La présente thèse du domaine de la « Perception Bio-inspirée » se focalise plus particulièrement sur l’Attention Visuelle Artificielle et la Saillance Visuelle. Un concept de l’Attention Visuelle Artificielle inspiré du vivant, conduisant un modèle d’une telle attention artificielle bio-inspirée, a été élaboré, mis en œuvre et testé dans le contexte de la robotique autonome. En effet, bien qu’il existe plusieurs dizaines de modèles de la saillance visuelle, à la fois en termes de contraste et de cognition, il n’existe pas de modèle hybridant les deux mécanismes d’attention : l’aspect visuel et l’aspect cognitif.Pour créer un tel modèle, nous avons exploré les approches existantes dans le domaine de l’attention visuelle, ainsi que plusieurs approches et paradigmes relevant des domaines connexes (tels que la reconnaissance d’objets, apprentissage artificiel, classification, etc.).Une architecture fonctionnelle d’un système d’attention visuelle hybride, combinant des principes et des mécanismes issus de l’attention visuelle humaine avec des méthodes calculatoires et algorithmiques, a été mise en œuvre, expliquée et détaillée.Une autre contribution majeure du présent travail doctoral est la modélisation théorique, le développement et l’application pratique du modèle d’Attention Visuelle bio-inspiré précité, pouvant constituer un socle pour l’autonomie des systèmes robotisés d’assistance.Les études menées ont conclu à la validation expérimentale des modèles proposés, confirmant la pertinence de l’approche proposée dans l’accroissement de l’autonomie des systèmes robotisés – et ceci dans un environnement réel / Dealing with the field of "Bio-inspired Perception", the present thesis focuses more particularly on Artificial Visual Attention and Visual Saliency. A concept of Artificial Visual Attention, inspired from the human mechanisms, providing a model of such artificial bio-inspired attention, was developed, implemented and tested in the context of autonomous robotics. Although there are several models of visual saliency, in terms of contrast and cognition, there is no hybrid model integrating both mechanisms of attention: the visual aspect and the cognitive aspect.To carryout such a model, we have explored existing approaches in the field of visual attention, as well as several approaches and paradigms in related fields (such as object recognition, artificial learning, classification, etc.).A functional architecture of a hybrid visual attention system, combining principles and mechanisms derived from human visual attention with computational and algorithmic methods, was implemented, explained and detailed.Another major contribution of this doctoral work is the theoretical modeling, development and practical application of the aforementioned Bio-inspired Visual Attention model, providing a basis for the autonomy of assistance-robotic systems.The carried out studies and experimental validation of the proposed models confirmed the relevance of the proposed approach in increasing the autonomy of robotic systems within a real environment

Une tâche importante qui a été étudiée dans le contexte de données à forte dimensionnalité est la tâche connue sous le nom de subspace clustering. Le subspace clustering est généralement reconnu comme étant plus compliqué que le clustering standard, étant donné que cette tâche vise à détecter des groupes d’objets similaires entre eux (clusters), et qu’en même temps elle vise à trouver les sous-espaces où apparaissent ces similitudes. Le subspace clustering, ainsi que le clustering traditionnel ont été récemment étendus au traitement de flux de données en mettant à jour les modèles de clustering de façon incrémentale. Les différents algorithmes qui ont été proposés dans la littérature, reposent sur des bases algorithmiques très différentes. Parmi ces approches, les algorithmes évolutifs ont été sous-explorés, même si ces techniques se sont avérées très utiles pour traiter d’autres problèmes NP-difficiles. L’objectif de cette thèse a été de tirer parti des nouvelles connaissances issues de l’évolution afin de concevoir des algorithmes évolutifs qui traitent le problème du subspace clustering sur des jeux de données statiques ainsi que sur des flux de données dynamiques. Chameleoclust, le premier algorithme développé au cours de ce projet, tire partie du grand degré de liberté fourni par des éléments bio-inspirés tels qu’un génome de longueur variable, l’existence d’éléments fonctionnels et non fonctionnels et des opérateurs de mutation incluant des réarrangements chromosomiques. KymeroClust, le deuxième algorithme conçu dans cette thèse, est un algorithme de k-medianes qui repose sur un mécanisme évolutif important: la duplication et la divergence des gènes. SubMorphoStream, le dernier algorithme développé ici, aborde le problème du subspace clustering sur des flux de données dynamiques. Cet algorithme repose sur deux mécanismes qui jouent un rôle clef dans l’adaptation rapide des bactéries à des