Piezo-electromechanical smart materials with distributed arrays of piezoelectric transducers: Current and upcoming applications

This review paper intends to gather and organize a series of works which discuss the possibility of exploiting the mechanical properties of distributed arrays of piezoelectric transducers. The concept can be described as follows: on every structural member one can uniformly distribute an array of piezoelectric transducers whose electric terminals are to be connected to a suitably optimized electric waveguide. If the aim of such a modification is identified to be the suppression of mechanical vibrations then the optimal electric waveguide is identified to be the 'electric analog' of the considered structural member. The obtained electromechanical systems were called PEM (PiezoElectroMechanical) structures. The authors especially focus on the role played by Lagrange methods in the design of these analog circuits and in the study of PEM structures and we suggest some possible research developments in the conception of new devices, in their study and in their technological application. Other potential uses of PEMs, such as Structural Health Monitoring and Energy Harvesting, are described as well. PEM structures can be regarded as a particular kind of smart materials, i.e. materials especially designed and engineered to show a specific andwell-defined response to external excitations: for this reason, the authors try to find connection between PEM beams and plates and some micromorphic materials whose properties as carriers of waves have been studied recently. Finally, this paper aims to establish some links among some concepts which are used in different cultural groups, as smart structure, metamaterial and functional structural modifications, showing how appropriate would be to avoid the use of different names for similar concepts. © 2015 - IOS Press and the authors

General Dynamic Surface Reconstruction: Application to the 3D Segmentation of the Left Ventricle

Aquesta tesi descriu la nostra contribució a la reconstrucció tridimensional de les superfícies interna i externa del ventricle esquerre humà. La reconstrucció és un primer procés dins d'una aplicació global de Realitat Virtual dissenyada com una important eina de diagnòstic per a hospitals. L'aplicació parteix de la reconstrucció de les superfícies i proveeix a l'expert de manipulació interactiva del model en temps real, a més de càlculs de volums i de altres paràmetres d'interès. El procés de recuperació de les superfícies es caracteritza per la seva velocitat de convergència, la suavitat a les malles finals i la precisió respecte de les dades recuperades. Donat que el diagnòstic de patologies cardíaques requereix d'experiència, temps i molt coneixement professional, la simulació és un procés clau que millora la eficiència.Els nostres algorismes i implementacions han estat aplicats a dades sintètiques i reals amb diferències relatives a la quantitat de dades inexistents, casuístiques presents a casos patològics i anormals. Els conjunts de dades inclouen adquisicions d'instants concrets i de cicles cardíacs complets. La bondat del sistema de reconstrucció ha estat avaluada mitjançant paràmetres mèdics per a poder comparar els nostres resultats finals amb aquells derivats a partir de programari típic utilitzat pels professionals de la medicina.A més de l'aplicació directa al diagnòstic mèdic, la nostra metodologia permet reconstruccions de tipus genèric en el camp dels Gràfics 3D per ordinador. Les nostres reconstruccions permeten generar models tridimensionals amb un baix cost en quant a la interacció manual necessària i a la càrrega computacional associada. Altrament, el nostre mètode pot entendre's com un robust algorisme de triangularització que construeix superfícies partint de núvols de punts que poden obtenir-se d'escàners làser o sensors magnètics, per exemple.Esta tesis describe nuestra contribución a la reconstrucción tridimensional de las superficies interna y externa del ventrículo izquierdo humano. La reconstrucción es un primer proceso que forma parte de una aplicación global de Realidad Virtual diseñada como una importante herramienta de diagnóstico para hospitales. La aplicación parte de la reconstrucción de las superficies y provee al experto de manipulación interactiva del modelo en tiempo real, además de cálculos de volúmenes y de otros parámetros de interés. El proceso de recuperación de las superficies se caracteriza por su velocidad de convergencia, la suavidad en las mallas finales y la precisión respecto de los datos recuperados. Dado que el diagnóstico de patologías cardíacas requiere experiencia, tiempo y mucho conocimiento profesional, la simulación es un proceso clave que mejora la eficiencia.Nuestros algoritmos e implementaciones han sido aplicados a datos sintéticos y reales con diferencias en cuanto a la cantidad de datos inexistentes, casuística presente en casos patológicos y anormales. Los conjuntos de datos incluyen adquisiciones de instantes concretos y de ciclos cardíacos completos. La bondad del sistema de reconstrucción ha sido evaluada mediante parámetros médicos para poder comparar nuestros resultados finales con aquellos derivados a partir de programario típico utilizado por los profesionales de la medicina.Además de la aplicación directa al diagnóstico médico, nuestra metodología permite reconstrucciones de tipo genérico en el campo de los Gráficos 3D por ordenador. Nuestras reconstrucciones permiten generar modelos tridimensionales con un bajo coste en cuanto a la interacción manual necesaria y a la carga computacional asociada. Por otra parte, nuestro método puede entenderse como un robusto algoritmo de triangularización que construye superficies a partir de nubes de puntos que pueden obtenerse a partir de escáneres láser o sensores magnéticos, por ejemplo.This thesis describes a contribution to the three-dimensional reconstruction of the internal and external surfaces of the human's left ventricle. The reconstruction is a first process fitting in a complete VR application that will serve as an important diagnosis tool for hospitals. Beginning with the surfaces reconstruction, the application will provide volume and interactive real-time manipulation to the model. We focus on speed, precision and smoothness for the final surfaces. As long as heart diseases diagnosis requires experience, time and professional knowledge, simulation is a key-process that enlarges efficiency.The algorithms and implementations have been applied to both synthetic and real datasets with differences regarding missing data, present in cases where pathologies and abnormalities arise. The datasets include single acquisitions and complete cardiac cycles. The goodness of the reconstructions has been evaluated with medical parameters in order to compare our results with those retrieved by typical software used by physicians.Besides the direct application to medicine diagnosis, our methodology is suitable for generic reconstructions in the field of computer graphics. Our reconstructions can serve for getting 3D models at low cost, in terms of manual interaction and CPU computation overhead. Furthermore, our method is a robust tessellation algorithm that builds surfaces from clouds of points that can be retrieved from laser scanners or magnetic sensors, among other available hardware

