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Dissertations / Theses on the topic 'Analysis (PCA)'

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Published: 4 June 2021

Last updated: 7 February 2022

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1

Renkjumnong, Wasuta. "SVD and PCA in Image Processing." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/math_theses/31.

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The Singular Value Decomposition is one of the most useful matrix factorizations in applied linear algebra, the Principal Component Analysis has been called one of the most valuable results of applied linear algebra. How and why principal component analysis is intimately related to the technique of singular value decomposition is shown. Their properties and applications are described. Assumptions behind this techniques as well as possible extensions to overcome these limitations are considered. This understanding leads to the real world applications, in particular, image processing of neurons.

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Le, Hanh T. Banking &amp Finance Australian School of Business UNSW. "Discrete PCA: an application to corporate governance research." Awarded by:University of New South Wales. Banking & Finance, 2007. http://handle.unsw.edu.au/1959.4/40753.

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This thesis introduces the application of discrete Principal Component Analysis (PCA) to corporate governance research. Given the presence of many discrete variables in typical governance studies, I argue that this method is superior to standard PCA that has been employed by others working in the area. Using a dataset of 244 companies listed on the London Stock Exchange in the year 2002-2003, I find that Pearson's correlations underestimate the strength of association between two variables, when at least one of them is discrete. Accordingly, standard PCA performed on the Pearson correlation ma

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Nelson, Philip R. C. MacGregor John F. Taylor Paul A. "The treatment of missing measurements in PCA and PLS models /." *McMaster only, 2002.

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4

Moravčíková, Simona. "Stanovenie hodnoty firmy PCA Slovakia, s.r.o." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-206699.

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The aim of this thesis is to estimate the value of the company PCA Slovakia, s.r.o. to the 31st December 2015. The thesis is divided into two parts, in the concrete the theoretical and practical parts. The theoretical part describes the basic concepts necessary for the valuation of the company and it is kind of the point for the practical part. On the other hand, the practical part is focused on the introduction of the company and the application of strategic analysis and financial analysis, the prognosis of revenue and other value drivers, financial plan and finally the actual valuation of th

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Vogetseder, Georg. "Functional Analysis of Real World Truck Fuel Consumption Data." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1148.

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<p>This thesis covers the analysis of sparse and irregular fuel consumption data of long</p><p>distance haulage articulate trucks. It is shown that this kind of data is hard to analyse with multivariate as well as with functional methods. To be able to analyse the data, Principal Components Analysis through Conditional Expectation (PACE) is used, which enables the use of observations from many trucks to compensate for the sparsity of observations in order to get continuous results. The principal component scores generated by PACE, can then be used to get rough estimates of the trajectories for

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Massaro, James. "A PCA based method for image and video pose sequencing /." Online version of thesis, 2010. http://hdl.handle.net/1850/11991.

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7

Moussavinasab, Nouraddin. "Analysis of point process data arising in self administered analgesia." Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308325.

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Eklund, Linnea. "Analysis of Instagram Stories: A quantitative study of Instagram Stories using PCA." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-418824.

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Alberi, Matteo. "La PCA per la riduzione dei dati di SPHERE IFS." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6563/.

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Nel primo capitolo di questa tesi viene presentata una panoramica dei principali metodi di rivelazione degli esopianeti: il metodo della Velocità Radiale, il metodo Astrometrico, il metodo del Pulsar Timing, il metodo del Transito, il metodo del Microlensing ed infine il metodo del Direct Imaging che verrà approfondito nei capitoli successivi. Nel secondo capitolo vengono presentati i principi della diffrazione, viene mostrato come attenuare la luce stellare con l'uso del coronografo; vengono descritti i fenomeni di aberrazione della luce provocati dalla strumentazione e dagli effetti distorsi

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Königsson, Sofia. "PCA för detektering av avvikande händelser i en kraftvärmeprocess." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-347516.

