Innovative Techniques for Testing and Diagnosing SoCs

We rely upon the continued functioning of many electronic devices for our everyday welfare, usually embedding integrated circuits that are becoming even cheaper and smaller with improved features. Nowadays, microelectronics can integrate a working computer with CPU, memories, and even GPUs on a single die, namely System-On-Chip (SoC). SoCs are also employed on automotive safety-critical applications, but need to be tested thoroughly to comply with reliability standards, in particular the ISO26262 functional safety for road vehicles. The goal of this PhD. thesis is to improve SoC reliability by proposing innovative techniques for testing and diagnosing its internal modules: CPUs, memories, peripherals, and GPUs. The proposed approaches in the sequence appearing in this thesis are described as follows: 1. Embedded Memory Diagnosis: Memories are dense and complex circuits which are susceptible to design and manufacturing errors. Hence, it is important to understand the fault occurrence in the memory array. In practice, the logical and physical array representation differs due to an optimized design which adds enhancements to the device, namely scrambling. This part proposes an accurate memory diagnosis by showing the efforts of a software tool able to analyze test results, unscramble the memory array, map failing syndromes to cell locations, elaborate cumulative analysis, and elaborate a final fault model hypothesis. Several SRAM memory failing syndromes were analyzed as case studies gathered on an industrial automotive 32-bit SoC developed by STMicroelectronics. The tool displayed defects virtually, and results were confirmed by real photos taken from a microscope. 2. Functional Test Pattern Generation: The key for a successful test is the pattern applied to the device. They can be structural or functional; the former usually benefits from embedded test modules targeting manufacturing errors and is only effective before shipping the component to the client. The latter, on the other hand, can be applied during mission minimally impacting on performance but is penalized due to high generation time. However, functional test patterns may benefit for having different goals in functional mission mode. Part III of this PhD thesis proposes three different functional test pattern generation methods for CPU cores embedded in SoCs, targeting different test purposes, described as follows: a. Functional Stress Patterns: Are suitable for optimizing functional stress during I Operational-life Tests and Burn-in Screening for an optimal device reliability characterization b. Functional Power Hungry Patterns: Are suitable for determining functional peak power for strictly limiting the power of structural patterns during manufacturing tests, thus reducing premature device over-kill while delivering high test coverage c. Software-Based Self-Test Patterns: Combines the potentiality of structural patterns with functional ones, allowing its execution periodically during mission. In addition, an external hardware communicating with a devised SBST was proposed. It helps increasing in 3% the fault coverage by testing critical Hardly Functionally Testable Faults not covered by conventional SBST patterns. An automatic functional test pattern generation exploiting an evolutionary algorithm maximizing metrics related to stress, power, and fault coverage was employed in the above-mentioned approaches to quickly generate the desired patterns. The approaches were evaluated on two industrial cases developed by STMicroelectronics; 8051-based and a 32-bit Power Architecture SoCs. Results show that generation time was reduced upto 75% in comparison to older methodologies while increasing significantly the desired metrics. 3. Fault Injection in GPGPU: Fault injection mechanisms in semiconductor devices are suitable for generating structural patterns, testing and activating mitigation techniques, and validating robust hardware and software applications. GPGPUs are known for fast parallel computation used in high performance computing and advanced driver assistance where reliability is the key point. Moreover, GPGPU manufacturers do not provide design description code due to content secrecy. Therefore, commercial fault injectors using the GPGPU model is unfeasible, making radiation tests the only resource available, but are costly. In the last part of this thesis, we propose a software implemented fault injector able to inject bit-flip in memory elements of a real GPGPU. It exploits a software debugger tool and combines the C-CUDA grammar to wisely determine fault spots and apply bit-flip operations in program variables. The goal is to validate robust parallel algorithms by studying fault propagation or activating redundancy mechanisms they possibly embed. The effectiveness of the tool was evaluated on two robust applications: redundant parallel matrix multiplication and floating point Fast Fourier Transform

On the Uncertainty in Active SLAM: Representation, Propagation and Monotonicity

