OPTIMIZING A SHORT-END ELECTROPHORETICALLY MEDIATED MICRO-ANALYSIS (EMMA) ASSAY FOR CREATININE

In this work electrophoretically mediated micro-analysis (EMMA) is used in conjunction with short end injection to improve the in-capillary Jaffé assay for creatinine. Key advances over prior work include (i) using simulation to ensure intimate overlap of reagent plugs, (ii) using OH- to drive the reaction, (iii) using short-end injection to minimize analysis time and in-line product degradation. The potential-driven overlapping time with the EMMA approach, as well as the borate buffer background electrolyte (BGE) concentration and pH are optimized with the short end approach. The best conditions for short-end analyses would not have been predicted by the prior long end work, owing to a complex interplay of separation time and product degradation rates. Raw peak areas and flow-adjusted peak areas for the Jaffé reaction product (at 505 nm) are used to assess the sensitivity of the short-end EMMA approach. Optimal overlap conditions depend heavily on local conductivity differences within the reagent zone(s), as these differences cause dramatic voltage field differences, which effect reagent overlap dynamics. Simul 5.0, a dynamic simulation program for capillary electrophoresis (CE) systems, is used to understand the ionic boundaries and profiles that give rise to the experimentally obtained data for EMMA analysis. Overall, fast migration of hydroxide ions from the picrate zone makes difficult reagent overlap. In addition, the challenges associated with the simultaneous overlapping of three reagent zones are considered, and experimental results validate the predictions made by the simulation. With one set of “optimized” conditions including OH- (253 mM) as the third reagent zone the response was linear with creatinine concentration (R2 = 0.998) and reproducible over the clinically relevant range (0.08 to 0.1 mM) of standard creatinine concentrations. An LOD (S/N = 3) of 0.02 mM and LOQ (S/N=10) of 0.08 mM were determined. A significant improvement (43%) in assay sensitivity was obtained compared to prior work that considered only two reagents in the overlap.

Towards optimal treatment with growth hormone in short children and adolescents: evidence and theses

Treatment with growth hormone (GH) has become standard practice for replacement in GH-deficient children or pharmacotherapy in a variety of disorders with short stature. However, even today, the reported adult heights achieved often remain below the normal range. In addition, the treatment is expensive and may be associated with long-term risks. Thus, a discussion of the factors relevant for achieving an optimal individual outcome in terms of growth, costs, and risks is required. In the present review, the heterogenous approaches of treatment with GH are discussed, considering the parameters available for an evaluation of the short- and long-term outcomes at different stages of treatment. This discourse introduces the potential of the newly emerging prediction algorithms in comparison to other more conventional approaches for the planning and evaluation of the response to GH. In rare disorders such as those with short stature, treatment decisions cannot easily be deduced from personal experience. An interactive approach utilizing the derived experience from large cohorts for the evaluation of the individual patient and the required decision-making may facilitate the use of GH. Such an approach should also lead to avoiding unnecessary long-term treatment in unresponsive individuals.

An Instrument Design for Space-Based Optical Observation of Space Debris

Currently, observations of space debris are primarily performed with ground-based sensors. These sensors have a detection limit at some centimetres diameter for objects in Low Earth Orbit (LEO) and at about two decimetres diameter for objects in Geostationary Orbit (GEO). The few space-based debris observations stem mainly from in-situ measurements and from the analysis of returned spacecraft surfaces. Both provide information about mostly sub-millimetre-sized debris particles. As a consequence the population of centimetre- and millimetre-sized debris objects remains poorly understood. The development, validation and improvement of debris reference models drive the need for measurements covering the whole diameter range. In 2003 the European Space Agency (ESA) initiated a study entitled “Space-Based Optical Observation of Space Debris”. The first tasks of the study were to define user requirements and to develop an observation strategy for a space-based instrument capable of observing uncatalogued millimetre-sized debris objects. Only passive optical observations were considered, focussing on mission concepts for the LEO, and GEO regions respectively. Starting from the requirements and the observation strategy, an instrument system architecture and an associated operations concept have been elaborated. The instrument system architecture covers the telescope, camera and onboard processing electronics. The proposed telescope is a folded Schmidt design, characterised by a 20 cm aperture and a large field of view of 6°. The camera design is based on the use of either a frame-transfer charge coupled device (CCD), or on a cooled hybrid sensor with fast read-out. A four megapixel sensor is foreseen. For the onboard processing, a scalable architecture has been selected. Performance simulations have been executed for the system as designed, focussing on the orbit determination of observed debris particles, and on the analysis of the object detection algorithms. In this paper we present some of the main results of the study. A short overview of the user requirements and observation strategy is given. The architectural design of the instrument is discussed, and the main tradeoffs are outlined. An insight into the results of the performance simulations is provided.

