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1

Chen, Huanting. "Portfolio Construction Using Principle Component Analysis." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/927.

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"Principal Components Analysis (PCA) is an important mathematical technique widely used in the world of quantitative finance. The ultimate goal of this paper is to construct a portfolio with hedging positions, which is able to outperform the SPY benchmark in terms of the Sharpe ratio. Mathematical techniques implemented in this paper besides principle component analysis are the Sharpe ratio, ARMA, ARCH, GARCH, ACF, and Markowitz methodology. Information about these mathematical techniques is listed in the introduction section. Through conducting in sample analysis, out sample analysis, and bac
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Shawli, Alaa. "Scoring the SF-36 health survey in scleroderma using independent component analysis and principle component analysis." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=97180.

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The short form SF-36 survey is a widely used survey of patient health related quality of life. It yields eight subscale scores of functional health and well-being that are summarized by two physical and mental component summary scores. However, recent studies have reported inconsistent results between the eight subscales and the two component summary measures when the scores are from a sick population. They claim that this problem is due to the method used to compute the SF-36 component summary scores, which is based on principal component analysis with orthogonal rotation.In this thesis, we e
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Yaseen, Muhammad Usman. "Identification of cause of impairment in spiral drawings, using non-stationary feature extraction approach." Thesis, Högskolan Dalarna, Datateknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:du-6473.

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Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is
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Holm, Klaus Herman. "Assessment of Atlanta’s PM [subscript 2.5] source profiles using principle component analysis and positive matrix factorization." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/20751.

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Mahmood, Muhammad Tariq. "Face Detection by Image Discriminating." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4352.

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Human face recognition systems have gained a considerable attention during last few years. There are very many applications with respect to security, sensitivity and secrecy. Face detection is the most important and first step of recognition system. Human face is non rigid and has very many variations regarding image conditions, size, resolution, poses and rotation. Its accurate and robust detection has been a challenge for the researcher. A number of methods and techniques are proposed but due to a huge number of variations no one technique is much successful for all kinds of faces and images
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Chisholm, Daniel J. "Use of Principle Component Analysis for the identification and mapping of phases from energy-dispersive x-ray spectra." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA359572.

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Li, Yancan. "The Effects of Ownership on Bank Performance: A Study of Commercial Banks in China." Scholarship @ Claremont, 2012. http://scholarship.claremont.edu/cmc_theses/515.

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Many Chinese commercial banks have experienced ownership transitions during the past decade, along with significant improvements in performance. In order to examine the effect of ownership on bank performance, an empirical study of Chinese commercial banks is performed. A dataset covering 16 Chinese commercial banks over the period of 2002 — 2011 is tested using linear regression model and principle component analysis. It is found that being a Joint-Stock Commercial Bank has a positive effect on earnings per share (EPS), and being a City Commercial Bank increases return on assets (ROA). On the
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Chemistruck, Heather Michelle. "A Galerkin Approach to Define Measured Terrain Surfaces with Analytic Basis Vectors to Produce a Compact Representation." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/29585.

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The concept of simulation-based engineering has been embraced by virtually every research and industry sector (Sinha, Liang et al. 2001; Mocko and Fenves 2003). Engineering and science communities have become increasingly aware that computer simulation is an indispensable tool for resolving a multitude of scientific and technological problems. It is clearly desirable to gain a reliable perspective on the behaviour of a system early in the design stage, long before building costly prototypes (Chul and Ro 2002; Letherwood, Gunter et al. 2004; Makarand Datar 2007; Ersal, Fathy et al. 2008; Muel
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Zito, Tiziano. "Exploring the slowness principle in the auditory domain." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2012. http://dx.doi.org/10.18452/16450.