La localización y mapeo simultáneo activo (SLAM activo) ha recibido mucha atención por parte de la comunidad de robótica por su relevancia en aplicaciones de robot móviles. El objetivo de un algoritmo de SLAM activo es planificar la trayectoria del robot para maximizar el área explorada y minimizar la incertidumbre asociada con la estimación de la posición del robot. Durante la fase de exploración de un algoritmo de SLAM, donde el robot navega en una región previamente desconocida, la incertidumbre asociada con la localización del robot crece sin límites. Solo después de volver a visitar regiones previamente conocidas, se espera una reducción en la incertidumbre asociada con la localización del robot mediante la detección de cierres de bucle. Esta tesis doctoral se centra en la importancia de representar y cuantificar la incertidumbre para calcular correctamente la confianza asociada con la estimación de la localización del robot en cada paso de tiempo a lo largo de su recorrido y, por lo tanto, decidir la trayectoria correcta de acuerdo con el objetivo de SLAM activo.En la literatura, se han propuesto fundamentalemente dos tipos de modelos de representación de la incertidumbre: absoluta y diferencial. En representación absoluta, la información sobre la incertidumbre asociada con la localización del robot está representada por una función de distribución de probabilidad, generalmente gausiana, sobre las variables de localización absoluta con respecto a una referencia base elegida. La estimación de la posición del robot está dada por la esperanza de las variables asociadas con la localización y la incertidumbre por su matriz de covarianza asociada. La representación diferencial utiliza una representación local de la incertidumbre, la posición estimada del robot se representa mediante la mejor aproximación de la posición absoluta y el error de estimación se representa localmente mediante un vector diferencial. Este vector generalmente también está representado por una función de distribución de probabilidad gausiana. Representaciones equivalentes al modelo diferencial han utilizado las herramientas de Grupos de Lie y Álgebras de Lie para representar la incertidumbre. Además de estos modelos, existen diferentes formas de representar la posición y orientación de la posición del robot, ángulos de Euler, cuaterniones y transformaciones homogéneas.Los enfoques más comunes para cuantificar la incertidumbre en SLAM se basan en criterios de optimalidad con el objetivo de cuantificar el mapa y la incertidumbre de la posición del robot: A-opt (traza de la matriz de covarianza, o suma de sus autovalores), D-opt (determinante de la matriz de covarianza, o producto de sus autovalores) y E-opt (criterio del mayor autovalor). Alternativamente, otros algoritmos de SLAM activo, basados en la Teoría de la Información, se basan en el uso de la entropía de Shannon para seleccionar acciones que lleven al robot al objetivo seleccionado. En un escenario de SLAM activo, garantizar la monotonicidad de estos criterios en la toma de decisiones durante la exploración, es decir, cuantificar correctamente que la incertidumbre encapsulada en una matriz de covarianza está aumentando, es un paso esencial para tomar decisiones correctas. Como ya se ha mencionado, durante la fase de exploración la incertidumbre asociada con la localización del robot aumenta. Por lo tanto, si no se preserva la monotonicidad de los criterios considerados, el sistema puede seleccionar trayectorias o caminos que creen falsamente que conducen a una menor incertidumbre de la localización del robot.En esta tesis, revisamos el trabajo relacionado sobre representación y propagación de la incertidumbre de la posición del robot en los diferentes modelos propuestos en la literatura. Además, se lleva a cabo un análisis de la incertidumbre representada localmente con un vector diferencial y la incertidumbre representada usando grupos de Lie. Investigamos la monotonicidad de diferentes criterios para la toma de decisiones, tanto en 2D como en 3D, dependiendo de la representación de la incertidumbre y de la representación de la orientación del robot. Nuestra conclusión fundamental es que la representación de la incertidumbre sobre grupos de Lie y usando un vector diferencial son similares e independientes de la representación utilizada para la parte rotacional de la posición del robot. Esto se debe a que la incertidumbre se representa localmente en el espacio de las transformaciones diferenciales que se corresponde con el álgebra de Lie del grupo euclidiano especial SE(n). Sin embargo, en el espacio tridimensional, la estimación de la localización del robot depende de las diferentes formas de representación de la parte rotacional. Por lo tanto, una forma adecuada de manipular conjuntamente la estimación y la incertidumbre del robot es utilizando la teoría de grupos de Lie debido a que es una representación que garantiza propiedades tales como una representación mínima y libre de singularidades en los ángulos de rotación. Analíticamente, demostramos que, utilizando representaciones diferenciales para la propagación de la incertidumbre, la monotonicidad se conserva para todos los criterios de optimalidad, A-opt, D-opt y E-opt y para la entropía de Shannon. También demostramos que la monotonicidad no se cumple para ninguno de ellos en representaciones absolutas usando ángulos Roll-Pitch-Yaw y Euler. Finalmente, mostramos que al usar cuaterniones unitarios en representaciones absolutas, los únicos criterios que