environnements changeants: l’amplification de gènes et l’absorption de matériel génétique externe. Ces algorithmes ont été comparés aux principales techniques de l’état de l’art, et ont obtenu des résultats compétitifs. En outre, deux applications appelées EvoWave et EvoMove ont été développés pour évaluer la capacité de ces algorithmes à résoudre des problèmes réels. EvoWave est une application d’analyse de signaux Wi-Fi pour détecter des contextes différents. EvoMove est un compagnon musical artificiel qui produit des sons basés sur le clustering des mouvements d’un danseur, décrits par des données provenant de capteurs de déplacements. / An important task that has been investigated in the context of high dimensional data is subspace clustering. This data mining task is recognized as more general and complicated than standard clustering, since it aims to detect groups of similar objects called clusters, and at the same time to find the subspaces where these similarities appear. Furthermore, subspace clustering approaches as well as traditional clustering ones have recently been extended to deal with data streams by updating clustering models in an incremental way. The different algorithms that have been proposed in the literature, rely on very different algorithmic foundations. Among these approaches, evolutionary algorithms have been under-explored, even if these techniques have proven to be valuable addressing other NP-hard problems. The aim of this thesis was to take advantage of new knowledge from evolutionary biology in order to conceive evolutionary subspace clustering algorithms for static datasets and dynamic data streams. Chameleoclust, the first algorithm developed in this work, takes advantage of the large degree of freedom provided by bio-like features such as a variable genome length, the existence of functional and non-functional elements and mutation operators including chromosomal rearrangements. KymeroClust, our second algorithm, is a k-medians based approach that relies on the duplication and the divergence of genes, a cornerstone evolutionary mechanism. SubMorphoStream, the last one, tackles the subspace clustering task over dynamic data streams. It relies on two important mechanisms that favor fast adaptation of bacteria to changing environments, namely gene amplification and foreign genetic material uptake. All these algorithms were compared to the main state-of-the-art techniques, obtaining competitive results. Results suggest that these algorithms are useful complementary tools in the analyst toolbox. In addition, two applications called EvoWave and EvoMove have been developed to assess the capacity of these algorithms to address real world problems. EvoWave is an application that handles the analysis of Wi-Fi signals to detect different contexts. EvoMove, the second one, is a musical companion that produces sounds based on the clustering of dancer moves captured using motion sensors.

Différentes composantes des systèmes de traduction automatique statistique sont considérées comme des problèmes d'optimisations. En effet, l'apprentissage du modèle de traduction, le décodage et l'optimisation des poids de la fonction log-linéaire sont trois importants problèmes d'optimisation. Savoir définir les bons algorithmes pour les résoudre est l'une des tâches les plus importantes afin de mettre en place un système de traduction performant. Plusieurs algorithmes d'optimisation sont proposés pour traiter les problèmes d'optimisation du décodeur. Ils sont combinés pour résoudre, d'une part, le problème de décodage qui produit une traduction dans la langue cible d'une phrase source, d'autre part, le problème d'optimisation des poids des scores combinés dans la fonction log-linéaire pour d'évaluation des hypothèses de traduction au cours du décodage. Le système de traduction statistique de référence est basé sur un algorithme de recherche en faisceau pour le décodage, et un algorithme de recherche linéaire pour l'optimisation des poids associés aux scores. Nous proposons un nouveau système de traduction avec un décodeur entièrement basé sur les algorithmes génétiques. Les algorithmes génétiques sont des algorithmes d'optimisation bio-inspirés qui simulent le processus de l'évolution naturelle des espèces. Ils permettent de manipuler un ensemble de solutions à travers plusieurs itérations pour converger vers des solutions optimales. Ce travail, nous permet d'étudier l'efficacité des algorithmes génétiques pour la traduction automatique statistique. L'originalité de notre proposition est de proposer deux algorithmes : un algorithme génétique, appelé GAMaT, comme décodeur pour un système de traduction statistique à base de segments, et un algorithme génétique, appelé GAWO, pour l'optimisation des poids de la fonction log-linéaire afin de l'utiliser comme fonction fitness pour GAMaT. Nous proposons également, une approche neuronale pour définir une nouvelle fonction fitness pour GAMaT. Cette approche consiste à