Prognostic and diagnostic value of EEG signal coupling measures in coma.

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

(Table 1) Lithofacies interpretation and distribution in sediment core CRP-3

Seven hundred and nineteen samples from throughout the Cainozoic section in CRP-3 were analysed by a Malvern Mastersizes laser particle analyser, in order to derive a stratigraphic distribution of grain-size parameters downhole. Entropy analysis of these data (using the method of Woolfe & Michibayashi, 1995) allowed recognition of four groups of samples, each group characterised by a distinctive grain-size distribution. Group 1, which shows a multi-modal distribution, corresponds to mudrocks, interbedded mudrock/sandstone facies, muddy sandstones and diamictites. Group 2, with a sand-grade mode but showing wide dispersion of particle size, corresponds to muddy sandstones, a few cleaner sandstones and some conglomerates. Group 3 and Group 4 are also sand-dominated, with better grain-size sorting, and correspond to clean, well-washed sandstones of varying mean grain-size (medium and fine modes, respectively). The downhole disappearance of Group 1, and dominance of Groups 3 and 4 reflect a concomitant change from mudrock- and diamictite-rich lithology to a section dominated by clean, well-washed sandstones with minor conglomerates. Progressive downhole increases in percentage sand and principal mode also reflect these changes. Significant shifts in grain-size parameters and entropy group membership were noted across sequence boundaries and seismic reflectors, as recognised in other studies.

MIRACLE’s Ad-Hoc and Geographical IR Approaches for CLEF 2006

This paper presents the 2006 Miracle team’s approaches to the Ad-Hoc and Geographical Information Retrieval tasks. A first set of runs was obtained using a set of basic components. Then, by putting together special combinations of these runs, an extended set was obtained. With respect to previous campaigns some improvements have been introduced in our system: an entity recognition prototype is integrated in our tokenization scheme, and the performance of our indexing and retrieval engine has been improved. For GeoCLEF, we tested retrieving using geo-entity and textual references separately, and then combining them with different approaches.

Robustness and Recoverability in Transport Logistics

Abstract Transport is the foundation of any economy: it boosts economic growth, creates wealth, enhances trade, geographical accessibility and the mobility of people. Transport is also a key ingredient for a high quality of life, making places accessible and bringing people together. The future prosperity of our world will depend on the ability of all of its regions to remain fully and competitively integrated in the world economy. Efficient transport is vital in making this happen. Operations research can help in efficiently planning the design and operating transport systems. Planning and operational processes are fields that are rich in combinatorial optimization problems. These problems can be analyzed and solved through the application of mathematical models and optimization techniques, which may lead to an improvement in the performance of the transport system, as well as to a reduction in the time required for solving these problems. The latter aspect is important, because it increases the flexibility of the system: the system can adapt in a faster way to changes in the environment (i.e.: weather conditions, crew illness, failures, etc.). These disturbing changes (called disruptions) often enforce the schedule to be adapted. The direct consequences are delays and cancellations, implying many schedule adjustments and huge costs. Consequently, robust schedules and recovery plans must be developed in order to fight against disruptions. This dissertation makes contributions to two different fields: rail and air applications. Robust planning and recovery methods are presented. In the field of railway transport we develop several mathematical models which answer to RENFE’s (the major railway operator in Spain) needs: 1. We study the rolling stock assignment problem: here, we introduce some robust aspects in order to ameliorate some operations which are likely to fail. Once the rolling stock assignment is known, we propose a robust routing model which aims at identifying the train units’ sequences while minimizing the expected delays and human resources needed to perform the sequences. 2. It is widely accepted that the sequential solving approach produces solutions that are not global optima. Therefore, we develop an integrated and robust model to determine the train schedule and rolling stock assignment. We also propose an integrated model to study the rolling stock circulations. Circulations are determined by the rolling stock assignment and routing of the train units. 3. Although our aim is to develop robust plans, disruptions will be likely to occur and recovery methods will be needed. Therefore, we propose a recovery method which aims to recover the train schedule and rolling stock assignment in an integrated fashion all while considering the passenger demand. In the field of air transport we develop several mathematical models which answer to IBERIA’s (the major airline in Spain) needs: 1. We look at the airline-scheduling problem and develop an integrated approach that optimizes schedule design, fleet assignment and passenger use so as to reduce costs and create fewer incompatibilities between decisions. Robust itineraries are created to ameliorate misconnected passengers. 2. Air transport operators are continuously facing competition from other air operators and different modes of transport (e.g., High Speed Rail). Consequently, airline profitability is critically influenced by the airline’s ability to estimate passenger demands and construct profitable flight schedules. We consider multi-modal competition including airline and rail, and develop a new approach that estimates the demand associated with a given schedule; and generates airline schedules and fleet assignments using an integrated schedule design and fleet assignment optimization model that captures the impacts of schedule decisions on passenger demand.

