Orientador: Jarbas Jose Rodrigues Rohwedder / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-04T14:11:39Z (GMT). No. of bitstreams: 1 Sacorague_LuizAlexandre_D.pdf: 20784130 bytes, checksum: 2641ccb25f9cfe431b6a3a0b551238f1 (MD5) Previous issue date: 2004 / Doutorado / Quimica Analitica / Doutor em Quimica

According to climatic models there will be an increase in the amount of greenhouse gases which results in a warming of the earth where the change will be most prominent in the high latitudes. Glaciers mass balance is a good climate change indicator as the response is fast when climate is changing. Glacier mass balance, area of glaciers, elevation line altitude data for 13 glaciers in Scandinavia as well as North Atlantic oscillation (NAO), Arctic oscillation (AO) and sunspot data where gathered and a principle component analysis (PCA) where made. PCA is a multivariate statistical technique with the goal to extract important information and reduce the dimension of data. Three distinct groupings where found within the data set and was identified as extreme years of North Atlantic Oscillation and Arctic Oscillation and one glacier which had the largest area of the 13 glaciers. The PCA explained that all the variables in the data set is correlated with North Atlantic and Arctic Oscillation to about 40 % and we can conclude that there is a regional and local forcing within our data where the regional (NAO and AO) is of more importance for the variance and for the mass balance. / Enligt klimatmodeller kommer en ökning av växthusgaser i atmosfären leda till en ökning av temperaturen på jorden, den ökningen kommer främst att ske på höga latituder. Glaciärer är bra indikation på förändrat klimat på grund av deras korta responstid när klimatet ändrar sig. För tillfället finns det ca 1900 glaciärer utspridda i de Skandinaviska bergen. Eftersom Skandinavien är så avlångt är det en skillnad i meterologiska och klimatiska förhållanden, både i en nord-syd riktning men även i en öst-väst riktning med kontinentala glaciärer i öst och mer marina i väst. Klimat och glaciärdata för 13 olika glaciärer i Skandinavien, 5 från Sverige och 8 ifrån Norge har samlats in och en statistisk analys, principle component analysis (PCA) har gjorts för att se vad som påverkar massbalansen för glaciärerna. De klimat parametrar som har undersökts är Nordatlantsika oscillationen (NAO), Arktiska oscillationen (AO) och solfläckar tillsammans med massbalans, equilibrium line altitude (ELA) och area för glaciärerna. Tre grupperingar har hittats som kan kopplas till olika klimatvariabler och PCA visar extremår för NAO och AO samt en glaciär som har den största arean. PCA analysen visade att alla variabler korrelerade till NAO och AO med omkring 40 % och vi kan dra slutsatsen att det finns en drivande regional och lokal kraft inom vårat dataset där NAO och AO är viktigast för massbalansen.

Os quimioterápicos antimicrobianos são considerados contaminantes emergentes, com a capacidade de criar resistência em bactérias. Têm sido o foco de inúmeras pesquisas relacionadas a impactos ambientais, mas no Brasil, as pesquisas sobre a sua ocorrência em ambientes aquáticos continentais e costeiros são escassas. A cidade de Ubatuba tem uma densidade demográfica cinco vezes maior que a média nacional, aumentada em até doze vezes no verão, pressionando ainda mais os ecossistemas da região. Os rios Acaraú, Lagoa-Tavares, Grande e Indaiá deságuam na baía de Ubatuba, comprometendo a qualidade das suas águas. Este trabalho investigou a contribuição da descarga desses rios para a ocorrência e distribuição de quimioterápicos antimicrobianos (fluoroquinolonas e sulfonamidas) na baía de Ubatuba. Foi analisado um total de 36 amostras de água superficial. As coletas foram realizadas no período seco/chuvoso de 2014/2015. Para a determinação e quantificação dos fármacos foi utilizada SPE como método de preparo de amostra e CLAE-MS/MS para a detecção e quantificação dos antimicrobianos estudados. As características físico-químicas pH, temperatura, salinidade, oxigênio dissolvido, potencial redox (ORP), além do Carbono Orgânico Dissolvido (COD) também foram determinados para caracterização das águas da região. A distribuição espaço-temporal dos fármacos e a possível associação com os demais dados investigados foi avaliada pela ferramenta quimiométrica CA, visando à extração da maior quantidade possível de