Ordenaciones de material genético a partir de información multidimensional

Nuevas biotecnologías permiten obtener información para caracterizar materiales genéticos a partir de múltiples marcadores, ya sean éstos moleculares y/o morfológicos. La ordenación del material genético a través de la exploración de patrones de variabilidad multidimensionales se aborda mediante diversas técnicas de análisis multivariado. Las técnicas multivariadas de reducción de dimensión (TRD) y la representación gráfica de las mismas cobran sustancial importancia en la visualización de datos multivariados en espacios de baja dimensión ya que facilitan la interpretación de interrelaciones entre las variables (marcadores) y entre los casos u observaciones bajo análisis. Tanto el Análisis de Componentes Principales, como el Análisis de Coordenadas Principales y el Análisis de Procrustes Generalizado son TRD aplicables a datos provenientes de marcadores moleculares y/o morfológicos. Los Árboles de Mínimo Recorrido y los biplots constituyen técnicas para lograr representaciones geométricas de resultados provenientes de TRD. En este trabajo se describen estas técnicas multivariadas y se ilustran sus aplicaciones sobre dos conjuntos de datos, moleculares y morfológicos, usados para caracterizar material genético fúngico.

Climate change technology transfer to developing countries: evidence analysis and policy recommendations

Developing countries are experiencing unprecedented levels of economic growth. As a result, they will be responsible for most of the future growth in energy demand and greenhouse gas (GHG) emissions. Curbing GHG emissions in developing countries has become one of the cornerstones of a future international agreement under the United Nations Framework Convention for Climate Change (UNFCCC). However, setting caps for developing countries’ GHG emissions has encountered strong resistance in the current round of negotiations. Continued economic growth that allows poverty eradication is still the main priority for most developing countries, and caps are perceived as a constraint to future growth prospects. The development, transfer and use of low-carbon technologies have more positive connotations, and are seen as the potential path towards low-carbon development. So far, the success of the UNFCCC process in improving the levels of technology transfer (TT) to developing countries has been limited. This thesis analyses the causes for such limited success and seeks to improve on the understanding about what constitutes TT in the field of climate change, establish the factors that enable them in developing countries and determine which policies could be implemented to reinforce these factors. Despite the wide recognition of the importance of technology and knowledge transfer to developing countries in the climate change mitigation policy agenda, this issue has not received sufficient attention in academic research. Current definitions of climate change TT barely take into account the perspective of actors involved in actual climate change TT activities, while respective measurements do not bear in mind the diversity of channels through which these happen and the outputs and effects that they convey. Furthermore, the enabling factors for TT in non-BRIC (Brazil, Russia, India, China) developing countries have been seldom investigated, and policy recommendations to improve the level and quality of TTs to developing countries have not been adapted to the specific needs of highly heterogeneous countries, commonly denominated as “developing countries”. This thesis contributes to enriching the climate change TT debate from the perspective of a smaller emerging economy (Chile) and by undertaking a quantitative analysis of enabling factors for TT in a large sample of developing countries. Two methodological approaches are used to study climate change TT: comparative case study analysis and quantitative analysis. Comparative case studies analyse TT processes in ten cases based in Chile, all of which share the same economic, technological and policy frameworks, thus enabling us to draw conclusions on the enabling factors and obstacles operating in TT processes. The quantitative analysis uses three methodologies – principal component analysis, multiple regression analysis and cluster analysis – to assess the performance of developing countries in a number of enabling factors and the relationship between these factors and indicators of TT, as well as to create groups of developing countries with similar performances. The findings of this thesis are structured to provide responses to four main research questions: What constitutes technology transfer and how does it happen? Is it possible to measure technology transfer, and what are the main challenges in doing so? Which factors enable climate change technology transfer to developing countries? And how do different developing countries perform in these enabling factors, and how can differentiated policy priorities be defined accordingly? vi Resumen Los paises en desarrollo estan experimentando niveles de crecimiento