UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Operational Aspects of Full Reduction in Lambda Calculi

Esta tesis estudia la reducción plena (‘full reduction’ en inglés) en distintos cálculos lambda. 1 En esencia, la reducción plena consiste en evaluar los cuerpos de las funciones en los lenguajes de programación funcional con ligaduras. Se toma el cálculo lambda clásico (i.e., puro y sin tipos) como el sistema formal que modela el paradigma de programación funcional. La reducción plena es una técnica fundamental cuando se considera a los programas como datos, por ejemplo para la optimización de programas mediante evaluación parcial, o cuando algún atributo del programa se representa a su vez por un programa, como el tipo en los demostradores automáticos de teoremas actuales. Muchas semánticas operacionales que realizan reducción plena tienen naturaleza híbrida. Se introduce formalmente la noción de naturaleza híbrida, que constituye el hilo conductor de todo el trabajo. En el cálculo lambda la naturaleza híbrida se manifiesta como una ‘distinción de fase’ en el tratamiento de las abstracciones, ya sean consideradas desde fuera o desde dentro de si mismas. Esta distinción de fase conlleva una estructura en capas en la que una semántica híbrida depende de una o más semánticas subsidiarias. Desde el punto de vista de los lenguajes de programación, la tesis muestra como derivar, mediante técnicas de transformación de programas, implementaciones de semánticas operacionales que reducen plenamente a partir de sus especificaciones. Las técnicas de transformación de programas consisten en transformaciones sintácticas que preservan la equivalencia semántica de los programas. Se ajustan las técnicas de transformación de programas existentes para trabajar con implementaciones de semánticas híbridas. Además, se muestra el impacto que tiene la reducción plena en las implementaciones que utilizan entornos. Los entornos son un ingrediente fundamental en las implementaciones realistas de una máquina abstracta. Desde el punto de vista de los sistemas formales, la tesis desvela una teoría novedosa para el cálculo lambda con paso por valor (‘call-by-value lambda calculus’ en inglés) que es consistente con la reducción plena. Dicha teoría induce una noción de equivalencia observacional que distingue más puntos que las teorías existentes para dicho cálculo. Esta contribución ayuda a establecer una ‘teoría estándar’ en el cálculo lambda con paso por valor que es análoga a la ‘teoría estándar’ del cálculo lambda clásico propugnada por Barendregt. Se presentan resultados de teoría de la demostración, y se sugiere como abordar el estudio de teoría de modelos. ABSTRACT This thesis studies full reduction in lambda calculi. In a nutshell, full reduction consists in evaluating the body of the functions in a functional programming language with binders. The classical (i.e., pure untyped) lambda calculus is set as the formal system that models the functional paradigm. Full reduction is a prominent technique when programs are treated as data objects, for instance when performing optimisations by partial evaluation, or when some attribute of the program is represented by a program itself, like the type in modern proof assistants. A notable feature of many full-reducing operational semantics is its hybrid nature, which is introduced and which constitutes the guiding theme of the thesis. In the lambda calculus, the hybrid nature amounts to a ‘phase distinction’ in the treatment of abstractions when considered either from outside or from inside themselves. This distinction entails a layered structure in which a hybrid semantics depends on one or more subsidiary semantics. From a programming languages standpoint, the thesis shows how to derive implementations of full-reducing operational semantics from their specifications, by using program transformations techniques. The program transformation techniques are syntactical transformations which preserve the semantic equivalence of programs. The existing program transformation techniques are adjusted to work with implementations of hybrid semantics. The thesis also shows how full reduction impacts the implementations that use the environment technique. The environment technique is a key ingredient of real-world implementations of abstract machines which helps to circumvent the issue with binders. From a formal systems standpoint, the thesis discloses a novel consistent theory for the call-by-value variant of the lambda calculus which accounts for full reduction. This novel theory entails a notion of observational equivalence which distinguishes more points than other existing theories for the call-by-value lambda calculus. This contribution helps to establish a ‘standard theory’ in that calculus which constitutes the analogous of the ‘standard theory’ advocated by Barendregt in the classical lambda calculus. Some prooftheoretical results are presented, and insights on the model-theoretical study are given.