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In dieser Arbeit werden - basierend auf dem Langsamkeitsprinzip - Modelle und Algorithmen für das auditorische System entwickelt. Verschiedene experimentelle Ergebnisse, sowie die erfolgreichen Ergebnisse im visuellen System legen nahe, dass, trotz der unterschiedlichen Beschaffenheit visueller und auditorischer sensorischer Signale, das Langsamkeitsprinzip auch im auditorischen System eine bedeutsame Rolle spielen könnte, und vielleicht auch im Kortex im Allgemeinen. Es wurden verschiedene Modelle für unterschiedliche Repräsentationen des auditorischen Inputs realisiert. Es werden die B
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Bloxson, Julie M. "Characterization of the Porosity Distribution within the Clinton Formation, Ashtabula County, Ohio by Geophysical Core and Well Logging." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1341879463.

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Pham, Duong Hung. "Contributions to the analysis of multicomponent signals : synchrosqueezing and associated methods." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM044/document.

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De nombreux signaux physiques incluant des signaux audio (musique, parole), médicaux (ECG, PCG), de mammifères marins ou d'ondes gravitationnelles peuvent être modélisés comme une superposition d'ondes modulées en amplitude et en fréquence (modes AM-FM), appelés signaux multicomposantes (SMCs). L'analyse temps-fréquence (TF) joue un rôle central pour la caractérisation de tels signaux et, dans ce cadre, diverses méthodes ont été développées au cours de la dernière décennie. Néanmoins, ces méthodes souffrent d'une limitation intrinsèque appelée le principe d'incertitude. Dans ce contexte, la mé
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12

Andersson, Moa. "Who supports non-traditional gender roles? : Exploring the Relationship Between Self-interest, Contextual Exposure and Gender Attitudes in Sweden." Thesis, Stockholms universitet, Sociologiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-118772.

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Abstract Beliefs about which behaviors and responsibilities should typical be assumed by women and men are central in shaping gender relations and gender equality in society. The belief that women should be responsible for domestic work, while men should provide economically for the family gives rise to an uneven opportunity structure, situating women in a disadvantaged position compared to men. In order to achieve gender equality traditional gender role attitudes need to liberalize. This thesis examines who supports non-traditional gender roles in Sweden. Data representative of the Swedish po
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Abuasbeh, Mohammad. "Fault Detection and Diagnosis for Brine to Water Heat Pump Systems." Thesis, KTH, Tillämpad termodynamik och kylteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183595.

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The overall objective of this thesis is to develop methods for fault detection and diagnosis for ground source heat pumps that can be used by servicemen to assist them to accurately detect and diagnose faults during the operation of the heat pump. The aim of this thesis is focused to develop two fault detection and diagnosis methods, sensitivity ratio and data-driven using principle component analysis. For the sensitivity ratio method model, two semi-empirical models for heat pump unit were built to simulate fault free and faulty conditions in the heat pump. Both models have been cross-validat
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Uygun, Nazli. "Validity Of Science Items In The Student Selection Test In Turkey." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609716/index.pdf.

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This thesis presents content-related and construct-related validity evidence for science sub-tests within Student Selection Test (SST) in Turkey via underlying the content, cognitive processes, item characteristics, factorial structure, and group differences based on high school type. A total number of 126,245 students were present in the research from six type of school in the data of SST 2006. Reliability Analysis, Item Analysis, Principle Component Analysis (PCA) and one-way ANOVA have been carried out to evaluate the content-related and construct-related evidence of validity of SST. SPSS a
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15

Vadapalli, Hima Bindu. "Recognition of facial action units from video streams with recurrent neural networks : a new paradigm for facial expression recognition." University of the Western Cape, 2011. http://hdl.handle.net/11394/5415.

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Philosophiae Doctor - PhD<br>This research investigated the application of recurrent neural networks (RNNs) for recognition of facial expressions based on facial action coding system (FACS). Support vector machines (SVMs) were used to validate the results obtained by RNNs. In this approach, instead of recognizing whole facial expressions, the focus was on the recognition of action units (AUs) that are defined in FACS. Recurrent neural networks are capable of gaining knowledge from temporal data while SVMs, which are time invariant, are known to be very good classifiers. Thus, the research cons
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Grener, Doreen Elaine. "A Content Analysis of Elementary Science Textbook Series From 1930 Through 1990 for The Presentation of The Principle of Humans as a Component of The Ecosystem /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487933648650631.

