• Title/Summary/Keyword: 함수적 주성분분석

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Cluster analysis for highway speed according to patterns and effects (고속도로 구간별 통행속도의 패턴과 영향에 따른 군집분석)

  • Kim, Byungsoo;An, Soyoung;Son, Jungmin;Park, Hyemi
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.949-960
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    • 2016
  • This paper uses all sections of highway data (VDS) for two years (Jan. 2014-Dec. 2015), with 15 minute units. The first purpose of this study is to find clusters with similar patterns that appear repeatedly with time variables of month, week and hour. The cluster analysis results indicate a variety of patterns of average traffic speeds by time variables depending on the clusters; subsequently, these can be utilized to model for the forecast of the speed at a specific time. The second purpose is to do cluster analysis for grouping sections by effect nets that are closely related to each other. For the similarity measure we use cross-correlation functions calculated after pre-whitening the speed of each section. The cluster analysis gets 19 clusters, and sections within a cluster are geographically close. These results are expected to help to forecast a real-time speed.

Lip Shape Representation and Lip Boundary Detection Using Mixture Model of Shape (형태계수의 Mixture Model을 이용한 입술 형태 표현과 입술 경계선 추출)

  • Jang Kyung Shik;Lee Imgeun
    • Journal of Korea Multimedia Society
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    • v.7 no.11
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    • pp.1531-1539
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    • 2004
  • In this paper, we propose an efficient method for locating human lips. Based on Point Distribution Model and Principle Component Analysis, a lip shape model is built. Lip boundary model is represented based on the concatenated gray level distribution model. We calculate the distribution of shape parameters using Gaussian mixture. The problem to locate lip is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with Gaussian Mixture for setting initial condition and refining estimate of lip shape parameter, which can refrain iteration from converging to local minima. The experiments have been performed for many images, and show very encouraging result.

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Evaluation of Freshness of Chicken Meat during Cold Storage Using a Portable Electronic Nose (휴대용 전자코를 이용한 계육의 냉장 중 신선도 평가)

  • Lee, Hoon-Soo;Chung, Chang-Ho;Kim, Ki-Bok;Cho, Byoung-Kwan
    • Food Science of Animal Resources
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    • v.30 no.2
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    • pp.313-320
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    • 2010
  • The purpose of this study was to evaluate the freshness of chicken meat during 19 d of storage at $4^{\circ}C$ using a portable electronic nose. The portable system consisted of six different metal oxide sensors and a moisture sensor. Determination of volatile compounds with gas chromatography-mass spectrometry, total bacterial count (TBC), and 2-thiobarbituric acid reactive substances (TBARS) monitored the quality change of the samples. These results were compared with the results measured by the electronic nose system. TBC and TBARS measurements could be separated into five groups and seven groups, respectively, among ten groups. According to principal component analysis and linear discriminant analysis with the signals of the portable electronic nose, the sample groups could be clearly separated into eight groups and nine groups, respectively, among ten groups. The portable electronic nose demonstrated potential for evaluating freshness of stored chicken.

Design of PCA-based pRBFNNs Pattern Classifier for Digit Recognition (숫자 인식을 위한 PCA 기반 pRBFNNs 패턴 분류기 설계)

  • Lee, Seung-Cheol;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.4
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    • pp.355-360
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    • 2015
  • In this paper, we propose the design of Radial Basis Function Neural Network based on PCA in order to recognize handwritten digits. The proposed pattern classifier consists of the preprocessing step of PCA and the pattern classification step of pRBFNNs. In the preprocessing step, Feature data is obtained through preprocessing step of PCA for minimizing the information loss of given data and then this data is used as input data to pRBFNNs. The hidden layer of the proposed classifier is built up by Fuzzy C-Means(FCM) clustering algorithm and the connection weights are defined as linear polynomial function. In the output layer, polynomial parameters are obtained by using Least Square Estimation (LSE). MNIST database known as one of the benchmark handwritten dataset is applied for the performance evaluation of the proposed classifier. The experimental results of the proposed system are compared with other existing classifiers.

Absolute Vehicle Speed Estimation of Unmanned Container Transporter using Neural Network Model (무인 컨테이너 운송차량의 절대속도 추정을 위한 뉴럴 네크워크 모델 적용)

  • Ha, Hee-Kwon;Oh, Kyeung-Heub
    • Journal of Navigation and Port Research
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    • v.28 no.3
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    • pp.227-232
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    • 2004
  • Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed supplies good results in normal conditions. But the estimation error in severe braking is discontented In this paper, we estimate the absolute vehicle speed of UCT(Unmanned Container Transporter) by using the wheel speed data from standard anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used 10 algorithms are verified experimentally to estimate the absolute vehicle speed and one of them is perfectly shown to estimate the vehicle speed within 4% error during a braking maneuver.

