Adaptive Interest Lifetimes for Information-Centric Wireless Multi-hop Communication

Information-centric networking (ICN) is a promising approach for wireless communication because users can exploit the broadcast nature of the wireless medium to quickly find desired content at nearby nodes. However, wireless multi-hop communication is prone to collisions and it is crucial to quickly detect and react to them to optimize transmission times and a void spurious retransmissions. Several adaptive retransmission timers have been used in related ICN literature but they have not been compared and evaluated in wireless multi-hop environments. In this work, we evaluate existing algorithms in wireless multi-hop communication. We find that existing algorithms are not optimized for wireless communication but slight modificati ons can result in considerably better performance without increasing the number of transmitted Interests.

Response profiles of murine spiral ganglion neurons on multi-electrode arrays.

OBJECTIVE Cochlear implants (CIs) have become the gold standard treatment for deafness. These neuroprosthetic devices feature a linear electrode array, surgically inserted into the cochlea, and function by directly stimulating the auditory neurons located within the spiral ganglion, bypassing lost or not-functioning hair cells. Despite their success, some limitations still remain, including poor frequency resolution and high-energy consumption. In both cases, the anatomical gap between the electrode array and the spiral ganglion neurons (SGNs) is believed to be an important limiting factor. The final goal of the study is to characterize response profiles of SGNs growing in intimate contact with an electrode array, in view of designing novel CI devices and stimulation protocols, featuring a gapless interface with auditory neurons. APPROACH We have characterized SGN responses to extracellular stimulation using multi-electrode arrays (MEAs). This setup allows, in our view, to optimize in vitro many of the limiting interface aspects between CIs and SGNs. MAIN RESULTS Early postnatal mouse SGN explants were analyzed after 6-18 days in culture. Different stimulation protocols were compared with the aim to lower the stimulation threshold and the energy needed to elicit a response. In the best case, a four-fold reduction of the energy was obtained by lengthening the biphasic stimulus from 40 μs to 160 μs. Similarly, quasi monophasic pulses were more effective than biphasic pulses and the insertion of an interphase gap moderately improved efficiency. Finally, the stimulation with an external electrode mounted on a micromanipulator showed that the energy needed to elicit a response could be reduced by a factor of five with decreasing its distance from 40 μm to 0 μm from the auditory neurons. SIGNIFICANCE This study is the first to show electrical activity of SGNs on MEAs. Our findings may help to improve stimulation by and to reduce energy consumption of CIs and thereby contribute to the development of fully implantable devices with better auditory resolution in the future.

Situational adaptiveness of control orientation mediates relation between fixed-world view and youth well-being in three cultures

When proposing primary control (changing the world to fit self)/secondary control (changing self to fit the world) theory, Weisz et al. (1984) argued for the importance of the “serenity to accept the things I cannot change, the courage to change the things I can” (p. 967), and the wisdom to choose the right control strategy that fits the context. Although the dual processes of control theory generated hundreds of empirical studies, most of them focused on the dichotomy of PC and SC, with none of these tapped into the critical concept: individuals’ ability to know when to use what. This project addressed this issue by using scenario questions to study the impact of situationally adaptive control strategies on youth well-being. To understand the antecedents of youths’ preference for PC or SC, we also connected PCSC theory with Dweck’s implicit theory about the changeability of the world. We hypothesized that youths’ belief about the world’s changeability impacts how difficult it was for them to choose situationally adaptive control orientation, which then impacts their well-being. This study included adolescents and emerging adults between the ages of 18 and 28 years (Mean = 20.87 years) from the US (n = 98), China (n = 100), and Switzerland (n = 103). Participants answered a questionnaire including a measure of implicit theories about the fixedness of the external world, a scenario-based measure of control orientation, and several measures of well-being. Preliminary analyses of the scenario-based control orientation measures showed striking cross-cultural similarity of preferred control responses: while for three of the six scenarios primary control was the predominately chosen control response in all cultures, for the other three scenarios secondary control was the predominately chosen response. This suggested that youths across cultures are aware that some situations call for primary control, while others demand secondary control. We considered the control strategy winning the majority of the votes to be the strategy that is situationally adaptive. The results of a multi-group structural equation mediation model with the extent of belief in a fixed world as independent variable, the difficulties of carrying out the respective adaptive versus non-adaptive control responses as two mediating variables and the latent well-being variable as dependent variable showed a cross-culturally similar pattern of effects: a belief in a fixed world was significantly related to higher difficulties in carrying out the normative as well as the non-normative control response, but only the difficulty of carrying out the normative control response (be it primary control in situations where primary control is normative or secondary control in situations where secondary control is normative) was significantly related to a lower reported well-being (while the difficulty of carrying out the non-normative response was unrelated to well-being). While previous research focused on cross-cultural differences on the choice of PC or SC, this study shed light on the universal necessity of applying the right kind of control to fit the situation.

