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Guidelines for the Specification of IoT Requirements: A Smart Cars Case
No full textInternational audienceIn the last five years, we witnessed the shift from the vision of the Internet of things (IoT), to an actual reality. It is currently shifting again from specific and single applications, to larger and more generic ones, which serves the needs of thousands of users, across borders and platforms. To avoid losing the personification of applications, on account of genericity, new approaches and languages that use generic knowledge as a steppingstone, while taking into consideration users and context's specific and evolutive needs are on the rise. This chapter aims to provide a framework to support the creation of such approaches (DSPL4IoT). It is later on used to asses notable IoT specification approaches, and extract conclusion of the trends and persistent challenges and directions. An approach for the specification of Natural Language (NL) requirements for IoT systems is also provided to assist domain and application engineers with the formulations of such requirements
A Fast Recursive Algorithm for Multiple Bridged Knife-Edge Diffraction
No full textInternational audienceMultiple bridged knife-edge diffraction estimation can be seen as a generalization of the multiple knife-edge diffraction one which can be found in many applications of wireless communications. The considered model is formed by bridging the spaces among knife-edges with reflecting planes. So far, the series-based standard solution for this problem suffers from high computational complexity, thus limiting its use in practice. We, thus, propose a fast recursive algorithm to tackle its computational burden. To illustrate the effectiveness of the proposed algorithm, we compare our results with the state-of-the-art algorithms. Numerical results show that the running time of the proposed algorithm is much faster than that of the standard solution while benefiting from similar accuracy. © 2021 European Signal Processing Conference. All rights reserved
Report on the Methodological Framework of new Pedagogical Approaches
No full textThis report summarises the methodology used to create scenarios as part of the innovative teachingpedagogies proposed in the A-STEP 2030 (Attracting diverSe Talent to the Engineering Professions of2030) project. This project is an EU Erasmus+ project funded under call number 2018-1-FR01-KA203-047854. The report begins by describing the overall project and the organisation of the learning andteaching activity. The scenarios were co-created with student participants and academic staff in thelearning and teaching activity - A-STEP 2030 Summer School which was held in August 2021.The specific scenarios created by participants are described in this report and can be used byengineering educators in delivery of engineering programmes. More detailed videos are also includedon the project website (www.astep2030.eu
Bénéfices fonctionnels à 6 et 9 mois d’une plateforme d’assistance domiciliaire auprès de personnes âgées fragiles et de leurs aidants
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Modèles d’ordre réduit pour les vibrations non linéaires géométriques de structures minces
No full textWhen vibrating with large amplitudes, thin structures experience geometric nonlinearity due to the nonlinear relationship between strains and displacements. Because full-order nonlinear analysis on geometrically nonlinear models are computationally very expensive, the derivation of efficient reduced-order models (ROMs) has always been a topic of interest.In this thesis, nonlinear reduction methods for building ROMs with geometric nonlinearity in the framework of the Finite Element (FE) procedure, are investigated. Three non-intrusive nonlinear reduction methods are specifically investigated and systematically compared. They are: implicit condensation and expansion (ICE), modal derivatives (MD), and the reduction to invariant manifold. Theoretical analysis shows that the first two methods can give reliable results only if a slow/fast assumption between slave and master coordinates holds. On the other hand, reduction to invariant manifolds allows proposing a simulation-free reduction method that can be applied without restricting assumptions on the frequencies of the slave modes.Numerical comparisons and numerous applications to continuous structures discretized with the FE procedure, are given subsequently. For application of the invariant manifold-based method, the computation is based on a direct application of the normal form to the physical space and hence to the nodes of the FE mesh, a method recently developed. The examples show the advantages and drawbacks of each reduction method when deriving ROM, and the results of the theoretical comparison are validated.Finally, the analysis of the dynamics of a system with 1:2 internal resonance and cubic nonlinearity is given in