Oseledets' Splitting of Standard-like Maps

For the class of differentiable maps of the plane and, in particular, for standard-like maps (McMillan form), a simple relation is shown between the directions of the local invariant manifolds of a generic point and its contribution to the finite-time Lyapunov exponents (FTLE) of the associated orbit. By computing also the point-wise curvature of the manifolds, we produce a comparative study between local Lyapunov exponent, manifold's curvature and splitting angle between stable/unstable manifolds. Interestingly, the analysis of the Chirikov-Taylor standard map suggests that the positive contributions to the FTLE average mostly come from points of the orbit where the structure of the manifolds is locally hyperbolic: where the manifolds are flat and transversal, the one-step exponent is predominantly positive and large; this behaviour is intended in a purely statistical sense, since it exhibits large deviations. Such phenomenon can be understood by analytic arguments which, as a by-product, also suggest an explicit way to point-wise approximate the splitting.Comment: 17 pages, 11 figure

Real-time human body detection and tracking for augmented reality mobile applications

Hoje em dia, cada vez mais experiências culturais são melhoradas tendo por base aplicações móveis, incluindo aqueles que usam Realidade Aumentada (RA). Estas aplicações têm crescido em número de utilizadores, em muito suportadas no aumento do poder de cálculo dos processadores mais recentes, na popularidade dos dispositivos móveis (com câmaras de alta definição e sistemas de posicionamento global – GPS), e na massificação da disponibilidade de conexões de internet. Tendo este contexto em mente, o projeto Mobile Five Senses Augmented Reality System for Museums (M5SAR) visa desenvolver um sistema de RA para ser um guia em eventos culturais, históricos e em museus, complementando ou substituindo a orientação tradicional dada pelos guias ou mapas. O trabalho descrito na presente tese faz parte do projeto M5SAR. O sistema completo consiste numa aplicação para dispositivos móveis e num dispositivo físico, a acoplar ao dispositivo móvel, que em conjunto visam explorar os 5 sentidos humanos: visão, audição, tato, olfacto e paladar. O projeto M5SAR tem como objetivos principais (a) detectar peças do museu (por exemplo, pinturas e estátuas (Pereira et al., 2017)), (b) detectar paredes / ambientes do museu (Veiga et al., 2017) e (c) detectar formas humanas para sobrepor o conteúdo de Realidade Aumentada (?). Esta tese apresenta uma abordagem relativamente ao último objectivo, combinando informações de articulações do corpo humano com métodos de sobreposição de roupas. Os atuais sistemas relacionados com a sobreposição de roupas, que permitem ao utilizador mover-se livremente, são baseados em sensores tridimensionais (3D), e.g., Sensor Kinect (Erra et al., 2018), sendo estes não portáteis. A contribuição desta tese é apresentar uma solução portátil baseado na câmara (RGB) do telemóvel que permite ao utilizador movimentar-se livremente, fazendo ao mesmo tempo a sobreposição de roupa (para o corpo completo). Nos últimos anos, a capacidade de Redes Neurais Convolucionais (CNN) foi comprovado numa grande variedade de tarefas de visão computacional, tais como classificação e detecção de objetos e no reconhecimento de faces e texto (Amos et al., 2016; Ren et al., 2015a). Uma das áreas de uso das CNN é a estimativa de posição (pose) humana em ambientes reais (Insafutdinov et al., 2017; Pishchulin et al., 2016). Recentemente, duas populares CNN frameworks para detecção e segmentação de formas humanas apresentam destaque, o OpenPose (Cao et al., 2017;Wei et al., 2016) e o Mask R-CNN (He et al., 2017). No entanto, testes experimentais mostraram que as implementações originais não são adequadas para dispositivos móveis. Apesar disso, estas frameworks são a base para as implementações mais recentes, que possibilitam o uso em dispositivos móveis. Uma abordagem que alcança a estimativa e