High-resolution multi-proxy record of the last interglacial period from Lake Van, eastern Anatolian high plateau, Turkey

A high-resolution multi-proxy record from Lake Van, eastern Anatolia, derived from a lacustrine sequence cored at the 357 m deep Ahlat Ridge (AR), allows a comprehensive view of paleoclimate and environmental history in the continental Near East during the last interglacial (LI). We combined paleovegetation (pollen), stable oxygen isotope (d18Obulk) and XRF data from the same sedimentary sequence, showing distinct variations during the period from 135 to 110 ka ago leading into and out of full interglacial conditions. The last interglacial plateau, as defined by the presence of thermophilous steppe-forest communities, lasted ca. 13.5 ka, from ~129.1-115.6 ka BP. The detailed palynological sequence at Lake Van documents a vegetation succession with several climatic phases: (I) the Pistacia zone (ca. 131.2-129.1 ka BP) indicates summer dryness and mild winter conditions during the initial warming, (II) the Quercus-Ulmus zone (ca. 129.1-127.2 ka BP) occurred during warm and humid climate conditions with enhanced evaporation, (III) the Carpinus zone (ca. 127.2-124.1 ka BP) suggest increasingly cooler and wetter conditions, and (IV) the expansion of Pinus at ~124.1 ka BP marks the onset of a colder/drier environment that extended into the interval of global ice growth. Pollen data suggest migration of thermophilous trees from refugial areas at the beginning of the last interglacial. Analogous to the current interglacial, the migration documents a time lag between the onset of climatic amelioration and the establishment of an oak steppe-forest, spanning 2.1 ka. Hence, the major difference between the last interglacial compared to the current interglacial (Holocene) is the abundance of Pinus as well as the decrease of deciduous broad-leaved trees, indicating higher continentality during the last interglacial. Finally, our results demonstrate intra-interglacial variability in the low mid-latitudes and suggest a close connection with the high-frequency climate variability recorded in Greenland ice cores.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.

An Economic Derivation on Trade Coefficients under the Framework of Multi-regional I-O Analysis

The gravity model, entropy model, potential type model and others like these have been adopted to formulate interregional trade coefficients under the framework of Multi-Regional I-O (MRIO) analysis. Since most of these models are based upon analogies in physics or on statistical principles, they do not provide a theoretical explanation from the view of a firm's or individual's rational and deterministic decision making. In this paper, according to the deterministic choice theory, not only is an alternative formulation of the trade coefficients presented, but also a discussion of an appropriate definition for purchasing prices indices. Since this formulation is consistent with the MRIO system, it can be employed as a useful model-building tool in multi-regional models such as the spatial CGE model.

Aplicaciones de interés forestal de las imágenes obtenidas con el sensor Multi-angle Imaging SpectroRadiometer (MISR)