Differentiating normal hyaline cartilage from post-surgical repair tissue using fast gradient echo imaging in delayed gadolinium-enhanced MRI (dGEMRIC) at 3 Tesla

The purpose was to evaluate the relative glycosaminoglycan (GAG) content of repair tissue in patients after microfracturing (MFX) and matrix-associated autologous chondrocyte transplantation (MACT) of the knee joint with a dGEMRIC technique based on a newly developed short 3D-GRE sequence with two flip angle excitation pulses. Twenty patients treated with MFX or MACT (ten in each group) were enrolled. For comparability, patients from each group were matched by age (MFX: 37.1 +/- 16.3 years; MACT: 37.4 +/- 8.2 years) and postoperative interval (MFX: 33.0 +/- 17.3 months; MACT: 32.0 +/- 17.2 months). The Delta relaxation rate (DeltaR1) for repair tissue and normal hyaline cartilage and the relative DeltaR1 were calculated, and mean values were compared between both groups using an analysis of variance. The mean DeltaR1 for MFX was 1.07 +/- 0.34 versus 0.32 +/- 0.20 at the intact control site, and for MACT, 1.90 +/- 0.49 compared to 0.87 +/- 0.44, which resulted in a relative DeltaR1 of 3.39 for MFX and 2.18 for MACT. The difference between the cartilage repair groups was statistically significant. The new dGEMRIC technique based on dual flip angle excitation pulses showed higher GAG content in patients after MACT compared to MFX at the same postoperative interval and allowed reducing the data acquisition time to 4 min.

THE SOLAR WIND AS A POSSIBLE SOURCE OF FAST TEMPORAL VARIATIONS OF THE HELIOSPHERIC RIBBON

We present a possible source of pickup ions (PUIs) the ribbon observed by the Interstellar Boundary EXplorer (IBEX). We suggest that a gyrating solar wind and PUIs in the ramp and in the near downstream region of the termination shock (TS) could provide a significant source of energetic neutral atoms (ENAs) in the ribbon. A fraction of the solar wind and PUIs are reflected and energized during the first contact with the TS. Some of the solar wind may be reflected propagating toward the Sun but most of the solar wind ions form a gyrating beam-like distribution that persists until it is fully thermalized further downstream. Depending on the strength of the shock, these gyrating distributions can exist for many gyration periods until they are scattered/thermalized due to wave-particle interactions at the TS and downstream in the heliosheath. During this time, ENAs can be produced by charge exchange of interstellar neutral atoms with the gyrating ions. In order to determine the flux of energetic ions, we estimate the solar wind flux at the TS using pressure estimates inferred from in situ measurements. Assuming an average path length in the radial direction of the order of a few AU before the distribution of gyrating ions is thermalized, one can explain a significant fraction of the intensity of ENAs in the ribbon observed by IBEX. With a localized source and such a short integration path, this model would also allow fast time variations of the ENA flux.

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.