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Panna 6 på Högdalenverket i södra Stockholm (P6) med tillhörande ångturbin producerar kraftvärme genom förbränning av utsorterat returbränsle från industri och samhälle. För att minimera underhållskostnader och öka anläggningens tillgänglighet är det viktigt att fel och oönskat processbeteende kan upptäckas i ett tidigt skede. I detta syfte testas här en metod för detektering av avvikande händelser med hjälp av principalkomponentanalys (PCA) på produktionsprocessen för kraftvärme. En PCA-modell med reducerad dimension skapas utifrån processdata från en problemfri driftperiod och används som ma

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11

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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Anjasmara, Ira Mutiara. "Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis." Curtin University of Technology, Department of Spatial Sciences, 2008. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=18720.

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Gravity Recovery and Climate Experiment (GRACE) mission has amplified the knowledge of both static and time-variable part of the Earth’s gravity field. Currently, GRACE maps the Earth’s gravity field with a near-global coverage and over a five year period, which makes it possible to apply statistical analysis techniques to the data. The objective of this study is to analyse the most dominant spatial and temporal variability of the Earth’s gravity field observed by GRACE using a combination of analytical and statistical methods such as Harmonic Analysis (HA) and Principal Component Analysis (PC

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Bianchi, Marcelo Franceschi de. "Extração de características de imagens de faces humanas através de wavelets, PCA e IMPCA." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-10072006-002119/.

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Reconhecimento de padrões em imagens é uma área de grande interesse no mundo científico. Os chamados métodos de extração de características, possuem as habilidades de extrair características das imagens e também de reduzir a dimensionalidade dos dados gerando assim o chamado vetor de características. Considerando uma imagem de consulta, o foco de um sistema de reconhecimento de imagens de faces humanas é pesquisar em um banco de imagens, a imagem mais similar à imagem de consulta, de acordo com um critério dado. Este trabalho de pesquisa foi direcionado para a geração de vetores de característ

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Allemang, Matthew R. "Comparison of Automotive Structures Using Transmissibility Functions and Principal Component Analysis." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367944783.

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Balasubramanian, Vijay. "Variance reduction and outlier identification for IDDQ testing of integrated chips using principal component analysis." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4766.

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Integrated circuits manufactured in current technology consist of millions of transistors with dimensions shrinking into the nanometer range. These small transistors have quiescent (leakage) currents that are increasingly sensitive to process variations, which have increased the variation in good-chip quiescent current and consequently reduced the effectiveness of IDDQ testing. This research proposes the use of a multivariate statistical technique known as principal component analysis for the purpose of variance reduction. Outlier analysis is applied to the reduced leakage current values as we

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Griffith, Alexander. "Non Parametric Unsupervised Clustering of ChIP Enrichment Regions Provides Isolation Vectors for Differential Functional Analysis." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35084.

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Gene transcription rates are influenced by proteins, known as Transcription Factors (TFs), that interact with DNA. The locations of TFs on the genome directly influence gene expression and the functional characteristics of a cell. TF binding locations can be estimated for entire genomes using high throughput chromatin immunoprecipitation sequencing (ChIP-Seq). While the analysis of ChIP-Seq binding locations is standardized for a single experiment, complications arise when data sets, taken from different labs and experimental conditions, are combined. In this thesis, I present my method for th

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Jot, Sapan. "pcaL1: An R Package of Principal Component Analysis using the L1 Norm." VCU Scholars Compass, 2011. http://scholarscompass.vcu.edu/etd/2488.

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Principal component analysis (PCA) is a dimensionality reduction tool which captures the features of data set in low dimensional subspace. Traditional PCA uses L2-PCA and has much desired orthogonality properties, but is sensitive to outliers. PCA using L1 norm has been proposed as an alternative to counter the effect of outliers. The R environment for statistical computing already provides L2-PCA function prcomp(), but there are not many options for L1 norm PCA methods. The goal of the research was to create one R package with different options of PCA methods using L1 norm. So, we choose thre

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Marques, Miguel Alexandre Castanheira. "On-line system for faults detection in induction motors based on PCA." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8578.

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Dissertation to obtain the degree of Master in Electrical and Computer Engineering<br>Nowadays in the industry there many processes where human intervention is replaced by electrical machines, especially induction machines due to his robustness, performance and low cost. Although, induction machines are a high reliable device, they are also susceptible to faults. Therefore, the study of induction machine state is essential to reduce human and financial costs. The faults in induction machines can be divided mainly into two types: electrical faults and mechanical faults. Electrical faults repre

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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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Rossi, Rafael Germano. "Análise de componentes principais em data warehouses." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-07012018-182730/.