Aerodynamic Optimization of the Nose Shape of a High-speed Train

La influencia de la aerodinámica en el diseño de los trenes de alta velocidad, unida a la necesidad de resolver nuevos problemas surgidos con el aumento de la velocidad de circulación y la reducción de peso del vehículo, hace evidente el interés de plantear un estudio de optimización que aborde tales puntos. En este contexto, se presenta en esta tesis la optimización aerodinámica del testero de un tren de alta velocidad, llevada a cabo mediante el uso de métodos de optimización avanzados. Entre estos métodos, se ha elegido aquí a los algoritmos genéticos y al método adjunto como las herramientas para llevar a cabo dicha optimización. La base conceptual, las características y la implementación de los mismos se detalla a lo largo de la tesis, permitiendo entender los motivos de su elección, y las consecuencias, en términos de ventajas y desventajas que cada uno de ellos implican. El uso de los algorimos genéticos implica a su vez la necesidad de una parametrización geométrica de los candidatos a óptimo y la generación de un modelo aproximado que complementa al método de optimización. Estos puntos se describen de modo particular en el primer bloque de la tesis, enfocada a la metodología seguida en este estudio. El segundo bloque se centra en la aplicación de los métodos a fin de optimizar el comportamiento aerodinámico del tren en distintos escenarios. Estos escenarios engloban los casos más comunes y también algunos de los más exigentes a los que hace frente un tren de alta velocidad: circulación en campo abierto con viento frontal o viento lateral, y entrada en túnel. Considerando el caso de viento frontal en campo abierto, los dos métodos han sido aplicados, permitiendo una comparación de las diferentes metodologías, así como el coste computacional asociado a cada uno, y la minimización de la resistencia aerodinámica conseguida en esa optimización. La posibilidad de evitar parametrizar la geometría y, por tanto, reducir el coste computacional del proceso de optimización es la característica más significativa de los métodos adjuntos, mientras que en el caso de los algoritmos genéticos se destaca la simplicidad y capacidad de encontrar un óptimo global en un espacio de diseño multi-modal o de resolver problemas multi-objetivo. El caso de viento lateral en campo abierto considera nuevamente los dos métoxi dos de optimización anteriores. La parametrización se ha simplificado en este estudio, lo que notablemente reduce el coste numérico de todo el estudio de optimización, a la vez que aún recoge las características geométricas más relevantes en un tren de alta velocidad. Este análisis ha permitido identificar y cuantificar la influencia de cada uno de los parámetros geométricos incluídos en la parametrización, y se ha observado que el diseño de la arista superior a barlovento es fundamental, siendo su influencia mayor que la longitud del testero o que la sección frontal del mismo. Finalmente, se ha considerado un escenario más a fin de validar estos métodos y su capacidad de encontrar un óptimo global. La entrada de un tren de alta velocidad en un túnel es uno de los casos más exigentes para un tren por el pico de sobrepresión generado, el cual afecta a la confortabilidad del pasajero, así como a la estabilidad del vehículo y al entorno próximo a la salida del túnel. Además de este problema, otro objetivo a minimizar es la resistencia aerodinámica, notablemente superior al caso de campo abierto. Este problema se resuelve usando algoritmos genéticos. Dicho método permite obtener un frente de Pareto donde se incluyen el conjunto de óptimos que minimizan