Diseño de algoritmos de guerra electrónica y radar para su implementación en sistemas de tiempo real

Esta tesis se centra en el estudio y desarrollo de algoritmos de guerra electrónica {electronic warfare, EW) y radar para su implementación en sistemas de tiempo real. La llegada de los sistemas de radio, radar y navegación al terreno militar llevó al desarrollo de tecnologías para combatirlos. Así, el objetivo de los sistemas de guerra electrónica es el control del espectro electomagnético. Una de la funciones de la guerra electrónica es la inteligencia de señales {signals intelligence, SIGINT), cuya labor es detectar, almacenar, analizar, clasificar y localizar la procedencia de todo tipo de señales presentes en el espectro. El subsistema de inteligencia de señales dedicado a las señales radar es la inteligencia electrónica {electronic intelligence, ELINT). Un sistema de tiempo real es aquel cuyo factor de mérito depende tanto del resultado proporcionado como del tiempo en que se da dicho resultado. Los sistemas radar y de guerra electrónica tienen que proporcionar información lo más rápido posible y de forma continua, por lo que pueden encuadrarse dentro de los sistemas de tiempo real. La introducción de restricciones de tiempo real implica un proceso de realimentación entre el diseño del algoritmo y su implementación en plataformas “hardware”. Las restricciones de tiempo real son dos: latencia y área de la implementación. En esta tesis, todos los algoritmos presentados se han implementado en plataformas del tipo field programmable gate array (FPGA), ya que presentan un buen compromiso entre velocidad, coste total, consumo y reconfigurabilidad. La primera parte de la tesis está centrada en el estudio de diferentes subsistemas de un equipo ELINT: detección de señales mediante un detector canalizado, extracción de los parámetros de pulsos radar, clasificación de modulaciones y localization pasiva. La transformada discreta de Fourier {discrete Fourier transform, DFT) es un detector y estimador de frecuencia quasi-óptimo para señales de banda estrecha en presencia de ruido blanco. El desarrollo de algoritmos eficientes para el cálculo de la DFT, conocidos como fast Fourier transform (FFT), han situado a la FFT como el algoritmo más utilizado para la detección de señales de banda estrecha con requisitos de tiempo real. Así, se ha diseñado e implementado un algoritmo de detección y análisis espectral para su implementación en tiempo real. Los parámetros más característicos de un pulso radar son su tiempo de llegada y anchura de pulso. Se ha diseñado e implementado un algoritmo capaz de extraer dichos parámetros. Este algoritmo se puede utilizar con varios propósitos: realizar un reconocimiento genérico del radar que transmite dicha señal, localizar la posición de dicho radar o bien puede utilizarse como la parte de preprocesado de un clasificador automático de modulaciones. La clasificación automática de modulaciones es extremadamente complicada en entornos no cooperativos. Un clasificador automático de modulaciones se divide en dos partes: preprocesado y el algoritmo de clasificación. Los algoritmos de clasificación basados en parámetros representativos calculan diferentes estadísticos de la señal de entrada y la clasifican procesando dichos estadísticos. Los algoritmos de localization pueden dividirse en dos tipos: triangulación y sistemas cuadráticos. En los algoritmos basados en triangulación, la posición se estima mediante la intersección de las rectas proporcionadas por la dirección de llegada de la señal. En cambio, en los sistemas cuadráticos, la posición se estima mediante la intersección de superficies con igual diferencia en el tiempo de llegada (time difference of arrival, TDOA) o diferencia en la frecuencia de llegada (frequency difference of arrival, FDOA). Aunque sólo se ha implementado la estimación del TDOA y FDOA mediante la diferencia de tiempos de llegada y diferencia de frecuencias, se presentan estudios exhaustivos sobre los diferentes algoritmos para la estimación del TDOA, FDOA y localización pasiva mediante TDOA-FDOA. La segunda parte de la tesis está dedicada al diseño e implementación filtros discretos de respuesta finita (finite impulse response, FIR) para dos aplicaciones radar: phased array de banda ancha mediante filtros retardadores (true-time delay, TTD) y la mejora del alcance de un radar sin modificar el “hardware” existente para que la solución sea de bajo coste. La operación de un phased array de banda ancha mediante desfasadores no es factible ya que el retardo temporal no puede aproximarse mediante un desfase. La solución adoptada e implementada consiste en sustituir los desfasadores por filtros digitales con retardo programable. El máximo alcance de un radar depende de la relación señal a ruido promedio en el receptor. La relación señal a ruido depende a su vez de la energía de señal transmitida, potencia