Fast Update of Conditional Simulation Ensembles

Gaussian random field (GRF) conditional simulation is a key ingredient in many spatial statistics problems for computing Monte-Carlo estimators and quantifying uncertainties on non-linear functionals of GRFs conditional on data. Conditional simulations are known to often be computer intensive, especially when appealing to matrix decomposition approaches with a large number of simulation points. This work studies settings where conditioning observations are assimilated batch sequentially, with one point or a batch of points at each stage. Assuming that conditional simulations have been performed at a previous stage, the goal is to take advantage of already available sample paths and by-products to produce updated conditional simulations at mini- mal cost. Explicit formulae are provided, which allow updating an ensemble of sample paths conditioned on n ≥ 0 observations to an ensemble conditioned on n + q observations, for arbitrary q ≥ 1. Compared to direct approaches, the proposed formulae proveto substantially reduce computational complexity. Moreover, these formulae explicitly exhibit how the q new observations are updating the old sample paths. Detailed complexity calculations highlighting the benefits of this approach with respect to state-of-the-art algorithms are provided and are complemented by numerical experiments.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

B-Neck: A Distributed and Quiescent Max-Min Fair Algorithm

The problem of fairly distributing the capacity of a network among a set of sessions has been widely studied. In this problem, each session connects via a single path a source and a destination, and its goal is to maximize its assigned transmission rate (i.e., its throughput). Since the links of the network have limited bandwidths, some criterion has to be defined to fairly distribute their capacity among the sessions. A popular criterion is max-min fairness that, in short, guarantees that each session i gets a rate λi such that no session s can increase λs without causing another session s' to end up with a rate λs/ <; λs. Many max-min fair algorithms have been proposed, both centralized and distributed. However, to our knowledge, all proposed distributed algorithms require control data being continuously transmitted to recompute the max-min fair rates when needed (because none of them has mechanisms to detect convergence to the max-min fair rates). In this paper we propose B-Neck, a distributed max-min fair algorithm that is also quiescent. This means that, in absence of changes (i.e., session arrivals or departures), once the max min rates have been computed, B-Neck stops generating network traffic. Quiescence is a key design concept of B-Neck, because B-Neck routers are capable of detecting and notifying changes in the convergence conditions of max-min fair rates. As far as we know, B-Neck is the first distributed max-min fair algorithm that does not require a continuous injection of control traffic to compute the rates. The correctness of B-Neck is formally proved, and extensive simulations are conducted. In them, it is shown that B-Neck converges relatively fast and behaves nicely in presence of sessions arriving and departing.

A comparative study of Monte Carlo-coupled depletion codes applied to a Sodium Fast Reactor design loaded with minor actinides

inor actinides (MAs) transmutation is a main design objective of advanced nuclear systems such as generation IV Sodium Fast Reactors (SFRs). In advanced fuel cycles, MA contents in final high level waste packages are main contributors to short term heat production as well as to long-term radiotoxicity. Therefore, MA transmutation would have an impact on repository designs and would reduce the environment burden of nuclear energy. In order to predict such consequences Monte Carlo (MC) transport codes are used in reactor design tasks and they are important complements and references for routinely used deterministic computational tools. In this paper two promising Monte Carlo transport-coupled depletion codes, EVOLCODE and SERPENT, are used to examine the impact of MA burning strategies in a SFR core, 3600 MWth. The core concept proposal for MA loading in two configurations is the result of an optimization effort upon a preliminary reference design to reduce the reactivity insertion as a consequence of sodium voiding, one of the main concerns of this technology. The objective of this paper is double. Firstly, efficiencies of the two core configurations for MA transmutation are addressed and evaluated in terms of actinides mass changes and reactivity coefficients. Results are compared with those without MA loading. Secondly, a comparison of the two codes is provided. The discrepancies in the results are quantified and discussed.