utiliser un réseau de neurones pour l'apprentissage d'une fonction qui combine plusieurs scores, évaluant différents aspects d'une hypothèse de traduction, combinés auparavant dans la fonction log-linéaire, et qui prédit le score BLEU de cette hypothèse de traduction. Ce travail, nous a permis de proposer un nouveau système de traduction automatique statistique ayant un décodeur entièrement basé sur des algorithmes génétiques / Different components of statistical machine translation systems are considered as optimization problems. Indeed, the learning of the translation model, the decoding and the optimization of the weights of the log-linear function are three important optimization problems. Knowing how to define the right algorithms to solve them is one of the most important tasks in order to build an efficient translation system. Several optimization algorithms are proposed to deal with decoder optimization problems. They are combined to solve, on the one hand, the decoding problem that produces a translation in the target language for each source sentence, on the other hand, to solve the problem of optimizing the weights of the combined scores in the log-linear function to fix the translation evaluation function during the decoding. The reference system in statistical translation is based on a beam-search algorithm for the decoding, and a line search algorithm for optimizing the weights associated to the scores. We propose a new statistical translation system with a decoder entirely based on genetic algorithms. Genetic algorithms are bio-inspired optimization algorithms that simulate the natural process of evolution of species. They allow to handle a set of solutions through several iterations to converge towards optimal solutions. This work allows us to study the efficiency of the genetic algorithms for machine translation. The originality of our work is the proposition of two algorithms: a genetic algorithm, called GAMaT, as a decoder for a phrase-based machine translation system, and a second genetic algorithm, called GAWO, for optimizing the weights of the log-linear function in order to use it as a fitness function for GAMaT. We propose also, a neuronal approach to define a new fitness function for GAMaT. This approach consists in using a neural network to learn a function that combines several scores, which evaluate different aspects of a translation hypothesis, previously combined in the log-linear function, and that predicts the BLEU score of this translation hypothesis. This work allowed us to propose a new machine translation system with a decoder entirely based on genetic algorithms

Les robots humanoïdes sont en passe d'être commercialisés pour le public à grande échelle, mais pour réussir cet objectif il est nécessaire de rendre ces robots fiables, fonctionnels et sécurisés. Ceci implique de nombreuses améliorations par rapport à de l'état de l'art, pour permettre un produit fini. Un des domaines à améliorer est la commande corps-complet des robots humanoïdes. Les objectifs de cette thèse sont de proposer une architecture de commande permettant de générer des mouvements corps-complet bio-inspirés. L'idée principale étant de s'inspirer de la marche humaine afin de reproduire ces mouvements sur un robot humanoïde. La solution de commande proposée utilise le principe de tâches pour quatre objectifs cinématiques: (i) la pose relative des pieds, (ii) la position du CoM, (iii) l'orientation du buste, et (iv) l'évitement des butées articulaires. La stabilité est renforcée en modifiant la position du CoM désirée à l'aide d'un stabilisateur basé sur la régulation non linéaire du ZMP. L'approche résultante est appelée architecture de commande hybride cinématique/dynamique. Cette approche a été validée expérimentalement sur deux prototypes de robots humanoïdes pour différentes tâches telles que le squat et la marche. / Humanoid robots are a rising trend, and are about to be sold to the public on a large scale, but for this to be possible it is necessary to make them reliable, secure and functional. This implies many improvements over the prior state of the art. A domain of improvement is the full-body control of humanoid robots. The objective of this thesis is to propose a control architecture for generating a bio-inspired full-body control. The main idea is to learn from human walking to replicate these movements on a humanoid robot. The proposed control solution uses the principle of kinematics task for four objectives: (i) the relative pose of the feet, (ii) the position of the Centre de masse (CoM), (iii) the orientation of the upper-body, and (iv) the joints' limits avoidance. Stability is enhanced by modifiying the CoM position by using a stabilizer based on nonlinear regulation of the Zero Moment Point (ZMP). The resulting approach is called hybrid kinematic / dynamic control architecture. This approach has been validated experimentally on two prototypes of humanoid robots for tasks such as squat and walking.