the last part of the thesis. The real normal form of the problem is first derived. Then the solution branches of the problem are investigated and compared to simpler solutions with the dynamics truncated at order two. The divergent behaviour of the hardening/softening characteristics for single-mode reduction is investigated with this more complete model.Lorsqu'elles vibrent avec de grandes amplitudes, les structures minces montrent un comportement non linéaire géométrique, provenant de la relation non linéaire entre les déformations et les déplacements. Les analyses des systèmes complets font appel à des calculs extrêmement couteux de telle sorte que l'établissement de modèles d'ordre réduit efficaces est un sujet d'intérêt majeur pour le calcul prédictif de vibrations de structures minces.Dans cette thèse, des méthodes non linéaires de réduction de modèle pour les structures discrétisées par la méthode des éléments finis et comportant une non-linéarité géométrique, sont étudiées. Trois méthodes non intrusives sont plus particulièrement examinées et systématiquement comparées: la méthode de condensation implicite, la méthode des dérivées modales, et la réduction sur variétés invariantes du système. Les analyses théoriques montrent que les deux premières méthodes ne peuvent donner de résultats fiables que sous hypothèse d'une séparation spectrale entre les fréquences propres des modes maitres et celles des modes esclaves. La méthode de réduction sur variétés invariantes permet quant à elle d'avoir une méthode directe, ne nécessitant pas de pré-calculs, ni d'hypothèses préalables sur les fréquences propres des modes esclaves, afin de fournir des résultats corrects.De nombreuses applications et de comparaisons numériques sont montrées sur diverses structures discrétisées avec la méthode des éléments finis. Pour appliquer la méthode des variétés invariantes, une méthode récemment développée, permet de proposer un calcul direct de la forme normale du problème, à partir de la base physique et donc des degrés de liberté du maillage éléments finis. Les exemples montrent clairement les avantage et inconvénients de chaque méthode, validant aussi les résultats théoriques montrés précédemment.Dans la dernière partie de la thèse, la dynamique non linéaire d'un système présentant une relation de résonance interne 1:2 est analysée, en tenant compte des termes cubiques. La forme normale réelle du problème est d'abord établie. Ensuite les branches de solution du problème sont analysées et comparées avec celles du modèle plus simple négligeant la non-linéarité cubique. Le comportement divergent observé lorsqu'on réduit le problème à un seul mode et que l'on cherche à prédire le comportement raidissant ou assouplissant, est ensuite étudié avec ce modèle plus complet
Taking residual stresses into account in low-cycle fatigue design using the adjustable localisation operator method
No full textInternational audienceThis paper assesses the ability of the Adjustable Localisation Operator (ALO) method to predict the influence of residual stresses on the fatigue behaviour of notched components. Different initial residual stress states are introduced into notched specimens, which are then tested under cyclic loadings in a fatigue range of 103 to 105 cycles. Experimental comparisons with initially stress-free specimens have shown how tensile residual stresses reduce fatigue life under repeated compressive loading while compressive residual stresses increase fatigue life under repeated tensile loading.Finite Element Analysis (FEA) and ALO method predictions of changes in residual stress are compared to experimental measurements beforehand to assess fatigue life predictions. A modified version of Morrow’s criterion is used to account for the mean stress effect. Results have shown that the ALO method can predict the influence of residual stresses on low-cycle fatigue with the same accuracy as finite element analysis and with a significant reduction in computation time
Concepts and Semantics of Programming Languages 1: A Semantical Approach with OCaml and Python
No full textInternational audienceThis book – the first of two volumes – explores the syntactical constructs of the most common programming languages, and sheds a mathematical light on their semantics, while also providing an accurate presentation of the material aspects that interfere with coding.Concepts and Semantics of Programming Languages 1 is dedicated to functional and imperative features. Included is the formal study of the semantics of typing and execution; their acquisition is facilitated by implementation into OCaml and Python, as well as by worked examples. Data representation is considered in detail: endianness, pointers, memory management, union types and pattern-matching, etc., with examples in OCaml, C and C++. The second volume introduces a specific model for studying modular and object features and uses this model to present Ada and OCaml modules, and subsequently Java, C++, OCaml and Python classes and objects.This book is intended not only for computer science students and teachers but also seasoned programmers, who will find a guide to reading reference manuals and the foundations of program verification