Slabsim: Simulador de dispositivos ópticos integrados

En los diseños y desarrollos de ingeniería, antes de comenzar la construcción e implementación de los objetivos de un proyecto, es necesario realizar una serie de análisis previos y simulaciones que corroboren las expectativas de la hipótesis inicial, con el fin de obtener una referencia empírica que satisfaga las condiciones de trabajo o funcionamiento de los objetivos de dicho proyecto. A menudo, los resultados que satisfacen las características deseadas se obtienen mediante la iteración de métodos de ensayo y error. Generalmente, éstos métodos utilizan el mismo procedimiento de análisis con la variación de una serie de parámetros que permiten adaptar una tecnología a la finalidad deseada. Hoy en día se dispone de computadoras potentes, así como algoritmos de resolución matemática que permiten resolver de forma veloz y eficiente diferentes tipos de problemas de cálculo. Resulta interesante el desarrollo de aplicaciones que permiten la resolución de éstos problemas de forma rápida y precisa en el análisis y síntesis de soluciones de ingeniería, especialmente cuando se tratan expresiones similares con variaciones de constantes, dado que se pueden desarrollar instrucciones de resolución con la capacidad de inserción de parámetros que definan el problema. Además, mediante la implementación de un código de acuerdo a la base teórica de una tecnología, se puede lograr un código válido para el estudio de cualquier problema relacionado con dicha tecnología. El desarrollo del presente proyecto pretende implementar la primera fase del simulador de dispositivos ópticos Slabsim, en cual se puede representar la distribución de la energía de una onda electromagnética en frecuencias ópticas guiada a través de una una guía dieléctrica plana, también conocida como slab. Este simulador esta constituido por una interfaz gráfica generada con el entorno de desarrollo de interfaces gráficas de usuario Matlab GUIDE, propiedad de Mathworks©, de forma que su manejo resulte sencillo e intuitivo para la ejecución de simulaciones con un bajo conocimiento de la base teórica de este tipo de estructuras por parte del usuario. De este modo se logra que el ingeniero requiera menor intervalo de tiempo para encontrar una solución que satisfaga los requisitos de un proyecto relacionado con las guías dieléctricas planas, e incluso utilizarlo para una amplia diversidad de objetivos basados en esta tecnología. Uno de los principales objetivos de este proyecto es la resolución de la base teórica de las guías slab a partir de métodos numéricos computacionales, cuyos procedimientos son extrapolables a otros problemas matemáticos y ofrecen al autor una contundente base conceptual de los mismos. Por este motivo, las resoluciones de las ecuaciones diferenciales y características que constituyen los problemas de este tipo de estructuras se realizan por estos medios de cálculo en el núcleo de la aplicación, dado que en algunos casos, no existe la alternativa de uso de expresiones analíticas útiles. ABSTRACT. The first step in engineering design and development is an analysis and simulation process which will successfully corroborate the initial hypothesis that was made and find solutions for a particular. In this way, it is possible to obtain empirical evidence which suitably substantiate the purposes of the project. Commonly, the characteristics to reach a particular target are found through iterative trial and error methods. These kinds of methods are based on the same theoretical analysis but with a variation of some parameters, with the objective to adapt the results for a particular aim. At present, powerful computers and mathematical algorithms are available to solve different kinds of calculation problems in a fast and efficient way. Computing application development is useful as it gives a high level of accurate results for engineering analysis and synthesis in short periods of time. This is more notable in cases where the mathematical expressions on a theoretical base are similar but with small variations of constant values. This is due to the ease of adaptation of the computer programming code into a parameter request system that defines a particular solution on each execution. Additionally, it is possible to code an application suitable to simulate any issue related to the studied technology. The aim of the present project consists of the construction of the first stage of an optoelectronics simulator named Slabsim. Slabism is capable of representing the energetic distribution of a light wave guided in the volume of a slab waveguide. The mentioned simulator is made through the graphic user interface development environment Matlab GUIDE, property of Mathworks©. It is designed for an easy and intuitive management by the user to execute simulations with a low knowledge of the technology theoretical bases. With this software it is possible to achieve several aims related to the slab waveguides by the user in low interval of time. One of the main purposes of this project is the mathematical solving of theoretical bases of slab structures through computing numerical analysis. This is due to the capability of adapting its criterion to other mathematical issues and provides a strong knowledge of its process. Based on these advantages, numerical solving methods are used in the core of the simulator to obtain differential and characteristic equations results that become represented on it.