In recent decades, many multinational corporations have used nature inspired innovation (NII) strategies as a mechanism of sustainability-oriented innovation (SOI). In this context, these activities are typically initiated by sustainability or innovation managers who are seeking to utilise novel tools and approaches but generally do not have specific innovation goals. For some, NII is viewed as a new product development tool and for others, it is a broad perspective that defines a larger sustainability narrative for the organisation. This analysis of six cases describes the diversity of innovation types of NII in multinational corporations aiming to apply these models to sustainability-oriented innovation at multiple levels. Data was collected via semi-structured interviews (n=45) with NII team members from both inside and outside of the organisation. Additional data included internal project documents and web-based content associated with the NII projects. Cases were then compared and contrasted to identify patterns and anomalies of factors that influence the adoption of NII. While perceptions of NII were relatively consistent across cases, several factors were identified related to sustainability perspectives, the role of management, organisational structures, and innovation culture that influenced adoption. This thesis makes an original contribution to knowledge within the NII, sustainability-oriented innovation, and innovation adoption literatures by differentiating NII as an approach to SOI in MNCs, establishing an innovation typology in this context, and identifying three SOI narratives that influence the adoption of NII. Specific factors related to sustainability narratives, innovation culture and infrastructure, and management styles that support and inhibit SOI and NII in MNCs are used to distinguish three unique SOI narratives – Ambiguous, Accountable, and Aspirational. Conclusions suggest a NII readiness assessment may facilitate the adoption of NII by identifying the most effective approaches depending on the narrative of SOI within the company.

<div>Wounds are created in soft and hard tissue through surgery or disease. As the wound heals, the tissue is held in place using sutures or staples for soft tissue or plates, pins, or screws for hard tissues. These fixation methods inherently damage the surrounding healthy tissue. Surgical adhesives are a non-damaging alternative to these methods. In order to be effective, surgical adhesives must be biocompatible,</div><div>adhere strongly in a moist environment, and have mechanical properties similar to those of the native tissue.</div><div><br></div><div><div>To address the design criteria for surgical adhesives, we look to nature to find inspiration from compounds that provide these properties. Mussels use catechol-based</div><div>molecules to adhere to surfaces in wet and turbulent environments. Incorporating catechols into polymer systems can provide adhesion even in moist biological environments.</div><div>Mimics of elastomeric proteins from soft tissue can be used as backbones for soft and flexible adhesive systems. In particular, elastin-inspired proteins have a well-defined modular sequence that allows for a range of design choices. In this work, we explored the behavior of elastin- and mussel-inspired natural and synthetic polymers in biologically relevant environments.</div></div><div><br></div><div><div>First, the cytocompatibility of a catechol-containing poly(lactic acid) (cPLA) hard tissue adhesive was studied. The cPLA polymer was reacted with iron- or periodatebased</div><div>crosslinkers and compared to PLA. Fibroblasts grown directly on cPLA or cultured with leachate from cPLA had high viability but slower growth than cells on PLA. The periodate crosslinker was significantly cytotoxic, and cells grown on cPLA crosslinked with periodate had reduced metabolism and slowed growth. Cells grown on or in leachate from iron-crosslinked cPLA had similar viability, metabolism, and growth to cells on or in leachate from cPLA. The iron-crosslinked cPLA is a promising</div><div>cytocompatible adhesive for hard tissue applications.