informações. Os rios e, consequentemente a baía estavam impactados pelo despejo de esgoto doméstico e os seguintes quimioterápicos antimicrobianos foram encontrados: sulfametoxazol (SMX), sulfatiazol (STZ), sulfacloropiridiazina (SCP), sulfaquinoxalina (SQX) e norfloxacina (NOR). Observou-se uma variação espacial e temporal, nos perfis de contaminação revelados pela CA. / Antimicrobial chemotherapeutical agents are considered emerging contaminants capable of creating bacterial resistance. They have been the focus of numerous studies related to environmental impacts, but in Brazil, there is little research on their occurrence in continental and coastal aquatic environments. The city of Ubatuba has a population density five times higher than the national average, which may be increased up to twelve times during the summer, pushing further the region\'s ecosystems. The rivers Acaraú, Lagoa-Tavares, Grande and Indaiá flow into Ubatuba Bay, compromising the quality of its waters. This work investigated those rivers\' discharge contribution on the occurrence and distribution of antimicrobial chemotherapeutical agents (fluoroquinolones and sulfonamides) in Ubatuba Bay. Thirty-six samples of surface water were analyzed. The samples were withdrawn during the dry and rainy seasons of 2014 and 2015, respectively. For the determining and quantifying the antimicrobial chemotherapeutical agents, it was used SPE as a sample preparation method and HPLC?MS/MS for their detection and quantification. Physicochemical characteristics like pH, temperature, salinity, dissolved oxygen, and redox potential (ORP), as well as dissolved organic carbon (DOC) were also determined to characterize the waters of the region. The spatial-temporal distribution of the agents and their possible association with other investigated data was assessed by the chemometric tool CA, aiming at extracting the greatest possible amount of information. The rivers and, consequently, the bay were contaminated by domestic sewage discharges and the following antimicrobial chemotherapeutical agents were detected: sulfamethoxazole (SMX), sulfathiazole (STZ), sulfachloropyridiazine (SCP), sulfaquinoxaline (SQX), and norfloxacin (NOR). The contamination profiles revealed by the CA showed a spatial variation and a temporal one.

Os quimioterápicos antimicrobianos são considerados contaminantes emergentes, com a capacidade de criar resistência em bactérias. Têm sido o foco de inúmeras pesquisas relacionadas a impactos ambientais, mas no Brasil, as pesquisas sobre a sua ocorrência em ambientes aquáticos continentais e costeiros são escassas. A cidade de Ubatuba tem uma densidade demográfica cinco vezes maior que a média nacional, aumentada em até doze vezes no verão, pressionando ainda mais os ecossistemas da região. Os rios Acaraú, Lagoa-Tavares, Grande e Indaiá deságuam na baía de Ubatuba, comprometendo a qualidade das suas águas. Este trabalho investigou a contribuição da descarga desses rios para a ocorrência e distribuição de quimioterápicos antimicrobianos (fluoroquinolonas e sulfonamidas) na baía de Ubatuba. Foi analisado um total de 36 amostras de água superficial. As coletas foram realizadas no período seco/chuvoso de 2014/2015. Para a determinação e quantificação dos fármacos foi utilizada SPE como método de preparo de amostra e CLAE-MS/MS para a detecção e quantificação dos antimicrobianos estudados. As características físico-químicas pH, temperatura, salinidade, oxigênio dissolvido, potencial redox (ORP), além do Carbono Orgânico Dissolvido (COD) também foram determinados para caracterização das águas da região. A distribuição espaço-temporal dos fármacos e a possível associação com os demais dados investigados foi avaliada pela ferramenta quimiométrica CA, visando à extração da maior quantidade possível de informações. Os rios e, consequentemente a baía estavam impactados pelo despejo de esgoto doméstico e os seguintes quimioterápicos antimicrobianos foram encontrados: sulfametoxazol (SMX), sulfatiazol (STZ), sulfacloropiridiazina (SCP), sulfaquinoxalina (SQX) e norfloxacina (NOR). Observou-se uma variação espacial e temporal, nos perfis de contaminação revelados pela CA. / Antimicrobial chemotherapeutical agents are considered emerging contaminants capable of creating bacterial resistance. They have been the focus of numerous studies related to environmental impacts, but in Brazil, there is little research