Drought Frequency Analysis Using Cluster Analysis and Bivariate Probability Distribution (군집분석과 이변량 확률분포를 이용한 가뭄빈도해석)

  • Yoo, Ji Young;Kim, Tae-Woong;Kim, Sangdan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.6B
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    • pp.599-606
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    • 2010
  • Due to the short period of precipitation data in Korea, the uncertainty of drought analysis is inevitable from a point frequency analysis. So it is desired to introduce a regional drought frequency analysis. This study first extracted drought characteristics from 3-month and 12-month moving average rainfalls which represent short and long-term droughts, respectively. Then, the homogeneous regions were distinguished by performing a principal component analysis and cluster analysis. The Korean peninsula was classified into five regions based on drought characteristics. Finally, this study applied the bivariate frequency analysis using a kernel density function to quantify the regionalized drought characteristics. Based on the bivariate drought frequency curves, the drought severities of five regions were evaluated for durations of 2, 5, 10, and 20 months, and return periods of 5, 10, 20, 50, and 100 years. As a result, the largest severity of drought was occurred in the Lower Geum River basin, in the Youngsan River basin, and over in the southern coast of Korea.

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

  • Hwang, Sung-Mook;Park, Young-Jin;Park, Youn-Sik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.4
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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.

Anomaly detection on simulation conditions for ship-handling safety assessment (시뮬레이션 실험조건 이상 진단 연구)

  • Kwon, Se-Hyug
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.5
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    • pp.853-861
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    • 2010
  • Experimental conditions are set with environmental factors which can affect ship navigation. In FTS simulation, infinite simulation can be theoretically tested with no time constraint but the simulated result with the same experimental condition is repeated due to mathematical model. RTS simulation can give more resonable results but costs at lest 30 minutes for only experimental time. The mixture of two simulation methods using probability density function has been proposed: some of experimental conditions in which ship-handling is most difficult are selected with FTS and are tested in RTS. It has drawback that it does not consider the navigation route but aggregated track index. In this paper, anomaly detection approach is suggested to select some experimental conditions of FTS simulation which are most difficult in ship-handling during the navigation route. An empirical result has been shown.

Determination of Simulation Conditions for Ship-handling Safety Assessment (선박운항 안전성 평가를 위한 시뮬레이션 조건 도출 연구)

  • Gong, In-Young;Kwon, Se-Hyug;Kim, Sun-Young
    • Journal of Navigation and Port Research
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    • v.32 no.3
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    • pp.207-213
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    • 2008
  • Ship-handling simulation system has been used for maritime traffic safety assessment for harbor and fairway. There exist various environmental conditions under which ship may navigate along a fairway or in harbor. Due to the time and budget limitations, however, ship-handling simulations are usually carried out for very limited number of environmental conditions. In this paper, statistical method for effective and systematic determination of real time simulation conditions is suggested and applied to the maritime traffic safety assessment problems. In the empirical study, the principal component analysis method and the concept of empirical cumulative distribution function are suggested to estimate synthetic navigational difficulty and to select simulation conditions which would impose high difficulty on shiphandling.

Context Dependent Fusion with Support Vector Machines (Support Vector Machine을 이용한 문맥 민감형 융합)

  • Heo, Gyeongyong
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.7
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    • pp.37-45
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    • 2013
  • Context dependent fusion (CDF) is a fusion algorithm that combines multiple outputs from different classifiers to achieve better performance. CDF tries to divide the problem context into several homogeneous sub-contexts and to fuse data locally with respect to each sub-context. CDF showed better performance than existing methods, however, it is sensitive to noise due to the large number of parameters optimized and the innate linearity limits the application of CDF. In this paper, a variant of CDF using support vector machines (SVMs) for fusion and kernel principal component analysis (K-PCA) for context extraction is proposed to solve the problems in CDF, named CDF-SVM. Kernel PCA can shape irregular clusters including elliptical ones through the non-linear kernel transformation and SVM can draw a non-linear decision boundary. Regularization terms is also included in the objective function of CDF-SVM to mitigate the noise sensitivity in CDF. CDF-SVM showed better performance than CDF and its variants, which is demonstrated through the experiments with a landmine data set.