Work in progress - Exploiting videoconferencing possibilities to promote the European convergence process

This paper introduces the experience of using videoconferencing and recording as a mechanism to support courses which need to be promoted or discontinued within the framework of the European convergence process. Our objective is to make these courses accessible as live streaming during the lessons as well as recorded lectures and associated documents available to the students as soon as the lesson has finished. The technology used has been developed in our university and it is all open source. Although this is a technical project the key is the human factor involved. The people managing the virtual sessions are students of the courses being recorded. However, they lack technical knowledge, so we had to train them in audiovisuals and enhance the usability of the videoconferencing tool and platform. The validation process is being carried out in five real scenarios at our university. During the whole period we are evaluating technical and pedagogical issues of this experience for both students and teachers to guide the future development of the service. Depending on the final results, the service of lectures recording will be available as educational resource for all of the teaching staff of our university.

Exploiting Structured Linked Data in Enterprise Knowledge Management Systems: An Idea Management Case Study

In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems

Exploiting goal independence in the analysis of logic programs

This paper illustrates the use of a top-down framework to obtain goal independent analyses of logic programs, a task which is usually associated with the bottom-up approach. While it is well known that the bottomup approach can be used, through the magic set transformation, for goal dependent analysis, it is less known that the top-down approach can be used for goal independent analysis. The paper describes two ways of doing the latter. We show how the results of a goal independent analysis can be used to speed up subsequent goal dependent analyses. However this speed-up may result in a loss of precisión. The influence of domain characteristics on this precisión is discussed and an experimental evaluation using a generic top-down analyzer is described.

The &-prolog system: Exploiting independent and-parallelism

The &-Prolog system, a practical implementation of a parallel execution niodel for Prolog exploiting strict and non-strict independent and-parallelism, is described. Both automatic and manual parallelization of programs is supported. This description includes a summary of the system's language and architecture, some details of its execution model (based on the RAP-WAM model), and data on its performance on sequential workstations and shared memory multiprocessors, which is compared to that of current Prolog systems. The results to date show significant speed advantages over state-of-the-art sequential systems.

&-prolog and its performance: exploiting independent and-parallelism

An Independent And-Parallel Prolog model and implementation, &-Prolog, are described. The description includes a summary of the system's architecture, some details of its execution model (based on the RAP-WAM model), and most importantly, its performance on sequential workstations and shared memory multiprocessors as compared with state-of-the-art Prolog systems. Speedup curves are provided for a collection of benchmark programs which demónstrate significant speed advantages over state-of the art sequential systems.

Transformation�based implementation and optimization of programs exploiting the basic Andorra model.

The characteristics of CC and CLP systems are in principle very dierent However a recent trend towards convergence in the implementation techniques for these systems can be observed While CLP and Prolog systems have been incorporating capabilities to deal with userdened suspension and coroutining CC compilers have been trying to coalesce negrained tasks into coarsergrained sequential threads This convergence of techniques opens up the possibility of having a general purpose kernel language and abstract machine to serve as a compilation target for a variety of userlevel languages We propose a transformation technique directed towards such an objective In particular we report on techniques to support the Andorra computational model essentially emulating the AndorraI system via program transformation into a sequential language with delay primitives The system is automatic comprising an optional program analyzer and a basic transformer to the kernel language It turns out that a simple parallel CLP or Prolog system with dynamic scheduling is sucient as a kernel language for this purpose The preliminary results are quite encouraging performance of the resulting system is comparable to the current AndorraI implementation.

Using pMOS Pass-Gates to Boost SRAM Performance by Exploiting Strain Effects in Sub-20-nm FinFET Technologies

Strained fin is one of the techniques used to improve the devices as their size keeps reducing in new nanoscale nodes. In this paper, we use a predictive technology of 14 nm where pMOS mobility is significantly improved when those devices are built on top of long, uncut fins, while nMOS devices present the opposite behavior due to the combination of strains. We explore the possibility of boosting circuit performance in repetitive structures where long uncut fins can be exploited to increase fin strain impact. In particular, pMOS pass-gates are used in 6T complementary SRAM cells (CSRAM) with reinforced pull-ups. Those cells are simulated under process variability and compared to the regular SRAM. We show that when layout dependent effects are considered the CSRAM design provides 10% to 40% faster access time while keeping the same area, power, and stability than a regular 6T SRAM cell. The conclusions also apply to 8T SRAM cells. The CSRAM cell also presents increased reliability in technologies whose nMOS devices have more mismatch than pMOS transistors.

Wave Statistics and Space-time Extremes via Stereo Imaging

We present an analysis of the space-time dynamics of oceanic sea states exploiting stereo imaging techniques. In particular, a novel Wave Acquisition Stereo System (WASS) has been developed and deployed at the oceanographic tower Acqua Alta in the Northern Adriatic Sea, off the Venice coast in Italy. The analysis of WASS video measurements yields accurate estimates of the oceanic sea state dynamics, the associated directional spectra and wave surface statistics that agree well with theoretical models. Finally, we show that a space-time extreme, defined as the expected largest surface wave height over an area, is considerably larger than the maximum crest observed in time at a point, in agreement with theoretical predictions.