on their occurrence in continental and coastal aquatic environments. The city of Ubatuba has a population density five times higher than the national average, which may be increased up to twelve times during the summer, pushing further the region\'s ecosystems. The rivers Acaraú, Lagoa-Tavares, Grande and Indaiá flow into Ubatuba Bay, compromising the quality of its waters. This work investigated those rivers\' discharge contribution on the occurrence and distribution of antimicrobial chemotherapeutical agents (fluoroquinolones and sulfonamides) in Ubatuba Bay. Thirty-six samples of surface water were analyzed. The samples were withdrawn during the dry and rainy seasons of 2014 and 2015, respectively. For the determining and quantifying the antimicrobial chemotherapeutical agents, it was used SPE as a sample preparation method and HPLC?MS/MS for their detection and quantification. Physicochemical characteristics like pH, temperature, salinity, dissolved oxygen, and redox potential (ORP), as well as dissolved organic carbon (DOC) were also determined to characterize the waters of the region. The spatial-temporal distribution of the agents and their possible association with other investigated data was assessed by the chemometric tool CA, aiming at extracting the greatest possible amount of information. The rivers and, consequently, the bay were contaminated by domestic sewage discharges and the following antimicrobial chemotherapeutical agents were detected: sulfamethoxazole (SMX), sulfathiazole (STZ), sulfachloropyridiazine (SCP), sulfaquinoxaline (SQX), and norfloxacin (NOR). The contamination profiles revealed by the CA showed a spatial variation and a temporal one.

Orientador: Celio Pasquini / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-09T09:59:17Z (GMT). No. of bitstreams: 1 Povia_GiovanaSoato_M.pdf: 1681817 bytes, checksum: d59818d169390e4a42e0555251507c27 (MD5) Previous issue date: 2007 / Resumo: Este trabalho visa o desenvolvimento de um método analítico para a determinação dos parâmetros de qualidade em detergentes em pó utilizando a Espectroscopia de Infravermelho Próximo (NIR) e técnicas de calibração multivariada. Foram utilizados dois conjuntos de amostras: o primeiro para as análises quantitativas e o segundo para análises qualitativas. As amostras do primeiro conjunto tiveram os parâmetros de qualidade determinados pelos respectivos métodos de referência. A técnica estatística utilizada para as calibrações foi o PLS. Foram desenvolvidos modelos de calibrações para a previsão do teor de umidade, matéria ativa e densidade. O desempenho dos modelos de calibrações foi avaliado por meio de validação externa. A determinação do teor de umidade apresentou RMSEP = 0,29% (m/m). O valor de RMSEP para a determinação da matéria ativa foi de 0,37% (m/m) e para a determinação da densidade o valor de RMSEP = 14 g L . Os modelos construídos apresentaram resultados satisfatórios e os erros encontrados são aceitáveis para a faixa de controle utilizada na indústria. O segundo conjunto é composto de 4 grupos, que apresentam características distintas. Foram avaliados dois métodos de classificação: SIMCA e PLS DA. É possível observar que ocorre a discriminação das amostras que apresentam teor de matéria ativa mais elevado, no entanto, os outros grupos não puderam ser discriminados. Os dois métodos de classificação avaliados apresentaram resultados semelhantes, com acerto de 100% na classificação de amostras externas somente em seus respectivos grupos / Abstract: This work aims the development of an analytical method for the determination of quality parameters on powder detergents using the near infrared spectroscopy (NIR) and multivariate calibration techniques. Two sets of samples were used: the first one for the quantitative analysis and the second one for qualitative analysis. The samples of the first set had the quality parameters determined by their respective methods of reference. The chemometric technique used for calibration was the PLS1. Calibrations for the prediction of de moisture content, active matter and density were developed. The performance of the calibration models was evaluated through external validation. The determination of the moisture content presented a RMSEP = 0,29% (w/w). The value of RMSEP for the determination of the active matter was 0,37% (w/w) and for the determination of moisture the value of RMSEP was 14 g L. The