ambos objetivos. ABSTRACT Aerodynamic design of trains influences several aspects of high-speed trains performance in a very significant level. In this situation, considering also that new aerodynamic problems have arisen due to the increase of the cruise speed and lightness of the vehicle, it is evident the necessity of proposing an optimization study concerning the train aerodynamics. Thus, the aerodynamic optimization of the nose shape of a high-speed train is presented in this thesis. This optimization is based on advanced optimization methods. Among these methods, genetic algorithms and the adjoint method have been selected. A theoretical description of their bases, the characteristics and the implementation of each method is detailed in this thesis. This introduction permits understanding the causes of their selection, and the advantages and drawbacks of their application. The genetic algorithms requirethe geometrical parameterization of any optimal candidate and the generation of a metamodel or surrogate model that complete the optimization process. These points are addressed with a special attention in the first block of the thesis, focused on the methodology considered in this study. The second block is referred to the use of these methods with the purpose of optimizing the aerodynamic performance of a high-speed train in several scenarios. These scenarios englobe the most representative operating conditions of high-speed trains, and also some of the most exigent train aerodynamic problems: front wind and cross-wind situations in open air, and the entrance of a high-speed train in a tunnel. The genetic algorithms and the adjoint method have been applied in the minimization of the aerodynamic drag on the train with front wind in open air. The comparison of these methods allows to evaluate the methdology and computational cost of each one, as well as the resulting minimization of the aerodynamic drag. Simplicity and robustness, the straightforward realization of a multi-objective optimization, and the capability of searching a global optimum are the main attributes of genetic algorithm. However, the requirement of geometrically parameterize any optimal candidate is a significant drawback that is avoided with the use of the adjoint method. This independence of the number of design variables leads to a relevant reduction of the pre-processing and computational cost. Considering the cross-wind stability, both methods are used again for the minimization of the side force. In this case, a simplification of the geometric parameterization of the train nose is adopted, what dramatically reduces the computational cost of the optimization process. Nevertheless, some of the most important geometrical characteristics are still described with this simplified parameterization. This analysis identifies and quantifies the influence of each design variable on the side force on the train. It is observed that the A-pillar roundness is the most demanding design parameter, with a more important effect than the nose length or the train cross-section area. Finally, a third scenario is considered for the validation of these methods in the aerodynamic optimization of a high-speed train. The entrance of a train in a tunnel is one of the most exigent train aerodynamic problems. The aerodynamic consequences of high-speed trains running in a tunnel are basically resumed in two correlated phenomena, the generation of pressure waves and an increase in aerodynamic drag. This multi-objective optimization problem is solved with genetic algorithms. The result is a Pareto front where a set of optimal solutions that minimize both objectives.