Detección de patrones y anomalías espectrales del terreno mediante espectrometría de imagen de alta resolución : reconocimiento, optimización y evaluación multiescenario

El objeto de esta Tesis doctoral es el desarrollo de una metodologia para la deteccion automatica de anomalias a partir de datos hiperespectrales o espectrometria de imagen, y su cartografiado bajo diferentes condiciones tipologicas de superficie y terreno. La tecnologia hiperespectral o espectrometria de imagen ofrece la posibilidad potencial de caracterizar con precision el estado de los materiales que conforman las diversas superficies en base a su respuesta espectral. Este estado suele ser variable, mientras que las observaciones se producen en un numero limitado y para determinadas condiciones de iluminacion. Al aumentar el numero de bandas espectrales aumenta tambien el numero de muestras necesarias para definir espectralmente las clases en lo que se conoce como Maldicion de la Dimensionalidad o Efecto Hughes (Bellman, 1957), muestras habitualmente no disponibles y costosas de obtener, no hay mas que pensar en lo que ello implica en la Exploracion Planetaria. Bajo la definicion de anomalia en su sentido espectral como la respuesta significativamente diferente de un pixel de imagen respecto de su entorno, el objeto central abordado en la Tesis estriba primero en como reducir la dimensionalidad de la informacion en los datos hiperespectrales, discriminando la mas significativa para la deteccion de respuestas anomalas, y segundo, en establecer la relacion entre anomalias espectrales detectadas y lo que hemos denominado anomalias informacionales, es decir, anomalias que aportan algun tipo de informacion real de las superficies o materiales que las producen. En la deteccion de respuestas anomalas se asume un no conocimiento previo de los objetivos, de tal manera que los pixeles se separan automaticamente en funcion de su informacion espectral significativamente diferenciada respecto de un fondo que se estima, bien de manera global para toda la escena, bien localmente por segmentacion de la imagen. La metodologia desarrollada se ha centrado en la implicacion de la definicion estadistica del fondo espectral, proponiendo un nuevo enfoque que permite discriminar anomalias respecto fondos segmentados en diferentes grupos de longitudes de onda del espectro, explotando la potencialidad de separacion entre el espectro electromagnetico reflectivo y emisivo. Se ha estudiado la eficiencia de los principales algoritmos de deteccion de anomalias, contrastando los resultados del algoritmo RX (Reed and Xiaoli, 1990) adoptado como estandar por la comunidad cientifica, con el metodo UTD (Uniform Targets Detector), su variante RXD-UTD, metodos basados en subespacios SSRX (Subspace RX) y metodo basados en proyecciones de subespacios de imagen, como OSPRX (Orthogonal Subspace Projection RX) y PP (Projection Pursuit). Se ha desarrollado un nuevo metodo, evaluado y contrastado por los anteriores, que supone una variacion de PP y describe el fondo espectral mediante el analisis discriminante de bandas del espectro electromagnetico, separando las anomalias con el algortimo denominado Detector de Anomalias de Fondo Termico o DAFT aplicable a sensores que registran datos en el espectro emisivo. Se han evaluado los diferentes metodos de deteccion de anomalias en rangos del espectro electromagnetico del visible e infrarrojo cercano (Visible and Near Infrared-VNIR), infrarrojo de onda corta (Short Wavelenght Infrared-SWIR), infrarrojo medio (Meadle Infrared-MIR) e infrarrojo termico (Thermal Infrared-TIR). La respuesta de las superficies en las distintas longitudes de onda del espectro electromagnetico junto con su entorno, influyen en el tipo y frecuencia de las anomalias espectrales que puedan provocar. Es por ello que se han utilizado en la investigacion cubos de datos hiperepectrales procedentes de los sensores aeroportados cuya estrategia y diseno en la construccion espectrometrica de la imagen difiere. Se han evaluado conjuntos de datos de test de los sensores AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) y MASTER (MODIS/ASTER Simulator). Se han disenado experimentos sobre ambitos naturales, urbanos y semiurbanos de diferente complejidad. Se ha evaluado el comportamiento de los diferentes detectores de anomalias a traves de 23 tests correspondientes a 15 areas de estudio agrupados en 6 espacios o escenarios: Urbano - E1, Semiurbano/Industrial/Periferia Urbana - E2, Forestal - E3, Agricola - E4, Geologico/Volcanico - E5 y Otros Espacios Agua, Nubes y Sombras - E6. El tipo de sensores evaluados se caracteriza por registrar imagenes en un amplio rango de bandas, estrechas y contiguas, del espectro electromagnetico. La Tesis se ha centrado en el desarrollo de tecnicas que permiten separar y extraer automaticamente pixeles o grupos de pixeles cuya firma espectral difiere de manera discriminante de las que tiene alrededor, adoptando para ello como espacio muestral parte o el conjunto de las bandas espectrales en las que ha registrado radiancia el sensor