economico sin precedentes. Como consecuencia, se espera que sean responsables de la mayor parte del futuro crecimiento global en demanda energetica y emisiones de Gases de Efecto de Invernadero (GEI). Reducir las emisiones de GEI en los paises en desarrollo es por tanto uno de los pilares de un futuro acuerdo internacional en el marco de la Convencion Marco de las Naciones Unidas para el Cambio Climatico (UNFCCC). La posibilidad de compromisos vinculantes de reduccion de emisiones de GEI ha sido rechazada por los paises en desarrollo, que perciben estos limites como frenos a su desarrollo economico y a su prioridad principal de erradicacion de la pobreza. El desarrollo, transferencia y uso de tecnologias bajas en carbono tiene connotaciones mas positivas y se percibe como la via hacia un crecimiento bajo en carbono. Hasta el momento, la UNFCCC ha tenido un exito limitado en la promocion de transferencias de tecnologia (TT) a paises en desarrollo. Esta tesis analiza las causas de este resultado y busca mejorar la comprension sobre que constituye transferencia de tecnologia en el area de cambio climatico, cuales son los factores que la facilitan en paises en desarrollo y que politicas podrian implementarse para reforzar dichos factores. A pesar del extendido reconocimiento sobre la importancia de la transferencia de tecnologia a paises en desarrollo en la agenda politica de cambio climatico, esta cuestion no ha sido suficientemente atendida por la investigacion existente. Las definiciones actuales de transferencia de tecnologia relacionada con la mitigacion del cambio climatico no tienen en cuenta la diversidad de canales por las que se manifiestan o los efectos que consiguen. Los factores facilitadores de TT en paises en desarrollo no BRIC (Brasil, Rusia, India y China) apenas han sido investigados, y las recomendaciones politicas para aumentar el nivel y la calidad de la TT no se han adaptado a las necesidades especificas de paises muy heterogeneos aglutinados bajo el denominado grupo de "paises en desarrollo". Esta tesis contribuye a enriquecer el debate sobre la TT de cambio climatico con la perspectiva de una economia emergente de pequeno tamano (Chile) y el analisis cuantitativo de factores que facilitan la TT en una amplia muestra de paises en desarrollo. Se utilizan dos metodologias para el estudio de la TT a paises en desarrollo: analisis comparativo de casos de estudio y analisis cuantitativo basado en metodos multivariantes. Los casos de estudio analizan procesos de TT en diez casos basados en Chile, para derivar conclusiones sobre los factores que facilitan u obstaculizan el proceso de transferencia. El analisis cuantitativo multivariante utiliza tres metodologias: regresion multiple, analisis de componentes principales y analisis cluster. Con dichas metodologias se busca analizar el posicionamiento de diversos paises en cuanto a factores que facilitan la TT; las relaciones entre dichos factores e indicadores de transferencia tecnologica; y crear grupos de paises con caracteristicas similares que podrian beneficiarse de politicas similares para la promocion de la transferencia de tecnologia. Los resultados de la tesis se estructuran en torno a cuatro preguntas de investigacion: .Que es la transferencia de tecnologia y como ocurre?; .Es posible medir la transferencia de tecnologias de bajo carbono?; .Que factores facilitan la transferencia de tecnologias de bajo carbono a paises en desarrollo? y .Como se puede agrupar a los paises en desarrollo en funcion de sus necesidades politicas para la promocion de la transferencia de tecnologias de bajo carbono?

Latest developments in data analysis tools for disruption prediction and for the exploration of multimachine operational spaces.

In the last years significant efforts have been devoted to the development of advanced data analysis tools to both predict the occurrence of disruptions and to investigate the operational spaces of devices, with the long term goal of advancing the understanding of the physics of these events and to prepare for ITER. On JET the latest generation of the disruption predictor called APODIS has been deployed in the real time network during the last campaigns with the new metallic wall. Even if it was trained only with discharges with the carbon wall, it has reached very good performance, with both missed alarms and false alarms in the order of a few percent (and strategies to improve the performance have already been identified). Since for the optimisation of the mitigation measures, predicting also the type of disruption is considered to be also very important, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been developed. This technique allows automatic classification of an incoming disruption with a success rate of better than 85%. Various other manifold learning tools, particularly Principal Component Analysis and Self Organised Maps, are also producing very interesting results in the comparative analysis of JET and ASDEX Upgrade (AUG) operational spaces, on the route to developing predictors capable of extrapolating from one device to another.