Las aplicaciones de la teledetección al seguimiento de lo que ocurre en la superficie terrestre se han ido multiplicando y afinando con el lanzamiento de nuevos sensores por parte de las diferentes agencias espaciales. La necesidad de tener información actualizada cada poco tiempo y espacialmente homogénea, ha provocado el desarrollo de nuevos programas como el Earth Observing System (EOS) de la National Aeronautics and Space Administration (NASA). Uno de los sensores que incorpora el buque insignia de ese programa, el satélite TERRA, es el Multi-angle Imaging SpectroRadiometer (MISR), diseñado para capturar información multiangular de la superficie terrestre. Ya desde los años 1970, se conocía que la reflectancia de las diversas ocupaciones y usos del suelo variaba en función del ángulo de observación y de iluminación, es decir, que eran anisotrópicas. Tal variación estaba además relacionada con la estructura tridimensional de tales ocupaciones, por lo que se podía aprovechar tal relación para obtener información de esa estructura, más allá de la que pudiera proporcionar la información meramente espectral. El sensor MISR incorpora 9 cámaras a diferentes ángulos para capturar 9 imágenes casi simultáneas del mismo punto, lo que permite estimar con relativa fiabilidad la respuesta anisotrópica de la superficie terrestre. Varios trabajos han demostrado que se pueden estimar variables relacionadas con la estructura de la vegetación con la información que proporciona MISR. En esta Tesis se ha realizado una primera aplicación a la Península Ibérica, para comprobar su utilidad a la hora de estimar variables de interés forestal. En un primer paso se ha analizado la variabilidad temporal que se produce en los datos, debido a los cambios en la geometría de captación, es decir, debido a la posición relativa de sensores y fuente de iluminación, que en este caso es el Sol. Se ha comprobado cómo la anisotropía es mayor desde finales de otoño hasta principios de primavera debido a que la posición del Sol es más cercana al plano de los sensores. También se ha comprobado que los valores máximo y mínimo se van desplazando temporalmente entre el centro y el extremo angular. En la caracterización multiangular de ocupaciones del suelo de CORINE Land Cover que se ha realizado, se puede observar cómo la forma predominante en las imágenes con el Sol más alto es convexa con un máximo en la cámara más cercana a la fuente de iluminación. Sin embargo, cuando el Sol se encuentra mucho más bajo, ese máximo es muy externo. Por otra parte, los datos obtenidos en verano son mucho más variables para cada ocupación que los de noviembre, posiblemente debido al aumento proporcional de las zonas en sombra. Para comprobar si la información multiangular tiene algún efecto en la obtención de imágenes clasificadas según ocupación y usos del suelo, se han realizado una serie de clasificaciones variando la información utilizada, desde sólo multiespectral, a multiangular y multiespectral. Los resultados muestran que, mientras para las clasificaciones más genéricas la información multiangular proporciona los peores resultados, a medida que se amplían el número de clases a obtener tal información mejora a lo obtenido únicamente con información multiespectral. Por otra parte, se ha realizado una estimación de variables cuantitativas como la fracción de cabida cubierta (Fcc) y la altura de la vegetación a partir de información proporcionada por MISR a diferentes resoluciones. En el valle de Alcudia (Ciudad Real) se ha estimado la fracción de cabida cubierta del arbolado para un píxel de 275 m utilizando redes neuronales. Los resultados muestran que utilizar información multiespectral y multiangular puede mejorar casi un 20% las estimaciones realizadas sólo con datos multiespectrales. Además, las relaciones obtenidas llegan al 0,7 de R con errores inferiores a un 10% en Fcc, siendo éstos mucho mejores que los obtenidos con el producto elaborado a partir de datos multiespectrales del sensor Moderate Resolution Imaging Spectroradiometer (MODIS), también a bordo de Terra, para la misma variable. Por último, se ha estimado la fracción de cabida cubierta y la altura efectiva de la vegetación para 700.000 ha de la provincia de Murcia, con una resolución de 1.100 m. Los resultados muestran la relación existente entre los datos espectrales y los multiangulares, obteniéndose coeficientes de Spearman del orden de 0,8 en el caso de la fracción de cabida cubierta de la vegetación, y de 0,4 en el caso de la altura efectiva. Las estimaciones de ambas variables con redes neuronales y diversas combinaciones de datos, arrojan resultados con R superiores a 0,85 para el caso del grado de cubierta vegetal, y 0,6 para la altura efectiva. Los parámetros multiangulares proporcionados en los productos elaborados con MISR a 1.100 m, no obtienen buenos resultados por sí mismos pero producen cierta mejora al incorporarlos a la información espectral. Los errores cuadráticos medios obtenidos son inferiores a 0,016 para la Fcc de la vegetación en tanto por uno, y 0,7 m para la altura efectiva de la misma. Regresiones geográficamente ponderadas muestran además que localmente se pueden obtener mejores resultados aún mejores, especialmente