Energy and Performance Analysis of Lossless Compression Algorithms for Wireless EMG Sensors
No full textInternational audienceElectromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data can thus be seen as a nice feature that could allow both longer battery life and more simultaneous channels at the same time. A lot of research has been done in lossy compression algorithms for EMG data, but being lossy, artifacts are inevitably introduced in the signal. Some artifacts can usually be tolerable for current applications. Nevertheless, for some research purposes and to enable future research on the collected data, that might need to exploit various and currently unforseen features that had been discarded by lossy algorithms, lossless compression of data may be very important, as it guarantees no extra artifacts are introduced on the digitized signal. The present paper aims at demonstrating the effectiveness of such approaches, investigating the performance of several algorithms and their implementation on a real EMG BLE wireless sensor node. It is demonstrated that the required bandwidth can be more than halved, even reduced to 1/4 on an average case, and if the complexity of the compressor is kept low, it also ensures significant power savings
Génération du Comportement du Robot et Compréhension du Comportement Humain dans L'interaction Naturelle Humain-Robot
No full textHaving a natural interaction makes a significant difference in a successful human-robot interaction (HRI). The natural HRI refers to both human multimodal behavior understanding and robot verbal or non-verbal behavior generation. Humans can naturally communicate through spoken dialogue and non-verbal behaviors. Hence, a robot should perceive and understand human behaviors so as to be capable of producing a natural multimodal and spontaneous behavior that matches the social context. In this thesis, we explore human behavior understanding and robot behavior generation for natural HRI. This includes multimodal human emotion recognition with visual information extracted from RGB-D and thermal cameras and non-verbal multimodal robot behavior synthesis.Emotion recognition based on multimodal human behaviors during HRI can help robots understand user states and exhibit a natural social interaction. In this thesis, we explored multimodal emotion recognition with thermal facial information and 3D gait data in HRI scene when the emotion cues from thermal face and gait data are difficult to disguise. A multimodal database with thermal face images and 3D gait data was built through the HRI experiments. We tested the various unimodal emotion classifiers (i.e., CNN, HMM, Random Forest model, SVM) and one decision-based hybrid emotion classifier on the database for offline emotion recognition. We also explored an online emotion recognition system with limited capability in the real-time HRI setting. Interaction plays a critical role in skills learning for natural communication. Robots can get feedback during the interaction to improve their social abilities in HRI.To improve our online emotion recognition system, we developed an interactive robot learning (IRL) model with the human in the loop. The IRL model can apply the human verbal feedback to label or relabel the data for retraining the emotion recognition model in a long-term interaction situation. After using the interactive robot learning model, the robot could obtain a better emotion recognition accuracy in real-time HRI.The human non-verbal behaviors such as gestures and face action occur spontaneously with speech, which leads to a natural and expressive interaction. Speech-driven gesture and face action generation are vital to enable a social robot to exhibit social cues and conduct a successful HRI. This thesis proposes a new temporal GAN (Generative Adversarial Network) architecture for a one-to-many mapping from acoustic speech representation to the humanoid robot's corresponding gestures. We also developed an audio-visual database to train the speaking gesture generation model. The database includes the speech audio data extracted directly from the videos and the associated 3D human pose data extracted from 2D RGB images. The generated gestures from the trained co-speech gesture synthesizer can be applied to social robots with arms. The evaluation result shows the effectiveness of our generative model for speech-driven robot gesture generation. Moreover, we developed an effective speech-driven facial action synthesizer based on GAN, i.e., given an acoustic speech, a synchronous and realistic 3D facial action sequence is generated. A mapping between the 3D human facial actions to real robot facial actions that regulate the Zeno robot facial