32 resultados para NIRS. Bactérias. PCA. SIMCA. PLS-DA
Resumo:
This study examines how structural determinants influence intermediary factors of child health inequities and how they operate through the communities where children live. In particular, we explore individual, family and community level characteristics associated with a composite indicator that quantitatively measures intermediary determinants of early childhood health in Colombia. We use data from the 2010 Colombian Demographic and Health Survey (DHS). Adopting the conceptual framework of the Commission on Social Determinants of Health (CSDH), three dimensions related to child health are represented in the index: behavioural factors, psychosocial factors and health system. In order to generate the weight of the variables and take into account the discrete nature of the data, principal component analysis (PCA) using polychoric correlations are employed in the index construction. Weighted multilevel models are used to examine community effects. The results show that the effect of household’s SES is attenuated when community characteristics are included, indicating the importance that the level of community development may have in mediating individual and family characteristics. The findings indicate that there is a significant variance in intermediary determinants of child health between-community, especially for those determinants linked to the health system, even after controlling for individual, family and community characteristics. These results likely reflect that whilst the community context can exert a greater influence on intermediary factors linked directly to health, in the case of psychosocial factors and the parent’s behaviours, the family context can be more important. This underlines the importance of distinguishing between community and family intervention programmes.
Resumo:
In order to obtain a high-resolution Pleistocene stratigraphy, eleven continuouslycored boreholes, 100 to 220m deep were drilled in the northern part of the PoPlain by Regione Lombardia in the last five years. Quantitative provenanceanalysis (QPA, Weltje and von Eynatten, 2004) of Pleistocene sands was carriedout by using multivariate statistical analysis (principal component analysis, PCA,and similarity analysis) on an integrated data set, including high-resolution bulkpetrography and heavy-mineral analyses on Pleistocene sands and of 250 majorand minor modern rivers draining the southern flank of the Alps from West toEast (Garzanti et al, 2004; 2006). Prior to the onset of major Alpine glaciations,metamorphic and quartzofeldspathic detritus from the Western and Central Alpswas carried from the axial belt to the Po basin longitudinally parallel to theSouthAlpine belt by a trunk river (Vezzoli and Garzanti, 2008). This scenariorapidly changed during the marine isotope stage 22 (0.87 Ma), with the onset ofthe first major Pleistocene glaciation in the Alps (Muttoni et al, 2003). PCA andsimilarity analysis from core samples show that the longitudinal trunk river at thistime was shifted southward by the rapid southward and westward progradation oftransverse alluvial river systems fed from the Central and Southern Alps.Sediments were transported southward by braided river systems as well as glacialsediments transported by Alpine valley glaciers invaded the alluvial plain.Kew words: Detrital modes; Modern sands; Provenance; Principal ComponentsAnalysis; Similarity, Canberra Distance; palaeodrainage
Resumo:
Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)
Resumo:
At CoDaWork'03 we presented work on the analysis of archaeological glass composi-tional data. Such data typically consist of geochemical compositions involving 10-12variables and approximates completely compositional data if the main component, sil-ica, is included. We suggested that what has been termed `crude' principal componentanalysis (PCA) of standardized data often identi ed interpretable pattern in the datamore readily than analyses based on log-ratio transformed data (LRA). The funda-mental problem is that, in LRA, minor oxides with high relative variation, that maynot be structure carrying, can dominate an analysis and obscure pattern associatedwith variables present at higher absolute levels. We investigate this further using sub-compositional data relating to archaeological glasses found on Israeli sites. A simplemodel for glass-making is that it is based on a `recipe' consisting of two `ingredients',sand and a source of soda. Our analysis focuses on the sub-composition of componentsassociated with the sand source. A `crude' PCA of standardized data shows two clearcompositional groups that can be interpreted in terms of di erent recipes being used atdi erent periods, reected in absolute di erences in the composition. LRA analysis canbe undertaken either by normalizing the data or de ning a `residual'. In either case,after some `tuning', these groups are recovered. The results from the normalized LRAare di erently interpreted as showing that the source of sand used to make the glassdi ered. These results are complementary. One relates to the recipe used. The otherrelates to the composition (and presumed sources) of one of the ingredients. It seemsto be axiomatic in some expositions of LRA that statistical analysis of compositionaldata should focus on relative variation via the use of ratios. Our analysis suggests thatabsolute di erences can also be informative
Resumo:
En aquest projecte es presenta l’aplicació per a dispositius mòbils Doppelganger. La seva funció és, a partir d’una fotografia, detectar la cara i mostrar la persona famosa de la nostra base de dades que més s’assembla a la persona en la fotografia. Per la implementació s’han utilitzat algoritmes de visió per computador i d’aprenentatge automàtic com per exemple el PCA i el K-Nearest Neighbor, tot utilitzant llibreries gratuïtes com són les OpenCV.