Biodiversidad de frijol (Phaseolus vulgaris L.) en Honduras. Caracterización agromorfológica, molecular y ecogeográfica

En el presente trabajo se ha llevado a cabo un estudio de la biodiversidad del frijol común (Phaseolus vulgaris L.) en Honduras, que es el segundo de los cultivos de granos básicos en importancia. Dicho estudio se ha realizado mediante una caracterización agromorfológica, molecular y ecogeográfica en una selección de 300 accesiones conservadas en el banco de germoplasma ubicado en la Escuela Agrícola Panamericana (EAP) El Zamorano, y que se colectaron en 13 departamentos del país durante el periodo de 1990 a 1994. Estas accesiones fueron colectadas cuatro años antes del acontecimiento del huracán Mitch, el cual a su paso afectó al 96% del área total cultivable en su momento, lo cual nos hace considerar que la biodiversidad de razas locales (landraces) de frijol común existentes in situ fueron severamente afectadas. Los trabajos dirigidos a analizar la biodiversidad de razas locales de frijol común en Honduras son escasos, y este trabajo se constituye como el primero que incluye una amplia muestra a ser estudiada a través de una caracterización en tres aspectos complementarios (agromorfológico, molecular y ecogeográfico). Se evaluaron 32 caracteres agromorfológicos, 12 cuantitativos y 20 cualitativos, en distintas partes de la planta. Se establecieron las correlaciones entre los caracteres agromorfológicos y se elaboró un dendrograma con los mismos, en el que se formaron ocho grupos, en parte relacionados principalmente con los colores y tamaños de la semilla. Mediante el análisis de componentes principales se estudiaron los caracteres de más peso en cada uno de los tres primeros componentes. Asimismo, se estudiaron las correlaciones entre caracteres, siendo las más altas la longitud y anchura de la hoja, días a madurez y a cosecha y longitud y peso de semilla. Por otra parte, el mapa de diversidad agromorfológica mostró la existencia de tres zonas con mayor diversidad: en el oeste (en los departamentos de Santa Bárbara, Lempira y Copán), en el centro-norte (en los departamentos de Francisco Morazán, Yoro y Atlántida) y en el sur (en el departamento de El Paraíso y al sur de Francisco Morazán). Para la caracterización molecular partimos de 12 marcadores de tipo microsatélite, evaluados en 54 accesiones, que fueron elegidas por constituir grupos que compartían un mismo nombre local. Finalmente, se seleccionaron los cuatro microsatélites (BM53, GATS91, BM211 y PV-AT007) que resultaron ser más polimórficos e informativos para el análisis de las 300 accesiones, con los que se detectaron un total de 119 alelos (21 de ellos únicos o privados de accesión) y 256 patrones alélicos diferentes. Para estudiar la estructura y relaciones genéticas en las 300 accesiones se incluyeron en el análisis tres controles o accesiones de referencia, pertenecientes dos de ellas al acervo genético Andino y una al Mesoamericano. En el dendrograma se obtuvieron 25 grupos de accesiones con idénticas combinaciones de alelos. Al comparar este dendrograma con el de caracteres agromorfológicos se observaron diversos grupos con marcada similitud en ambos. Un total de 118 accesiones resultaron ser homogéneas y homocigóticas, a la vez que representativas del grupo de 300 accesiones, por lo que se analizaron con más detalle. El análisis de la estructura genética definió la formación de dos grupos, supuestamente relacionados con los acervos genéticos Andino (48) y Mesoamericano (61), y un reducido número de accesiones (9) que podrían tener un origen híbrido, debido a la existencia de un cierto grado de introgresión entre ambos acervos. La diferenciación genética entre ambos grupos fue del 13,3%. Asimismo, 66 de los 82 alelos detectados fueron privados de grupo, 30 del supuesto grupo Andino y 36 del Mesoamericano. Con relación al mapa de diversidad molecular, presentó una distribución bastante similar al de la diversidad agromorfológica, detectándose también las zonas de mayor diversidad genética en el oeste (en los departamentos de Lempira y Santa Bárbara), en el centro-norte (en los departamentos de Yoro y Atlántida) y en el sur (en el departamento de El Paraíso y al sur de Francisco Morazán). Para la caracterización ecogeográfica se seleccionaron variables de tipo bioclimático (2), geofísico (2) y edáfico (8), y mediante el método de agrupamiento de partición alrededor de los medoides, la combinación de los grupos con cada uno de los tres tipos de variables definió un total de 32 categorías ecogeográficas en el país, detectándose accesiones en 16 de ellas. La distribución de las accesiones previsiblemente esté relacionada con la existencia de condiciones más favorables al cultivo de frijol. En el mapa de diversidad ecogeográfica, nuevamente, se observaron varias zonas con alta diversidad tanto en el oeste, como en el centro-norte y en el sur del país. Como consecuencia del estudio realizado, se concluyó la existencia de una marcada biodiversidad en el material analizado, desde el punto de vista tanto agromorfológico como molecular. Por