expression is completed. The application of co-speech non-verbal robot behaviors (gesture and face action) synthesis for the social robot can make a friendly and natural human-robot interaction.Pouvoir afficher une interaction naturelle a un impact significatif dans la réussite d’une interaction humain-robot (HRI). Quand nous parlons d’une HRI naturelle, nous faisons référence à la fois à la compréhension du comportement multimodal humain et à la génération de comportements verbaux ou non verbaux du robot. Les humains peuvent naturellement communiquer par le biais du langage et de comportements non verbaux. Par conséquent, un robot doit percevoir et comprendre les comportements humains afin d'être capable de produire un comportement multimodal et naturel qui corresponde au contexte social. Dans cette thèse, nous explorons la compréhension du comportement humain et la génération du comportement du robot pour une HRI naturelle. Cela comprend la reconnaissance multimodale des émotions humaines avec des informations visuelles extraites des cameras RGB-D et thermiques, et la synthèse du comportement non verbal du robot.La perception des émotions humaines en tant que composante fondamentale de la communication joue un rôle important dans le succès des interactions entre un robot et un humain. La reconnaissance des émotions basée sur les comportements humains multimodaux lors d’une HRI peut aider les robots à comprendre les états des utilisateurs et à produire une interaction sociale naturelle. Dans cette thèse, nousinvestiguons la reconnaissance multimodale des émotions avec des informations thermiques du visage et des données de la marche humaine. Une base de données multimodale contenant des images thermiques du visage et des données de la marche en 3D a été créée grâce aux expériences d'HRI. Nous avons testé les différents classificateurs d'émotions unimodaux (c-à-d, CNN, HMM, forêts aléatoires, SVM) et un classificateur d'émotions hybride pour la reconnaissance des émotions hors ligne. Nous avons également exploré un système de reconnaissance des émotions en ligne avec des capacités limitées dans le cadre de l’HRI en temps réel. L'interaction joue un rôle essentiel dans l'apprentissage des compétences pour une communication naturelle. Pour améliorer notre système de reconnaissance des émotions en ligne, nous avons développé un modèle d'apprentissage robotique interactif (IRL) avec l'humain dans la boucle. Le modèle IRL peut appliquer la rétroaction verbale humaine pour étiqueter ou réétiqueter les données pour améliorer le modèle de reconnaissance des émotions dans une situation d'interaction à long terme. Après avoir utilisé le modèle d'apprentissage interactif du robot, le robot a pu obtenir une meilleure précision de reconnaissance des émotions en temps réel.Les comportements humains non verbaux tels que les gestes et les expressions faciales se produisent spontanément avec la parole, ce qui conduit à une interaction naturelle et expressive. La génération de gestes et d’expressions faciales par la parole est essentielle pour permettre à un robot social d'exposer des signaux sociaux et de mener une HRI réussie. Cette thèse propose une nouvelle architecture temporelle GAN (Generative Adversarial Network) pour une cartographie un-à-plusieurs de la représentation acoustique de la parole aux gestes correspondants du robot humanoïde. Nous avons également développé une base de données audiovisuelle pour entraîner le modèle de génération de gestes à partir de la parole. La base de données comprend les données audio extraites directement des vidéos et les données des gestes humaines. Notre synthétiseur de gestes peut être appliqué à des robots sociaux avec des bras. Le résultat de l'évaluation montre l'efficacité de notre modèle génératif pour la génération de gestes de robot à partir de la parole. De plus, nous avons développé un synthétiseur d'expression faciale efficace basé sur GAN. Etant donné un signal audio, une séquence faciale synchrone et réaliste est générée. Nous avons testé cette partie avec le robot Zeno
Remote triggering of air-gap discharge by a femtosecond laser filament and postfilament at distances up to 80 m
No full textInternational audienceWe experimentally observed laser-induced remote high-voltage discharge triggering between two needle electrodes with half-a-cm spacing. The discharge was initiated by a 744-nm, 90-fs, 6-mJ laser pulse undergoing filamentation in air. For the direct voltage below the self-breakdown threshold, triggering of air-gap discharge was synchronized with a 10-Hz laser repetition rate and occurred between 40 and 80 m of the propagation path. No discharge guiding was observed. The experimentally registered and simulated remote triggering probability was above 80% in the range of 45–60 m from laser output and about 50% in the range of 60–80 m. The probability decreases as the postfilament hot spot diverges with a simultaneous increase in stochastic laser beam wandering