preservan la monotonicidad son D-opt y la entropía de Shannon.Estos hallazgos pueden guiar a los investigadores de SLAM activo a seleccionar adecuadamente un modelo de representación de la incertidumbre, de modo que la planificación de trayectorias y los algoritmos de exploración puedan evaluar correctamente la evolución de la incertidumbre asociada a la posición del robot.Active Simultaneous Localization and Mapping (Active SLAM) has received a lot of attention from the robotics community for its relevance in mobile robotics applications. The objective of an active SLAM algorithm is to plan ahead the robot motion in order to maximize the area explored and minimize the uncertainty associated with the estimation, all within a time and computation budget. During the exploration phase of a SLAM algorithm, where the robot navigates in a previously unknown region, the uncertainty associated with the robot's localization grows unbounded. Only after revisiting previously known regions a reduction in the robot's localization uncertainty is expected by detecting loop-closures. This doctoral thesis focuses on the paramount importance of representing and quantifying uncertainty to correctly report the associated confidence of the robot's location estimate at each time step along its trajectory and therefore deciding the correct course of action in an active SLAM mission. Two fundamental types of models of probabilistic representation of the uncertainty have been proposed in the literature: absolute and dfferential. In absolute representations, the information about the uncertainty in the location of the robot's pose is represented by a probability distribution function, usually Gaussian, over the variables of the absolute location with respect to a chosen base reference. The estimated location is given by the expected location variables and the uncertainty by its associated covariance matrix. Differential representations use a local representation of the uncertainty, the estimated location of the robot is represented by the best approximation of the absolute location and the estimation error is represented locally by a differential location vector. This vector is usually also represented by a Gaussian probability distribution function. Equivalent representations to differential models have used the tools of Lie groups and Lie algebras to represent uncertainties. In addition to uncertainty models, there are different ways to represent the position and orientation of the robot's pose, Euler angles, quaternions and homogeneous transformations. The most common approaches to quantifying uncertainty in SLAM are based on optimality criteria which aim at quantifying the map and robot's pose uncertainty, namely A-opt (trace of the covariance matrix, or sum of its eigenvalues), D-opt (determinant of the covariance matrix, or product of its eigenvalues) and E-opt (largest eigenvalue) criteria. Alternatively, other active SLAM algorithms, based on Information Theory, rely on the use of the Shannon's entropy to select courses of action for the robot to reach the commanded goal location. In an active SLAM scenario, guaranteeing monotonicity of these decision making criteria during exploration, i.e. quantifying correctly that the uncertainty encapsulated in a covariance matrix is increasing, is an essential step towards making correct decisions. As already mentioned, during exploration the uncertainty associated with the robot's localization increases. Therefore, if monotonicity of the criteria considered is not preserved, the system might select courses of action or paths that it falsely believes lead to less uncertainty in the robot. In this thesis, we review related work about representation and propagation of the uncertainty of robot's pose and present a survey of different types of models proposed in the literature. Additionally, an analysis of the uncertainty represented with a differential uncertainty vector and the uncertainty represented on Lie groups is carried out. We investigate the monotonicity of different decision making criteria, both in 2D and 3D, depending on the representation of uncertainty and the orientation of the robot's pose. Our fundamental conclusion is that uncertainty representation over Lie groups and using differential location vectors are similar and independent of the representation used for rotational part of the robot's pose. This is due to the uncertainty is represented locally in the space of differential transformations for translation and rotation that correspond with the Lie algebra of special Euclidean group SE(n). However, in 3-dimensional space, the homogeneous transformation associated to the approximation of the real location depend on the different ways of representation the rotational part. Therefore, a proper way to jointly manipulating the estimation and uncertainty of the pose is to use the theory of Lie groups due to it is a representation to guarantee properties such as a minimal representation and free of singularities in rotation angles. We analytically show that, using differential representations to propagate spatial uncertainties, monotonicity is preserved for all optimality criteria, A-opt, D-opt and E-opt and for Shannon's entropy. We also show that monotonicity does not hold for any of them in absolute representations using Roll-Pitch-Yaw and Euler angles. Finally, we show that using unit quaternions in absolute representations, the only criteria that preserve monotonicity are D-opt and Shannon's entropy. These findings can guide active SLAM researchers to adequately select a representation model for uncertainty, so that path planning and exploration algorithms can correctly assess the evolution of location uncertainty.<br /

Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

Advanced GPS signal processing techniques for LBS services

Par le passé, il était indispensable, pour le bon fonctionnement du GPS (Global Positioning System), que le signal soit en vision directe entre le satellite et le récepteur, et les signaux faibles n'étaient pas exploitables. Mais l'extension du GPS aux services LBS (Location Based Services) et à d'autres applications de navigation a changé ce paradigme. Par conséquent, on prévoit une augmentation considérable de techniques de localisation de plus en plus performantes, surtout dans des environnements du type indoor ou urbain. Les exigences de la localisation dans ce type d'environnements posent un véritable défi pour la conception des récepteurs GPS. Le but de la thèse est d'optimiser les techniques existantes de traitement du signal GPS pour la localisation dans des milieux contraints, dans le cadre de l'AGPS (Assisted GPS). Ce système suppose que le récepteur GPS est connecté ou introduit dans un téléphone portable. Ce genre de couplage permet de transférer au récepteur GPS des données d'assistance via le réseau GSM (Global System for Mobile communications). Ces données fournissent au récepteur GPS la liste des satellites visibles, mais aussi des valeurs estimées de leur Doppler et leur retard de code, réduisant ainsi la fenêtre de recherche de ces paramètres. Les travaux de la thèse consistent à explorer différentes techniques d'acquisition du signal GPS pour réduire le temps d'acquisition nécessaire ou TTFF (Time To First Fix), sans affecter la sensibilité du récepteur GPS. Ceci est réalisé après une étude du canal GPS radio. L'étude débute par une revue du GPS et de la structure du signal utilisé dans ce système. Le processus d'acquisition est ensuite décrit en détails: l'acquisition classique est décrite en premier pour mettre en évidence par la suite l'effet du milieu de propagation sur cette étape du traitement du signal. A cet effet, les milieux contraignants (Indoors et Urbains) seront modélisés et analysés. Cette analyse permettra de mettre en évidence les problèmes subits par les ondes radio se propageant dans ce type d'environnements. On notera que le canal urbain a été analysé en utilisant un modèle déjà existant élaboré par Alexander Steingass et Andreas Lehner du DLR (Centre Aérospatial Allemand) [Steingass et al., 2005]. D'autre part, un modèle statistique du canal indoor a été développé par l'ESA (European Space Agency) dans le cadre du projet intitulé “Navigation signal measurement campaign for critical environments” et présenté dans [Pérez-Fontán et al, 2004]. Mais ce modèle considère un canal statistique invariable dans le temps. Pour cela nous avons développé un modèle Indoor qui envisage plutôt un canal variant avec le temps, en prenant en compte les variations temporelles de certains paramètres du canal, comme le retard et la phase de la fonction de transfert. Les valeurs initiales de ces paramètres utilisés dans notre modèle sont toutefois basées sur les distributions statistiques fournies par le modèle de l'ESA. L'étude des canaux de propagation porte surtout sur les multitrajets, les inter-corrélations, et le masquage du signal. Les multitrajets sont particulièrement gênants dans le cas de milieux urbains, les intercorrélations et le masquage sont par contre plus gênants dans les milieux indoors. Ces phénomènes peuvent impliquer des erreurs dans la position calculée par le récepteur. Pour y remédier, une des solutions est d'augmenter la durée d'observation du signal pour améliorer le rapport signal sur bruit. Mais ceci conduit à des temps d'acquisition beaucoup plus longs. Par conséquent, la qualité commerciale du récepteur est mise en cause vues les contraintes sur le TTFF nécessaires pour fournir une première solution. Ces contraintes en termes de temps ii de traitements sont aussi importantes que les contraintes en termes de précision pour les utilisateurs du GPS. Mais ces deux contraintes vont en général l'une à l'encontre de l'autre. Par conséquent, une solution idéale consistera à réduire le temps d'acquisition sans pour autant affecter la sensibilité du récepteur. Ainsi, dans la suite de l'exposé des méthodes avancées de traitement du signal dans la phase d'acquisition seront présentées. La plupart de ces méthodes vise à réduire le temps total d'acquisition plutôt qu'à améliorer la sensibilité du récepteur: ceci permet de tolérer) le traitement de signaux plus longs - afin d'améliorer la sensibilité - sans augmenter la durée globale de traitement. Ces méthodes seront tout d'abord caractérisées en évaluant les avantages et les inconvénients de chacune d'elles. Une évaluation de performances de ces algorithmes, utilisant des signaux générés avec un Spirent STR4500 sera conduite dans une étape finale de cette étude. ABSTRACT : In the past, in order