An adaptive population importance sampler

Monte Carlo (MC) methods are widely used in signal processing, machine learning and communications for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling and its adaptive extensions (e.g., population Monte Carlo). In this work, we introduce an adaptive importance sampler using a population of proposal densities. The novel algorithm provides a global estimation of the variables of interest iteratively, using all the samples generated. The cloud of proposals is adapted by learning from a subset of previously generated samples, in such a way that local features of the target density can be better taken into account compared to single global adaptation procedures. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error and robustness to initialization.

Quality of experience and HTTP adaptive streaming: a review of subjective studies

HTTP adaptive streaming technology has become widely spread in multimedia services because of its ability to provide adaptation to characteristics of various viewing devices and dynamic network conditions. There are various studies targeting the optimization of adaptation strategy. However, in order to provide an optimal viewing experience to the end-user, it is crucial to get knowledge about the Quality of Experience (QoE) of different adaptation schemes. This paper overviews the state of the art concerning subjective evaluation of adaptive streaming QoE and highlights the challenges and open research questions related to QoE assessment.

Crowdsourcing based subjective quality assessment of adaptive video streaming

In order to cater for user's quality of experience (QoE) requirements, HTTP adaptive streaming (HAS) based solutions of video services have become popular recently. User QoE feedback can be instrumental in improving the capabilities of such services. Perceptual quality experiments that involve humans are considered to be the most valid method of the assessment of QoE. Besides lab-based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative method. This paper presents insights into a study that investigates perceptual preferences of various adaptive video streaming scenarios through crowdsourcing based subjective quality assessment.

The Monge-Ampére equation method in freeform optics design

The Monge-Ampére equation method could be the most advanced point source algorithm of freeform optics design. This paper introduces this method, and outlines two key issues that should be tackles to improve this method.

Fabrication and tolerances of optics for high concentration photovoltaics

High Concentration Photovoltaics (HCPV) require an optical system with high efficiency, low cost and large tolerance. We describe the particularities of the HCPV applications, which constrain the optics design and the manufacturing techonologies.

Subjective quality study of adaptive streaming of monoscopic and stereoscopic video

Nowadays, HTTP adaptive streaming (HAS) has become a reliable distribution technology offering significant advantages in terms of both user perceived Quality of Experience (QoE) and resource utilization for content and network service providers. By trading-off the video quality, HAS is able to adapt to the available bandwidth and display requirements so that it can deliver the video content to a variety of devices over the Internet. However, until now there is not enough knowledge of how the adaptation techniques affect the end user's visual experience. Therefore, this paper presents a comparative analysis of different bitrate adaptation strategies in adaptive streaming of monoscopic and stereoscopic video. This has been done through a subjective experiment of testing the end-user response to the video quality variations, considering the visual comfort issue. The experimental outcomes have made a good insight into the factors that can influence on the QoE of different adaptation strategies.

Effect of content characteristics on quality of experience of adaptive streaming

The growing popularity of adaptive streaming-based video delivery nowadays has raised the interest about the user's perception when experiencing quality adaptation. The impact of the video content characteristics on user's perceptual quality has already become evident. The aim of this study is to investigate the influence of this factor on the quality of experience of adaptive streaming scenarios. Our results show that the perceptual quality of adaptation strategies applied on videos with high spatial and low temporal amount of activity is significantly lower compared to the other content types.

Real-Time Adaptive Multi-Classifier Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles

This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.

Rate-Adaptive LDPC-based key reconciliation for high performance quantum key distribution

The postprocessing or secret-key distillation process in quantum key distribution (QKD) mainly involves two well-known procedures: information reconciliation and privacy amplification. Information or key reconciliation has been customarily studied in terms of efficiency. During this, some information needs to be disclosed for reconciling discrepancies in the exchanged keys. The leakage of information is lower bounded by a theoretical limit, and is usually parameterized by the reconciliation efficiency (or inefficiency), i.e. the ratio of additional information disclosed over the Shannon limit. Most techniques for reconciling errors in QKD try to optimize this parameter. For instance, the well-known Cascade (probably the most widely used procedure for reconciling errors in QKD) was recently shown to have an average efficiency of 1.05 at the cost of a high interactivity (number of exchanged messages). Modern coding techniques, such as rate-adaptive low-density parity-check (LDPC) codes were also shown to achieve similar efficiency values exchanging only one message, or even better values with few interactivity and shorter block-length codes.

