926 resultados para Multivariate Statistical Process Monitoring


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Herbs and spices have long been used to improve the flavour of food without being considered as nutritionally significant ingredients. However, the bioactive phenolic content of these plant-based products is currently attracting interest.In the present work, liquid chromatography coupled to high-resolution/accurate mass measurement LTQ-Orbitrap mass spectrometry was applied for the comprehensive identification of phenolic constituents of six of the most widely used culinary herbs (rosemary, thyme, oregano and bay) and spices (cinnamon and cumin). In this way, up to 52 compounds were identified in these culinary ingredients, some of them, as far as we know, for the first time. In order to establish the phenolic profiles of the different herbs and spices, accurate quantification of the major phenolics was performed by multiple reaction monitoring in a triple quadrupole mass spectrometer. Multivariate statistical treatment of the results allowed the assessment of distinctive features among the studied herbs and spices. (C) 2014 Elsevier Ltd. All rights reserved.

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Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process monitoring, among them, UV–Vis spectroscopy has found scarce applications. This work aimed to define artificial neural networks architecture and fit its parameters to predict some nutrients and metabolites, as well as viable cell concentration based on UV–Vis spectral data of mammalian cell bioprocess using phenol red in culture medium. The BHK-21 cell line was used as a mammalian cell model. Off-line spectra of supernatant samples taken from batches performed at different dissolved oxygen concentrations in two bioreactor configurations and with two pH control strategies were used to define two artificial neural networks. According to absolute errors, glutamine (0.13 ± 0.14 mM), glutamate (0.02 ± 0.02 mM), glucose (1.11 ± 1.70 mM), lactate (0.84 ± 0.68 mM) and viable cell concentrations (1.89 105 ± 1.90 105 cell/mL) were suitably predicted. The prediction error averages for monitored variables were lower than those previously reported using different spectroscopic techniques in combination with partial least squares or artificial neural network. The present work allows for UV–VIS sensor development, and decreases cost related to nutrients and metabolite quantifications.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Engenharia Mecânica - FEIS

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this paper we describe how morphological castes can be distinguished using multivariate statistical methods combined with jackknife estimators of the allometric coefficients. Data from the polymorphic ant, Camponotus rufipes, produced two distinct patterns of allometric variation, and thus two morphological castes. Morphometric analysis distinguished different allometric patterns within the two castes, with overall variability being greater in the major workers. Caste-specific scaling variabilities were associated with the relative importance of first principal component. The static multivariate allometric coefficients for each of 10 measured characters were different between castes, but their relative magnitudes within castes were similar. Multivariate statistical analysis of worker polymorphism in ants is a more complete descriptor of shape variation than, and provides statistical and conceptual advantages over, the standard bivariate techniques commonly used.

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Background Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

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In which refers to statistical process control, the analysis of univariate cases is not enough for many types of company, being necessary to resort to multivariate cases. Besides, it is usually supposed that the observations are independent. However, the violation of this hypothesis indicates the existence of autocorrelation in the process. In this work, by a basic quantitative approach for an exploratory and experimental research, the study target are the multivariate autocorrelated control charts, using Hotteling T². The ARL values were collected by simulations of a computational program on FORTRAN language, with objective of studying the charts properties, in addition to compare with the

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In which refers to statistical process control, the analysis of univariate cases is not enough for many types of company, being necessary to resort to multivariate cases. Besides, it is usually supposed that the observations are independent. However, the violation of this hypothesis indicates the existence of autocorrelation in the process. In this work, by a basic quantitative approach for an exploratory and experimental research, the study target are the multivariate autocorrelated control charts, using Hotteling T². The ARL values were collected by simulations of a computational program on FORTRAN language, with objective of studying the charts properties, in addition to compare with the

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The quality concepts represent one of the important factors for the success of organizations and among these concepts the stabilization of the production process contributes to the improvement, waste reduction and increased competitiveness. Thus, this study aimed to evaluate the production process of solid wood flooring on its predictability and capacity, based on its critical points. Therefore, the research was divided into three stages. The first one was the process mapping of the company and the elaboration of flowcharts for the activities. The second one was the identification and the evaluation of the critical points using FMEA (Failure Mode and Effect Analysis) adapted methodology. The third one was the evaluation of the critical points applying the statistical process control and the determination of the process capability for the C-pk index. The results showed the existence of six processes, two of them are critical. In those two ones, fifteen points were considered critical and two of them, related with the dimension of the pieces and defects caused by sandpaper, were selected for evaluation. The productive process of the company is unstable and not capable to produce wood flooring according to the specifications and, therefore these specifications should be reevaluated.

