Monitorización de estructuras aeronáuticas mediante técnicas de inteligencia artificial

Una de las barreras para la aplicación de las técnicas de monitorización de la integridad estructural (SHM) basadas en ondas elásticas guiadas (GLW) en aeronaves es la influencia perniciosa de las condiciones ambientales y de operación (EOC). En esta tesis se ha estudiado dicha influencia y la compensación de la misma, particularizando en variaciones del estado de carga y temperatura. La compensación de dichos efectos se fundamenta en Redes Neuronales Artificiales (ANN) empleando datos experimentales procesados con la Transformada Chirplet. Los cambios en la geometría y en las propiedades del material respecto al estado inicial de la estructura (lo daños) provocan cambios en la forma de onda de las GLW (lo que denominamos característica sensible al daño o DSF). Mediante técnicas de tratamiento de señal se puede buscar una relación entre dichas variaciones y los daños, esto se conoce como SHM. Sin embargo, las variaciones en las EOC producen también cambios en los datos adquiridos relativos a las GLW (DSF) que provocan errores en los algoritmos de diagnóstico de daño (SHM). Esto sucede porque las firmas de daño y de las EOC en la DSF son del mismo orden. Por lo tanto, es necesario cuantificar y compensar el efecto de las EOC sobre la GLW. Si bien existen diversas metodologías para compensar los efectos de las EOC como por ejemplo “Optimal Baseline Selection” (OBS) o “Baseline Signal Stretching” (BSS), estas, se emplean exclusivamente en la compensación de los efectos térmicos. El método propuesto en esta tesis mezcla análisis de datos experimentales, como en el método OBS, y modelos basados en Redes Neuronales Artificiales (ANN) que reemplazan el modelado físico requerido por el método BSS. El análisis de datos experimentales consiste en aplicar la Transformada Chirplet (CT) para extraer la firma de las EOC sobre la DSF. Con esta información, obtenida bajo diversas EOC, se entrena una ANN. A continuación, la ANN actuará como un interpolador de referencias de la estructura sin daño, generando información de referencia para cualquier EOC. La comparación de las mediciones reales de la DSF con los valores simulados por la ANN, dará como resultado la firma daño en la DSF, lo que permite el diagnóstico de daño. Este esquema se ha aplicado y verificado, en diversas EOC, para una estructura unidimensional con un único camino de daño, y para una estructura representativa de un fuselaje de una aeronave, con curvatura y múltiples elementos rigidizadores, sometida a un estado de cargas complejo, con múltiples caminos de daños. Los efectos de las EOC se han estudiado en detalle en la estructura unidimensional y se han generalizado para el fuselaje, demostrando la independencia del método respecto a la configuración de la estructura y el tipo de sensores utilizados para la adquisición de datos GLW. Por otra parte, esta metodología se puede utilizar para la compensación simultánea de una variedad medible de EOC, que afecten a la adquisición de datos de la onda elástica guiada. El principal resultado entre otros, de esta tesis, es la metodología CT-ANN para la compensación de EOC en técnicas SHM basadas en ondas elásticas guiadas para el diagnóstico de daño. ABSTRACT One of the open problems to implement Structural Health Monitoring techniques based on elastic guided waves in real aircraft structures at operation is the influence of the environmental and operational conditions (EOC) on the damage diagnosis problem. This thesis deals with the compensation of these environmental and operational effects, specifically, the temperature and the external loading, by the use of the Chirplet Transform working with Artificial Neural Networks. It is well known that the guided elastic wave form is affected by the damage appearance (what is known as the damage sensitive feature or DSF). The DSF is modified by the temperature and by the load applied to the structure. The EOC promotes variations in the acquired data (DSF) and cause mistakes in damage diagnosis algorithms. This effect promotes changes on the waveform due to the EOC variations of the same order than the damage occurrence. It is difficult to separate both effects in order to avoid damage diagnosis mistakes. Therefore it is necessary to quantify and compensate the effect of EOC over the GLW forms. There are several approaches to compensate the EOC effects such as Optimal Baseline Selection (OBS) or Baseline Signal Stretching (BSS). Usually, they are used for temperature compensation. The new method proposed here mixes experimental data analysis, as in the OBS method, and Artificial Neural Network (ANN) models to replace the physical modelling which involves the BSS method. The experimental data analysis studied is based on apply the Chirplet Transform (CT) to extract the EOC signature on the DSF. The information obtained varying EOC is employed to train an ANN. Then, the ANN will act as a baselines interpolator of the undamaged structure. The ANN generates reference information at any EOC. By comparing real measurements of the DSF against the ANN simulated values, the damage signature appears clearly in the DSF, enabling an accurate damage diagnosis. This schema has been applied in a range of EOC for a one-dimensional structure containing single damage path and two dimensional real fuselage structure with stiffener elements and multiple damage paths. The EOC effects tested in the one-dimensional structure have been generalized to the fuselage showing its independence from structural arrangement and the type of sensors used for GLW data acquisition. Moreover, it can be used for the simultaneous compensation of a variety of measurable EOC, which affects the guided wave data acquisition. The main result, among others, of this thesis is the CT-ANN methodology for the compensation of EOC in GLW based SHM technique for damage diagnosis.