</div></div><div><br></div><div><div>Second, two elastin-like proteins (ELP) were developed that had pH-sensitive properties in solution and when crosslinked into hydrogels. Both ELPs had a large number of ionizable tyrosine and lysine residues, and one design also had a large number of ionizable histidine and aspartic acid residues. The stiffness of the hydrogels was maximized at pH values near the isoelectric point of the protein. The stoichometric ratio of crosslinker used affected hydrogel stiffness but did not significantly alter the pH-sensitivity of the gel. The crosslinked gel shrank when swelled at physiological pH. The pH-sensitive mechanical properties of hydrogels made from the two ELPs did not vary significantly. The tyrosine and lysine residues in one ELP were also</div><div>chemically blocked through acetylation to lower the isolectric point of the protein. The acetylated hydrogels had maximum stiffness at a pH near the isoelectric point of the acetylated ELP. The stiffness of both the native and acetylated gels were within the range of soft tissue. Through a combination of crosslinker ratio and chemical modification, the pH-responsive properties of the elastin-inspired hydrogels could be tuned.</div></div><div><br></div><div><div>Finally, adhesive proteins were created that were inspired by both elastin and mussels. An ELP was modified to include catechol groups (mELP). The ELP and mELP were optimized for adhesive use in a soft tissue system. A warm and humid environment was used to study the adhesion of these proteins on pig skin. Iron and (hydroxymethyl) phosphine crosslinkers increased the adhesive strength of both proteins, and periodate increased the adhesive strength of mELP. The adhesive strengths of the proteins were maximized when mELP was mixed with iron or when either protein were mixed with (hydroxymethyl)phosphine crosslinkers. These maximized adhesives were 12-17 times stronger than a commercially available sealant. In addition,</div><div>the iron and mELP adhesive formulation achieved high adhesive strengths even when cured for only ten minutes. This adhesive formula shows promise for adhesive</div><div>applications on soft tissue.</div></div>

Sistemas de vigilância são geralmente empregados no monitoramento de áreas de grandes dimensões nas quais seus usuários visam detectar ou observar fenômenos de seu interesse. O uso de redes de sensores sem fio nesses sistemas apresenta especial interesse, uma vez que essas redes podem apresentar soluções de baixo custo e robustas para cobrir áreas extensas. Neste contexto, novas aplicações têm surgido propondo o uso de redes de sensores sem fio compostas por nós sensores estáticos e móveis. Uma das motivações para esta tendência é a redução do custo de implantação e operação do sistema, além da possibilidade de proporcionar incremento em suas funcionalidades. O foco desta tese se concentra na proposta de soluções para redes de sensores sem fio com uso cooperativo de sensores estáticos e móveis, com particular atenção a sensibilidade ao contexto na configuração e execução de missões de sensoriamento. O objetivo é manter um baixo custo de comunicação associado às soluções propostas. Esta preocupação se dá pelo fato da comunicação aumentar o consumo de energia em redes de sensores, o que é um problema importante para nós sensores com limitada fonte de energia, i.e. baterias. No caso de nós sensores móveis, esta limitação pode não ser relevante, uma vez que seu movimento deve consumir uma quantidade muito mais expressiva de energia do que a comunicação. Neste caso, o problema se relaciona à estabilidade dos enlaces, bem como ao curto intervalo de tempo disponível para transmitir e receber dados. Logo, o melhor é comunicar o menos possível. Com relação à interação entre nós sensores estáticos, os problemas de disseminação e alocação de missões de sensoriamento são estudados e uma solução que explora o uso de informações locais é proposta e avaliada. Esta solução emprega agentes de software móveis que têm a capacidade de tomar decisões autônomas através do uso de informações de contexto local. Para redes de sensores móveis, o problema estudado se refere a como transferir missões entre os nós sensores de acordo com seu movimento e localização em relação aos locais onde as missões devem ser executadas. Para tratar este problema, uma