Synthesis and characterization of GaAsSb-capped InAs-based QDIPs

Quantum dot infrared photodetectors (QDIPs) are very attractive for infrared imaging applications due to its promising features such as high temperature operation, normal incidence response and low dark current [1]. However, the key issue is to obtain a high quality active region which requires a structural optimization of the nanostructures. With using GaAsSb capping layer, the optical properties, such as the PL intensity and its full width at half maximum (FWHM), of InAs QDs have been improved in the range between 1.15 and 1.5 m, because of the reduction of the compressive strain in QDs and the increment of QD height [2]. In this work, we have demonstrated strong and narrow intraband photoresponse spectra from GaAsSb-capped InAs-based QDIPs

Mid-infrared photodetectors based on GaAsSb-capped InAs quantum dots

Quantum dot infrared photodetectors (QDIPs) are very attractive for many applications such as infrared imaging, remote sensing and gas sensing, thanks to its promising features such as high temperature operation, normal incidence response and low dark current [1]. However, the key issue is to obtain a high-quality active region which requires an optimization of the nanostructure. By using GaAsSb capping layer, InAs QDs have improved their optical emission in the range between 1.15 and 1.3 m (at Sb composition of 14 %), due to a reduction of a compressive strain in QD and an increment of a QD height [2]. In this work, we have demonstrated strong and narrow intraband photoresponses at ~ 5 m from GaAsSb-capped InAs/GaAs QDIPs under normal light-incidence.

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation.

Simulation of a mechanical thrombectomy device based in the use of self-expandable stents for the blood clots extraction

Recently, we have presented some studies concerning the analysis, design and optimization of one experimental device developed in the UK - GPTAD - which has been designed to remove blood clots without the need to make contact with the clot itself, thereby potentially reducing the risk of problems such as downstream embolisation. Based on the idea of a modification of the previous device, in this work, we present a model based in the use of stents like the SolitaireTM FR, which is in contact with the clot itself. In the case of such devices, the stent is self-expandable and the extraction of the blood clot is faciliatated by the stent, which must be inside the clot. Such stents are generally inserted in position by using the guidewire inserted into the catheter. This type of modeling could potentially be useful in showing how the blood clot is moved by the various different forces involved. The modelling has been undertaken by analyzing the resistances, compliances and inertances effects. We model an artery and blood clot for range of forces for the guidewire. In each case we determine the interaction between blood clot, stent and artery.

Serial or Parallel Linear-Assisted Switching Converter as Envelope Amplifier: Optimization and Comparison

This paper presents a theoretical analysis and an optimization method for envelope amplifier. Highly efficient envelope amplifiers based on a switching converter in parallel or series with a linear regulator have been analyzed and optimized. The results of the optimization process have been shown and these two architectures are compared regarding their complexity and efficiency. The optimization method that is proposed is based on the previous knowledge about the transmitted signal type (OFDM, WCDMA...) and it can be applied to any signal type as long as the envelope probability distribution is known. Finally, it is shown that the analyzed architectures have an inherent efficiency limit.

Self-reference Scrubber for TMR Systems Based on Xilinx Virtex FPGAs

SRAM-based FPGAs are sensitive to radiation effects. Soft errors can appear and accumulate, potentially defeating mitigation strategies deployed at the Application Layer. Therefore, Configuration Memory scrubbing is required to improve radiation tolerance of such FPGAs in space applications. Virtex FPGAs allow runtime scrubbing by means of dynamic partial reconfiguration. Even with scrubbing, intra-FPGA TMR systems are subjected to common-mode errors affecting more than one design domain. This is solved in inter-FPGA TMR systems at the expense of a higher cost, power and mass. In this context, a self-reference scrubber for device-level TMR system based on Xilinx Virtex FPGAs is presented. This scrubber allows for a fast SEU/MBU detection and correction by peer frame comparison without needing to access a golden configuration memory

PV self-consumption optimization with storage and Active DSM for the residential sector

