplitude divided by rise time and to extract the significant AE parameters, correlation analysis was performed. Over 96 of the variance of AE parameters could be accounted for by the first and second principal components. An ANN analysis was successfully used to classify the Af signals into two patterns. The ANN classifier based on PCA appeared to be a promising tool to classify the AE signals from wood drying.

참나물의 휘발성 향기성분 분석 (Analysis of Volatile Flavor Components of Pimpinella brachycarpa)

  • 송희순;최향숙;이미순
    • 한국식품조리과학회지
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    • 제13권5호
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    • pp.674-680
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    • 1997
  • Volatile flavor components of fresh, shady air dried, and presteamed shady air dried Chamnamul (Pimpinella brachycarpa) were collected by simultaneous steam distillation-extraction method, and essential oils were analyzed by gas chromatography-mass spectrometry (GC/MS). Twenty five, 17 and 23 volatile flavor components were identified in essential oils extracted from the fresh, shady air dried, and presteamed shady air dried Chamnamul samples, respectively; however, the kinds of individual components and its percent content of the total volatiles were varied depending on samples. The principal components of Chamnamul were isobutanal, trans caryophyllene, trans ${\beta}$-farnesene, and ${\alpha}$-selinene. Terpenoid compounds reached 44.11%, 33.91% and 72.63% respectively in fresh, shady air dried, and presteamed shady air dried Chamnamul.

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Quality Assessment of Curcuma longa L. by Gas Chromatography-Mass Spectrometry Fingerprint, Principle Components Analysis and Hierarchical Clustering Analysis

  • Li, Ming;Zhou, Xin;Zhao, Yang;Wang, Dao-Ping;Hu, Xiao-Na
    • Bulletin of the Korean Chemical Society
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    • 제30권10호
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    • pp.2287-2293
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    • 2009
  • Gas Chromatography-Mass Spectrometry (GC-MS) fingerprint analysis, Principle Components Analysis (PCA), and Hierarchical Cluster Analysis (HCA) were introduced for quality assessment of Curcuma longa L. (C. longa). The GC-MS fingerprint method was developed and validated by analyzing 33 batches of samples of C. longa from different geographic locations. 18 chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression. Two principal components (PCs) were extracted by PCA. C. longa collected from Guizhou and Fujian were separated from other samples by PC1, capturing 71.83% of variance. While, PC2 contributed for their further separation, capturing 11.13% of variance. HCA confirmed the result of PCA analysis. Therefore, GC-MS fingerprint study with chemometric techniques provides a very flexible and reliable method for quality assessment of C. longa.

Development of Human Resources Competency Components: An Empirical Study in the Stock Exchange of Thailand

  • CHINNAPONG, Pruksaya;KOOMPAI, Somjintana;AUJIRAPONGPAN, Somnuk;RITKAEW, Supit;JUTIDHARABONGSE, Jaturon
    • The Journal of Asian Finance, Economics and Business
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    • 제8권7호
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    • pp.635-646
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    • 2021
  • The objectives of this research are to establish and confirm the human resources competency components for listed companies in the Stock Exchange of Thailand. The sample group used in this research includes the company president, business owner, managing director, assistant managing director, general manager or human resources manager of 140 listed companies. The research instrument is a scale-estimated questionnaire. The obtained data were subjected to principal component analysis and were analyzed for the rotation of the perpendicular component using the Varimax method. Results were generated through the analysis of eight components, consisting of decision-making, creativity, strategic thinking, relationship and communication, teamwork, adaptability, self-management, and motivation. The research results demonstrate important components in human resource performance that are critical to the successful development of organizations. Organizations can apply these components to the development of human resource competencies in accordance with the operations that need to be adjusted to suit the changes that occur. These rapidly-changing conditions are important factors that can be studied and developed into variables and components that affect human resource performance in the future. As a result, organizations need to adjust to be well prepared to face problems and challenges in the harsh competitive environment in the future.