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Se presenta un producto de satélite optimizado para estudios de mesoescala, obtenido como una mejora de la imagen media. El producto optimizado como media que es, no ofrece una visión instantánea del medio, pero sin embargo es adecuado para el estudio en mesoescala de áreas marinas sometidas a condiciones de nubosidad persistente, ya que proporciona una visión continuada en el espacio y en el tiempo. Ambas características le confieren una gran utilidad en la observación y seguimiento de las estructuras oceanográficas. El ritmo de la variación en el tiempo para fenómenos marinos es del orden de varios días, por lo que el proceso estadístico no merma de forma significativa ninguna característica física sino que por el contrario aumenta la posibilidad de observarlas ya que es capaz de secuestrar las señales que más se conservan y elimina las que provocan ruido en la información. Se presentan también los resultados de la validación de este producto. ABSTRACT obtained as an improvement of average image is presented. The average optimal product does not provide an instantaneous view of the area; however it is adequated to study at mesoescale level marine areas under cloudy conditions. It gives a continous vision in time and in space. Both characteristics confer it a great use for observation and monitoring of oceanographic structures. The rate of time variation in the ocean of marine phenomena is in the order of several days so the statistical process does not significantly affect any physical charactheristic. On the contrary, it improve the possibility to catch the permanent signal and remove noisy signals. Validation results are also presented for the proposed product.

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PROBLEM In the last few years farm tourism or agritourism as it is also referred to has enjoyed increasing success because of its generally acknowledged role as a promoter of economic and social development of rural areas. As a consequence, a plethora of studies have been dedicated to this tourist sector, focusing on a variety of issues. Nevertheless, despite the difficulties of many farmers to orient their business towards potential customers, the contribution of the marketing literature has been moderate. PURPOSE This dissertation builds upon studies which advocate the necessity of farm tourism to innovate itself according to the increasingly demanding needs of customers. Henceforth, the purpose of this dissertation is to critically evaluate the level of professionalism reached in the farm tourism market within a marketing approach. METHODOLOGY This dissertation is a cross-country perspective incorporating the marketing of farm tourism studied in Germany and Italy. Hence, the marketing channels of this tourist sector are examined both from the supply and the demand side by means of five exploratory studies. The data collection has been conducted in the timeframe of 2006 to 2009 in manifold ways (online survey, catalogues of industry associations, face-to-face interviews, etc.) according to the purpose of the research of each study project. The data have been analyzed using multivariate statistical analysis. FINDINGS A comprehensive literature review provides the state of the art of the main differences and similarities of farm tourism in the two countries of study. The main findings contained in the empirical chapters provide insights on many aspects of agritourism including how the expectations of farm operators and customers differ, which development scenarios of farm tourism are more likely to meet individuals’ needs, how new technologies can impact the demand for farm tourism, etc. ORIGINALITY/VALUE The value of this study is in the investigation of the process by which farmers’ participation in the development of this sector intersects with consumer consumption patterns. Focusing on this process should allow farm operators and others including related businesses to more efficiently allocate resources.

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Questa tesi descrive alcuni studi di messa a punto di metodi di analisi fisici accoppiati con tecniche statistiche multivariate per valutare la qualità e l’autenticità di oli vegetali e prodotti caseari. L’applicazione di strumenti fisici permette di abbattere i costi ed i tempi necessari per le analisi classiche ed allo stesso tempo può fornire un insieme diverso di informazioni che possono riguardare tanto la qualità come l’autenticità di prodotti. Per il buon funzionamento di tali metodi è necessaria la costruzione di modelli statistici robusti che utilizzino set di dati correttamente raccolti e rappresentativi del campo di applicazione. In questo lavoro di tesi sono stati analizzati oli vegetali e alcune tipologie di formaggi (in particolare pecorini per due lavori di ricerca e Parmigiano-Reggiano per un altro). Sono stati utilizzati diversi strumenti di analisi (metodi fisici), in particolare la spettroscopia, l’analisi termica differenziale, il naso elettronico, oltre a metodiche separative tradizionali. I dati ottenuti dalle analisi sono stati trattati mediante diverse tecniche statistiche, soprattutto: minimi quadrati parziali; regressione lineare multipla ed analisi discriminante lineare.