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Bršlíková, Jana. "Analýza úmrtnostních tabulek pomocí vybraných vícerozměrných statistických metod." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-201859.

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The mortality is historically one of the most important demographic indicator and definitely reflects the maturity of each country. The objective of this diploma thesis is the comparison of mortality rates in analyzed countries around the world over time and among each other using the principle component analysis that allows assessing data different way. The big advantage of this method is minimal loss of information and quite understandable interpretation of mortality in each country. This thesis offers several interesting graphical outputs, that for example confirm higher mortality rate in E
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18

Nunes, Madalena Baioa Paraíso. "Portfolio selection : a study using principal component analysis." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14598.

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Mestrado em Finanças<br>Nesta tese aplicámos a análise de componentes principais ao mercado bolsista português usando os constituintes do índice PSI-20, de Julho de 2008 a Dezembro de 2016. Os sete primeiros componentes principais foram retidos, por se ter verificado que estes representavam as maiores fontes de risco deste mercado em específico. Assim, foram construídos sete portfólios principais e comparámo-los com outras estratégias de alocação. Foram construídos o portfólio 1/N (portfólio com investimento igual para cada um dos 26 ativos), o PPEqual (portfólio com igual investimento em cada
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19

Koyuncu, Fulya. "Validity Of Biology Items In 2006, 2007, And 2008 Student Selection Test In Turkey." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612946/index.pdf.

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Student selection test in Turkey compose of two parts. The purpose of the first part is to assess students&rsquo<br>higher order thinking skills like analytical thinking, interpretation and reasoning about elementary school curriculum and 9th grade curricula objectives. On the other hand, second part of the test aims to assess students&rsquo<br>higher order thinking skills given in the high school curriculum. The main aim of this thesis is to analyze to what extend 2006, 2007 and 2008 student selection tests biology items assess higher order cognitive skills. In accordance with this purpose,
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20

Brand, Hilmarie. "PCA and CVA biplots : a study of their underlying theory and quality measures." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80363.

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Thesis (MComm)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: The main topics of study in this thesis are the Principal Component Analysis (PCA) and Canonical Variate Analysis (CVA) biplots, with the primary focus falling on the quality measures associated with these biplots. A detailed study of different routes along which PCA and CVA can be derived precedes the study of the PCA biplot and CVA biplot respectively. Different perspectives on PCA and CVA highlight different aspects of the theory that underlie PCA and CVA biplots respectively and so contribute to a more solid understa
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Nandong, Jobrun. "Modelling and control strategies for extractive alcoholic fermentation: partial control approach." Thesis, Curtin University, 2010. http://hdl.handle.net/20.500.11937/2197.

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The vast majority of chemical and bio-chemical process plants are normally characterized by large number of measurements and relatively small number of manipulated variables; these thin plants have more output than input variables. As the number of manipulated variables restricts the number of controlled variables, thin plant has presented a daunting challenge to the engineers in selecting which measured variables to be controlled. In general, this is an important problem in modern process control today, because controlled variables selection is one of the key questions which must be carefully
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Zhang, Yuyao. "Non-linear dimensionality reduction and sparse representation models for facial analysis." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0019/document.

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Les techniques d'analyse du visage nécessitent généralement une représentation pertinente des images, notamment en passant par des techniques de réduction de la dimension, intégrées dans des schémas plus globaux, et qui visent à capturer les caractéristiques discriminantes des signaux. Dans cette thèse, nous fournissons d'abord une vue générale sur l'état de l'art de ces modèles, puis nous appliquons une nouvelle méthode intégrant une approche non-linéaire, Kernel Similarity Principle Component Analysis (KS-PCA), aux Modèles Actifs d'Apparence (AAMs), pour modéliser l'apparence d'un visage dan
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Dickens, Peter Martin. "Facilitating Emergence: Complex, Adaptive Systems Theory and the Shape of Change." Antioch University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1339016565.