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A técnica de Análise de Componentes Principais (PCA) tem como objetivo principal a descrição da variância e covariância entre um conjunto de variáveis. Essa técnica é utilizada para mitigar redundâncias no conjunto de variáveis e para redução de dimensionalidade em várias aplicações nas áreas científica, tecnológica e administrativa. Por outro lado, o modelo de dados multidimensionais é composto por relações de fato e dimensões (tabelas) que descrevem um evento usando métricas e a relação entre suas dimensões. No entanto, o volume de dados armazenados e a complexidade de suas dimensões geralme

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Štens, Radovan. "Analýza obrazových dat funkční magnetické rezonance (fMRI)." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-375489.

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Master's thesis focuses on processing fMRI data, which are mapping blood oxygenation level dependence in a state of brain activity. Usable and necessarily preprocessing tech- niques of the data, together with two main analysis approaches are introduced. The area of univariate methods, especially general linear model and multivariate principal or independent component analysis is explained. Practical application of the methods involved on the real fMRI data set is implemented. Relevant results as well as theirs mutual possible comparison is presented.

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La, Alex W. "Eigenblades: Application of Computer Vision and Machine Learning for Mode Shape Identification." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/7228.

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On August 27, 2016, Southwest Airlines flight 3472 from New Orleans to Orlando had to perform an emergency landing when a fan blade separated from the engine hub and destroyed the cowling and punctured the fuselage. Initial findings from the metallurgical examination conducted in the National Transpiration Safety Board Materials Laboratory found that the fracture surface of the missing blade showed curving crack arrest lines consistent with fatigue crack growth. Fatigue is often cause by resonate vibrations. Modal analysis is a method that can model the natural frequencies and bending modes of

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SILVA, Thiago César de Oliveira. "CLASSIFICAÇÃO DE CERVEJAS POR ANÁLISE DE IMAGENS E PCA." Universidade Federal de Goiás, 2008. http://repositorio.bc.ufg.br/tede/handle/tde/1035.

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Made available in DSpace on 2014-07-29T15:12:43Z (GMT). No. of bitstreams: 1 Dissertacao Thiago Cesar.pdf: 841884 bytes, checksum: cee2fa330f9f584e1e3feaa6524d8a0e (MD5) Previous issue date: 2008-06-30<br>In this work a simple and new approach for lager beer pattern recognition based on image analysis was accomplished using Principal Component Analysis (PCA). Digital color images obtained from a scanner were decomposed into a binary form with the help of Scilab and SIP softwares. The PCA data matrix consisted of RGB color histograms for each sample. 350 mL beer cans were chosen at random on

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Öqvist, Per-Olof. "Multivariate Data Analysis on (Ti,Al)N Arc-PVD coating process : MVDA of the growth parameters thickness, stress,composition, and cutting performance." Thesis, Uppsala universitet, Oorganisk kemi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448547.

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This diploma work was done at Seco Tools AB (SECO) in Fagersta and aimed to evaluate the possibility to model the relationship between deposition data, deposition properties and, cutting performance of a (Ti,Al)N coating on cutting inserts by applying the Multivariate Data Analysis (MVDA) modeling technique Partial Least Squares Projection to Latent Structures Modeling (PLS). Cathodic Arc Deposition (Arc-PVD) was the PVD technique focused on this study. The deposition technique that was focused on in this study was Cathodic Arc Deposition (Arc-PVD). For this purpose, two series of Arc-PVD coat

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Nikfetrat, Nima. "Video-based Fire Analysis and Animation Using Eigenfires." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23471.

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We introduce new approaches of modeling and synthesizing realistic-looking 2D fire animations using video-based techniques and statistical analysis. Our approaches are based on real footage of various small-scale fire samples with customized motions that we captured for this research, and the final results can be utilized as a sequence of images in video games, motion graphics and cinematic visual effects. Instead of conventional physically-based simulation, we utilize example-based principal component analysis (PCA) and take it to a new level by introducing “Eigenfires”, as a new way to repre

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Santos, Anderson Rodrigo dos. "Identificação de faces humanas através de PCA-LDA e redes neurais SOM." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-21042006-222231/.