abordagem baseada em agentes móveis é proposta, na qual os agentes implementam a migração das missões de sensoriamento usando informações de contexto geográfico para decidir a respeito de suas migrações. Para redes de sensores com sensores estáticos e móveis, a cooperação entre eles é abordada através de um mecanismo com inspiração biológica para realizar a realizar a entrega de dados emitidos pelos sensores estáticos aos sensores móveis. Para isto, explora-se uma analogia baseada no comportamento de formigas na construção e seguimento de trilhas. As soluções propostas são flexíveis, sendo aplicáveis a diferentes domínios de aplicação. Resultados experimentais evidenciam sua escalabilidade, avaliando, por exemplo, seu custo em termos de comunicação, além de outras métricas de interesse para cada uma das soluções. Estes resultados são comparados aos atingidos por soluções de referência (solução ótima teórica e baseada em inundação), indicando sua eficiência. Estes resultados são próximos do ótimo teórico e significativamente melhores que aqueles atingidos por soluções baseadas em técnicas de inundação. / Surveillance systems are usually employed to monitor wide areas in which their users are interested in detecting and/or observing events or phenomena of their interest. The use of wireless sensor networks in such systems is of particular interest as these networks can provide a relative low cost and robust solution to cover large areas. Emerging applications in this context are proposing the use of wireless sensor networks composed of both static and mobile sensor nodes. Motivation for this trend is to reduce deployment and operating costs, besides providing enhanced functionalities. This work focuses on the proposal of solutions for wireless sensor networks including static and mobile sensor nodes specifically regarding cooperative and context aware mission setup and performance. The goal is to keep the communication costs as low as possible in the execution of the proposed solutions. This concern comes from the fact that communication increases energy consumption, which is a particular issue for energy constrained sensor nodes often used in wireless sensor networks, especially if battery supplied. In the case of the mobile nodes, this energy constraint may not be valid, since their motion might need much more energy, but links instabilities and short time windows available to receive and transmit data. Therefore, it is better to communicate as little as possible. For the interaction among static sensor nodes, the problems of dissemination and allocation of sensing missions are studied and a solution that explores local information is proposed and evaluated. This solution uses mobile software agents that have capabilities to take autonomous decisions about the mission dissemination and allocation using local context information. For mobile wireless sensor networks, the problem studied is how to perform handover of missions among the nodes according to their movements and locations in relation to the place where the missions have to be performed. To handle this problem, a mobile agent approach is proposed in which the agents implement the sensing missions’ migration from node to node using geographical context information to decide about their migrations. For the networks combining static and mobile sensor nodes, the cooperation among them is approached by a biologically-inspired mechanism to deliver data from the static to the mobile nodes. The data delivery mechanism explores an analogy based on the behaviour of ants building and following trails, inspired by the ant colony algorithm. The proposed solutions are flexible, being able to be applied to different application domains. Obtained experimental results provide evidence of the scalability of these proposed solutions, for example by evaluating their cost in terms of communication, among other metrics of interest for each solution. These results are compared to those achieved by reference solutions (theoretical optimum and floodingbased), providing indications of the proposed solutions’ efficiency. These results are considered close to the theoretical optimum one and significantly better than the ones achieved by flooding-based solutions.

