269 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

    Visual Processing and Latent Representations in Biological and Artificial Neural Networks

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    The human visual system performs the impressive task of converting light arriving at the retina into a useful representation that allows us to make sense of the visual environment. We can navigate easily in the three-dimensional world and recognize objects and their properties, even if they appear from different angles and under different lighting conditions. Artificial systems can also perform well on a variety of complex visual tasks. While they may not be as robust and versatile as their biological counterpart, they have surprising capabilities that are rapidly improving. Studying the two types of systems can help us understand what computations enable the transformation of low-level sensory data into an abstract representation. To this end, this dissertation follows three different pathways. First, we analyze aspects of human perception. The focus is on the perception in the peripheral visual field and the relation to texture perception. Our work builds on a texture model that is based on the features of a deep neural network. We start by expanding the model to the temporal domain to capture dynamic textures such as flames or water. Next, we use psychophysical methods to investigate quantitatively whether humans can distinguish natural textures from samples that were generated by a texture model. Finally, we study images that cover the entire visual field and test whether matching the local summary statistics can produce metameric images independent of the image content. Second, we compare the visual perception of humans and machines. We conduct three case studies that focus on the capabilities of artificial neural networks and the potential occurrence of biological phenomena in machine vision. We find that comparative studies are not always straightforward and propose a checklist on how to improve the robustness of the conclusions that we draw from such studies. Third, we address a fundamental discrepancy between human and machine vision. One major strength of biological vision is its robustness to changes in the appearance of image content. For example, for unusual scenarios, such as a cow on a beach, the recognition performance of humans remains high. This ability is lacking in many artificial systems. We discuss on a conceptual level how to robustly disentangle attributes that are correlated during training, and test this on a number of datasets

    Innovative designs and applications of Janus micromotors with (photo)-catalytic and magnetic motion

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    El objetivo principal de esta Tesis Doctoral es el diseño y desarrollo de micromotores Janus biocompatibles y su aplicación en ámbitos relevantes de la salud y de la protección medioambiental. Los micromotores Janus son dispositivos en la microescala autopropulsados que tienen al menos dos regiones en su superficie con diferentes propiedades físicas y químicas, lo que les convierte en una clase distintiva de materiales que pueden combinar características ópticas, magnéticas y eléctricas en una sola entidad. Como la naturaleza del micromotor Janus -el dios romano de las dos caras- los objetivos de esta Tesis Doctoral presentan naturaleza dual y comprenden desarrollos de química fundamental y de química aplicada. En efecto, por una parte, el objetivo central aborda el diseño, síntesis y ensamblaje, así como la caracterización de micromotores Janus poliméricos propulsados por mecanismos (foto)-catalíticos y/o accionados por campos magnéticos. Por otra parte, el objetivo central implica la aplicación de los micromotores desarrollados para resolver desafíos sociales relevantes en los ámbitos químico-analítico, biomédico y ambiental. Partiendo de estas premisas, en la primera parte de la Tesis Doctoral, se sintetizaron micromotores Janus de policaprolactona propulsados químicamente integrando nanomateriales para el diseño de sensores móviles para la detección selectiva de endotoxinas bacterianas. De esta forma, el movimiento autónomo del micromotor mejora la mezcla de fluidos y la eficacia de las reacciones implicadas permitiendo detectar el analito en pocos minutos, incluso en muestras viscosas y medios donde la agitación no es posible. Además, esta autopropulsión es altamente compatible con su empleo en formatos ultra-miniaturizados para el desarrollo de futuros dispositivos portátiles en el marco de la tecnología point of care para aplicaciones clínicas y agroalimentarias. Con el fin de incrementar su biocompatibilidad para aplicaciones in vivo, en una segunda etapa de la Tesis Doctoral, se diseñaron micromotores Janus con propulsión autónoma utilizando luz visible para la eliminación de toxinas relevantes en procesos inflamatorios. El fenómeno autopropulsivo del micromotor y su capacidad de interacción con agentes tóxicos condujo a metodologías más rápidas y eficaces infiriéndose un futuro prometedor de estos micromotores para el tratamiento del shock séptico o intoxicación. En una tercera etapa, se sintetizaron micromotores propulsados por campos magnéticos. Estos micromotores utilizan una aproximación elegante de propulsión, exenta del empleo de combustibles químicos tóxicos como sucede en la propulsión catalítica y, en consecuencia, biocompatible. Asimismo, este mecanismo propulsivo permite controlar e incluso programar su trayectoria para aplicaciones que requieran de un guiado y de un control preciso de esta. De manera específica, estos micromotores han sido aplicados en esta Tesis Doctoral para la liberación controlada de fármacos en el tratamiento de cáncer pancreático y como elementos de remediación ambiental en la eliminación de agentes nerviosos en aguas contaminadas

    Antennas and Propagation Aspects for Emerging Wireless Communication Technologies

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    The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of novel antenna configurations able to support wideband applications is of utmost importance for 5G context support. Furthermore, in order to design reliable 5G systems, the channel characterization in these frequencies and in the complex propagation environments cannot be ignored because it plays a significant role. In this Special Issue, fourteen papers are published, covering various aspects of novel antenna designs for broadband applications, propagation models at mmWave bands, the deployment of NOMA techniques, radio network planning for 5G networks, and multi-beam antenna technologies for 5G wireless communications