lo que resulta de gran importancia plantear la conservación de este patrimonio genético tanto ex situ, en bancos de germoplasma, como on farm, en las propias explotaciones de los agricultores del país, siempre que sea posible. ABSTRACT In the present work we have carried out a study of the biodiversity of the common bean (Phaseolus vulgaris L) in Honduras, which is the second of the basic grain crops in importance. This study was conducted through agro-morphological, molecular and ecogeographical characterization of a selection of 300 accessions conserved in the genebank located in the ‘Escuela Agrícola Panamericana (EAP) El Zamorano’ that were collected in 13 departments of the country during the 1990 to 1994 period. These accessions were collected four years before the occurrence of Mitch hurricane, which affected 96% of the total cultivable area at the time, which makes us to consider that the biodiversity of local landraces of common bean existing in situ were severely affected. The work aimed to analyze the biodiversity of local races of common bean in Honduras are scarce, and this work constitutes the first to include a large sample to be studied through a characterization on three complementary aspects (agromorphological, molecular and ecogeographical). Thirty two agromorphological characters, 12 quantitative and 20 qualitative, in various parts of the plant were evaluated. Correlations between agromorphological characters were established and a dendrogram with them was constructed, in which eight groups were formed, in part mainly related to the colors and sizes of the seeds. By principal component analysis the characters with more weight in each of the first three components were studied. Also, correlations between characters were studied, the highest of them being length and leaf width, days to maturity and harvest, and seed length and weight. Moreover, the map of agromorphological diversity showed the existence of three areas with more diversity: the west (departments of Santa Barbara, Copan and Lempira), the center-north (departments of Francisco Morazán, Yoro and Atlántida) and the south (department of El Paraiso and south of Francisco Morazán). For molecular characterization we started with 12 microsatellite markers, evaluated in 54 accessions, which were chosen because they formed groups that shared the same local name. Finally, four microsatellites (BM53, GATS91, BM211 and PV-AT007) were selected for the analysis of 300 accessions, since they were the most polymorphic and informative. They gave a total of 119 alleles (21 of them unique or private for the accession) and 256 different allelic patterns. To study the structure and genetic relationships in the 300 accessions, three controls or accessions of reference were included in the analysis: two of them belonging to the Andean gene pool and one to the Mesoamerican. In the dendrogram, 25 accession groups with identical allele combinations were obtained. Comparing this dendrogram to the obtained with agromorphological characters, several groups with marked similarity in both were observed. A total of 118 accessions were homozygous and homogeneous, while representing the group of 300 accessions, therefore they were analyzed in more detail. The analysis of the genetic structure defined the formation of two groups, supposedly related to the Andean (48) and the Mesoamerican (61) gene pools, and a small number of accessions (9) which may have a hybrid origin, due to the existence of some degree of introgression between both gene pools. Genetic differentiation between both groups was 13.3%. Also, 66 of the 82 detected alleles were private or unique for the group, 30 of the supposed Andean group and 36 of the Mesoamerican. With relation to the map of molecular diversity, it showed a quite similar distribution to the agromorphological, also detecting the areas of greatest genetic diversity in the west (departments of Lempira and Santa Bárbara), in the center-north (departments Atlántida and Yoro) and in the south (departments of El Paraíso and south of Francisco Morazán). For the ecogeographical characterization, bioclimatic (2), geophysical (2) and edaphic (8) variables were selected, and by the method of clustering partition around the medoids, the combination of the groups to each of the three types of variables defined a total of 32 ecogeographical categories in the country, having accessions in 16 of them. The distribution of accessions is likely related to the existence of more favorable conditions for the cultivation of beans. The map of ecogeographical diversity, again, several areas with high diversity both in the west and in the center-north and in the south of the country were observed. As a result of study, the existence of marked biodiversity in the analyzed material was concluded, both from the agromorphological and from the molecular point of view. Consequently it is very important to propose the conservation of this genetic heritage both ex situ, in genebanks, as on farm, in the holdings of the farmers of the country, whenever possible.