cuando hay una mayor variabilidad espacial de las variables estimadas. En resumen, la utilización de los datos proporcionados por MISR ofrece una prometedora vía de mejora de resultados en la media-baja resolución, tanto para la clasificación de imágenes como para la obtención de variables cuantitativas de la estructura de la vegetación. ABSTRACT Applications of remote sensing for monitoring what is happening on the land surface have been multiplied and refined with the launch of new sensors by different Space Agencies. The need of having up to date and spatially homogeneous data, has led to the development of new programs such as the Earth Observing System (EOS) of the National Aeronautics and Space Administration (NASA). One of the sensors incorporating the flagship of that program, the TERRA satellite, is Multi-angle Imaging Spectroradiometer (MISR), designed to capture the multi-angle information of the Earth's surface. Since the 1970s, it was known that the reflectance of various land covers and land uses varied depending on the viewing and ilumination angles, so they are anisotropic. Such variation was also related to the three dimensional structure of such covers, so that one could take advantage of such a relationship to obtain information from that structure, beyond which spectral information could provide. The MISR sensor incorporates 9 cameras at different angles to capture 9 almost simultaneous images of the same point, allowing relatively reliable estimates of the anisotropic response of the Earth's surface. Several studies have shown that we can estimate variables related to the vegetation structure with the information provided by this sensor, so this thesis has made an initial application to the Iberian Peninsula, to check their usefulness in estimating forest variables of interest. In a first step we analyzed the temporal variability that occurs in the data, due to the changes in the acquisition geometry, i.e. the relative position of sensor and light source, which in this case is the Sun. It has been found that the anisotropy is greater from late fall through early spring due to the Sun's position closer to the plane of the sensors. It was also found that the maximum and minimum values are displaced temporarily between the center and the ends. In characterizing CORINE Land Covers that has been done, one could see how the predominant form in the images with the highest sun is convex with a maximum in the camera closer to the light source. However, when the sun is much lower, the maximum is external. Moreover, the data obtained for each land cover are much more variable in summer that in November, possibly due to the proportional increase in shadow areas. To check whether the information has any effect on multi-angle imaging classification of land cover and land use, a series of classifications have been produced changing the data used, from only multispectrally, to multi-angle and multispectral. The results show that while for the most generic classifications multi-angle information is the worst, as there are extended the number of classes to obtain such information it improves the results. On the other hand, an estimate was made of quantitative variables such as canopy cover and vegetation height using information provided by MISR at different resolutions. In the valley of Alcudia (Ciudad Real), we estimated the canopy cover of trees for a pixel of 275 m by using neural networks. The results showed that using multispectral and multiangle information can improve by almost 20% the estimates that only used multispectral data. Furthermore, the relationships obtained reached an R coefficient of 0.7 with errors below 10% in canopy cover, which is much better result than the one obtained using data from the Moderate Resolution Imaging Spectroradiometer (MODIS), also onboard Terra, for the same variable. Finally we estimated the canopy cover and the effective height of the vegetation for 700,000 hectares in the province of Murcia, with a spatial resolution of 1,100 m. The results show a relationship between the spectral and the multi-angle data, and provide estimates of the canopy cover with a Spearman’s coefficient of 0.8 in the case of the vegetation canopy cover, and 0.4 in the case of the effective height. The estimates of both variables using neural networks and various combinations of data, yield results with an R coefficient greater than 0.85 for the case of the canopy cover, and 0.6 for the effective height. Multi-angle parameters provided in the products made from MISR at 1,100 m pixel size, did not produce good results from themselves but improved the results when included to the spectral information. The mean square errors were less than 0.016 for the canopy cover, and 0.7 m for the effective height. Geographically weighted regressions also showed that locally we can have even better results, especially when there is high spatial variability of estimated variables. In summary, the use of the data provided by MISR offers a promising way of improving remote sensing performance in the low-medium spatial resolution, both for image classification and for the estimation of quantitative variables of the vegetation structure.

Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data

Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.

A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Development of the infrastructure for a multi-agent traffic management system simulation

This document contains detailed description of the design and the implementation of a multi-agent application controlling traffic lights in a city together with a system for simulating traffic and testing. The goal of this thesis is to design and build a simplified intelligent and distributed solution to the problem with the traffic in the big cities following different good practices in order to allow future refining of the model of the real world. The problem of the traffic in the big cities is still a problem that cannot be solved. Not only is the increasing number of cars a reason for the traffic jams, but also the way the traffic is organized. Usually, the intersections with traffic lights are replaced by roundabouts or interchanges to increase the number of cars that can cross the intersection in certain time. But still there are places where the infrastructure cannot be changed and the traffic light semaphores are the only way to control the car flows. In real life, the traffic lights have a predefined plan for change or they receive information from a centralized system when and how they have to change. But what if the traffic lights can cooperate and decide on their own when and how to change? Using this problem, the purpose of the thesis is to explore different agent-based software engineering approaches to design and build a non-conventional distributed system. From the software engineering point of view, the goal of the thesis is to apply the knowledge and use the skills, acquired during the various courses of the master program in Software Engineering, while solving a practical and complex problem such as the traffic in the cities.

Is building renovation truly sustainable? The need for applying a multi-criteria assessment through life cycle approach

The aim of the present research is to characterise the international scene in the field of building refurbishment, by thoroughly reviewing the literature relating to building renovation and systematising the results according to the different aspects considered by the authors. Even though there is certain consensus with respect to the criteria for the selection of energy efficiency measures, the assessment criteria differ broadly and widely. The present work highlights the lack of consensus on the assessment criteria and the need of harmonization. A holistic view is required in order to identify the most sustainable strategies in each particular case, considering social, environmental and economic impacts from a life cycle perspective.

Design and development of compact optical systems = Diseño y desarrollo de sistemas ópticos compactos