hiperespectral. Un factor a tener en cuenta en la investigacion ha sido el propio instrumento de medida, es decir, la caracterizacion de los distintos subsistemas, sensores imagen y auxiliares, que intervienen en el proceso. Para poder emplear cuantitativamente los datos medidos ha sido necesario definir las relaciones espaciales y espectrales del sensor con la superficie observada y las potenciales anomalias y patrones objetivos de deteccion. Se ha analizado la repercusion que en la deteccion de anomalias tiene el tipo de sensor, tanto en su configuracion espectral como en las estrategias de diseno a la hora de registrar la radiacion prodecente de las superficies, siendo los dos tipos principales de sensores estudiados los barredores o escaneres de espejo giratorio (whiskbroom) y los barredores o escaneres de empuje (pushbroom). Se han definido distintos escenarios en la investigacion, lo que ha permitido abarcar una amplia variabilidad de entornos geomorfologicos y de tipos de coberturas, en ambientes mediterraneos, de latitudes medias y tropicales. En resumen, esta Tesis presenta una tecnica de deteccion de anomalias para datos hiperespectrales denominada DAFT en su variante de PP, basada en una reduccion de la dimensionalidad proyectando el fondo en un rango de longitudes de onda del espectro termico distinto de la proyeccion de las anomalias u objetivos sin firma espectral conocida. La metodologia propuesta ha sido probada con imagenes hiperespectrales reales de diferentes sensores y en diferentes escenarios o espacios, por lo tanto de diferente fondo espectral tambien, donde los resultados muestran los beneficios de la aproximacion en la deteccion de una gran variedad de objetos cuyas firmas espectrales tienen suficiente desviacion respecto del fondo. La tecnica resulta ser automatica en el sentido de que no hay necesidad de ajuste de parametros, dando resultados significativos en todos los casos. Incluso los objetos de tamano subpixel, que no pueden distinguirse a simple vista por el ojo humano en la imagen original, pueden ser detectados como anomalias. Ademas, se realiza una comparacion entre el enfoque propuesto, la popular tecnica RX y otros detectores tanto en su modalidad global como local. El metodo propuesto supera a los demas en determinados escenarios, demostrando su capacidad para reducir la proporcion de falsas alarmas. Los resultados del algoritmo automatico DAFT desarrollado, han demostrado la mejora en la definicion cualitativa de las anomalias espectrales que identifican a entidades diferentes en o bajo superficie, reemplazando para ello el modelo clasico de distribucion normal con un metodo robusto que contempla distintas alternativas desde el momento mismo de la adquisicion del dato hiperespectral. Para su consecucion ha sido necesario analizar la relacion entre parametros biofisicos, como la reflectancia y la emisividad de los materiales, y la distribucion espacial de entidades detectadas respecto de su entorno. Por ultimo, el algoritmo DAFT ha sido elegido como el mas adecuado para sensores que adquieren datos en el TIR, ya que presenta el mejor acuerdo con los datos de referencia, demostrando una gran eficacia computacional que facilita su implementacion en un sistema de cartografia que proyecte de forma automatica en un marco geografico de referencia las anomalias detectadas, lo que confirma un significativo avance hacia un sistema en lo que se denomina cartografia en tiempo real. The aim of this Thesis is to develop a specific methodology in order to be applied in automatic detection anomalies processes using hyperspectral data also called hyperspectral scenes, and to improve the classification processes. Several scenarios, areas and their relationship with surfaces and objects have been tested. The spectral characteristics of reflectance parameter and emissivity in the pattern recognition of urban materials in several hyperspectral scenes have also been tested. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) and MASTER (MODIS/ASTER Simulator) have been used in this research. It is assumed that there is not prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Several experiments on different scenarios have been designed, analyzing the behavior of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. Results and their consequences in unsupervised classification processes are discussed. Detection of spectral anomalies aims at extracting automatically pixels that show significant responses in relation of their surroundings. This Thesis deals with the unsupervised technique of target detection, also called anomaly detection. Since this technique assumes no prior knowledge about the target or the statistical characteristics of the data, the only available option is to look for objects that are differentiated from the background. Several methods have been developed in the last decades, allowing a better understanding of the relationships between the image dimensionality and the optimization of search procedures as well as the subpixel differentiation of the spectral mixture