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Gunnarsson, Fredrik. "Filtered Historical SimulationValue at Risk for Options : A Dimension Reduction Approach to Model the VolatilitySurface Shifts." Thesis, Umeå universitet, Institutionen för fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160344.

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Kpamegan, Neil Racheed. "Robust Principal Component Analysis." Thesis, American University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10784806.

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<p> In multivariate analysis, principal component analysis is a widely popular method which is used in many different fields. Though it has been extensively shown to work well when data follows multivariate normality, classical PCA suffers when data is heavy-tailed. Using PCA with the assumption that the data follows a stable distribution, we will show through simulations that a new method is better. We show the modified PCA can be used for heavy-tailed data and that we can more accurately estimate the correct number of components compared to classical PCA and more accurately identify the subs
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Akinduko, Ayodeji Akinwumi. "Multiscale principal component analysis." Thesis, University of Leicester, 2016. http://hdl.handle.net/2381/36616.

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The problem of approximating multidimensional data with objects of lower dimension is a classical problem in complexity reduction. It is important that data approximation capture the structure(s) and dynamics of the data, however distortion to data by many methods during approximation implies that some geometric structure(s) of the data may not be preserved during data approximation. For methods that model the manifold of the data, the quality of approximation depends crucially on the initialization of the method. The first part of this thesis investigates the effect of initialization on manif
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Der, Ralf, Ulrich Steinmetz, Gerd Balzuweit, and Gerrit Schüürmann. "Nonlinear principal component analysis." Universität Leipzig, 1998. https://ul.qucosa.de/id/qucosa%3A34520.

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We study the extraction of nonlinear data models in high-dimensional spaces with modified self-organizing maps. We present a general algorithm which maps low-dimensional lattices into high-dimensional data manifolds without violation of topology. The approach is based on a new principle exploiting the specific dynamical properties of the first order phase transition induced by the noise of the data. Moreover we present a second algorithm for the extraction of generalized principal curves comprising disconnected and branching manifolds. The performance of the algorithm is demonstrated for both
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Solat, Karo. "Generalized Principal Component Analysis." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/83469.

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The primary objective of this dissertation is to extend the classical Principal Components Analysis (PCA), aiming to reduce the dimensionality of a large number of Normal interrelated variables, in two directions. The first is to go beyond the static (contemporaneous or synchronous) covariance matrix among these interrelated variables to include certain forms of temporal (over time) dependence. The second direction takes the form of extending the PCA model beyond the Normal multivariate distribution to the Elliptically Symmetric family of distributions, which includes the Normal, the Student'
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Khwambala, Patricia Helen. "The importance of selecting the optimal number of principal components for fault detection using principal component analysis." Master's thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/11930.

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Includes summary.<br>Includes bibliographical references.<br>Fault detection and isolation are the two fundamental building blocks of process monitoring. Accurate and efficient process monitoring increases plant availability and utilization. Principal component analysis is one of the statistical techniques that are used for fault detection. Determination of the number of PCs to be retained plays a big role in detecting a fault using the PCA technique. In this dissertation focus has been drawn on the methods of determining the number of PCs to be retained for accurate and effective fault detect
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Fučík, Vojtěch. "Principal component analysis in Finance." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-264205.

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The main objective of this thesis is to summarize and possibly interconnect the existing methodology on principal components analysis, hierarchical clustering and topological organization in the financial and economic networks, linear regression and GARCH modeling. In the thesis the clustering ability of PCA is compared with the more conventional approaches on a set of world stock market indices returns in different time periods where the time division is represented by The World Financial Crisis of 2007-2009. It is also observed whether the clustering of DJIA index components is underlied by
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Wedlake, Ryan Stuart. "Robust principal component analysis biplots." Thesis, Link to the online version, 2008. http://hdl.handle.net/10019/929.

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Brennan, Victor L. "Principal component analysis with multiresolution." [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/ank7079/brennan%5Fdissertation.pdf.