a segmentação de pose de corpo inteiro é o Mask R-CNN2Go (Jindal, 2018), baseado na estrutura original do Mask R-CNN. A principal razão para o tempo de processamento ser reduzido foi a otimização do número de camadas de convolução e a largura de cada camada. Outra abordagem para obter a estimativa de pose humana em dispositivos móveis foi a modificação da arquitetura original do OpenPose para mobile (Kim, 2018; Solano, 2018) e sua combinação com MobileNets (Howard et al., 2017). MobileNets, como o nome sugere, é projetado para aplicativos móveis, fazendo uso de camadas de convoluções separáveis em profundidade. Essa modificação reduz o tempo de processamento, mas também reduz a precisão na estimativa da pose, quando comparado à arquitetura original. É importante ressaltar que apesar de a detecção de pessoas com a sobreposição de roupas ser um tema atual, já existem aplicações disponíveis no mercado, como o Pozus (GENTLEMINDS, 2018). O Pozus é disponibilizado numa versão beta que é executado no sistema operativo iOS, usa a câmera do telemóvel como entrada para a estimação da pose humana aplicando segmentos de texturas sobre o corpo humano. No entanto, Pozus não faz ajuste de texturas (roupas) à forma da pessoa. Na presente tese, o modelo OpenPose foi usado para determinar as articulações do corpo e diferentes abordagens foram usadas para sobreposição de roupas, enquanto uma pessoa se move em ambientes reais. A primeira abordagem utiliza o algoritmo GrabCut (Rother et al., 2004) para segmentação de pessoas, permitindo o ajuste de segmentos de roupas. Uma segunda abordagem usa uma ferramenta bidimensional (2D) de Animação do Esqueleto para permitir deformações em texturas 2D de acordo com as poses estimadas. A terceira abordagem é semelhante à anterior, mas usa modelos 3D, volumes, para obter uma simulação mais realista do processo de sobreposição de roupas. Os resultados e a prova de conceito são mostrados. Os resultados são coerentes com uma prova de conceito. Os testes revelaram que como trabalho futuro as otimizações para melhorar a precisão do modelo de estimação da pose e o tempo de execução ainda são necessárias para dispositivos móveis. O método final utilizado para sobrepor roupas no corpo demonstrou resultados positivos, pois possibilitaram uma simulação mais realística do processo de sobreposição de roupas.When it comes to visitors at museums and heritage places, objects speak for themselves. Nevertheless, it is important to give visitors the best experience possible, this will lead to an increase in the visits number and enhance the perception and value of the organization. With the aim of enhancing a traditional museum visit, a mobile Augmented Reality (AR) framework is being developed as part of the Mobile Five Senses Augmented Reality (M5SAR) project. This thesis presents an initial approach to human shape detection and AR content superimposition in a mobile environment, achieved by combining information of human body joints with clothes overlapping methods. The present existing systems related to clothes overlapping, that allow the user to move freely, are based mainly in three-dimensional (3D) sensors (e.g., Kinect sensor (Erra et al., 2018)), making them far from being portable. The contribution of this thesis is to present a portable system that allows the user to move freely and does full body clothes overlapping. The OpenPose model (Kim, 2018; Solano, 2018) was used to compute the body joints and different approaches were used for clothes overlapping, while a person is moving in real environments. The first approach uses GrabCut algorithm (Rother et al., 2004) for person segmentation, allowing to fit clothes segments. A second approach uses a bi-dimensional (2D) skeletal animation tool to allow deformations on 2D textures according to the estimated poses. The third approach is similar to the previous, but uses 3D clothes models (volumes) to achieve a more realistic simulation of the process of clothes superimposition. Results and proof-of-concept are shown