User experience with immersive and interactive media = Experiencia de usuario en entornos 3D inmersivos e interactivos

Estudios recientes promueven la integración de estímulos multisensoriales en activos multimedia con el fin de mejorar la experiencia de usuario mediante la estimulación de nuevos sentidos, más allá de la tradicional experiencia audiovisual. Del mismo modo, varios trabajos proponen la introducción de componentes de interacción capaces de complementar con nuevas características, funcionalidades y/o información la experiencia multimedia. Efectos sensoriales basados en el uso de nuevas técnicas de audio, olores, viento, vibraciones y control de la iluminación, han demostrado tener un impacto favorable en la sensación de Presencia, en el disfrute de la experiencia multimedia y en la calidad, relevancia y realismo de la misma percibidos por el usuario. Asimismo, los servicios basados en dos pantallas y la manipulación directa de (elementos en) la escena de video tienen el potencial de mejorar la comprensión, la concentración y la implicación proactiva del usuario en la experiencia multimedia. El deporte se encuentra entre los géneros con mayor potencial para integrar y explotar éstas soluciones tecnológicas. Trabajos previos han demostrado asimismo la viabilidad técnica de integrar éstas tecnologías con los estándares actualmente adoptados a lo largo de toda la cadena de transmisión de televisión. De este modo, los sistemas multimedia enriquecidos con efectos sensoriales, los servicios interactivos multiplataforma y un mayor control del usuario sobre la escena de vídeo emergen como nuevas formas de llevar la multimedia immersiva e interactiva al mercado de consumo de forma no disruptiva. Sin embargo, existen numerosas interrogantes relativas a los efectos sensoriales y/o soluciones interactivas más adecuadas para complementar un contenido audiovisual determinado o a la mejor manera de de integrar y combinar dichos componentes para mejorar la experiencia de usuario de un segmento de audiencia objetivo. Además, la evidencia científica sobre el impacto de factores humanos en la experiencia de usuario con estas nuevas formas de immersión e interacción en el contexto multimedia es aún insuficiente y en ocasiones, contradictoria. Así, el papel de éstos factores en el potencial de adopción de éstas tecnologías ha sido amplia-mente ignorado. La presente tesis analiza el impacto del audio binaural, efectos sensoriales (de iluminación y olfativos), interacción con objetos 3D integrados en la escena de vídeo e interacción con contenido adicional utilizando una segunda pantalla en la experiencia de usuario con contenidos de deporte. La posible influencia de dichos componentes en las variables dependientes se explora tanto a nivel global (efecto promedio) como en función de las características de los usuarios (efectos heterogéneos). Para ello, se ha llevado a cabo un experimento con usuarios orientado a explorar la influencia de éstos componentes immersivos e interactivos en dos grandes dimensiones de la experiencia multimedia: calidad y Presencia. La calidad de la experiencia multimedia se analiza en términos de las posibles variaciones asociadas a la calidad global y a la calidad del contenido, la imagen, el audio, los efectos sensoriales, la interacción con objetos 3D y la interacción con la segunda pantalla. El posible impacto en la Presencia considera dos de las dimensiones definidas por el cuestionario ITC-SOPI: Presencia Espacial (Spatial Presence) e Implicación (Engagement). Por último, los individuos son caracterizados teniendo en cuenta los siguientes atributos afectivos, cognitivos y conductuales: preferencias y hábitos en relación con el contenido, grado de conocimiento de las tecnologías integradas en el sistema, tendencia a involucrarse emocionalmente, tendencia a concentrarse en una actividad bloqueando estímulos externos y los cinco grandes rasgos de la personalidad: extroversión, amabilidad, responsabilidad, inestabilidad emocional y apertura a nuevas experiencias. A nivel global, nuestro estudio revela que los participantes prefieren el audio binaural frente al sistema estéreo y que los efectos sensoriales generan un aumento significativo del nivel de Presencia Espacial percibido por los usuarios. Además, las manipulaciones experimentales realizadas permitieron identificar una gran variedad de efectos heterogéneos. Un resultado interesante es que dichos efectos no se encuentran distribuidos de forma equitativa entre las medidas de calidad y Presencia. Nuestros datos revelan un impacto generalizado del audio binaural en la mayoría de las medidas de calidad y Presencia analizadas. En cambio, la influencia de los efectos sensoriales y de la interacción con la segunda pantalla se concentran en las medidas de Presencia y calidad, respectivamente. La magnitud de los efectos heterogéneos identificados está modulada por las siguientes características personales: preferencias en relación con el contenido, frecuencia con la que el usuario suele ver contenido similar, conocimiento de las tecnologías integradas en el demostrador, sexo, tendencia a involucrarse emocionalmente, tendencia a a concentrarse en una actividad bloqueando estímulos externos y niveles de amabilidad, responsabilidad y apertura a nuevas experiencias. Las características personales consideradas en nuestro experimento explicaron la mayor parte de la variación en las variables dependientes, confirmando así el importante (y frecuentemente ignorado) papel de las diferencias individuales en la experiencia multimedia. Entre las características de los usuarios con un impacto más generalizado se encuentran las preferencias en relación con el contenido, el grado