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Deformable Template models are first applied to track the inner wall of coronary arteries in intravascular ultrasound sequences, mainly in the assistance to angioplasty surgery. A circular template is used for initializing an elliptical deformable model to track wall deformation when inflating a balloon placed at the tip of the catheter. We define a new energy function for driving the behavior of the template and we test its robustness both in real and synthetic images. Finally we introduce a framework for learning and recognizing spatio-temporal geometric constraints based on Principal Component Analysis (eigenconstraints).

Chemical analysis of powdered metallurgical slags by X-ray fluorescence spectrometry

Slag composition determines the physical and chemical properties as well as the application performance of molten oxide mixtures. Therefore, it is necessary to establish a routine instrumental technique to produce accurate and precise analytical results for better process and production control. In the present paper, a multi-component analysis technique of powdered metallurgical slag samples by X-ray Fluorescence Spectrometer (XRFS) has been demonstrated. This technique provides rapid and accurate results, with minimum sample preparation. It eliminates the requirement for a fused disc, using briquetted samples protected by a layer of Borax(R). While the use of theoretical alpha coefficients has allowed accurate calibrations to be made using fewer standard samples, the application of pseudo-Voight function to curve fitting makes it possible to resolve overlapped peaks in X-ray spectra that cannot be physically separated. The analytical results of both certified reference materials and industrial slag samples measured using the present technique are comparable to those of the same samples obtained by conventional fused disc measurements.

Non-linear principal components analysis: an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia, Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore. three geographical areas with unique environmental characteristics could be identified. Copyright (c) 2005 John Wiley & Sons, Ltd.

Using multivariate analysis to predict the behaviour of soils under effluent irrigation

Onsite wastewater treatment systems aim to assimilate domestic effluent into the environment. Unfortunately failure of such systems is common and inadequate effluent treatment can have serious environmental implications. The capacity of a particular soil to treat wastewater will change over time. The physical properties influence the rate of effluent movement through the soil and its chemical properties dictate the ability to renovate effluent. A research project was undertaken to determine the role that physical and chemical soil properties play in predicting the long-term behaviour of soil under effluent irrigation and to determine if they have a potential function as early indicators of adverse effects of effluent irrigation on treatment sustainability. Principal Component Analysis (PCA) and Cluster Analysis grouped the soils independently of their soil classifications and allowed us to distinguish the most suitable soils for sustainable long term effluent irrigation and determine the most influential soil parameters to characterise them. Multivariate analysis allowed a clear distinction between soils based on the cation exchange capacities. This in turn correlated well with the soil mineralogy. Mixed mineralogy soils in particular sodium or magnesium dominant soils are the most susceptible to dispersion under effluent irrigation. The soil Exchangeable Sodium Percentage (ESP) was identified as a crucial parameter and was highly correlated with percentage clay, electrical conductivity, exchangeable sodium, exchangeable magnesium and low Ca:Mg ratios (less than 0.5).

Validation of multicriteria analysis models

Validation procedures play an important role in establishing the credibility of models, improving their relevance and acceptability. This article reviews the testing of models relevant to environmental and natural resource management with particular emphasis on models used in multicriteria analysis (MCA). Validation efforts for a model used in a MCA catchment management study in North Queensland, Australia, are presented. Determination of face validity is found to be a useful approach in evaluating this model, and sensitivity analysis is useful in checking the stability of the model. (C) 2000 Elsevier Science Ltd. All rights reserved.

Performance analysis using equivariant kernel density estimator in nonlinear mixture

This paper investigates the performance analysis of separation of mutually independent sources in nonlinear models. The nonlinear mapping constituted by an unsupervised linear mixture is followed by an unknown and invertible nonlinear distortion, are found in many signal processing cases. Generally, blind separation of sources from their nonlinear mixtures is rather difficult. We propose using a kernel density estimator incorporated with equivariant gradient analysis to separate the sources with nonlinear distortion. The kernel density estimator parameters of which are iteratively updated to minimize the output independence expressed as a mutual information criterion. The equivariant gradient algorithm has the form of nonlinear decorrelation to perform the convergence analysis. Experiments are proposed to illustrate these results.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.