O agente comunitário e o usuário de álcool: discursos sobre a concepção e a assistência na Atenção Básica

Estima-se que 52% da população mundial faz uso de álcool, sendo a droga mais consumida no mundo. Ao usuário, o álcool torna-se prejudicial devido às consequências nos níveis biológicos, sociais e funcionais. Assim, a redução do uso abusivo da substância é um dos objetivos da Organização Mundial de Saúde (OMS) e uma das prioridades na agenda de saúde pública mundial. No Brasil, a Política do Ministério da Saúde para a Atenção Integral aos Usuários de Álcool e Outras Drogas teve como objetivo a criação de uma rede de atenção integral a eles - a RAPS (Rede de Atenção Psicossocial). A RAPS é considerada um grande avanço da Reforma Psiquiátrica, já que integra os diversos pontos de atenção disponíveis no Sistema Único de Saúde (SUS). Um dos pontos da RAPS é a Atenção Básica (AB), que através da atuação das equipes da Estratégia Saúde da Família (ESF) tem a possibilidade de monitoração, prevenção do uso e colaboração na reinserção social dos usuários de álcool e outras drogas devido à proximidade e criação de vínculo entre o serviço e usuário. Para que o vínculo seja estabelecido o Agente Comunitário de Saúde (ACS) é a peça fundamental, visto que conhece a comunidade e reconhece suas necessidades, além de ser a figura que medeia as relações entre a equipe de saúde e os usuários. Assim sendo, o objetivo deste estudo foi descrever e analisar o discurso de ACS sobre o uso de álcool e a assistência prestada na AB. Trata-se de um estudo qualitativo de teor descritivo, cuja pesquisa ocorreu em cinco municípios da região central do Estado de Santa Catarina. Foram realizadas entrevistas semiestruturadas, analisadas através do método da Análise de Conteúdo. A análise das entrevistas resultou na formulação de duas categorias e quatro subcategorias empíricas. Os resultados evidenciaram que os ACS percebem o consumo de álcool como inerente a população em virtude da cultura caracterizada pelo consumo habitual e festivo da droga. Eles percebem que o uso do álcool torna-se um problema quanto à definição social atribuída pela comunidade, ressaltando as consequências para a família e outras perdas vivenciadas pelos usuários com base nas repercussões sociais. Quanto à assistência prestada por eles aos usuários de álcool, os resultados indicaram uma prática desprovida de instrumentos ou habilidades para a abordagem adequada do uso, evidenciando uma prática infundada pelos ACS. A prática está pautada também nas crenças em relação aos usuários de álcool, que estão muito ligadas aos estigmas relacionados a estes usuários em geral e não em evidências científicas. Conclui-se que a partir do conhecimento das percepções e práticas deste profissional, é possível direcionar ações que potencialize a prática dos ACS, já que são profissionais com grandes possibilidades de atuação diante da prevenção e tratamento do abuso de álcool e reabilitação social do usuário