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Mehr als hundert Jahre archäologischer Forschung haben gezeigt, dass in Mayen in römischer und mittelalterlicher Zeit eines der wichtigsten europäischen Produktionszentren für die Herstellung qualitätsvoller Gebrauchskeramik bestand. Im Rahmen dieser Studie wurden vier Befundkomplexe aus Töpfereisiedlungen vom 4. bis in das 14. Jahrhundert untersucht. Genauer handelt es sich um Keramik aus zwei spätantiken Brennanlagen des 4. Jahrhunderts im Bereich der Flur „Auf der Eich“ an den Straßen „Am Sonnenhang“ und „Frankenstraße“. Weiterhin konnte Material aus zwei Töpferofenfüllungen des 5. bis 9. Jahrhunderts analysiert werden, das 1975 auf dem Grundstück 55 an der „Siegfriedstraße“ in Brennanlagen entdeckt wurde. Hinzu kam Brenngut aus elf Töpferöfen des späten 8. bis 14. Jahrhunderts, welches in den so genannten „Burggärten“ der Genovevaburg von Mayen in den Jahren 1986/87 durch die archäologische Denkmalpflege in Koblenz geborgen wurde. Die mineralogischen Untersuchungen zur Charakterisierung der „Mayener Keramik“ wurden systematisch an den Keramikmaterialien aus diesen Fundstellen durchgeführt. Mittelalterliche Keramik aus Bornheim-Walberberg, Brühl-Eckdorf, Höhr-Grenzhausen, Langerwehe, Frechen, Brühl-Pingsdorf, Paffrath, Raeren, Ratingen-Breitscheid, Siegburg-Seehofstraße, Siegburg-Scherbenhügel, Fredelsloh und Brühl-Badorf konnte für diese Arbeit als Referenzmaterialien ebenfalls untersucht werden. Provenienzanalysen wurden an Keramikproben aus 27 Fundorten, die makroskopisch nach Mayener Ware aussehen, mit mineralogischen Methoden durchgeführt, um sie der Fundregion Mayen eindeutig zuordnen zu können.rnPhasenanalyse, chemische Analyse und thermische Analyse wurden an Keramik sowie Ton durchgeführt. Die Phasenanalyse wurde zur Bestimmung der mineralischen Zusammensetzung von Grundmasse und Magerungsmittel (Röntgendiffraktometrie (XRD), Polarisationsmikroskop, Mikro-Raman-Spektroskopie) verwendet. Die chemische Zusammensetzung wurde durch Röntgenfluoreszenzanalyse (RFA) ermittelt. Elektronenstrahlmikroanalyse (ESMA) und Laser-Massenspektrometrie mit induktiv gekoppeltem Plasma (LA-ICP-MS) wurden bei den Proben, bei denen weniger als 2g Material zur Verfügung standen, eingesetzt. Brennexperimente wurden am originalen Rohstoff der Keramik aus den „Burggärten“ der Genovevaburg durchgeführt. Gebrannter Ton wurde durch Röntgendiffraktometrie (XRD), Infrarotspektroskopie (IR) und Differential-Thermoanalyse (DTA) analysiert. rnAnhand der Messergebnisse lässt sich die Mayener Keramik aus den vier Fundplätzen in zwei Typen zusammenzufassen: der mit Feldspat-reichem Sand gemagerte römische Typ und der mit Quarz-reichem Sand gemagerte mittelalterliche Typ. Die Änderung des Magerungsmittels von Feldspat- zu Quarzsand weist eine technische Entwicklung zu höheren Brenntemperaturen von der Römerzeit bis in das Mittelalter nach. Nach der Untersuchung und dem Vergleich mit den Referenzkeramikgruppen ist festzustellen, dass durch multivariate Statistikanalysen der chemischen Komponenten die Charakterisierung der Keramik und eine Differenzierung zwischen den Keramikgruppen gelingt. Diese Erkenntnisse bildeten die Basis für Provenienzanalysen. 16 Fundorte können durch Provenienzanalyse sicher als Exportregionen der Mayener Ware festgestellt werden. Gemäß den Brennexperimenten lassen sich die chemischen Reaktionen während des Brandprozesses nachvollziehen. Zwei Methoden wurden mittels Röntgendiffraktometrie (XRD) und Differential-Thermoanalyse (DTA) zur Bestimmung der Brenntemperaturen der Keramik modelliert. Die Töpferöfen der „Burggärten“ können nach der Brenntemperatur in zwei Typen zusammengefasst werden: solche mit einer Brenntemperatur unter 1050°C und solche mit einer Brenntemperatur über 1050°C.rn