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Thesis (Ph. D.)--University of Florida, 2001.<br>Title from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also contains graphics. Vita. Includes bibliographical references (p. 120-123).
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Jahirul, Md Islam. "Experimental and statistical investigation of Australian native plants for second-generation biodiesel production." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/83778/9/Jahirul_Islam_Thesis.pdf.

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This work explores the potential of Australian native plants as a source of second-generation biodiesel for internal combustion engines application. Biodiesels were evaluated from a number of non-edible oil seeds which are grow naturally in Queensland, Australia. The quality of the produced biodiesels has been investigated by several experimental and numerical methods. The research methodology and numerical model developed in this study can be used for a broad range of biodiesel feedstocks and for the future development of renewable native biodiesel in Australia.
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Phala, Adeela Colyne. "Application of multivariate regression techniques to paint: for the quantitive FTIR spectroscopic analysis of polymeric components." Thesis, Cape Peninsula University of Technology, 2011. http://hdl.handle.net/20.500.11838/733.

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Thesis submitted in fulfilment of the requirements for the degree Master of Technology Chemistry in the Faculty of (Science) Supervisor: Professor T.N. van der Walt Bellville campus Date submitted: October 2011<br>It is important to quantify polymeric components in a coating because they greatly influence the performance of a coating. The difficulty associated with analysis of polymers by Fourier transform infrared (FTIR) analysis’s is that colinearities arise from similar or overlapping spectral features. A quantitative FTIR method with attenuated total reflectance coupled to multivariate/ ch
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Lee, Colin K. "Infrared face recognition." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Jun%5FLee%5FColin.pdf.

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Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2004.<br>Thesis advisor(s): Monique P. Fargues, Gamani Karunasiri. Includes bibliographical references (p. 135-136). Also available online.
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Cadima, Jorge Filipe Campinos Landerset. "Topics in descriptive Principal Component Analysis." Thesis, University of Kent, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314686.

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Isaac, Benjamin. "Principal component analysis based combustion models." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209278.

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Energy generation through combustion of hydrocarbons continues to dominate, as the most common method for energy generation. In the U.S. nearly 84% of the energy consump- tion comes from the combustion of fossil fuels. Because of this demand there is a continued need for improvement, enhancement and understanding of the combustion process. As computational power increases, and our methods for modelling these complex combustion systems improve, combustion modelling has become an important tool in gaining deeper insight and understanding for these complex systems. The constant state of change in
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Alfonso, Miñambres Javier de. "Face recognition using principal component analysis." Master's thesis, Universidade de Aveiro, 2010. http://hdl.handle.net/10773/10221.

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Mestrado em Engenharia Electrónica e Telecomunicações<br>The purpose of this dissertation was to analyze the image processing method known as Principal Component Analysis (PCA) and its performance when applied to face recognition. This algorithm spans a subspace (called facespace) where the faces in a database are represented with a reduced number of features (called feature vectors). The study focused on performing various exhaustive tests to analyze in what conditions it is best to apply PCA. First, a facespace was spanned using the images of all the people in the database. We obtaine
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Roveroni, Alessandro <1997&gt. "Principal Component Analysis on ESG data." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/19941.

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The objective of the dissertation is to perform a principal component analysis on ESG data. The ESG database is provided by the ESG-Credit.eu project and contains information of 11.104 firms of all Europe. The research focuses on companies residing in French, Italy and Germany. The data present in the database are extracted from three different sources of information: Bloomberg, Thomson Reuters Eikon and CDP. The number of overall measures collected is 609 distributed among the three main pillars of the ESG score: Environment, Social and Governance. In the 20th century, ESG has played a crucia
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Brubaker, S. Charles. "Extensions of principal components analysis." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29645.

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Thesis (Ph.D)--Computing, Georgia Institute of Technology, 2009.<br>Committee Chair: Santosh Vempala; Committee Member: Adam Kalai; Committee Member: Haesun Park; Committee Member: Ravi Kannan; Committee Member: Vladimir Koltchinskii. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Teixeira, Sérgio Coichev. "Utilização de análise de componentes principais em séries temporais." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-09052013-224741/.