constructed models presented satisfactory results and the errors that were found are acceptable for the control range used in industry. The second set is composed of four groups of power detergents which present different characteristics. Two methods of classification were evaluated: SIMCA and PLS DA. It was possible to observe the discrimination of the samples which presents higher active matter content. However, the other groups could not be discriminated. Both methods of classifications evaluated presented similar results, with 100% correcte results of the classification of samples only in their respective groups / Mestrado / Quimica Analitica / Mestre em Química

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Orientador: Marcia Miguel Castro Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-14T13:05:23Z (GMT). No. of bitstreams: 1 Pedro_AndreMessiasKrell_D.pdf: 1179705 bytes, checksum: 302be0a6ab2e796d557a625c76f92bc4 (MD5) Previous issue date: 2009 / Resumo: DESENVOLVIMENTO DO MÉTODO MULTIVARIADO ACELERADO PARA DETERMINAÇÃO DO PRAZO DE VALIDADE DE PRODUTOS UNINDO QUIMIOMETRIA E CINÉTICA QUÍMICA descreve um novo conceito de análise de dados que permite avaliar os mecanismos que governam a degradação de bens de consumo e determinar o período de tempo no qual os bens de consumo mantém suas características dentro de níveis aceitáveis. O algoritmo une técnicas quimiométricas com a teoria cinética química formal, constituindo um avanço sobre os protocolos para determinação da validade de produto existentes. Além de ser de fácil interpretação, suas principais vantagens incluem a capacidade de unir informações provenientes de diferentes disciplinas ¿ analíticos, físico-químicos, sensoriais - e a possibilidade de utilização direta de dados oriundos de instrumentação analítica como espectroscópios, cromatógrafos, calorímetros, etc. O trabalho é dividido em seis capítulos. O Capítulo I traz uma revisão da cinética química e dos métodos convencionais para determinação do prazo de validade de produtos. O algoritmo do Método Multivariado Acelerado, bem como suas premissas, vantagens e desvantagens, são descritos no capítulo II. Os Capítulos III e IV trazem aplicações do Método Multivariado Acelerado. No Capítulo III dados físico-químicos e sensoriais foram utilizados para determinar o prazo de validade de um produto alimentíco. No Capítulo IV utilizaram-se dados instrumentais, oriundos de espectroscopia no infravermelho próximo (NIR), como fonte de informação quantitativa que, aliados a avaliações sensoriais, permitiram a determinação da validade de um produto cosmético e forneceram informações relevantes sobre seus modos de degradação. Uma comparação com o método tri-linear PARAFAC é apresentada no Capítulo V. Apesar de constituir ferramenta importante para avaliação dos modos de degradação de produtos, o método PARAFAC carece de estratégias para determinação efetiva do prazo de bens de consumo. Finalmente, o Capítulo VI mostra o desenvolvimento de um protocolo para determinação de várias propriedades de produtos concentrados de tomate utilizando regressão PLS2. Demonstrou-se que, apesar da preferência pelo método de calibração PLS1 por parte dos pesquisadores, a regressão PLS2 é vantajosa quando há correlação entre propriedades cujos métodos de referência são precisos e outras, cuja quantificação é imprecisa. / Abstract: DEVELOPMENT OF THE MULTIVARIATE ACCELERATED SHELF-LIFE TEST (MASLT) FOR DETERMINING THE SHELF-LIFE OF PRODUCTS BY MERGING CHEMOMETRICS AND CHEMICAL KINETICS describes a new concept of data analysis for evaluating the mechanisms that rule out the degradation of consumer goods. The algorithm herein developed took advantage of the soft modeling concepts from chemometrics and of chemical kinetics for determining the period of time within which products would be able to keep their quality characteristics within acceptable levels. Besides being of easy interpretation, the main advantages of the MASLT are the capacity to merge data from different sources ¿ analytical, physical chemical, sensorial ¿ and the ability of handling instrumental data (spectroscopic, chromatographic, calorimetric, etc.) directly for determining the shelf-life of products. This work and some applications are presented in six chapters. In Chapter I, a review of the chemical kinetics theory, as well as the concepts of conventional shelf-life methods, is presented. The MASLT