Resumo:
Los principales objetivos del presente trabajo son la puesta a punto de un método NIR por reflectancia para la determinación del contenido de los principios activos (API) de un preparado farmacéutico comercial y la comparación del efecto que tiene la forma física sobre la que se registra el espectro de las muestras de calibración sobre la sensibilidad y el camino óptico; polvo o comprimidos. El preparado comercial analizado es el Perifem® y los principios activos determinados son el valerato de estradiol y el acetato de medroxiprogesterona. El método utilizado para la preparación de las muestras de calibración ha sido la sobredosificación con API o con una mezcla de excipientes comprimidos comerciales molturados y como procedimiento de calibración se ha utilizado la Regresión Parcial por Mínimos Cuadrados (PLS). Además, se ha desarrollado un método HPLC para ser utilizado como método de referencia. A partir de los resultados obtenidos se puede concluir que la compactación de las muestras aumenta el camino óptico efectivo y, por tanto, la sensibilidad del método analítico.
Resumo:
La qualitat d’un producte elaborat és un factor important, tant pels consumidors, com pels òrgans reguladors que en defineixen normatives cada cop més estrictes. Iniciatives com la del PAT (Process Analytical Technology) en el sector farmacèutic, responen a aquestes necessitats. El PAT afavoreix la implantació de noves tècniques analítiques que facilitin el monitoratge i el control de paràmetres clau in-/on-line durant els processos de producció. En aquest sentit, el NIR-CI (Near Infrarred-Chemical Imaging) podria ser una eina molt útil en la millora de la qualitat de la indústria farmacèutica, ja que aprofita les avantatges del NIR com a tècnica analítica (ràpid, no invasiu, no destructiu) i les aplica a tota la superfície espacial de la mostra. És una tècnica capaç de proporcionar una gran quantitat d’informació, tant espectral com espacial, en una sola imatge. L’objectiu d’aquest treball és avaluar la capacitat de la tècnica NIR-CI, com a eina pel control de paràmetres de qualitat de comprimits farmacèutics. Concretament, s’han analitzat quantitativament la concentració i la distribució dels components (principi actiu i excipients) d’un comprimit farmacèutic amb i sense recobriment. A més, també s’ha determinat el gruix de la pel·lícula de laca de recobriment i la seva distribució a la superfície del comprimit. Per obtenir aquesta informació, es parteix d’imatges NIR-CI hiperespectrals dels comprimits. Per a l’extracció de les dades d’interès s’ha usat l’algoritme PLS en les diferents versions dels softwares Isys 5.0 i Unscrambler 9.8. La versió de l’Isys permet determinar la contribució de cada component pur a cada punt de la imatge, emprant únicament l’espectre del component en estudi. Amb la de l’Unscrambler, en canvi, es construeix un model de calibratge que, a partir d’unes mostres de referència, prediu la distribució del gruix de recobriment sobre la superfície del comprimit.
Resumo:
This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage
Resumo:
The chemical composition of sediments and rocks, as well as their distribution at theMartian surface, represent a long term archive of processes, which have formed theplanetary surface. A survey of chemical compositions by means of Compositional DataAnalysis represents a valuable tool to extract direct evidence for weathering processesand allows to quantify weathering and sedimentation rates. clr-biplot techniques areapplied for visualization of chemical relationships across the surface (“chemical maps”).The variability among individual suites of data is further analyzed by means of clr-PCA,in order to extract chemical alteration vectors between fresh rocks and their crusts andfor an assessment of different source reservoirs accessible to soil formation. Bothtechniques are applied to elucidate the influence of remote weathering by combinedanalysis of several soil forming branches. Vector analysis in the Simplex provides theopportunity to study atmosphere surface interactions, including the role andcomposition of volcanic gases
Technologies de procédé et de contrôle pour réduire la teneur en sel du jambon sec et des saucissons
Resumo:
Dans certains pays européens, les produits carnés élaborés peuvent représenter près de 20% de la consommation journalière de sodium. De ce fait, les industries de la viande tentent de réduire la teneur en sel dans les produits carnés pour répondre, d’une part aux attentes des consommateurs et d’autre part aux demandes des autorités sanitaires. Le système Quick‐Dry‐Slice process (QDS®), couplé avec l’utilisation de sels substituant le chlorure de sodium (NaCl), a permis de fabriquer, avec succès, des saucisses fermentées à basse teneur en sel en réduisant le cycle de fabrication et sans ajout de NaCl supplémentaire. Les technologies de mesure en ligne non destructives, comme les rayons X et l’induction électromagnétique, permettent de classifier les jambons frais suivant leur teneur en gras, un paramètre crucial pour adapter la durée de l’étape de salaison. La technologie des rayons X peut aussi être utilisée pour estimer la quantité de sel incorporée pendant la salaison. L’information relative aux teneurs en sel et en gras est importante pour optimiser le processus d’élaboration du jambon sec en réduisant la variabilité de la teneur en sel entre les lots et dans un même lot, mais aussi pour réduire la teneur en sel du produit final. D’autres technologies comme la spectroscopie en proche infrarouge (NIRS) ou spectroscopie microondes sont aussi utiles pour contrôler le processus d’élaboration et pour caractériser et classifier les produits carnés élaborés, selon leur teneur en sel. La plupart de ces technologies peuvent être facilement appliquées en ligne dans l’industrie afin de contrôler le processus de fabrication et d’obtenir ainsi des produits carnés présentant les caractéristiques recherchées.