multiplicado por la anchura de pulso. Cualquier cambio hardware que se realice conlleva un alto coste. La solución que se propone es utilizar una técnica de compresión de pulsos, consistente en introducir una modulación interna a la señal, desacoplando alcance y resolución. ABSTRACT This thesis is focused on the study and development of electronic warfare (EW) and radar algorithms for real-time implementation. The arrival of radar, radio and navigation systems to the military sphere led to the development of technologies to fight them. Therefore, the objective of EW systems is the control of the electromagnetic spectrum. Signals Intelligence (SIGINT) is one of the EW functions, whose mission is to detect, collect, analyze, classify and locate all kind of electromagnetic emissions. Electronic intelligence (ELINT) is the SIGINT subsystem that is devoted to radar signals. A real-time system is the one whose correctness depends not only on the provided result but also on the time in which this result is obtained. Radar and EW systems must provide information as fast as possible on a continuous basis and they can be defined as real-time systems. The introduction of real-time constraints implies a feedback process between the design of the algorithms and their hardware implementation. Moreover, a real-time constraint consists of two parameters: Latency and area of the implementation. All the algorithms in this thesis have been implemented on field programmable gate array (FPGAs) platforms, presenting a trade-off among performance, cost, power consumption and reconfigurability. The first part of the thesis is related to the study of different key subsystems of an ELINT equipment: Signal detection with channelized receivers, pulse parameter extraction, modulation classification for radar signals and passive location algorithms. The discrete Fourier transform (DFT) is a nearly optimal detector and frequency estimator for narrow-band signals buried in white noise. The introduction of fast algorithms to calculate the DFT, known as FFT, reduces the complexity and the processing time of the DFT computation. These properties have placed the FFT as one the most conventional methods for narrow-band signal detection for real-time applications. An algorithm for real-time spectral analysis for user-defined bandwidth, instantaneous dynamic range and resolution is presented. The most characteristic parameters of a pulsed signal are its time of arrival (TOA) and the pulse width (PW). The estimation of these basic parameters is a fundamental task in an ELINT equipment. A basic pulse parameter extractor (PPE) that is able to estimate all these parameters is designed and implemented. The PPE may be useful to perform a generic radar recognition process, perform an emitter location technique and can be used as the preprocessing part of an automatic modulation classifier (AMC). Modulation classification is a difficult task in a non-cooperative environment. An AMC consists of two parts: Signal preprocessing and the classification algorithm itself. Featurebased algorithms obtain different characteristics or features of the input signals. Once these features are extracted, the classification is carried out by processing these features. A feature based-AMC for pulsed radar signals with real-time requirements is studied, designed and implemented. Emitter passive location techniques can be divided into two classes: Triangulation systems, in which the emitter location is estimated with the intersection of the different lines of bearing created from the estimated directions of arrival, and quadratic position-fixing systems, in which the position is estimated through the intersection of iso-time difference of arrival (TDOA) or iso-frequency difference of arrival (FDOA) quadratic surfaces. Although TDOA and FDOA are only implemented with time of arrival and frequency differences, different algorithms for TDOA, FDOA and position estimation are studied and analyzed. The second part is dedicated to FIR filter design and implementation for two different radar applications: Wideband phased arrays with true-time delay (TTD) filters and the range improvement of an operative radar with no hardware changes to minimize costs. Wideband operation of phased arrays is unfeasible because time delays cannot be approximated by phase shifts. The presented solution is based on the substitution of the phase shifters by FIR discrete delay filters. The maximum range of a radar depends on the averaged signal to noise ratio (SNR) at the receiver. Among other factors, the SNR depends on the transmitted signal energy that is power times pulse width. Any possible hardware change implies high costs. The proposed solution lies in the use of a signal processing technique known as pulse compression, which consists of introducing an internal modulation within the pulse width, decoupling range and resolution.