Astronomical Imaging… Atmospheric Turbulence? Adaptive Optics!

This book is a collection of 19 articles which reflect the courses given at the Collège de France/Summer school “Reconstruction d'images − Applications astrophysiques“ held in Nice and Fréjus, France, from June 18 to 22, 2012. The articles presented in this volume address emerging concepts and methods that are useful in the complex process of improving our knowledge of the celestial objects, including Earth

Statistical properties of the Disk Counterparts of Type II Spicules from simultaneous observations of RBEs in Ca II 8542 and H{\alpha}

Spicules were recently found to exist as two types when a new class of so-called type II spicules was discovered at the solar limb with Hinode. The type II spicules have been linked with on-disk observations of Rapid Blue-shifted Excursions (RBEs) in the Ha and Ca 8542 lines. Here we analyze observations optimized for the detection of RBEs in both Ha and Ca 8542 simultaneously at a high temporal cadence taken with CRISP at the SST. This study used a high-quality time sequence for RBEs at different blue-shifts and employed an automated detection routine to detect a large number of RBEs in order to expand on the statistics of RBEs. We find that the number of detected RBEs is dependent on the Doppler velocity of the images on which the search is performed. Detection of RBEs at lower velocities increases the estimated number of RBEs to the same order of magnitude expected from limb spicules. This shows that RBEs and type II spicules are exponents of the same phenomenon. We provide evidence that Ca 8542 RBEs are connected to Ha RBEs and are located closer to the network regions with the Ha RBEs being the continuation, and show that RBEs have an average lifetime of 83.9 s when observed in both spectral lines with Doppler velocity ranges of 10-25 km/s in Ca 8542 and 30-50 km/s in Ha. In addition, we determine the transverse motion of a much larger sample of RBEs than previous studies and find that like type II spicules, RBEs undergo significant transverse motions, 5-10 km/s. Finally, we find that the intergranular jets discovered in BBSO are a subset of RBEs.Comment: Accepted for publication in the Astrophysical Journal, 15 pages, 10 figure

Computationally efficient deformable 3D object tracking with a monocular RGB camera

182 p.Monocular RGB cameras are present in most scopes and devices, including embedded environments like robots, cars and home automation. Most of these environments have in common a significant presence of human operators with whom the system has to interact. This context provides the motivation to use the captured monocular images to improve the understanding of the operator and the surrounding scene for more accurate results and applications.However, monocular images do not have depth information, which is a crucial element in understanding the 3D scene correctly. Estimating the three-dimensional information of an object in the scene using a single two-dimensional image is already a challenge. The challenge grows if the object is deformable (e.g., a human body or a human face) and there is a need to track its movements and interactions in the scene.Several methods attempt to solve this task, including modern regression methods based on Deep NeuralNetworks. However, despite the great results, most are computationally demanding and therefore unsuitable for several environments. Computational efficiency is a critical feature for computationally constrained setups like embedded or onboard systems present in robotics and automotive applications, among others.This study proposes computationally efficient methodologies to reconstruct and track three-dimensional deformable objects, such as human faces and human bodies, using a single monocular RGB camera. To model the deformability of faces and bodies, it considers two types of deformations: non-rigid deformations for face tracking, and rigid multi-body deformations for body pose tracking. Furthermore, it studies their performance on computationally restricted devices like smartphones and onboard systems used in the automotive industry. The information extracted from such devices gives valuable insight into human behaviour a crucial element in improving human-machine interaction.We tested the proposed approaches in different challenging application fields like onboard driver monitoring systems, human behaviour analysis from monocular videos, and human face tracking on embedded devices