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O uso de dados biométricos da face para verificação automática de identidade é um dos maiores desafios em sistemas de controle de acesso seguro. O processo é extremamente complexo e influenciado por muitos fatores relacionados à forma, posição, iluminação, rotação, translação, disfarce e oclusão de características faciais. Hoje existem muitas técnicas para se reconhecer uma face. Esse trabalho apresenta uma investigação buscando identificar uma face no banco de dados ORL com diferentes grupos de treinamento. É proposto um algoritmo para o reconhecimento de faces baseado na técnica de subespaço

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Reising, Justin. "Function Space Tensor Decomposition and its Application in Sports Analytics." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/etd/3676.

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Recent advancements in sports information and technology systems have ushered in a new age of applications of both supervised and unsupervised analytical techniques in the sports domain. These automated systems capture large volumes of data points about competitors during live competition. As a result, multi-relational analyses are gaining popularity in the field of Sports Analytics. We review two case studies of dimensionality reduction with Principal Component Analysis and latent factor analysis with Non-Negative Matrix Factorization applied in sports. Also, we provide a review of a framewor

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Stark, Love. "Outlier detection with ensembled LSTM auto-encoders on PCA transformed financial data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296161.

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Financial institutions today generate a large amount of data, data that can contain interesting information to investigate to further the economic growth of said institution. There exists an interest in analyzing these points of information, especially if they are anomalous from the normal day-to-day work. However, to find these outliers is not an easy task and not possible to do manually due to the massive amounts of data being generated daily. Previous work to solve this has explored the usage of machine learning to find outliers in these financial datasets. Previous studies have shown that

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Aguirre, Jurado Ricardo. "Resilient Average and Distortion Detection in Sensor Networks." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/962.

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In this paper a resilient sensor network is built in order to lessen the effects of a small portion of corrupted sensors when an aggregated result such as the average needs to be obtained. By examining the variance in sensor readings, a change in the pattern can be spotted and minimized in order to maintain a stable aggregated reading. Offset in sensors readings are also analyzed and compensated to help reduce a bias change in average. These two analytical techniques are later combined in Kalman filter to produce a smooth and resilient average given by the readings of individual sensors.

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Bista, Astha. "ASSESSMENT OF SPATIOTEMPORAL VARIATIONS OF GROUNDWATER LEVELS IN THE PLATTE RIVER BASIN USING DATA MINING." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/theses/2575.

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Rapid population growth and climate variability have been posing pressure on groundwater management, especially in regions dominated by irrigation agriculture. Effective management practices require a better understanding of groundwater dynamics and its contributing factors, such as recharge, groundwater-surface water interactions, soil and unsaturated zone characteristics. Although groundwater models can provide valuable insights into these questions, these models are often nonexistent or cost prohibitive.

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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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Mendonça, Marcelo Aparecido. "Classificação de gasolinas comerciais através de métodos estatísticos multivariáveis." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/3/3137/tde-06042006-132932/.

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Neste trabalho estuda-se a aplicação de métodos estatísticos multivariáveis para a classificação de gasolinas comerciais em conformidade à legislação vigente. Atualmente, a ANP baseia a classificação em limites máximos e mínimos para uma série de diferentes propriedades físico-químicas. O objetivo do trabalho é propor uma metodologia para fazer uma triagem das amostras coletadas durante o Programa de Monitoramento da Qualidade dos Combustíveis através de um método de classificação. Ela utiliza a espectroscopia NIR, que é uma técnica rápida e não destrutiva, como método analítico. Com isto será

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Strindlund, Olle. "Evaluation of Homogeneity in Drug Seizures Using Near-Infrared (NIR) Hyperspectral Imaging and Principal Component Analysis (PCA)." Thesis, Linköpings universitet, Kemi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166747.

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The selection of a representative sample is a delicate problem when drug seizures comprised of large number of units arrive at the Swedish National Forensic Centre (NFC). If deviating objects in the selected sample size are found, additional analyzes are required to investigate how representative the results are for the entire population. This generates further pressure on operational analysis flow. With the goal to provide a tool which forensic scientists at NFC can base their assessment of the representative nature of the selected sampling of large drug seizures on, this project investigated

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Harmeling, Stefan. "Independent component analysis and beyond." Phd thesis, [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=973631805.