Conditional density approximations with mixtures of polynomials

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated basis functions (MoTBFs). The empirical results show that the proposed methods generally yield models that are comparable to or significantly better than those found using the MoTBF-based method.

Real-time incidents detection in the highways of the future

Due to ever increasing transportation of people and goods, automatic traffic surveillance is becoming a key issue for both providing safety to road users and improving traffic control in an efficient way. In this paper, we propose a new system that, exploiting the capabilities that both computer vision and machine learning offer, is able to detect and track different types of real incidents on a highway. Specifically, it is able to accurately detect not only stopped vehicles, but also drivers and passengers leaving the stopped vehicle, and other pedestrians present in the roadway. Additionally, a theoretical approach for detecting vehicles which may leave the road in an unexpected way is also presented. The system works in real-time and it has been optimized for working outdoor, being thus appropriate for its deployment in a real-world environment like a highway. First experimental results on a dataset created with videos provided by two Spanish highway operators demonstrate the effectiveness of the proposed system and its robustness against noise and low-quality videos.

Inteligencia artificial para la predicción y control del acabado superficial en procesos de fresado a alta velocidad

El objetivo principal de esta tesis doctoral es profundizar en el análisis y diseño de un sistema inteligente para la predicción y control del acabado superficial en un proceso de fresado a alta velocidad, basado fundamentalmente en clasificadores Bayesianos, con el prop´osito de desarrollar una metodolog´ıa que facilite el diseño de este tipo de sistemas. El sistema, cuyo propósito es posibilitar la predicción y control de la rugosidad superficial, se compone de un modelo aprendido a partir de datos experimentales con redes Bayesianas, que ayudar´a a comprender los procesos dinámicos involucrados en el mecanizado y las interacciones entre las variables relevantes. Dado que las redes neuronales artificiales son modelos ampliamente utilizados en procesos de corte de materiales, también se incluye un modelo para fresado usándolas, donde se introdujo la geometría y la dureza del material como variables novedosas hasta ahora no estudiadas en este contexto. Por lo tanto, una importante contribución en esta tesis son estos dos modelos para la predicción de la rugosidad superficial, que se comparan con respecto a diferentes aspectos: la influencia de las nuevas variables, los indicadores de evaluación del desempeño, interpretabilidad. Uno de los principales problemas en la modelización con clasificadores Bayesianos es la comprensión de las enormes tablas de probabilidad a posteriori producidas. Introducimos un m´etodo de explicación que genera un conjunto de reglas obtenidas de árboles de decisión. Estos árboles son inducidos a partir de un conjunto de datos simulados generados de las probabilidades a posteriori de la variable clase, calculadas con la red Bayesiana aprendida a partir de un conjunto de datos de entrenamiento. Por último, contribuimos en el campo multiobjetivo en el caso de que algunos de los objetivos no se puedan cuantificar en números reales, sino como funciones en intervalo de valores. Esto ocurre a menudo en aplicaciones de aprendizaje automático, especialmente las basadas en clasificación supervisada. En concreto, se extienden las ideas de dominancia y frontera de Pareto a esta situación. Su aplicación a los estudios de predicción de la rugosidad superficial en el caso de maximizar al mismo tiempo la sensibilidad y la especificidad del clasificador inducido de la red Bayesiana, y no solo maximizar la tasa de clasificación correcta. Los intervalos de estos dos objetivos provienen de un m´etodo de estimación honesta de ambos objetivos, como e.g. validación cruzada en k rodajas o bootstrap.---ABSTRACT---The main objective of this PhD Thesis is to go more deeply into the analysis and design of an intelligent system for surface roughness prediction and control in the end-milling machining process, based fundamentally on Bayesian network classifiers, with the aim of developing a methodology that makes easier the design of this type of systems. The system, whose purpose is to make possible the surface roughness prediction and control, consists of a model learnt from experimental data with the aid of Bayesian networks, that will help to understand the dynamic processes involved in the machining and the interactions among the relevant variables. Since artificial neural networks are models widely used in material cutting proceses, we include also an end-milling model using them, where the geometry and hardness of the piecework are introduced as novel variables not studied so far within this context. Thus, an important contribution in this thesis is these two models for surface roughness prediction, that are then compared with respecto to different aspects: influence of the new variables, performance evaluation metrics, interpretability. One of the main problems with Bayesian classifier-based modelling is the understanding of the enormous posterior probabilitiy tables produced. We introduce an explanation method that generates a set of rules obtained from decision trees. Such trees are induced from a simulated data set generated from the posterior probabilities of the class variable, calculated with the Bayesian network learned from a training data set. Finally, we contribute in the multi-objective field in the case that some of the objectives cannot be quantified as real numbers but as interval-valued functions. This often occurs in machine learning applications, especially those based on supervised classification. Specifically, the dominance and Pareto front ideas are extended to this setting. Its application to the surface roughness prediction studies the case of maximizing simultaneously the sensitivity and specificity of the induced Bayesian network classifier, rather than only maximizing the correct classification rate. Intervals in these two objectives come from a honest estimation method of both objectives, like e.g. k-fold cross-validation or bootstrap.