With the rising prices of the retail electricity and the decreasing cost of the PV technology, grid parity with commercial electricity will soon become a reality in Europe. This fact, together with less attractive PV feed-in-tariffs in the near future and incentives to promote self-consumption suggest, that new operation modes for the PV Distributed Generation should be explored; differently from the traditional approach which is only based on maximizing the exported electricity to the grid. The smart metering is experiencing a growth in Europe and the United States but the possibilities of its use are still uncertain, in our system we propose their use to manage the storage and to allow the user to know their electrical power and energy balances. The ADSM has many benefits studied previously but also it has important challenges, in this paper we can observe and ADSM implementation example where we propose a solution to these challenges. In this paper we study the effects of the Active Demand-Side Management (ADSM) and storage systems in the amount of consumed local electrical energy. It has been developed on a prototype of a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead–acid batteries, controllable appliances and smart metering. We carried out simulations for long-time experiments (yearly studies) and real measures for short and mid-time experiments (daily and weekly studies). Results show the relationship between the electricity flows and the storage capacity, which is not linear and becomes an important design criterion.

Optimization of urban mobility measures to achieve win-win strategies

European cities are essential in the development of Europe as they constitute the living environment of more than 60% of the population in the European Union and are drivers of the European economy – just under 85% of the EU’s gross domestic product is produced in urban areas (EC, 2007a). The car has been one of the main factors of development during the 20th century, but it is at the same time the origin of the key problems cities have to face: traffic increase. This has resulted in chronic congestion with many adverse consequences such as air pollution and noise. This loss of environmental quality is one of the reasons for urban sprawl in European cities during recent decades. But this urban sprawl at the same time worsens the environmental conditions. We must return to the dense city, but clean and competitive, and this implies reducing car use yet provides quality transport alternatives sufficient to recover and maintain the competitiveness of cities (EC, 2007a). Consequently, European cities need to establish an urban transport strategy which helps reduce their environmental problems –mainly emissions and noise – but without decreasing their trip attraction. This aspect is very important because a loss of trip attraction would result in an increase of people moving to more disperse areas, contributing towards worsening the current situation. This thesis is an attempt to contribute solutions to this problem in two ways: 1) The first is to analyze the complementarity and possible synergies of several urban transport measures aimed at improving a modal split to a more sustainable means of transport. This analysis will focus on the three aspects already mentioned: emissions, noise and attractiveness or competitiveness. 2) Once possible synergies and complementarities have been analyzed, the second objective is to propose the best combination of these measures, in terms of level of implementation, to achieve the maximum benefit with respect to the three aspects previously established: emissions, noise and attractiveness or competitiveness. Therefore, within the wide range of measures enhancing sustainable urban transport, three of them have been be selected in this thesis to establish a methodology for achieving these objectives. The analysis will be based on the region of Madrid, which is also the case study selected for this research. Las ciudades europeas son piezas fundamentales para el desarrollo europeo, ya que son el lugar de residencia de más del 60% de la población de la unión europea así como los motores de su economía – casi el 85% del PIB europeo se produce en áreas urbanas (EC, 2007a). El coche ha sido uno de los principales motores de desarrollo de las ciudades durante el siglo XX, pero se ha terminado por convertir a su vez en uno de los principales problemas con los que tiene que lidiar las ciudades: el aumento del tráfico. Esto ha derivado en unos niveles crónicos de congestión, con multitud de efectos adversos, entre los que cabe destacar la contaminación del aire y el ruido. Esta pérdida de calidad ambiental es una de las razones que ha propiciado la dispersión urbana que han experimentado las ciudades europeas en las últimas décadas. Pero esta dispersión urbana a su vez contribuye a empeorar las condiciones ambientales de las ciudades. Debemos retornar a la ciudad densa, pero limpia y competitiva, y esto implica reducir el uso del coche, pero proporcionando alternativas de transporte que permitan recuperar y mantener la competitividad de las ciudades (EC, 2007a). Por lo tanto, las ciudades europeas necesitan encontrar una estrategia de transporte urbano que ayude a reducir sus problemas medio ambientales – principalmente ruido y emisiones – pero sin hacerlas perder atractividad o competitividad. Este aspecto tiene gran importancia porque una pérdida de la misma se traduciría en un aumento de dispersión de la población hacia áreas periféricas, contribuyendo a empeorar la situación actual. Esta tesis contribuye a solucionar este problema de dos maneras: 1) La primera, analizando la complementariedad y posibles sinergias de diferentes medidas de transporte urbano orientadas a promover un reparto modal hacia modos más sostenibles. Este análisis se centrará en los tres aspectos anteriormente citados: emisiones, ruido y atractividad o competitividad. 2) Una vez las posibles sinergias y complementariedades se han analizado, el segundo objetivo es proponer la mejor combinación de estas medidas – en términos de grado de aplicación - para lograr el máximo beneficio en lo que respecta a los tres objetivos previamente establecidos. Para ello, en esta tesis se han seleccionado una serie de medidas que permitan establecer una metodología para alcanzar estos objetivos previamente definidos. El análisis se centra en la ciudad de Madrid y su área metropolitana, la cual se ha escogido como caso de estudio para realizar esta investigación.