Resumo:
Customer satisfaction and retention are key issues for organizations in today’s competitive market place. As such, much research and revenue has been invested in developing accurate ways of assessing consumer satisfaction at both the macro (national) and micro (organizational) level, facilitating comparisons in performance both within and between industries. Since the instigation of the national customer satisfaction indices (CSI), partial least squares (PLS) has been used to estimate the CSI models in preference to structural equation models (SEM) because they do not rely on strict assumptions about the data. However, this choice was based upon some misconceptions about the use of SEM’s and does not take into consideration more recent advances in SEM, including estimation methods that are robust to non-normality and missing data. In this paper, both SEM and PLS approaches were compared by evaluating perceptions of the Isle of Man Post Office Products and Customer service using a CSI format. The new robust SEM procedures were found to be advantageous over PLS. Product quality was found to be the only driver of customer satisfaction, while image and satisfaction were the only predictors of loyalty, thus arguing for the specificity of postal services
Resumo:
Context.LS 5039 has been observed with several X-ray instruments so far showing quite steady emission in the long term and no signatures of accretion disk. The source also presents X-ray variability at orbital timescales in flux and photon index. The system harbors an O-type main sequence star with moderate mass-loss. At present, the link between the X-rays and the stellar wind is unclear. Aims.We study the X-ray fluxes, spectra, and absorption properties of LS 5039 at apastron and periastron passages during an epoch of enhanced stellar mass-loss, and the long term evolution of the latter in connection with the X-ray fluxes. Methods.New XMM-Newton observations were performed around periastron and apastron passages in September 2005, when the stellar wind activity was apparently higher. April 2005 Chandra observations on LS 5039 were revisited. Moreover, a compilation of H EW data obtained since 1992, from which the stellar mass-loss evolution can be approximately inferred, was carried out. Results.XMM-Newton observations show higher and harder emission around apastron than around periastron. No signatures of thermal emission or a reflection iron line indicating the presence of an accretion disk are found in the spectrum, and the hydrogen column density () is compatible with being the same in both observations and consistent with the interstellar value. 2005 Chandra observations show a hard X-ray spectrum, and possibly high fluxes, although pileup effects preclude conclusive results from being obtained. The H EW shows yearly variations of 10%, and does not seem to be correlated with X-ray fluxes obtained at similar phases, unlike what is expected in the wind accretion scenario. Conclusions.2005 XMM-Newton and Chandra observations are consistent with 2003 RXTE/PCA results, namely moderate flux and spectral variability at different orbital phases. The constancy of the seems to imply that either the X-ray emitter is located at 1012 cm from the compact object, or the density in the system is 3 to 27 times smaller than that predicted by a spherical symmetric wind model. We suggest that the multiwavelength non-thermal emission of LS 5039 is related to the observed extended radio jets and is unlikely to be produced inside the binary system.
Resumo:
Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.
Resumo:
A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.
Resumo:
The correlation between the species composition of pasture communities and soil properties in Plana de Vic has been studied using two multivariate methods, Correspondence Analysis (CA) for the vegetation data and Principal Component Analysis (PCA) for the soil data. To analyse the pastures, we took 144 vegetation relevés (comprising 201 species) that have been classified into 10 phytocoenological communities elsewhere. Most of these communities are almost entirely built up by perennials, ranging from xerophilous, clearly Mediterranean, to mesophilous, related to medium-European pastures, but a few occurring in shallow soils are dominated by therophytes. As for the soil properties, we analysed texture, pH, depth, bulk density, organic matter, C/N ratio and the carbonates content of 25 samples, correspondingto representative relevés of the communities studied.