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Characterisation of the operation & maintenance phase in PV rural electrification programmes

Con 1.300 millones de personas en el mundo sin acceso a la electricidad (la mayoría en entornos rurales de países empobrecidos), la energía solar fotovoltaica constituye una solución viable técnica y económicamente para electrificar las zonas más remotas del planeta donde las redes eléctricas convencionales no llegan. Casi todos los países en el mundo han desarrollado algún tipo de programa de electrificación fotovoltaica rural durante los últimos 40 años, principalmente los países más pobres, donde a través de diferentes modelos de financiación, se han instalado millones de sistemas solares domiciliarios (pequeños sistemas fotovoltaicos para uso doméstico). Durante este largo período, se han ido superando muchas barreras, como la mejora de la calidad de los sistemas fotovoltaicos, la reducción de costes, la optimización del diseño y del dimensionado de los sistemas, la disponibilidad financiera para implantar programas de electrificación rural, etc. Gracias a esto, la electrificación rural descentralizada ha experimentado recientemente un salto de escala caracterizada por la implantación de grandes programas con miles de sistemas solares domiciliarios e integrando largos períodos de mantenimiento. Muchos de estos grandes programas se están llevando a cabo con limitado éxito, ya que generalmente parten de supuestos e hipótesis poco contrastadas con la realidad, comprometiendo así un retorno económico que permita el desarrollo de esta actividad a largo plazo. En este escenario surge un nuevo reto: el de cómo garantizar la sostenibilidad de los grandes programas de electrificación rural fotovoltaica. Se argumenta que la principal causa de esta falta de rentabilidad es el imprevisto alto coste de la fase de operación y mantenimiento. Cuestiones clave tales como la estructura de costes de operación y mantenimiento o la fiabilidad de los componentes del sistema fotovoltaico no están bien caracterizados hoy en día. Esta situación limita la capacidad de diseñar estructuras de mantenimiento capaces de asegurar la sostenibilidad y la rentabilidad del servicio de operación y mantenimiento en estos programas. Esta tesis doctoral tiene como objetivo responder a estas cuestiones. Se ha realizado varios estudios sobre la base de un gran programa de electrificación rural fotovoltaica real llevado a cabo en Marruecos con más de 13.000 sistemas solares domiciliarios instalados. Sobre la base de este programa se ha hecho una evaluación en profundidad de la fiabilidad de los sistemas solares a partir de los datos de mantenimiento recogidos durante 5 años con más de 80.000 inputs. Los resultados han permitido establecer las funciones de fiabilidad de los equipos tal y como se comportan en condiciones reales de operación, las tasas de fallos y los tiempos medios hasta el fallo para los principales componentes del sistema, siendo este el primer caso de divulgación de resultados de este tipo en el campo de la electrificación rural fotovoltaica. Los dos principales componentes del sistema solar domiciliario, la batería y el módulo fotovoltaico, han sido analizados en campo a través de una muestra de 41 sistemas trabajando en condiciones reales pertenecientes al programa solar marroquí. Por un lado se ha estudiado la degradación de la capacidad de las baterías y por otro la degradación de potencia de los módulos fotovoltaicos. En el caso de las baterías, los resultados nos han permitido caracterizar la curva de degradación en capacidad llegando a obtener una propuesta de nueva definición del umbral de vida útil de las baterías en electrificación rural. También sobre la base del programa solar de Marruecos se ha llevado a cabo un estudio de caracterización de los costes reales de operación y mantenimiento a partir de la base de datos de contabilidad del programa registrados durante 5 años. Los resultados del estudio han permitido definir cuáles son costes que más incidencia tienen en el coste global. Se han obtenido los costes unitarios por sistema instalado y se han calculado los montantes de las cuotas