de conocimiento de las tecnologías integradas en el sistema y la tendencia a involucrarse emocionalmente. En particular, los primeros dos factores parecen generar un conflicto de atención hacia el contenido versus las características/elementos técnicos del sistema, respectivamente. Asimismo, la experiencia multimedia de los fans del fútbol parece estar modulada por procesos emociona-les, mientras que para los no-fans predominan los procesos cognitivos, en particular aquellos directamente relacionados con la percepción de calidad. Abstract Recent studies encourage the integration of multi-sensorial stimuli into multimedia assets to enhance the user experience by stimulating other senses beyond sight and hearing. Similarly, the introduction of multi-modal interaction components complementing with new features, functionalities and/or information the multimedia experience is promoted. Sensory effects as odor, wind, vibration and light effects, as well as an enhanced audio quality, have been found to favour media enjoyment and to have a positive influence on the sense of Presence and on the perceived quality, relevance and reality of a multimedia experience. Two-screen services and a direct manipulation of (elements in) the video scene have the potential to enhance user comprehension, engagement and proactive involvement of/in the media experience. Sports is among the genres that could benefit the most from these solutions. Previous works have demonstrated the technical feasibility of implementing and deploying end-to-end solutions integrating these technologies into legacy systems. Thus, sensorially-enhanced media, two-screen services and an increased user control over the displayed scene emerge as means to deliver a new form of immersive and interactive media experiences to the mass market in a non-disruptive manner. However, many questions remain concerning issues as the specific interactive solutions or sensory effects that can better complement a given audiovisual content or the best way in which to integrate and combine them to enhance the user experience of a target audience segment. Furthermore, scientific evidence on the impact of human factors on the user experience with these new forms of immersive and interactive media is still insufficient and sometimes, contradictory. Thus, the role of these factors on the potential adoption of these technologies has been widely ignored. This thesis analyzes the impact of binaural audio, sensory (light and olfactory) effects, interaction with 3D objects integrated into the video scene and interaction with additional content using a second screen on the sports media experience. The potential influence of these components on the dependent variables is explored both at the overall level (average effect) and as a function of users’ characteristics (heterogeneous effects). To these aims, we conducted an experimental study exploring the influence of these immersive and interactive elements on the quality and Presence dimensions of the media experience. Along the quality dimension, we look for possible variations on the quality scores as-signed to the overall media experience and to the media components content, image, audio, sensory effects, interaction with 3D objects and interaction using the tablet device. The potential impact on Presence is analyzed by looking at two of the four dimensions defined by the ITC-SOPI questionnaire, namely Spatial Presence and Engagement. The users’ characteristics considered encompass the following personal affective, cognitive and behavioral attributes: preferences and habits in relation to the content, knowledge of the involved technologies, tendency to get emotionally involved and tendency to get absorbed in an activity and block out external distractors and the big five personality traits extraversion, agreeableness, conscientiousness, neuroticism and openness to experience. At the overall level, we found that participants preferred binaural audio than standard stereo audio and that sensory effects increase significantly the level of Spatial Presence. Several heterogeneous effects were also revealed as a result of our experimental manipulations. Interestingly, these effects were not equally distributed across the quality and Presence measures analyzed. Whereas binaural audio was foud to have an influence on the majority of the quality and Presence measures considered, the effects of sensory effects and of interaction with additional content through the tablet device concentrate mainly on the dimensions of Presence and on quality measures, respectively. The magnitude of these effects was modulated by individual’s characteristics, such as: preferences in relation to the content, frequency of viewing similar content, knowledge of involved technologies, gender, tendency to get emotionally involved, tendency to absorption and levels of agreeableness, conscientiousness and openness to experience. The personal characteristics collected in our experiment explained most of the variation in the dependent variables, confirming the frequently neglected role of individual differences on the media experience. Preferences in relation to the content, knowledge of involved technologies and tendency to get emotionally involved were among the user variables with the most generalized influence. In particular, the former two features seem to present a conflict in the allocation of attentional resources towards the media content versus the technical features of the system, respectively. Additionally, football fans’ experience seems to be modulated by emotional processes whereas for not fans, cognitive processes (and in particular those related to quality judgment) prevail.