for GPS (Global Positioning System) to work accurately, the presence of an unobstructed LOS (Line-Of- ight) signal was necessary. Weak signals were not suitable for use because they may have large associated noise and other errors. The expansion of GPS to LBS (Location- ased Services) and other navigation applications all over the world, such as the E-911 and the E-112 mandates in the United States and Europe respectively, changed the paradigm. Consequently a dramatic increase in the need for more and more performant positioning techniques is expected, especially in urban and indoor environments. These rising localization requirements pose a particularly difficult challenge for GPS receivers design. The thesis objective is to evaluate and enhance existing GPS signal acquisition techniques for positioning goals in harsh environments, in the context of AGPS (Assisted GPS). The AGPS system assumes that the GPS receiver is connected to or introduced in a mobile phone. This allows for the transfer of AD (Assistance Data) to the GPS receiver via the GSM (Global System for Mobile communications) cellular network. Amongst others, the AD provides the GPS receiver with the list of visible satellites and estimates of their Dopplers and code delays, thus reducing the search window of these parameters. This work consists in exploring different GPS signal acquisition to reduce the acquisition time or TTFF (Time To First Fix), without affecting the receiver sensitivity. This is done after a prior study of the GPS radio channel. The study starts out with a revue of the GPS system and the GPS transmitted and received signal structure. The acquisition process is then described in details: the classical acquisition is first described in order to proceed afterwards with the impact of the propagation environment on this stage of the signal processing. For this purpose, harsh environments (urban and indoor) are modelled and analysed. This analysis enables to study the problems which encounter the radio frequency signal propagation through such environments. Note that the urban channel is studied using an existing statistical model developed by Alexander Steingass and Andreas Lehner at the DLR (German Aerospace Center) [Steingass et al., 2005]. On the other hand, an indoor channel model was developed by the ESA (European Space Agency) in the frame of a project entitled “Navigation signal measurement campaign for critical environments” and presented in [Pérez-Fontán et al, 2004]. But this model considers a time invariant statistical channel. Consequently, we developed an Indoor model which rather considers a time variant channel, by taking into account temporal variations of some channel parameters, like the transfer function delay and phase. The initial values are however based on the statistical distributions provided by the ESA model. The channels are analysed is terms of multipaths, cross-correlations and signal masking. The multipaths replicas are particularly disturbing in urban environments while the cross-correlations and masking effects are more disturbing in indoor environments. These phenomena may induce errors in the final solution calculated by the receiver. In order to avoid this error, one solution consists in increasing the signal observation duration in order to enhance the signal to noise ratio. But this generally implies longer acquisition time, thus affecting the receiver iv performance, commercially speaking. Indeed, the time requirements are as important as sensitivity requirements for GPS users. However, these two requirements are not generally compatible with each other. Consequently, an ideal solution consists in reducing the acquisition time without greatly affecting the receiver sensitivity. Accordingly, such advanced methods for acquisition signal processing are described next. Most of these methods aim at reducing the total acquisition time, rather than enhancing the receiver sensitivity. This means however that longer signal blocks can be processed (thus enhancing sensitivity) without affecting the global processing duration. At first, each of these methods is evaluated through the description of its advantages and drawbacks. A performance evaluation of these algorithms, using signals generated with a Spirent STR4500, ensues as a final step of this stud

Multibody dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: Formulations and Numerical Methods, Efficient Methods and Real-Time Applications, Flexible Multibody Dynamics, Contact Dynamics and Constraints, Multiphysics and Coupled Problems, Control and Optimization, Software Development and Computer Technology, Aerospace and Maritime Applications, Biomechanics, Railroad Vehicle Dynamics, Road Vehicle Dynamics, Robotics, Benchmark Problems. The conference is organized by the Department of Mechanical Engineering of the Universitat Politècnica de Catalunya (UPC) in Barcelona. The organizers would like to thank the authors for submitting their contributions, the keynote lecturers for accepting the invitation and for the quality of their talks, the awards and scientific committees for their support to the organization of the conference, and finally the topic organizers for reviewing all extended abstracts and selecting the awards nominees.Postprint (published version