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Yang, Libin. "An Application of Principal Component Analysis to Stock Portfolio Management." Thesis, University of Canterbury. Department of economics and finance, 2015. http://hdl.handle.net/10092/10293.

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This thesis investigates the application of principal component analysis to the Australian stock market using ASX200 index and its constituents from April 2000 to February 2014. The first ten principal components were retained to present the major risk sources in the stock market. We constructed portfolio based on each of the ten principal components and named these “principal portfolios

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FANEGAN, JULIUS BOLUDE. "A FUZZY MODEL FOR ESTIMATING REMAINING LIFETIME OF A DIESEL ENGINE." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1188951646.

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Yu, Xiaoqian. "The Impact of Latency Jitter on the Interpretation of P300 in the Assessment of Cognitive Function." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6443.

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When stimuli processing time varies in an oddball paradigm, the latency of the P300 will vary across trials. In an oddball task requiring difficult response selections, as the variation of stimuli processing time increases, so does the variation of the P300 latency, causing latency jitters in the measurement. Averaging the P300 across different trials without adjusting this latency jitter will lead to diminished P300 amplitude, resulting in inaccurate conclusions from the data. Verleger et al. (2014) reported a diminished P300 amplitude in a difficult oddball task that required subjects to mak

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Ragozzine, Brett A. "Modeling the Point Spread Function Using Principal Component Analysis." Ohio University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1224684806.

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Britto, Rodrigo da Silva. "Detecção de falhas com PCA e PLS aplicados a uma planta didática." Pós-Graduação em Engenharia Elétrica, 2014. https://ri.ufs.br/handle/riufs/5012.

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A fault monitoring system in general, which, beside the detection, isolation, diagnosis and fault recuperation steps is a research area of great interest, since the fault occurrence may lead to negative consequences on different levels on social, economical and environmental bases. With the increasing complexity of the industrial process, it is often necessary a quick detection leading to an optimized fault management system and therefore avoiding the loss of material and human resources. This work develops a study on fault detection statistical techniques applied to a didactic plant. The dida

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Rodeia, José Pedro dos Santos. "Analysis and recognition of similar environmental sounds." Master's thesis, FCT - UNL, 2009. http://hdl.handle.net/10362/2305.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática<br>Humans have the ability to identify sound sources just by hearing a sound. Adapting the same problem to computers is called (automatic) sound recognition. Several sound recognizers have been developed throughout the years. The accuracy provided by these recognizers is influenced by the features they use and the classification method implemented. While there are many approaches in sound feature extraction and in sound classification, most have

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Huawei, Ren. "Transfer Path Analysis of Wind Noise on a Passenger Car." Thesis, KTH, Farkost och flyg, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-261091.

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Over the last years, due to the development of quieter engines and drivetrains, the importance of addressing the vehicle wind noise problem has significantly increased.In this thesis work, several existing Transfer Path Analysis methods have been applied on an experimental database acquired during a wind tunnel test on a passenger car with the objective of analyzing the distribution of the wind noise sources and their contribution to the target microphones located inside the vehicle. A major challenge for the Transfer Path Analysis (TPA) consists of the high complexity of the aerodynamic sourc

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Gonzalez, Nicolas Alejandro. "Principal Components Analysis, Factor Analysis and Trend Correlations of Twenty-Eight Years of Water Quality Data of Deer Creek Reservoir, Utah." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3309.

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I evaluated twenty-eight years (1980-2007) of spatial-temporal water quality data from Deer Creek Reservoir in Utah. The data came from three sampling points representing the lotic, transitional and lentic zones. The data included measurements of climatological, hydrological and water quality conditions at four depths; Surface, Above Thermocline, Below Thermocline and Bottom. The time frame spanned dates before and after the completion of the Jordanelle Reservoir (1987-1992), approximately fourteen miles upstream of Deer Creek. I compared temporal groupings and found that a traditional month d

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Martins, Diogo Miguel dos Santos. "Análise da variabilidade espacial e temporal da precipitação e seca em Portugal." Master's thesis, ISA/UTL, 2012. http://hdl.handle.net/10400.5/5282.