A framework for adaptive e-learning for continuum mechanics and structural analysis

This paper presents a project for providing the students of Structural Engineering with the flexibility to learn outside classroom schedules. The goal is a framework for adaptive E-learning based on a repository of open educational courseware with a set of basic Structural Engineering concepts and fundamentals. These are paramount for students to expand their technical knowledge and skills in structural analysis and design of tall buildings, arch-type structures as well as bridges. Thus, concepts related to structural behaviour such as linearity, compatibility, stiffness and influence lines have traditionally been elusive for students. The objective is to facilitate the student a teachinglearning process to acquire the necessary intuitive knowledge, cognitive skills and the basis for further technological modules and professional development in this area. As a side effect, the system is expected to help the students improve their preparation for exams on the subject. In this project, a web-based open-source system for studying influence lines on continuous beams is presented. It encompasses a collection of interactive user-friendly applications accessible via Web, written in JavaScript under JQuery and Dygraph Libraries, taking advantage of their efficiency and graphic capabilities. It is performed in both Spanish and English languages. The student is enabled to set the geometric, topologic, boundary and mechanic layout of a continuous beam. While changing the loading and the support conditions, the changes in the beam response prompt on the screen, so that the effects of the several issues involved in structural analysis become apparent. This open interaction with the user allows the student to simulate and virtually infer the structural response. Different levels of complexity can be handled, whereas an ongoing help is at hand for any of them. Students can freely boost their experiential learning on this subject at their own pace, in order to further share, process, generalize and apply the relevant essential concepts of Structural Engineering analysis. Besides, this collection is being added to the "Virtual Lab of Continuum Mechanics" of the UPM, launched in 2013 (http://serviciosgate.upm.es/laboratoriosvirtuales/laboratorios/medios-continuos-en-construcci%C3%B3n)

Self-adaptive strategy based on fuzzy control systems for improving performance in wireless sensors networks

The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

Vigilancia tecnológica: un aprendizaje adaptativo a través del pensamiento divergente Technological surveillance: an adaptive learning through divergent thinking

El estudio de la evolución tecnológica a partir de logros concretos de la humanidad es una forma de aproximación a la enseñanza de la ingeniería. Comprender que las tecnologías existentes son el resultado de un depurado proceso de creación/selección no es trivial. Por ello combinar un conocimiento deductivo profundo con un pensamiento divergente que favorezca la obtención de soluciones viables y creativas es fundamental en el contexto de incertidumbre económica actual. En este ensayo se comparan siete técnicas de enseñanza que pretenden favorecer el PD en una estrategia adaptativa para alumnos con distintos estilos cognitivos (AA) sobre la base de un proceso de vigilancia tecnológica (VT) aplicada a algunos objetos cotidianos y otros muy especializados.