An Interval-based Multiobjective Approach to Feature Subset Selection Using Joint Modeling of Objectives and Variables

This paper studies feature subset selection in classification using a multiobjective estimation of distribution algorithm. We consider six functions, namely area under ROC curve, sensitivity, specificity, precision, F1 measure and Brier score, for evaluation of feature subsets and as the objectives of the problem. One of the characteristics of these objective functions is the existence of noise in their values that should be appropriately handled during optimization. Our proposed algorithm consists of two major techniques which are specially designed for the feature subset selection problem. The first one is a solution ranking method based on interval values to handle the noise in the objectives of this problem. The second one is a model estimation method for learning a joint probabilistic model of objectives and variables which is used to generate new solutions and advance through the search space. To simplify model estimation, l1 regularized regression is used to select a subset of problem variables before model learning. The proposed algorithm is compared with a well-known ranking method for interval-valued objectives and a standard multiobjective genetic algorithm. Particularly, the effects of the two new techniques are experimentally investigated. The experimental results show that the proposed algorithm is able to obtain comparable or better performance on the tested datasets.

Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables

This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint modeling of objectives and variables. This EDA uses the multi-dimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find better trade-off solutions to the multi-objective problem. In addition to Pareto set approximation, the algorithm is also able to estimate the structure of the multi-objective problem. To apply the algorithm to many-objective problems, the algorithm includes four different ranking methods proposed in the literature for this purpose. The algorithm is applied to the set of walking fish group (WFG) problems, and its optimization performance is compared with an evolutionary algorithm and another multi-objective EDA. The experimental results show that the proposed algorithm performs significantly better on many of the problems and for different objective space dimensions, and achieves comparable results on some compared with the other algorithms.

Towards description and optimization of abstract machines in an extension of prolog

Competitive abstract machines for Prolog are usually large, intricate, and incorpórate sophisticated optimizations. This makes them difñcult to code, optimize, and, especially, maintain and extend. This is partly due to the fact that efñciency considerations make it necessary to use low-level languages in their implementation. Writing the abstract machine (and ancillary code) in a higher-level language can help harness this inherent complexity. In this paper we show how the semantics of basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog which retains much of its semantics. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog the abstract machine descriptions can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of highly-tuned, hand-crafted emulators.