Revisando el uso de grupos focalizados en la investigación social

Las reflexiones metodológicas sobre grupos focalizados (GF) de este artículo tienen como punto de partida una investigación con sectores medios del Área Metropolitana de Buenos Aires. El estudio de referencia aborda los discursos y prácticas de cuidado de la salud en el escenario contemporáneo caracterizado por la diversificación de especialistas, la creciente cobertura mediática de recomendaciones sobre la vida sana y el bienestar, la implementación de políticas públicas de promoción de la salud, y el crecimiento de la industria de productos y servicios vinculados con la temática. El objetivo del artículo es reflexionar, a partir de nuestra experiencia de investigación, sobre dos aspectos que han recibido especial atención en la literatura metodológica más reciente: los criterios para componer los grupos y sus consecuencias para la dinámica de las conversaciones grupales, y las estrategias para dar cuenta de la interacción grupal en el análisis de los datos. En este último eje exploramos el potencial de los GF para observar el trabajo identitario vinculado con el cuidado de la salud. Enmarcamos nuestro estudio y las decisiones metodológicas tomadas en los debates actuales sobre la variedad de usos de los GF.

BOMEX synoptic weather atlas /

Mode of access: Internet.

Revisando el uso de grupos focalizados en la investigación social

Las reflexiones metodológicas sobre grupos focalizados (GF) de este artículo tienen como punto de partida una investigación con sectores medios del Área Metropolitana de Buenos Aires. El estudio de referencia aborda los discursos y prácticas de cuidado de la salud en el escenario contemporáneo caracterizado por la diversificación de especialistas, la creciente cobertura mediática de recomendaciones sobre la vida sana y el bienestar, la implementación de políticas públicas de promoción de la salud, y el crecimiento de la industria de productos y servicios vinculados con la temática. El objetivo del artículo es reflexionar, a partir de nuestra experiencia de investigación, sobre dos aspectos que han recibido especial atención en la literatura metodológica más reciente: los criterios para componer los grupos y sus consecuencias para la dinámica de las conversaciones grupales, y las estrategias para dar cuenta de la interacción grupal en el análisis de los datos. En este último eje exploramos el potencial de los GF para observar el trabajo identitario vinculado con el cuidado de la salud. Enmarcamos nuestro estudio y las decisiones metodológicas tomadas en los debates actuales sobre la variedad de usos de los GF.

Sea-surface temperature and salinity reconstruction for sediment core GeoB5844-2

We present high-resolution paleoceanographic records of surface and deep water conditions within the northern Red Sea covering the last glacial maximum and termination I using alkenone paleothermometry, stable oxygen isotopes, and sediment compositional data. Paleoceanographic records in the restricted desert-surrounded northern Red Sea are strongly affected by the stepwise sea level rise and appear to record and amplify well-known millennial-scale climate events from the North Atlantic realm. During the last glacial maximum (LGM), sea surface temperatures were about 4°C cooler than the late Holocene. Pronounced coolings associated with Heinrich event 1 (~2°C below the LGM level) and the Younger Dryas imply strong atmospheric teleconnections to the North Atlantic. Owing to the restricted exchange with the Indian Ocean, Red Sea salinity is particularly sensitive to changes in global sea level. Paleosalinities exceeded 50 psu during the LGM. A pronounced freshening of the surface waters is associated with the meltwater peaks MWP1a and MWP1b owing to an increased surface-near inflow of "normal" saline water from the Indian Ocean. Vertical delta18O gradients are also increased during these phases, indicating stronger surface water stratification. The combined effect of deglacial changes in sea surface temperature and salinity on water column stratification initiated the formation of two sapropel layers, which were deposited under almost anoxic condition in a stagnant water body.