and its implications in anomalous responses. In other sense, image spectrometry has proven to be efficient in the characterization of materials, based on statistical methods using a specific reflection and absorption bands. Spectral configurations in the VNIR, SWIR and TIR have been successfully used for mapping materials in different urban scenarios. There has been an increasing interest in the use of high resolution data (both spatial and spectral) to detect small objects and to discriminate surfaces in areas with urban complexity. This has come to be known as target detection which can be either supervised or unsupervised. In supervised target detection, algorithms lean on prior knowledge, such as the spectral signature. The detection process for matching signatures is not straightforward due to the complications of converting data airborne sensor with material spectra in the ground. This could be further complicated by the large number of possible objects of interest, as well as uncertainty as to the reflectance or emissivity of these objects and surfaces. An important objective in this research is to establish relationships that allow linking spectral anomalies with what can be called informational anomalies and, therefore, identify information related to anomalous responses in some places rather than simply spotting differences from the background. The development in recent years of new hyperspectral sensors and techniques, widen the possibilities for applications in remote sensing of the Earth. Remote sensing systems measure and record electromagnetic disturbances that the surveyed objects induce in their surroundings, by means of different sensors mounted on airborne or space platforms. Map updating is important for management and decisions making people, because of the fast changes that usually happen in natural, urban and semi urban areas. It is necessary to optimize the methodology for obtaining the best from remote sensing techniques from hyperspectral data. The first problem with hyperspectral data is to reduce the dimensionality, keeping the maximum amount of information. Hyperspectral sensors augment considerably the amount of information, this allows us to obtain a better precision on the separation of material but at the same time it is necessary to calculate a bigger number of parameters, and the precision lowers with the increase in the number of bands. This is known as the Hughes effects (Bellman, 1957) . Hyperspectral imagery allows us to discriminate between a huge number of different materials however some land and urban covers are made up with similar material and respond similarly which produces confusion in the classification. The training and the algorithm used for mapping are also important for the final result and some properties of thermal spectrum for detecting land cover will be studied. In summary, this Thesis presents a new technique for anomaly detection in hyperspectral data called DAFT, as a PP's variant, based on dimensionality reduction by projecting anomalies or targets with unknown spectral signature to the background, in a range thermal spectrum wavelengths. The proposed methodology has been tested with hyperspectral images from different imaging spectrometers corresponding to several places or scenarios, therefore with different spectral background. The results show the benefits of the approach to the detection of a variety of targets whose spectral signatures have sufficient deviation in relation to the background. DAFT is an automated technique in the sense that there is not necessary to adjust parameters, providing significant results in all cases. Subpixel anomalies which cannot be distinguished by the human eye, on the original image, however can be detected as outliers due to the projection of the VNIR end members with a very strong thermal contrast. Furthermore, a comparison between the proposed approach and the well-known RX detector is performed at both modes, global and local. The proposed method outperforms the existents in particular scenarios, demonstrating its performance to reduce the probability of false alarms. The results of the automatic algorithm DAFT have demonstrated improvement in the qualitative definition of the spectral anomalies by replacing the classical model by the normal distribution with a robust method. For their achievement has been necessary to analyze the relationship between biophysical parameters such as reflectance and emissivity, and the spatial distribution of detected entities with respect to their environment, as for example some buried or semi-buried materials, or building covers of asbestos, cellular polycarbonate-PVC or metal composites. Finally, the DAFT method has been chosen as the most suitable for anomaly detection using imaging spectrometers that acquire them in the thermal infrared spectrum, since it presents the best results in comparison with the reference data, demonstrating great computational efficiency that facilitates its implementation in a mapping system towards, what is called, Real-Time Mapping.