An abstract interpretation-based approach to mobile code safety

Recent approaches to mobile code safety, like proof- arrying code, involve associating safety information to programs. The code supplier provides a program and also includes with it a certifícate (or proof) whose validity entails compliance with a predefined safety policy. The intended benefit is that the program consumer can locally validate the certifícate w.r.t. the "untrusted" program by means of a certifícate checker—a process which should be much simpler, eflicient, and automatic than generating the original proof. We herein introduce a novel approach to mobile code safety which follows a similar scheme, but which is based throughout on the use of abstract interpretation techniques. In our framework the safety policy is specified by using an expressive assertion language defined over abstract domains. We identify a particular slice of the abstract interpretation-based static analysis results which is especially useful as a certifícate. We propose an algorithm for checking the validity of the certifícate on the consumer side which is itself in fact a very simplified and eflicient specialized abstract-interpreter. Our ideas are illustrated through an example implemented in the CiaoPP system. Though further experimentation is still required, we believe the proposed approach is of interest for bringing the automation and expressiveness which is inherent in the abstract interpretation techniques to the área of mobile code safety.

Biosensors based on vertically interrogated optofluidic sensing cells

El objetivo de la presente tesis doctoral es el desarrollo de un nuevo concepto de biosensor óptico sin marcado, basado en una combinación de técnicas de caracterización óptica de interrogación vertical y estructuras sub-micrométricas fabricadas sobre chips de silicio. Las características más importantes de dicho dispositivo son su simplicidad, tanto desde el punto de vista de medida óptica como de introducción de las muestras a medir en el área sensible, aspectos que suelen ser críticos en la mayoría de sensores encontrados en la literatura. Cada uno de los aspectos relacionados con el diseño de un biosensor, que son fundamentalmente cuatro (diseño fotónico, caracterización óptica, fabricación y fluídica/inmovilización química) son desarrollados en detalle en los capítulos correspondientes. En la primera parte de la tesis se hace una introducción al concepto de biosensor, en qué consiste, qué tipos hay y cuáles son los parámetros más comunes usados para cuantificar su comportamiento. Posteriormente se realiza un análisis del estado del arte en la materia, enfocado en particular en el área de biosensores ópticos sin marcado. Se introducen también cuáles son las reacciones bioquímicas a estudiar (inmunoensayos). En la segunda parte se describe en primer lugar cuáles son las técnicas ópticas empleadas en la caracterización: Reflectometría, Elipsometría y Espectrometría; además de los motivos que han llevado a su empleo. Posteriormente se introducen diversos diseños de las denominadas "celdas optofluídicas", que son los dispositivos en los que se va a producir la interacción bioquímica. Se presentan cuatro dispositivos diferentes, y junto con ellos, se proponen diversos métodos de cálculo teórico de la respuesta óptica esperada. Posteriormente se procede al cálculo de la sensibilidad esperada para cada una de las celdas, así como al análisis de los procesos de fabricación de cada una de ellas y su comportamiento fluídico. Una vez analizados todos los aspectos críticos del comportamiento del biosensor, se puede realizar un proceso de optimización de su diseño. Esto se realiza usando un modelo de cálculo simplificado (modelo 1.5-D) que permite la obtención de parámetros como la sensibilidad y el límite de detección de un gran número de dispositivos en un tiempo relativamente reducido. Para este proceso se escogen dos de las celdas optofluídicas propuestas. En la parte final de la tesis se muestran los resultados experimentales obtenidos. En primer lugar, se caracteriza una celda basada en agujeros sub-micrométricos como sensor de índice de refracción, usando para ello diferentes líquidos orgánicos; dichos resultados experimentales presentan una buena correlación con los cálculos teóricos previos, lo que permite validar el modelo conceptual presentado. Finalmente, se realiza un inmunoensayo químico sobre otra de las celdas propuestas (pilares nanométricos de polímero SU-8). Para ello se utiliza el inmunoensayo de albumina de suero bovino (BSA) y su anticuerpo (antiBSA). Se detalla el proceso de obtención de la celda, la funcionalización de la superficie con los bioreceptores (en este caso, BSA) y el proceso de biorreconocimiento. Este proceso permite dar una primera estimación de cuál es el límite de detección esperable para este tipo de sensores en un inmunoensayo estándar. En este caso, se alcanza un valor de 2.3 ng/mL, que es competitivo comparado con otros ensayos similares encontrados en la literatura. La principal conclusión de la tesis es que esta tipología de dispositivos puede ser usada como inmunosensor, y