Subjective QoE Analysis of HTTP Adaptive Streaming Applications

Actualmente la optimization de la calidad de experiencia (Quality of Experience- QoE) de HTTP Adaptive Streaming (HAS) de video recibe una atención creciente. Este incremento de interés proviene fundamentalmente de las carencias de las soluciones actuales HAS, que, al no ser QoE-driven, no incluyen la percepción de la calidad de los usuarios finales como una parte integral de la lógica de adaptación. Por lo tanto, la obtención de información de referencia fiable en QoE en HAS presenta retos importantes, ya que las metodologías de evaluación subjetiva de la calidad de vídeo propuestas en las normas actuales no son adecuadas para tratar con la variación temporal de la calidad que es consustancial de HAS. Esta tesis investiga la influencia de la adaptación dinámica en la calidad de la transmisión de vídeo considerando métodos de evaluación subjetiva. Tras un estudio exhaustivo del estado del arte en la evaluación subjetiva de QoE en HAS, se han resaltado los retos asociados y las líneas de investigación abiertas. Como resultado, se han seleccionado dos líneas principales de investigación: el análisis del impacto en la QoE de los parámetros de las técnicas de adaptación y la investigación de las metodologías de prueba subjetiva adecuada para evaluación de QoE en HAS. Se han llevado a cabo un conjunto de experimentos de laboratorio para investigar las cuestiones planteadas mediante la utilización de diferentes metodologáas para pruebas subjetivas. El análisis estadístico muestra que no son robustas todas las suposiciones y reivindicaciones de las referencias analizadas, en particular en lo que respecta al impacto en la QoE de la frecuencia de las variaciones de calidad, de las adaptaciones suaves o abruptas y de las oscilaciones de calidad. Por otra parte, nuestros resultados confirman la influencia de otros parámetros, como la longitud de los segmentos de vídeo y la amplitud de las oscilaciones de calidad. Los resultados también muestran que tomar en consideración las características objetivas de los contenidos puede ser beneficioso para la mejora de la QoE en HAS. Además, todos los resultados han sido validados mediante extensos análisis experimentales que han incluido estudio tanto en otros laboratorios como en crowdsourcing Por último, sobre los aspectos metodológicos de las pruebas subjetivas de QoE, se ha realizado la comparación entre los resultados experimentales obtenidos a partir de un método estandarizado basado en estímulos cortos (ACR) y un método semi continuo (desarrollado para la evaluación de secuencias prolongadas de vídeo). A pesar de algunas diferencias, el resultado de los análisis estadísticos no muestra ningún efecto significativo de la metodología de prueba. Asimismo, aunque se percibe la influencia de la presencia de audio en la evaluación de degradaciones del vídeo, no se han encontrado efectos estadísticamente significativos de dicha presencia. A partir de la ausencia de influencia del método de prueba y de la presencia de audio, se ha realizado un análisis adicional sobre el impacto de realizar comparaciones estadísticas múltiples en niveles estadísticos de importancia que aumentan la probabilidad de los errores de tipo-I (falsos positivos). Nuestros resultados muestran que, para obtener un efectos sólido en el análisis estadístico de los resultados subjetivos, es necesario aumentar el número de sujetos de las pruebas claramente por encima de los tamaños de muestras propuestos por las normas y recomendaciones actuales. ABSTRACT Optimizing the Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) is receiving increasing attention nowadays. The growth of interest is mainly caused by the fact that current HAS solutions are not QoE-driven, i.e. end-user quality perception is not integral part of the adaptation logic. However, obtaining the necessary reliable ground truths on HAS QoE faces substantial challenges, since the subjective video quality assessment methodologies as proposed by current standards are not well-suited for dealing with the time-varying quality properties that are characteristic for HAS. This thesis investigates the influence of dynamic quality adaptation on the QoE of streaming video by means of subjective evaluation approaches. Based on a comprehensive survey of related work on subjective HAS QoE assessment, the related challenges and open research questions are highlighted and discussed. As a result, two main research directions are selected for further investigation: analysis of the QoE impact of different technical adaptation parameters, and investigation of testing methodologies suitable for HAS QoE evaluation. In order to investigate related research issues and questions, a set of laboratory experiments have been conducted using different subjective testing methodologies. Our statistical analysis demonstrates that not all assumptions and claims reported in the literature are robust, particularly as regards the QoE impact of switching frequency, smooth vs. abrupt switching, and quality oscillation. On the other hand, our results confirm the influence of some other parameters such as chunk length and switching amplitude on perceived quality. We also show that taking the objective characteristics of the content into account can be beneficial to improve the adaptation viewing experience. In addition, all aforementioned findings are validated by means of an extensive cross-experimental analysis that involves external laboratory and crowdsourcing studies. Finally, to address the methodological aspects of subjective QoE testing, a comparison between the experimental results obtained from a (short stimuli-based) ACR standardized method and a semi-continuous method (developed for assessment of long video sequences) has been performed. In spite of observation of some differences, the result of statistical analysis does not show any significant effect of testing methodology. Similarly, although the influence of audio presence on evaluation of video-related degradations is perceived, no statistically significant effect of audio presence could be found. Motivating by this finding (no effect of testing method and audio presence), a subsequent analysis has been performed investigating the impact of performing multiple statistical comparisons on statistical levels of significance which increase the likelihood of Type-I errors (false positives). Our results show that in order to obtain a strong effect from the statistical analysis of the subjective results, it is necessary to increase the number of test subjects well beyond the sample sizes proposed by current quality assessment standards and recommendations.