Esta tesis considera dos tipos de aplicaciones del diseño óptico: óptica formadora de imagen por un lado, y óptica anidólica (nonimaging) o no formadora de imagen, por otro. Las ópticas formadoras de imagen tienen como objetivo la obtención de imágenes de puntos del objeto en el plano de la imagen. Por su parte, la óptica anidólica, surgida del desarrollo de aplicaciones de concentración e iluminación, se centra en la transferencia de energía en forma de luz de forma eficiente. En general, son preferibles los diseños ópticos que den como resultado sistemas compactos, para ambos tipos de ópticas (formadora de imagen y anidólica). En el caso de los sistemas anidólicos, una óptica compacta permite tener costes de producción reducidos. Hay dos razones: (1) una óptica compacta presenta volúmenes reducidos, lo que significa que se necesita menos material para la producción en masa; (2) una óptica compacta es pequeña y ligera, lo que ahorra costes en el transporte. Para los sistemas ópticos de formación de imagen, además de las ventajas anteriores, una óptica compacta aumenta la portabilidad de los dispositivos, que es una gran ventaja en tecnologías de visualización portátiles, tales como cascos de realidad virtual (HMD del inglés Head Mounted Display). Esta tesis se centra por tanto en nuevos enfoques de diseño de sistemas ópticos compactos para aplicaciones tanto de formación de imagen, como anidólicas. Los colimadores son uno de los diseños clásicos dentro la óptica anidólica, y se pueden utilizar en aplicaciones fotovoltaicas y de iluminación. Hay varios enfoques a la hora de diseñar estos colimadores. Los diseños convencionales tienen una relación de aspecto mayor que 0.5. Con el fin de reducir la altura del colimador manteniendo el área de iluminación, esta tesis presenta un diseño de un colimador multicanal. En óptica formadora de imagen, las superficies asféricas y las superficies sin simetría de revolución (o freeform) son de gran utilidad de cara al control de las aberraciones de la imagen y para reducir el número y tamaño de los elementos ópticos. Debido al rápido desarrollo de sistemas de computación digital, los trazados de rayos se pueden realizar de forma rápida y sencilla para evaluar el rendimiento del sistema óptico analizado. Esto ha llevado a los diseños ópticos modernos a ser generados mediante el uso de diferentes técnicas de optimización multi-paramétricas. Estas técnicas requieren un buen diseño inicial como punto de partida para el diseño final, que será obtenido tras un proceso de optimización. Este proceso precisa un método de diseño directo para superficies asféricas y freeform que den como resultado un diseño cercano al óptimo. Un método de diseño basado en ecuaciones diferenciales se presenta en esta tesis para obtener un diseño óptico formado por una superficie freeform y dos superficies asféricas. Esta tesis consta de cinco capítulos. En Capítulo 1, se presentan los conceptos básicos de la óptica formadora de imagen y de la óptica anidólica, y se introducen las técnicas clásicas del diseño de las mismas. El Capítulo 2 describe el diseño de un colimador ultra-compacto. La relación de aspecto ultra-baja de este colimador se logra mediante el uso de una estructura multicanal. Se presentará su procedimiento de diseño, así como un prototipo fabricado y la caracterización del mismo. El Capítulo 3 describe los conceptos principales de la optimización de los sistemas ópticos: función de mérito y método de mínimos cuadrados amortiguados. La importancia de un buen punto de partida se demuestra mediante la presentación de un mismo ejemplo visto a través de diferentes enfoques de diseño. El método de las ecuaciones diferenciales se presenta como una herramienta ideal para obtener un buen punto de partida para la solución final. Además, diferentes técnicas de interpolación y representación de superficies asféricas y freeform se presentan para el procedimiento de optimización. El Capítulo 4 describe la aplicación del método de las ecuaciones diferenciales para un diseño de un sistema óptico de una sola superficie freeform. Algunos conceptos básicos de geometría diferencial son presentados para una mejor comprensión de la derivación de las ecuaciones diferenciales parciales. También se presenta un procedimiento de solución numérica. La condición inicial está elegida como un grado de libertad adicional para controlar la superficie donde se forma la imagen. Basado en este enfoque, un diseño anastigmático se puede obtener fácilmente y se utiliza como punto de partida para un ejemplo de diseño de un HMD con una única superficie reflectante. Después de la optimización, dicho diseño muestra mejor rendimiento. El Capítulo 5 describe el método de las ecuaciones diferenciales ampliado para diseños de dos superficies asféricas. Para diseños ópticos de una superficie, ni la superficie de imagen ni la correspondencia entre puntos del objeto y la imagen pueden ser prescritas. Con esta superficie adicional, la superficie de la imagen se puede prescribir. Esto conduce a un conjunto de tres ecuaciones diferenciales ordinarias implícitas. La solución numérica se puede obtener a través de cualquier software de cálculo numérico. Dicho procedimiento también se explica en este capítulo. Este método de diseño da como resultado una lente anastigmática, que se comparará con una lente aplanática. El diseño anastigmático converge mucho más rápido en la optimización y la solución final muestra un mejor rendimiento. ABSTRACT We will consider optical design from two points of view: imaging optics and nonimaging optics. Imaging optics focuses on the imaging of the points of the object. Nonimaging optics arose from the development of concentrators and illuminators, focuses on the transfer of light energy, and has wide applications in illumination and concentration photovoltaics. In general, compact optical systems are necessary for both imaging and nonimaging designs. For nonimaging optical systems, compact optics use to be important for reducing cost. The reasons are twofold: (1) compact optics is small in volume, which means less material is needed for mass-production; (2) compact optics is small in size and light in weight, which saves cost in transportation. For imaging optical systems, in addition to the above advantages, compact optics increases portability of devices as well, which contributes a lot to wearable display technologies such as Head Mounted Displays (HMD). This thesis presents novel design approaches of compact optical systems for both imaging and nonimaging applications. Collimator is a typical application of nonimaging optics in illumination, and can be used in concentration photovoltaics as well due to the reciprocity of light. There are several approaches for collimator designs. In general, all of these approaches have an aperture diameter to collimator height not greater than 2. In order to reduce the height of the collimator while maintaining the illumination area, a multichannel design is presented in this thesis. In imaging optics, aspheric and freeform surfaces are useful in controlling image aberrations and reducing the number and size of optical elements. Due to the rapid development of digital computing systems, ray tracing can be easily performed to evaluate the performance of optical system. This has led to the modern optical designs created by using different multi-parametric optimization techniques. These techniques require a good initial design to be a starting point so that the final design after optimization procedure can reach the optimum solution. This requires a direct design method for aspheric and freeform surface close to the optimum. A differential equation based design method is presented in this thesis to obtain single freeform and double aspheric surfaces. The thesis comprises of five chapters. In Chapter 1, basic concepts of imaging and nonimaging optics are presented and typical design techniques are introduced. Readers can obtain an understanding for the following chapters. Chapter 2 describes the design of ultra-compact collimator. The ultra-low aspect ratio of this collimator is achieved by using a multichannel structure. Its design procedure is presented together with a prototype and its evaluation. The ultra-compactness of the device has been approved. Chapter 3 describes the main concepts of optimizing optical systems: merit function and Damped Least-Squares method. The importance of a good starting point is demonstrated by presenting an example through different design approaches. The differential equation method is introduced as an ideal tool to obtain a good starting point for the final solution. Additionally, different interpolation and representation techniques for aspheric and freeform surface are presented for optimization procedure. Chapter 4 describes the application of differential equation method in the design of single freeform surface optical system. Basic concepts of differential geometry are presented for understanding the derivation of partial differential equations. A numerical solution procedure is also presented. The initial condition is chosen as an additional freedom to control the image surface. Based on this approach, anastigmatic designs can be readily obtained and is used as starting point for a single reflective surface HMD design example. After optimization, the evaluation shows better MTF. Chapter 5 describes the differential equation method extended to double aspheric surface designs. For single optical surface designs, neither image surface nor the mapping from object to image can be prescribed. With one more surface added, the image surface can be prescribed. This leads to a set of three implicit ordinary differential equations. Numerical solution can be obtained by MATLAB and its procedure is also explained. An anastigmatic lens is derived from this design method and compared with an aplanatic lens. The anastigmatic design converges much faster in optimization and the final solution shows better performance.