de mantenimiento de los usuarios para garantizar la rentabilidad de la operación y mantenimiento. Finalmente, se propone un modelo de optimización matemática para diseñar estructuras de mantenimiento basado en los resultados de los estudios anteriores. La herramienta, elaborada mediante programación lineal entera mixta, se ha aplicado al programa marroquí con el fin de validar el modelo propuesto. ABSTRACT With 1,300 million people worldwide deprived of access to electricity (mostly in rural environments), photovoltaic solar energy has proven to be a cost‐effective solution and the only hope for electrifying the most remote inhabitants of the planet, where conventional electric grids do not reach because they are unaffordable. Almost all countries in the world have had some kind of rural photovoltaic electrification programme during the past 40 years, mainly the poorer countries, where through different organizational models, millions of solar home systems (small photovoltaic systems for domestic use) have been installed. During this long period, many barriers have been overcome, such as quality enhancement, cost reduction, the optimization of designing and sizing, financial availability, etc. Thanks to this, decentralized rural electrification has recently experienced a change of scale characterized by new programmes with thousands of solar home systems and long maintenance periods. Many of these large programmes are being developed with limited success, as they have generally been based on assumptions that do not correspond to reality, compromising the economic return that allows long term activity. In this scenario a new challenge emerges, which approaches the sustainability of large programmes. It is argued that the main cause of unprofitability is the unexpected high cost of the operation and maintenance of the solar systems. In fact, the lack of a paradigm in decentralized rural services has led to many private companies to carry out decentralized electrification programmes blindly. Issues such as the operation and maintenance cost structure or the reliability of the solar home system components have still not been characterized. This situation does not allow optimized maintenance structure to be designed to assure the sustainability and profitability of the operation and maintenance service. This PhD thesis aims to respond to these needs. Several studies have been carried out based on a real and large photovoltaic rural electrification programme carried out in Morocco with more than 13,000 solar home systems. An in‐depth reliability assessment has been made from a 5‐year maintenance database with more than 80,000 maintenance inputs. The results have allowed us to establish the real reliability functions, the failure rate and the main time to failure of the main components of the system, reporting these findings for the first time in the field of rural electrification. Both in‐field experiments on the capacity degradation of batteries and power degradation of photovoltaic modules have been carried out. During the experiments both samples of batteries and modules were operating under real conditions integrated into the solar home systems of the Moroccan programme. In the case of the batteries, the results have enabled us to obtain a proposal of definition of death of batteries in rural electrification. A cost assessment of the Moroccan experience based on a 5‐year accounting database has been carried out to characterize the cost structure of the programme. The results have allowed the major costs of the photovoltaic electrification to be defined. The overall cost ratio per installed system has been calculated together with the necessary fees that users would have to pay to make the operation and maintenance affordable. Finally, a mathematical optimization model has been proposed to design maintenance structures based on the previous study results. The tool has been applied to the Moroccan programme with the aim of validating the model.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Engineering a tRNA and aminoacyl-tRNA synthetase for the site-specific incorporation of unnatural amino acids into proteins in vivo