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Mestrado em Engenharia do Ambiente - Tecnologias Ambientais - Instituto Superior de Agronomia<br>The spatial variability of precipitation and drought are investigated for Portugal using monthly precipitation from 74 stations and minimum and maximum temperature from 27 stations, covering the common period of 1941– 2006. Seasonal precipitation and the corresponding percentages in the year, as well as the precipitation concentration index (PCI), was computed for all 74 stations and then used as an input matrix for an R-mode principal component analysis to identify the precipitation patterns.

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Petters, Patrik. "Development of a Supervised Multivariate Statistical Algorithm for Enhanced Interpretability of Multiblock Analysis." Thesis, Linköpings universitet, Matematiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138112.

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In modern biological research, OMICs techniques, such as genomics, proteomics or metabolomics, are often employed to gain deep insights into metabolic regulations and biochemical perturbations in response to a specific research question. To gain complementary biologically relevant information, multiOMICs, i.e., several different OMICs measurements on the same specimen, is becoming increasingly frequent. To be able to take full advantage of this complementarity, joint analysis of such multiOMICs data is necessary, but this is yet an underdeveloped area. In this thesis, a theoretical background

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Norouzi, Mehdi. "Tracking Long-Term Changes in Bridges using Multivariate Correlational Data Analysis." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1416570591.

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Radhakrishnan, Anirudh. "Automated pavement condition analysis based on AASHTO guidelines." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1920.

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Edberg, Alexandra. "Monitoring Kraft Recovery Boiler Fouling by Multivariate Data Analysis." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-230906.

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This work deals with fouling in the recovery boiler at Montes del Plata, Uruguay. Multivariate data analysis has been used to analyze the large amount of data that was available in order to investigate how different parameters affect the fouling problems. Principal Component Analysis (PCA) and Partial Least Square Projection (PLS) have in this work been used. PCA has been used to compare average values between time periods with high and low fouling problems while PLS has been used to study the correlation structures between the variables and consequently give an indication of which parameters

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Šrenk, David. "Vizualizace spektroskopických dat pomocí metody analýzy hlavních komponent." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-401532.

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This diploma thesis deals with using laser-induced breakdown plasma spectroscopy for determining the elemental structure of unknown samples. It was necessary to design an appropriate method to qualify material by laser-induced emission spectrum. Pretreatment of data and using a variety of chemometrics methods had to be done in order to qualify the structure of elements. We achieved a required solution by projecting the data to a new PCA space, creating clusters and computing the Euclidean distance between each cluster. The experiment in the practical part was set to detect an interface of two

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Gomes, Róbson Koszeniewski. "Uma Abordagem para Detecção Automática de Planos em Modelos Digitais de Afloramentos Baseada em PCA." Universidade do Vale do Rio dos Sinos, 2014. http://www.repositorio.jesuita.org.br/handle/UNISINOS/4465.

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Submitted by Nara Lays Domingues Viana Oliveira (naradv) on 2015-07-15T18:16:55Z No. of bitstreams: 1 ROBSON.pdf: 2705073 bytes, checksum: d6eefccd3ecb288572c9262f7dc4079a (MD5)<br>Made available in DSpace on 2015-07-15T18:16:55Z (GMT). No. of bitstreams: 1 ROBSON.pdf: 2705073 bytes, checksum: d6eefccd3ecb288572c9262f7dc4079a (MD5) Previous issue date: 2014<br>PROCERGS - Companhia de Processamento Dados do Estado Rio Grande Sul<br>A coleta de dados espaciais tem sido intensamente empregada na área geológica, através da técnica de LIDAR (Light Detection and Ranging). Este tipo de sensoria

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Xian, Qing. "Statistical Assessment of Hydrochemical Characteristics of Streams and Rivers in Eastern New England." Thesis, Boston College, 2009. http://hdl.handle.net/2345/1364.

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Thesis advisor: Rudolph Hon<br>This study characterizes the current state of water quality of surface streams and rivers in the eastern New England region. A set of water quality data for nine rivers, part of the USGS National Water-Quality Assessment (NAWQA) Program was statistically evaluated to identify natural and anthropogenic persistent influential factors on water quality in surface waters. Binary analysis and multivariate analysis, mainly Principal Component Analysis (PCA) and Factor Analysis (FA) were applied to determine the least number of independent relationships among multiple ch

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