Dans cette thèse, nous étudions un métamatériau inspiré de la paille de blé pour l'absorption parfaite du son. Une botte de paille estidéalisée comme un milieu poreux anisotrope, composé d’un arrangement périodique très concentré de tubes creux cylindriques. L’approche théorique de ce métamatériau repose sur l'homogénéisation asymptotique à deux échelles d'un réseau perméable de résonateursparfaitement rigides dont la physique est enrichi par des résonances internes. Les principales caractéristiques de ce milieu poreux sont lacompressibilité effective négative autour de la résonance du tube et la réduction drastique de la vitesse de propagation du son (slowsound) à très basse fréquence. Une configuration optimale est conçue, basée sur la condition de couplage critique, pour laquelle la fuited’énergie du système résonnant ouvert est parfaitement compensée par les pertes intrinsèques induites par les pertes viscothermiques.Des mesures en tube à impédance sont effectuées sur des échantillons fabriqués par impression additive pour valider les résultatsthéoriques. Nous montrons que ce métamatériau est un absorbeur sub-longueur d'onde capable d’une absorption parfaite à très bassefréquence et d'introduire une quasi-bande interdite autour de la résonance du tube. De plus, la nature anisotrope de ce matériau conduit àune absorption globalement élevée à basse fréquence et ce pour toutes les incidences. Cette étude offre la possibilité de concevoir unabsorbeur acoustique sélectif en angle et en fréquence. Pour conclure, les résultats de cette thèse montrent que la paille est un boncandidat pour une absorption acoustique parfaite. / Straw-inspired metamaterials for sound absorption are investigated in this Thesis. A straw stack is idealized as a highly concentratedresonant anisotropic porous medium constituted of a periodic arrangement of densely packed cylindrical hollow tubes. The approach tothis metamaterial relies on the two-scale asymptotic homogenization of a permeable array of perfectly rigid resonators, where the physicsis further enriched by tailoring inner resonances. The main features of such sound absorbing medium are the possibility for the effectivecompressibility to become negative around the tube resonance and the drastic reduction of the effective sound speed (slow sound) at verylow frequency in the system. Moreover, an optimal configuration for sound absorption is designed, based on the critical couplingcondition, in which the energy leakage out of the open resonant system is perfectly compensated by the intrinsic losses induced by thevisco-thermal losses both in the anisotropic matrix and in the resonators. Impedance tube measurements are performed on 3-D printedsamples with controlled parameters to validate the theoretical results. This metamaterial is a sub-wavelength absorber that can achievetotal absorption at a very low frequency and possesses a quasi-band-gap around the tube resonance. Furthermore, the anisotropic nature ofthe configuration gives rise to high absorption at low-frequency range for all incidences and diffuse field excitation. It paves the way tothe design of angular and frequency selective sound absorber. To conclude, the results of this Thesis show that straw is a good candidatefor perfect sound absorption.

The objective of the dissertation research is to investigate noise reduction methods for binaural hearing aids based on array and statistical signal processing and inspired by a human auditory model. In digital hearing aids, wide dynamic range compression (WDRC) is the most successful technique to deal with monaural hearing losses. This WDRC processing is usually performed after a monaural noise reduction algorithm. When hearing losses are present in both ears, i.e., a binaural hearing loss, independent monaural hearing aids have been shown not to be comfortable for most users, preferring a processing that involves synchronization between both hearing devices. In addition, psycho-acoustical studies have identified that under hostile environments, e.g., babble noise at very low SNR conditions, users prefer to use linear amplification rather than WDRC. In this sense, the noise reduction algorithm becomes an important component of a digital hearing aid to provide improvement in speech intelligibility and user comfort. Including a wireless link between both hearing aids offers new ways to implement more efficient methods to reduce the background noise and coordinate processing for the two ears. This approach, called binaural hearing aid, has been recently introduced in some commercial products but using very simple processing strategies. This research analyzes the existing binaural noise-reduction techniques, proposes novel perceptually-inspired methods based on blind source separation (BSS) and multichannel Wiener filter (MWF), and identifies different strategies for the real-time implementation of these methods. The proposed methods perform efficient spatial filtering, improve SNR and speech intelligibility, minimize block processing artifacts, and can be implemented in low-power architectures.

Aquesta tesi està inspirada en els agents naturals per tal de planificar de manera dinàmica la navegació d'un robot diferencial de dues rodes. Les dades dels sistemes de percepció són integrades dins una graella d'ocupació de l'entorn local del robot. La planificació de les trajectòries es fa considerant la configuració desitjada del robot, així com els vértexs més significatius dels obstacles més propers. En el seguiment de les trajectòries s'utilitzen tècniques locals de control predictiu basades en el model, amb horitzons de predicció inferiors a un segon. La metodologia emprada és validada mitjançant nombrosos experiments. / In this thesis are used natural agents for dinamic navigation of a differential driven wheeled mobile robot. The perception data are integrated on a local occupancy grid framework where planar floor model is assumed. The path-planning is done by considering the local desired configuration, as well as the meaningful local obstacle vertexes. The trajectory-tracking is implemented by using LMPC (local model predictive control) techniques, with prediction horizons of less than one second. Many experiments are tested in order to report the validity of the prosed methodology.