In an effort to expand the scope of protein mutagenesis, we have completed the first steps toward a general method to allow the site-specific incorporation of unnatural amino acids into proteins in vivo. Our approach involves the generation of an “orthogonal” suppressor tRNA that is uniquely acylated in Escherichia coli by an engineered aminoacyl-tRNA synthetase with the desired unnatural amino acid. To this end, eight mutations were introduced into tRNA2Gln based on an analysis of the x-ray crystal structure of the glutaminyl-tRNA aminoacyl synthetase (GlnRS)–tRNA2Gln complex and on previous biochemical data. The resulting tRNA satisfies the minimal requirements for the delivery of an unnatural amino acid: it is not acylated by any endogenous E. coli aminoacyl-tRNA synthetase including GlnRS, and it functions efficiently in protein translation. Repeated rounds of DNA shuffling and oligonucleotide-directed mutagenesis followed by genetic selection resulted in mutant GlnRS enzymes that efficiently acylate the engineered tRNA with glutamine in vitro. The mutant GlnRS and engineered tRNA also constitute a functional synthetase–tRNA pair in vivo. The nature of the GlnRS mutations, which occur both at the protein–tRNA interface and at sites further away, is discussed.

HSP70 homolog functions in cell-to-cell movement of a plant virus

Plant closteroviruses encode a homolog of the HSP70 (heat shock protein, 70 kDa) family of cellular proteins. To facilitate studies of the function of HSP70 homolog (HSP70h) in viral infection, the beet yellows closterovirus (BYV) was modified to express green fluorescent protein. This tagged virus was competent in cell-to-cell movement, producing multicellular infection foci similar to those formed by the wild-type BYV. Inactivation of the HSP70h gene by replacement of the start codon or by deletion of 493 codons resulted in complete arrest of BYV translocation from cell to cell. Identical movement-deficient phenotypes were observed in BYV variants possessing HSP70h that lacked the computer-predicted ATPase domain or the C-terminal domain, or that harbored point mutations in the putative catalytic site of the ATPase. These results demonstrate that the virus-specific member of the HSP70 family of molecular chaperones functions in intercellular translocation and represents an additional type of a plant viral-movement protein.

Drosophila coracle, a Member of the Protein 4.1 Superfamily, Has Essential Structural Functions in the Septate Junctions and Developmental Functions in Embryonic and Adult Epithelial Cells

Although extensively studied biochemically, members of the Protein 4.1 superfamily have not been as well characterized genetically. Studies of coracle, a Drosophila Protein 4.1 homologue, provide an opportunity to examine the genetic functions of this gene family. coracle was originally identified as a dominant suppressor of EgfrElp, a hypermorphic form of the Drosophila Epidermal growth factor receptor gene. In this article, we present a phenotypic analysis of coracle, one of the first for a member of the Protein 4.1 superfamily. Screens for new coracle alleles confirm the null coracle phenotype of embryonic lethality and failure in dorsal closure, and they identify additional defects in the embryonic epidermis and salivary glands. Hypomorphic coracle alleles reveal functions in many imaginal tissues. Analysis of coracle mutant cells indicates that Coracle is a necessary structural component of the septate junction required for the maintenance of the transepithelial barrier but is not necessary for apical–basal polarity, epithelial integrity, or cytoskeletal integrity. In addition, coracle phenotypes suggest a specific role in cell signaling events. Finally, complementation analysis provides information regarding the functional organization of Coracle and possibly other Protein 4.1 superfamily members. These studies provide insights into a range of in vivo functions for coracle in developing embryos and adults.