presenta ciertas ventajas respecto a los actualmente existentes. Estas ventajas vienen asociadas, de nuevo, a su simplicidad, tanto a la hora de medir ópticamente, como dentro del proceso de introducción de los bioanalitos en el área sensora (depositando simplemente una gota sobre la micro-nano-estructura). Los cálculos teorícos realizados en los procesos de optimización sugieren a su vez que el comportamiento del sensor, medido en magnitudes como límite de detección biológico puede ser ampliamente mejorado con una mayor compactación de pilares, alcanzandose un valor mínimo de 0.59 ng/mL). The objective of this thesis is to develop a new concept of optical label-free biosensor, based on a combination of vertical interrogation optical techniques and submicron structures fabricated over silicon chips. The most important features of this device are its simplicity, both from the point of view of optical measurement and regarding to the introduction of samples to be measured in the sensing area, which are often critical aspects in the majority of sensors found in the literature. Each of the aspects related to the design of biosensors, which are basically four (photonic design, optical characterization, fabrication and fluid / chemical immobilization) are developed in detail in the relevant chapters. The first part of the thesis consists of an introduction to the concept of biosensor: which elements consists of, existing types and the most common parameters used to quantify its behavior. Subsequently, an analysis of the state of the art in this area is presented, focusing in particular in the area of label free optical biosensors. What are also introduced to study biochemical reactions (immunoassays). The second part describes firstly the optical techniques used in the characterization: reflectometry, ellipsometry and spectrometry; in addition to the reasons that have led to their use. Subsequently several examples of the so-called "optofluidic cells" are introduced, which are the devices where the biochemical interactions take place. Four different devices are presented, and their optical response is calculated by using various methods. Then is exposed the calculation of the expected sensitivity for each of the cells, and the analysis of their fabrication processes and fluidic behavior at the sub-micrometric range. After analyzing all the critical aspects of the biosensor, it can be performed a process of optimization of a particular design. This is done using a simplified calculation model (1.5-D model calculation) that allows obtaining parameters such as sensitivity and the detection limit of a large number of devices in a relatively reduced time. For this process are chosen two different optofluidic cells, from the four previously proposed. The final part of the thesis is the exposition of the obtained experimental results. Firstly, a cell based sub-micrometric holes is characterized as refractive index sensor using different organic fluids, and such experimental results show a good correlation with previous theoretical calculations, allowing to validate the conceptual model presented. Finally, an immunoassay is performed on another typology of cell (SU-8 polymer pillars). This immunoassay uses bovine serum albumin (BSA) and its antibody (antiBSA). The processes for obtaining the cell surface functionalization with the bioreceptors (in this case, BSA) and the biorecognition (antiBSA) are detailed. This immunoassay can give a first estimation of which are the expected limit of detection values for this typology of sensors in a standard immunoassay. In this case, it reaches a value of 2.3 ng/mL, which is competitive with other similar assays found in the literature. The main conclusion of the thesis is that this type of device can be used as immunosensor, and has certain advantages over the existing ones. These advantages are associated again with its simplicity, by the simpler coupling of light and in the process of introduction of bioanalytes into the sensing areas (by depositing a droplet over the micro-nano-structure). Theoretical calculations made in optimizing processes suggest that the sensor Limit of detection can be greatly improved with higher compacting of the lattice of pillars, reaching a minimum value of 0.59 ng/mL).

Specialization and optimization of constraint programs with dynamic scheduling

In this report we discuss some of the issues involved in the specialization and optimization of constraint logic programs with dynamic scheduling. Dynamic scheduling, as any other form of concurrency, increases the expressive power of constraint logic programs, but also introduces run-time overhead. The objective of the specialization and optimization is to reduce as much as possible such overhead automatically, while preserving the semantics of the original programs. This is done by program transformation based on global analysis. We present implementation techniques for this purpose and report on experimental results obtained from an implementation of the techniques in the context of the CIAO compiler.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.