Mixtures of probabilistic principal component analysers

Principal component analysis (PCA) is one of the most popular techniques for processing, compressing and visualising data, although its effectiveness is limited by its global linearity. While nonlinear variants of PCA have been proposed, an alternative paradigm is to capture data complexity by a combination of local linear PCA projections. However, conventional PCA does not correspond to a probability density, and so there is no unique way to combine PCA models. Previous attempts to formulate mixture models for PCA have therefore to some extent been ad hoc. In this paper, PCA is formulated within a maximum-likelihood framework, based on a specific form of Gaussian latent variable model. This leads to a well-defined mixture model for probabilistic principal component analysers, whose parameters can be determined using an EM algorithm. We discuss the advantages of this model in the context of clustering, density modelling and local dimensionality reduction, and we demonstrate its application to image compression and handwritten digit recognition.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

Understanding U.S. regional linguistic variation with Twitter data analysis

We analyze a Big Data set of geo-tagged tweets for a year (Oct. 2013–Oct. 2014) to understand the regional linguistic variation in the U.S. Prior work on regional linguistic variations usually took a long time to collect data and focused on either rural or urban areas. Geo-tagged Twitter data offers an unprecedented database with rich linguistic representation of fine spatiotemporal resolution and continuity. From the one-year Twitter corpus, we extract lexical characteristics for twitter users by summarizing the frequencies of a set of lexical alternations that each user has used. We spatially aggregate and smooth each lexical characteristic to derive county-based linguistic variables, from which orthogonal dimensions are extracted using the principal component analysis (PCA). Finally a regionalization method is used to discover hierarchical dialect regions using the PCA components. The regionalization results reveal interesting linguistic regional variations in the U.S. The discovered regions not only confirm past research findings in the literature but also provide new insights and a more detailed understanding of very recent linguistic patterns in the U.S.

Thermal imaging as a biometrics approach to facial signature authentication

This dissertation develops an image processing framework with unique feature extraction and similarity measurements for human face recognition in the thermal mid-wave infrared portion of the electromagnetic spectrum. The goals of this research is to design specialized algorithms that would extract facial vasculature information, create a thermal facial signature and identify the individual. The objective is to use such findings in support of a biometrics system for human identification with a high degree of accuracy and a high degree of reliability. This last assertion is due to the minimal to no risk for potential alteration of the intrinsic physiological characteristics seen through thermal infrared imaging. The proposed thermal facial signature recognition is fully integrated and consolidates the main and critical steps of feature extraction, registration, matching through similarity measures, and validation through testing our algorithm on a database, referred to as C-X1, provided by the Computer Vision Research Laboratory at the University of Notre Dame. Feature extraction was accomplished by first registering the infrared images to a reference image using the functional MRI of the Brain’s (FMRIB’s) Linear Image Registration Tool (FLIRT) modified to suit thermal infrared images. This was followed by segmentation of the facial region using an advanced localized contouring algorithm applied on anisotropically diffused thermal images. Thermal feature extraction from facial images was attained by performing morphological operations such as opening and top-hat segmentation to yield thermal signatures for each subject. Four thermal images taken over a period of six months were used to generate thermal signatures and a thermal template for each subject, the thermal template contains only the most prevalent and consistent features. Finally a similarity measure technique was used to match signatures to templates and the Principal Component Analysis (PCA) was used to validate the results of the matching process. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using an Euclidean-based similarity measure showed 88% accuracy in the case of skeletonized signatures and templates, we obtained 90% accuracy for anisotropically diffused signatures and templates. We also employed the Manhattan-based similarity measure and obtained an accuracy of 90.39% for skeletonized and diffused templates and signatures. It was found that an average 18.9% improvement in the similarity measure was obtained when using diffused templates. The Euclidean- and Manhattan-based similarity measure was also applied to skeletonized signatures and templates of 25 subjects in the C-X1 database. The highly accurate results obtained in the matching process along with the generalized design process clearly demonstrate the ability of the thermal infrared system to be used on other thermal imaging based systems and related databases. A novel user-initialization registration of thermal facial images has been successfully implemented. Furthermore, the novel approach at developing a thermal signature template using four images taken at various times ensured that unforeseen changes in the vasculature did not affect the biometric matching process as it relied on consistent thermal features.