algorithm, together with its assumptions, characteristics and advantages, is presented in Chapter II. Chapters III e IV describe applications where the shelf-life was determined successfully by using the MASLT. In Chapter III, physical chemical and sensorial data were merged not only for determining the shelf-life of an industrialized tomato product, but also to study the correlation between the various properties. In Chapter IV, instrumental data from NIR spectroscopy were used as source of quantitative information and, together with sensory analyses, allowed the determination of the shelf-life of a cosmetic product as well as provided valuable information with regards to its degradation mechanisms. A comparison between the tri-linear method PARAFAC is presented in Chapter V. Despite being an important tool for evaluating the degradation mechanisms of consumer goods, the PARAFAC method lacks strategies for effectively determining the shelf-life of products. Finally, Chapter VI describes the development of a new protocol for determining several properties of tomato concentrate products using PLS2 regression. It was demonstrated that, despite most researchers having a preference for using PLS1 regression, PLS2 is advantageous when there is strong correlations between properties that can be determined quite accurately by their reference methods with those presenting lower accuracy. / Doutorado / Físico-Química / Doutor em Ciências

As machine learning becomes an increasingly relevant field being incorporated into everyday life, so does the need for consistently high performing models. With these high expectations, along with potentially restrictive data sets, it is crucial to be able to use techniques for machine learning that increase the likelihood of success. Robust Principal Component Analysis (RPCA) not only extracts anomalous data, but also finds correlations among the given features in a data set, in which these correlations can themselves be used as features. By taking a novel approach to utilizing the output from RPCA, we address how our method effects the performance of such models. We take into account the efficiency of our approach, and use projectors to enable our method to have a 99.79% faster run time. We apply our method primarily to cyber security data sets, though we also investigate the effects on data sets from other fields (e.g. medical).

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 three different L1-PCA algorithms: PCA-L1 proposed by Kwak [10], L1-PCA* by Brooks et. al. [1], and L1-PCA by Ke and Kanade [9]; to create a package pcaL1 in R, interfacing with C implementation of these algorithms. An open source software for solving linear problems, CLP, is used to solve the optimization problems for L1-PCA* and L1-PCA. We use this package on human microbiome data to investigate the relationship between people based on colonizing bacteria.

This thesis presents an efficient and biologically informed 3D human body morphing technique through data-driven alteration of standardized 3D models. The anthropometric data is derived from a large empirical database and processed using principal component analysis (PCA). Although techniques using PCA are relatively commonplace in computer graphics, they are mainly used for scientific visualizations and animation. Here we focus on uncovering the underlying mathematical structure of anthropometric data and using it to build an intuitive interface that allows the interactive manipulation of body shape within the normal range of human variation. We achieve weight/gender based body morphing by using PCA. First we calculate the principal vector space of the original data. The data then are transformed into a new orthogonal multidimensional space. Next, we reduce the dimension of the data by only keeping the components of the most significant principal vectors. We then fit a curve through the original data points and are able to generate a new human body shape by inversely transforming the data from principal vector space back to the original measuring data space. Finally, we sort the original data by the body weight, calculating males and females separately. This enables us to use weight and gender as two intuitive controls for body morphing. The Deformer program is implemented using the programming language C++ with OPENGL and FLTK API. 3D and human body models are created using Alias MayaTm.