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Um dos principais objetivos da análise de componentes principais consiste em reduzir o número de variáveis observadas em um conjunto de variáveis não correlacionadas, fornecendo ao pesquisador subsídios para entender a variabilidade e a estrutura de correlação dos dados observados com uma menor quantidade de variáveis não correlacionadas chamadas de componentes principais. A técnica é muito simples e amplamente utilizada em diversos estudos de diferentes áreas. Para construção, medimos a relação linear entre as variáveis observadas pela matriz de covariância ou pela matriz de correlação. Entre
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Broadbent, Lane David. "Recognition of Infrastructure Events Using Principal Component Analysis." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6197.

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Information Technology systems generate system log messages to allow for the monitoring of the system. In increasingly large and complex systems the volume of log data can overwhelm the analysts tasked with monitoring these systems. A system was developed that utilizes Principal Component Analysis to assist the analyst in the characterization of system health and events. Once trained, the system was able to accurately identify a state of heavy load on a device with a low false positive rate. The system was also able to accurately identify an error condition when trained on a single event. The
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Burka, Zak. "Perceptual audio classification using principal component analysis /." Online version of thesis, 2010. http://hdl.handle.net/1850/12247.

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Patak, Zdenek. "Robust principal component analysis via projection pursuit." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29737.

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In principal component analysis (PCA), the principal components (PC) are linear combinations of the variables that minimize some objective function. In the classical setup the objective function is the variance of the PC's. The variance of the PC's can be easily upset by outlying observations; hence, Chen and Li (1985) proposed a robust alternative for the PC's obtained by replacing the variance with an M-estimate of scale. This approach cannot achieve a high breakdown point (BP) and efficiency at the same time. To obtain both high BP and efficiency, we propose to use MM- and τ-estimates in pl
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Monahan, Adam Hugh. "Nonlinear principal component analysis of climate data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ48678.pdf.

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Nilsson, Jakob, and Tim Lestander. "Detecting network failures using principal component analysis." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-132258.

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The dataset is first analyzed on a basic level by looking at the correlations between number of measurements and average download speed for every day. Second, our PCA-based methodology applied on the dataset, taking into account many factors, including the number of correlated measurements. The results from each analysis is compared and evaluated. Based on the results, we give insights to just how efficient the tested methods are and what improvements that can be made on the methods.This thesis investigates the efficiency of a methodology that first performs a Principal Component Analysis (PCA), f
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Dauwe, Alexander. "Principal component analysis of the yield curve." Master's thesis, NSBE - UNL, 2009. http://hdl.handle.net/10362/9439.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics<br>This report deals with one of the remaining key problems in financial decision taking: the forecast of the term structure at different time horizons. Specifically: I will forecast the Euro Interest Rate Swap with a macro factor augmented autoregressive principal component model. I achieve forecasts that significantly outperform the Random Walk for medium to long term horizons when using a short rolling time window. Including macro factors lead
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Graner, Johannes. "On Asymptotic Properties of Principal Component Analysis." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-420649.

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Li, Liubo Li. "Trend-Filtered Projection for Principal Component Analysis." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1503277234178696.

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Roy, Samita. "Pyrite oxidation in coal-bearing strata : controls on in-situ oxidation as a precursor of acid mine drainage formation." Thesis, Durham University, 2002. http://etheses.dur.ac.uk/3753/.

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Pyrite oxidation in coal-bearing strata is recognised as the main precursor to Acidic Mine Drainage (AMD) generation. Predicting AMD quality and quantity for remediation, or proposed extraction, requires assessment of interactions between oxidising fluids and pyrite, and between oxidation products and groundwater. Current predictive methods and models rarely account for individual mineral weathering rates, or their distribution within rock. Better constraints on the importance of such variables in controlling rock leachate are required to provide more reliable predictions of AMD quality. In th
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