    Towards a Common Software/Hardware Methodology for Future Advanced Driver Assistance Systems

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    The European research project DESERVE (DEvelopment platform for Safe and Efficient dRiVE, 2012-2015) had the aim of designing and developing a platform tool to cope with the continuously increasing complexity and the simultaneous need to reduce cost for future embedded Advanced Driver Assistance Systems (ADAS). For this purpose, the DESERVE platform profits from cross-domain software reuse, standardization of automotive software component interfaces, and easy but safety-compliant integration of heterogeneous modules. This enables the development of a new generation of ADAS applications, which challengingly combine different functions, sensors, actuators, hardware platforms, and Human Machine Interfaces (HMI). This book presents the different results of the DESERVE project concerning the ADAS development platform, test case functions, and validation and evaluation of different approaches. The reader is invited to substantiate the content of this book with the deliverables published during the DESERVE project. Technical topics discussed in this book include:Modern ADAS development platforms;Design space exploration;Driving modelling;Video-based and Radar-based ADAS functions;HMI for ADAS;Vehicle-hardware-in-the-loop validation system

    Terahertz antenna design for future wireless communication

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    A Terahertz (THz) antenna with a size of a few micrometres cannot be accomplished by just reducing the extent of a traditional metallic antenna down to a couple of micrometres. This approach has several downsides. For example, the low mobility of electrons in nanoscale metallic structures would result in high channel attenuation. Thus, using traditional micrometre metallic antennas for THz wireless communication becomes unfeasible. The THz band refers to the electromagnetic spectrum between the microwave and infrared frequency bands, which is colloquially referred to as the band gap due to the lack of materials and technological advancements. As opposed to their visible-spectrum features, metals such as gold and silver, which typically exhibit surface plasmon polaritons (SPPs), have completely different THz physical properties. 2D materials, which typically refer to single-layer materials, have been the focal point of researchers since the advent of graphene. 2D materials, for example, graphene, perovskite, and MoS2 (TMDs), provide a ground-breaking stage to control the propagation, modulation, and detection of THz waves. Moreover, 2D materials can enable the propagation of SPP waves in the THz band. These materials offer a promise of a future technological revolution. Combined with other profound advantages in lightweight, mechanical flexibility, and environmental friendliness, 2D materials can be used to fabricate low-cost wearable devices. This study also reported CH3NH3PbI3 perovskite as a promising material for THz antennas for wearable applications. CH3NH3PbI3 has a high charge carrier mobility and diffusion length, indicating that this material is a potential candidate for antenna design. The attractive feature about perovskite, graphene and other 2D materials is the ultra-high specific surface areas that enable their energy band structures to be sensitive to external basing. In the literature, scientists have tested a wide range of nano-antenna designs using modelling and simulation approaches. Nano-antenna fabrication and measurement using 2D materials is still the missing piece in the THz band. The design, fabrication, and measurement of THz antennas based on 2D materials for wearable wireless communication is the primary goal of this PhD study, including designing, fabrication, and measurement. In this study, we have designed, fabricated, and measured five different designs using different materials in the THz band, which will pave the way for enabling future THz short-range wireless communication

    Proceedings of the 19th Sound and Music Computing Conference

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    Proceedings of the 19th Sound and Music Computing Conference - June 5-12, 2022 - Saint-Étienne (France). https://smc22.grame.f

    Vehicle and Traffic Safety

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    The book is devoted to contemporary issues regarding the safety of motor vehicles and road traffic. It presents the achievements of scientists, specialists, and industry representatives in the following selected areas of road transport safety and automotive engineering: active and passive vehicle safety, vehicle dynamics and stability, testing of vehicles (and their assemblies), including electric cars as well as autonomous vehicles. Selected issues from the area of accident analysis and reconstruction are discussed. The impact on road safety of aspects such as traffic control systems, road infrastructure, and human factors is also considered

    Variational methods and its applications to computer vision

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    Many computer vision applications such as image segmentation can be formulated in a ''variational'' way as energy minimization problems. Unfortunately, the computational task of minimizing these energies is usually difficult as it generally involves non convex functions in a space with thousands of dimensions and often the associated combinatorial problems are NP-hard to solve. Furthermore, they are ill-posed inverse problems and therefore are extremely sensitive to perturbations (e.g. noise). For this reason in order to compute a physically reliable approximation from given noisy data, it is necessary to incorporate into the mathematical model appropriate regularizations that require complex computations. The main aim of this work is to describe variational segmentation methods that are particularly effective for curvilinear structures. Due to their complex geometry, classical regularization techniques cannot be adopted because they lead to the loss of most of low contrasted details. In contrast, the proposed method not only better preserves curvilinear structures, but also reconnects some parts that may have been disconnected by noise. Moreover, it can be easily extensible to graphs and successfully applied to different types of data such as medical imagery (i.e. vessels, hearth coronaries etc), material samples (i.e. concrete) and satellite signals (i.e. streets, rivers etc.). In particular, we will show results and performances about an implementation targeting new generation of High Performance Computing (HPC) architectures where different types of coprocessors cooperate. The involved dataset consists of approximately 200 images of cracks, captured in three different tunnels by a robotic machine designed for the European ROBO-SPECT project.Open Acces
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