Applying logic forms and statistical methods to CL-SR performance

This paper describes a CL-SR system that employs two different techniques: the first one is based on NLP rules that consist on applying logic forms to the topic processing while the second one basically consists on applying the IR-n statistical search engine to the spoken document collection. The application of logic forms to the topics allows to increase the weight of topic terms according to a set of syntactic rules. Thus, the weights of the topic terms are used by IR-n system in the information retrieval process.

Comics Explosion: Representations of Persecution in Graphic Narrative, 1995-2015

Thesis (Ph.D.)--University of Washington, 2016-06

Facilitating communication in children with multiple disabilities: three case studies of girls with Rett syndrome

Purpose: To investigate the effect of cueing on communicative responses of children with multiple disabilities in an educational setting. It was hypothesized that differences would exist in teacher interactional styles and the use of orienting cues would increase the communicative responses of the participants. Method: A naturalistic observation research method was employed in order to examine the interaction of three student-teacher dyads in three special schools. Three different activity types were videotaped from which interactions were coded and analysed. Results: Multi-modal cueing facilitated communicative responses of children with Rett syndrome. However, increased communication opportunities provided by caregivers did not elicit increased responses from the girls. Conclusion: There is a difference in cueing by teachers in their interactions with children with multiple disabilities. Also, more frequent communicative interactions did not necessarily lead to increased student responses. It is suggested that amount and type of cueing may need to be considered to be effective in generating student responses. The small number of participants, however, means findings should be viewed cautiously and that more research is indicated.

Biochemical correlates of cognition: exploring the relationships between blood, brain and behaviour

This multi-modal investigation aimed to refine analytic tools including proton magnetic resonance spectroscopy (1H-MRS) and fatty acid gas chromatography-mass spectrometry (GC-MS) analysis, for use with adult and paediatric populations, to investigate potential biochemical underpinnings of cognition (Chapter 1). Essential fatty acids (EFAs) are vital for the normal development and function of neural cells. There is increasing evidence of behavioural impairments arising from dietary deprivation of EFAs and their long-chain fatty acid metabolites (Chapter 2). Paediatric liver disease was used as a deficiency model to examine the relationships between EFA status and cognitive outcomes. Age-appropriate Wechsler assessments measured Full-scale IQ (FSIQ) and Information Processing Speed (IPS) in clinical and healthy cohorts; GC-MS quantified surrogate markers of EFA status in erythrocyte membranes; and 1H-MRS quantified neurometabolite markers of neuronal viability and function in cortical tissue (Chapter 3). Post-transplant children with early-onset liver disease demonstrated specific deficits in IPS compared to age-matched acute liver failure transplant patients and sibling controls, suggesting that the time-course of the illness is a key factor (Chapter 4). No signs of EFA deficiency were observed in the clinical cohort, suggesting that EFA metabolism was not significantly impacted by liver disease. A strong, negative correlation was observed between omega-6 fatty acids and FSIQ, independent of disease diagnosis (Chapter 5). In a study of healthy adults, effect sizes for the relationship between 1H-MRS- detectable neurometabolites and cognition fell within the range of previous work, but were not statistically significant. Based on these findings, recommendations are made emphasising the need for hypothesis-driven enquiry and greater subtlety of data analysis (Chapter 6). Consistency of metabolite values between paediatric clinical cohorts and controls indicate normal neurodevelopment, but the lack of normative, age-matched data makes it difficult to assess the true strength of liver disease-associated metabolite changes (Chapter 7). Converging methods offer a challenging but promising and novel approach to exploring brain-behaviour relationships from micro- to macroscopic levels of analysis (Chapter 8).

Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

A pragmatic Bayesian approach to wind field retrieval

The ERS-1 Satellite was launched in July 1991 by the European Space Agency into a polar orbit at about 800 km, carrying a C-band scatterometer. A scatterometer measures the amount of backscatter microwave radiation reflected by small ripples on the ocean surface induced by sea-surface winds, and so provides instantaneous snap-shots of wind flow over large areas of the ocean surface, known as wind fields. Inherent in the physics of the observation process is an ambiguity in wind direction; the scatterometer cannot distinguish if the wind is blowing toward or away from the sensor device. This ambiguity implies that there is a one-to-many mapping between scatterometer data and wind direction. Current operational methods for wind field retrieval are based on the retrieval of wind vectors from satellite scatterometer data, followed by a disambiguation and filtering process that is reliant on numerical weather prediction models. The wind vectors are retrieved by the local inversion of a forward model, mapping scatterometer observations to wind vectors, and minimising a cost function in scatterometer measurement space. This thesis applies a pragmatic Bayesian solution to the problem. The likelihood is a combination of conditional probability distributions for the local wind vectors given the scatterometer data. The prior distribution is a vector Gaussian process that provides the geophysical consistency for the wind field. The wind vectors are retrieved directly from the scatterometer data by using mixture density networks, a principled method to model multi-modal conditional probability density functions. The complexity of the mapping and the structure of the conditional probability density function are investigated. A hybrid mixture density network, that incorporates the knowledge that the conditional probability distribution of the observation process is predominantly bi-modal, is developed. The optimal model, which generalises across a swathe of scatterometer readings, is better on key performance measures than the current operational model. Wind field retrieval is approached from three perspectives. The first is a non-autonomous method that confirms the validity of the model by retrieving the correct wind field 99% of the time from a test set of 575 wind fields. The second technique takes the maximum a posteriori probability wind field retrieved from the posterior distribution as the prediction. For the third technique, Markov Chain Monte Carlo (MCMC) techniques were employed to estimate the mass associated with significant modes of the posterior distribution, and make predictions based on the mode with the greatest mass associated with it. General methods for sampling from multi-modal distributions were benchmarked against a specific MCMC transition kernel designed for this problem. It was shown that the general methods were unsuitable for this application due to computational expense. On a test set of 100 wind fields the MAP estimate correctly retrieved 72 wind fields, whilst the sampling method correctly retrieved 73 wind fields.

Evolutionary neural networks : models and applications

The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithms (GAs) are disclosed. A novel GA-NN hybrid is introduced, based on the bumptree, a little-used connectionist model. As well as being computationally efficient, the bumptree is shown to be more amenable to genetic coding lthan other NN models. A hierarchical genetic coding scheme is developed for the bumptree and shown to have low redundancy, as well as being complete and closed with respect to the search space. When applied to optimising bumptree architectures for classification problems the GA discovers bumptrees which significantly out-perform those constructed using a standard algorithm. The fields of artificial life, control and robotics are identified as likely application areas for the evolutionary optimisation of NNs. An artificial life case-study is presented and discussed. Experiments are reported which show that the GA-bumptree is able to learn simulated pole balancing and car parking tasks using only limited environmental feedback. A simple modification of the fitness function allows the GA-bumptree to learn mappings which are multi-modal, such as robot arm inverse kinematics. The dynamics of the 'geographic speciation' selection model used by the GA-bumptree are investigated empirically and the convergence profile is introduced as an analytical tool. The relationships between the rate of genetic convergence and the phenomena of speciation, genetic drift and punctuated equilibrium arc discussed. The importance of genetic linkage to GA design is discussed and two new recombination operators arc introduced. The first, linkage mapped crossover (LMX) is shown to be a generalisation of existing crossover operators. LMX provides a new framework for incorporating prior knowledge into GAs.Its adaptive form, ALMX, is shown to be able to infer linkage relationships automatically during genetic search.

Signal processing for molecular and cellular biological physics:an emerging field

Recent advances in our ability to watch the molecular and cellular processes of life in action-such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer-raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions

In this paper we develop set of novel Markov Chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. The novel diffusion bridge proposal derived from the variational approximation allows the use of a flexible blocking strategy that further improves mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample applications the algorithm is accurate except in the presence of large observation errors and low to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient. © 2011 Springer-Verlag.