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

Development of a fuzzy control based self-adaptive system for energy saving in constrained networks for the Internet of Things

Las redes del futuro, incluyendo las redes de próxima generación, tienen entre sus objetivos de diseño el control sobre el consumo de energía y la conectividad de la red. Estos objetivos cobran especial relevancia cuando hablamos de redes con capacidades limitadas, como es el caso de las redes de sensores inalámbricos (WSN por sus siglas en inglés). Estas redes se caracterizan por estar formadas por dispositivos de baja o muy baja capacidad de proceso y por depender de baterías para su alimentación. Por tanto la optimización de la energía consumida se hace muy importante. Son muchas las propuestas que se han realizado para optimizar el consumo de energía en este tipo de redes. Quizás las más conocidas son las que se basan en la planificación coordinada de periodos de actividad e inactividad, siendo una de las formas más eficaces para extender el tiempo de vida de las baterías. La propuesta que se presenta en este trabajo se basa en el control de la conectividad mediante una aproximación probabilística. La idea subyacente es que se puede esperar que una red mantenga la conectividad si todos sus nodos tienen al menos un número determinado de vecinos. Empleando algún mecanismo que mantenga ese número, se espera que se pueda mantener la conectividad con un consumo energético menor que si se empleara una potencia de transmisión fija que garantizara una conectividad similar. Para que el mecanismo sea eficiente debe tener la menor huella posible en los dispositivos donde se vaya a emplear. Por eso se propone el uso de un sistema auto-adaptativo basado en control mediante lógica borrosa. En este trabajo se ha diseñado e implementado el sistema descrito, y se ha probado en un despliegue real confirmando que efectivamente existen configuraciones posibles que permiten mantener la conectividad ahorrando energía con respecto al uso de una potencia de transmisión fija. ABSTRACT. Among the design goals for future networks, including next generation networks, we can find the energy consumption and the connectivity. These two goals are of special relevance when dealing with constrained networks. That is the case of Wireless Sensors Networks (WSN). These networks consist of devices with low or very low processing capabilities. They also depend on batteries for their operation. Thus energy optimization becomes a very important issue. Several proposals have been made for optimizing the energy consumption in this kind of networks. Perhaps the best known are those based on the coordinated planning of active and sleep intervals. They are indeed one of the most effective ways to extend the lifetime of the batteries. The proposal presented in this work uses a probabilistic approach to control the connectivity of a network. The underlying idea is that it is highly probable that the network will have a good connectivity if all the nodes have a minimum number of neighbors. By using some mechanism to reach that number, we hope that we can preserve the connectivity with a lower energy consumption compared to the required one if a fixed transmission power is used to achieve a similar connectivity. The mechanism must have the smallest footprint possible on the devices being used in order to be efficient. Therefore a fuzzy control based self-adaptive system is proposed. This work includes the design and implementation of the described system. It also has been validated in a real scenario deployment. We have obtained results supporting that there exist configurations where it is possible to get a good connectivity saving energy when compared to the use of a fixed transmission power for a similar connectivity.