New infinite families of exact sums of squares formulas, Jacobi elliptic functions, and Ramanujan’s tau function

In this paper, we give two infinite families of explicit exact formulas that generalize Jacobi’s (1829) 4 and 8 squares identities to 4n2 or 4n(n + 1) squares, respectively, without using cusp forms. Our 24 squares identity leads to a different formula for Ramanujan’s tau function τ(n), when n is odd. These results arise in the setting of Jacobi elliptic functions, Jacobi continued fractions, Hankel or Turánian determinants, Fourier series, Lambert series, inclusion/exclusion, Laplace expansion formula for determinants, and Schur functions. We have also obtained many additional infinite families of identities in this same setting that are analogous to the η-function identities in appendix I of Macdonald’s work [Macdonald, I. G. (1972) Invent. Math. 15, 91–143]. A special case of our methods yields a proof of the two conjectured [Kac, V. G. and Wakimoto, M. (1994) in Progress in Mathematics, eds. Brylinski, J.-L., Brylinski, R., Guillemin, V. & Kac, V. (Birkhäuser Boston, Boston, MA), Vol. 123, pp. 415–456] identities involving representing a positive integer by sums of 4n2 or 4n(n + 1) triangular numbers, respectively. Our 16 and 24 squares identities were originally obtained via multiple basic hypergeometric series, Gustafson’s Cℓ nonterminating 6φ5 summation theorem, and Andrews’ basic hypergeometric series proof of Jacobi’s 4 and 8 squares identities. We have (elsewhere) applied symmetry and Schur function techniques to this original approach to prove the existence of similar infinite families of sums of squares identities for n2 or n(n + 1) squares, respectively. Our sums of more than 8 squares identities are not the same as the formulas of Mathews (1895), Glaisher (1907), Ramanujan (1916), Mordell (1917, 1919), Hardy (1918, 1920), Kac and Wakimoto, and many others.

Real-time detection of DNA hybridization and melting on oligonucleotide arrays by using optical wave guides.

The challenge of the Human Genome Project is to increase the rate of DNA sequence acquisition by two orders of magnitude to complete sequencing of the human genome by the year 2000. The present work describes a rapid detection method using a two-dimensional optical wave guide that allows measurement of real-time binding or melting of a light-scattering label on a DNA array. A particulate label on the target DNA acts as a light-scattering source when illuminated by the evanescent wave of the wave guide and only the label bound to the surface generates a signal. Imaging/visual examination of the scattered light permits interrogation of the entire array simultaneously. Hybridization specificity is equivalent to that obtained with a conventional system using autoradiography. Wave guide melting curves are consistent with those obtained in the liquid phase and single-base discrimination is facile. Dilution experiments showed an apparent lower limit of detection at 0.4 nM oligonucleotide. This performance is comparable to the best currently known fluorescence-based systems. In addition, wave guide detection allows manipulation of hybridization stringency during detection and thereby reduces DNA chip complexity. It is anticipated that this methodology will provide a powerful tool for diagnostic applications that require rapid cost-effective detection of variations from known sequences.

Proper placement of the Escherichia coli division site requires two functions that are associated with different domains of the MinE protein.

The proper placement of the Escherichia coli division septum requires the MinE protein. MinE accomplishes this by imparting topological specificity to a division inhibitor coded by the minC and minD genes. As a result, the division inhibitor prevents septation at potential division sites that exist at the cell poles but permits septation at the normal division site at midcell. In this paper, we define two functions of MinE that are required for this effect and present evidence that different domains within the 88-amino acid MinE protein are responsible for each of these two functions. The first domain, responsible for the ability of MinE to counteract the activity of the MinCD division inhibitor, is located in a small region near the N terminus of the protein. The second domain, required for the topological specificity of MinE function, is located in the more distal region of the protein and affects the site specificity of placement of the division septum even when separated from the domain responsible for suppression of the activity of the division inhibitor.