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

Distributed models in P-Systems architectures to reduce computation time

Membrane systems are computational equivalent to Turing machines. However, their distributed and massively parallel nature obtains polynomial solutions opposite to traditional non-polynomial ones. At this point, it is very important to develop dedicated hardware and software implementations exploiting those two membrane systems features. Dealing with distributed implementations of P systems, the bottleneck communication problem has arisen. When the number of membranes grows up, the network gets congested. The purpose of distributed architectures is to reach a compromise between the massively parallel character of the system and the needed evolution step time to transit from one configuration of the system to the next one, solving the bottleneck communication problem. The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processors.

A Mobile Feedback System for Integrated E-health Platforms to improve Self-Care and Compliance of Diabetes Mellitus Patients

Exploiting the full potential of telemedical systems means using platform based solutions: data are recovered from biomedical sensors, hospital information systems, care-givers, as well as patients themselves, and are processed and redistributed in an either centralized or, more probably, decentralized way. The integration of all these different devices, and interfaces, as well as the automated analysis and representation of all the pieces of information are current key challenges in telemedicine. Mobile phone technology has just begun to offer great opportunities of using this diverse information for guiding, warning, and educating patients, thus increasing their autonomy and adherence to their prescriptions. However, most of these existing mobile solutions are not based on platform systems and therefore represent limited, isolated applications. This article depicts how telemedical systems, based on integrated health data platforms, can maximize prescription adherence in chronic patients through mobile feedback. The application described here has been developed in an EU-funded R&D project called METABO, dedicated to patients with type 1 or type 2 Diabetes Mellitus

Eco-entrepreneurship in developing countries: the case of renewable energy sector in Bolivia

The change towards a sustainable economic system represents a big challenge for the present as well as next generations. Such a process requires important long-term changes in technologies, lifestyle, infrastructures and institutions. In this scenario the innovation process is a crucial element for fostering sustainability as well as an egalitarian development in developing countries. For those reasons the concept of Eco-Innovation System is introduced and further considerations are provided for the case of less-developed countries. The paper illustrates that sustainable development is possible by exploiting local potential and traditional knowledge in order to achieve at the same time economic growth, social equality and environmental sustainability. In order to prove such an assumption a specific case study is described: The renewable energy sector in Bolivia. The case study summarizes many important dimensions of the innovation process in developing countries such as technological transfer, diffusion and adaptation, social dimension and development issues.

A Novel Scalable Deblocking-Filter Architecture for H.264/AVC and SVC Video Codecs

A highly parallel and scalable Deblocking Filter (DF) hardware architecture for H.264/AVC and SVC video codecs is presented in this paper. The proposed architecture mainly consists on a coarse grain systolic array obtained by replicating a unique and homogeneous Functional Unit (FU), in which a whole Deblocking-Filter unit is implemented. The proposal is also based on a novel macroblock-level parallelization strategy of the filtering algorithm which improves the final performance by exploiting specific data dependences. This way communication overhead is reduced and a more intensive parallelism in comparison with the existing state-of-the-art solutions is obtained. Furthermore, the architecture is completely flexible, since the level of parallelism can be changed, according to the application requirements. The design has been implemented in a Virtex-5 FPGA, and it allows filtering 4CIF (704 × 576 pixels @30 fps) video sequences in real-time at frequencies lower than 10.16 Mhz.

Linear instability of orthogonal compressible leading-edge boundary layer flow

Instability analysis of compressible orthogonal swept leading-edge boundary layer flow was performed in the context of BiGlobal linear theory. 1, 2 An algorithm was developed exploiting the sparsity characteristics of the matrix discretizing the PDE-based eigenvalue problem. This allowed use of the MUMPS sparse linear algebra package 3 to obtain a direct solution of the linear systems associated with the Arnoldi iteration. The developed algorithm was then applied to efficiently analyze the effect of compressibility on the stability of the swept leading-edge boundary layer and obtain neutral curves of this flow as a function of the Mach number in the range 0 ≤ Ma ≤ 1. The present numerical results fully confirmed the asymptotic theory results of Theofilis et al. 4 Up to the maximum Mach number value studied, it was found that an increase of this parameter reduces the critical Reynolds number and the range of the unstable spanwise wavenumbers.

Consciousness, Meaning and the Future Phenomenology

Phenomenological states are generally considered sources of intrinsic motivation for autonomous biological agents. In this paper we will address the issue of exploiting these states for robust goal-directed systems. We will provide an analysis of consciousness in terms of a precise definition of how an agent “understands” the informational flows entering the agent. This model of consciousness and understanding is based in the analysis and evaluation of phenomenological states along potential trajectories in the phase space of the agents. This implies that a possible strategy to follow in order to build autonomous but useful systems is to embed them with the particular, ad-hoc phenomenology that captures the requirements that define the system usefulness from a requirements-strict engineering viewpoint.