Web-based museum trails on PDAs for university-level design students: Design and evaluation

This paper describes the development and evaluation of web-based museum trails for university-level design students to access on handheld devices in the Victoria and Albert Museum (V&A) in London. The trails offered students a range of ways of exploring the museum environment and collections, some encouraging students to interpret objects and museum spaces in lateral and imaginative ways, others more straightforwardly providing context and extra information. In a three-stage qualitative evaluation programme, student feedback showed that overall the trails enhanced students’ knowledge of, interest in, and closeness to the objects. However, the trails were only partially successful from a technological standpoint due to device and network problems. Broader findings suggest that technology has a key role to play in helping to maintain the museum as a learning space which complements that of universities as well as schools. This research informed my other work in visitor-constructed learning trails in museums, specifically in the theoretical approach to data analysis used, in the research design, and in informing ways to structure visitor experiences in museums. It resulted in a conference presentation, and more broadly informed my subsequent teaching practice.

Utilisation de l'indicateur chlorophyllien au SPAD pour un diagnostic de précision de l'état d'équilibre nutritif d'un champ de pommes de terre au Québec

La pomme de terre est l’une des cultures les plus exigeantes en engrais et elle se cultive généralement sur des sols légers ayant de faibles réserves en N, P, K, Ca et Mg. Ces cinq éléments sont essentiels à la croissance des plants, à l’atteinte des bons rendements et à l’obtention de bonne qualité des tubercules de pomme de terre à la récolte et à l’entreposage. La recherche d’un équilibre entre ces cinq éléments constitue l’un des défis de pratiques agricoles de précision. La collecte de 168 échantillons de feuilles de pommes de terre selon une grille de 40 m × 60 m (densité d’échantillonnage de 2,9 échantillons ha-1) dans un champ de pommes de terre de 54 ha au Saguenay-Lac-Saint-Jean et la détermination de leur teneur en N, P, K, Ca et Mg au stade début floraison, jumelée à une lecture de l’indice de chlorophylle avec SPAD-502, a permis d’établir les faits suivants : parmi tous les indicateurs de diagnostic foliaire selon les 3 approches connues VMC, DRIS et CND, le contraste logarithmique entre les deux éléments nutritifs type anioniques (N et P) vs les trois éléments type cationiques (K, Ca et Mg), noté ilr (log ratio isométrique) du coda (Compositional Data Analysis) est l’indicateur le plus fortement relié à la lecture SPAD-502 (r=0,77). L’étude géostatique spatiale appliquée au Coda a montré une grande similitude entre le CND-ilr (anions vs cations) et la lecture SPAD-502. Ce CND-ilr devrait être interprété en termes de fertilisation de démarrage (N+P), en lien avec les apports des cations sous forme d’engrais (K, Ca et Mg) ou d’amendement (Ca et Mg).

Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data.Many of the issues that are discussed with reference to the statistical analysis of compositionaldata have a natural counterpart in the construction of a Bayesian statistical model for categoricaldata.This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986)in his seminal book on compositional data. Particular emphasis is put on the problem of whatparameterization to use

Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data. Many of the issues that are discussed with reference to the statistical analysis of compositional data have a natural counterpart in the construction of a Bayesian statistical model for categorical data. This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986) in his seminal book on compositional data. Particular emphasis is put on the problem of what parameterization to use

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Analysis of Consumption Data to Detect Commercial Losses Using Performance Evaluation Methods in a Smart Grid

Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Comparing correspondence analysis and the log-ratio alternative for representing categorical data

We compare correspondance análisis to the logratio approach based on compositional data. We also compare correspondance análisis and an alternative approach using Hellinger distance, for representing categorical data in a contingency table. We propose a coefficient which globally measures the similarity between these approaches. This coefficient can be decomposed into several components, one component for each principal dimension, indicating the contribution of the dimensions to the difference between the two representations. These three methods of representation can produce quite similar results. One illustrative example is given

Compositional analysis of archaeological glasses

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