243 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

    SoDaCam: Software-defined Cameras via Single-Photon Imaging

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    Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon-cubes represent the spatio-temporal detections of photons as a sequence of binary frames, at frame-rates as high as 100 kHz. We show that simple transformations of the photon-cube, or photon-cube projections, provide the functionality of numerous imaging systems including: exposure bracketing, flutter shutter cameras, video compressive systems, event cameras, and even cameras that move during exposure. Our photon-cube projections offer the flexibility of being software-defined constructs that are only limited by what is computable, and shot-noise. We exploit this flexibility to provide new capabilities for the emulated cameras. As an added benefit, our projections provide camera-dependent compression of photon-cubes, which we demonstrate using an implementation of our projections on a novel compute architecture that is designed for single-photon imaging.Comment: Accepted at ICCV 2023 (oral). Project webpage can be found at https://wisionlab.com/project/sodacam

    AI for time-resolved imaging: from fluorescence lifetime to single-pixel time of flight

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    Time-resolved imaging is a field of optics which measures the arrival time of light on the camera. This thesis looks at two time-resolved imaging modalities: fluorescence lifetime imaging and time-of-flight measurement for depth imaging and ranging. Both of these applications require temporal accuracy on the order of pico- or nanosecond (10−12 − 10−9s) scales. This demands special camera technology and optics that can sample light-intensity extremely quickly, much faster than an ordinary video camera. However, such detectors can be very expensive compared to regular cameras while offering lower image quality. Further, information of interest is often hidden (encoded) in the raw temporal data. Therefore, computational imaging algorithms are used to enhance, analyse and extract information from time-resolved images. "A picture is worth a thousand words". This describes a fundamental blessing and curse of image analysis: images contain extreme amounts of data. Consequently, it is very difficult to design algorithms that encompass all the possible pixel permutations and combinations that can encode this information. Fortunately, the rise of AI and machine learning (ML) allow us to instead create algorithms in a data-driven way. This thesis demonstrates the application of ML to time-resolved imaging tasks, ranging from parameter estimation in noisy data and decoding of overlapping information, through super-resolution, to inferring 3D information from 1D (temporal) data

    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

    Engineering a Low-Cost Remote Sensing Capability for Deep-Space Applications

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    Systems engineering (SE) has been a useful tool for providing objective processes to breaking down complex technical problems to simpler tasks, while concurrently generating metrics to provide assurance that the solution is fit-for-purpose. Tailored forms of SE have also been used by cubesat mission designers to assist in reducing risk by providing iterative feedback and key artifacts to provide managers with the evidence to adjust resources and tasking for success. Cubesat-sized spacecraft are being planned, built and in some cases, flown to provide a lower-cost entry point for deep-space exploration. This is particularly important for agencies and countries with lower space exploration budgets, where specific mission objectives can be used to develop tailored payloads within tighter constraints, while also returning useful scientific results or engineering data. In this work, a tailored SE tradespace approach was used to help determine how a 6 unit (6U) cubesat could be built from commercial-off-the-shelf (COTS)-based components and undertake remote sensing missions near Mars or near-Earth Asteroids. The primary purpose of these missions is to carry a hyperspectral sensor sensitive to 600-800nm wavelengths (hereafter defined as “red-edge”), that will investigate mineralogy characteristics commonly associated with oxidizing and hydrating environments in red-edge. Minerals of this type remain of high interest for indicators of present or past habitability for life, or active geologic processes. Implications of operating in a deep-space environment were considered as part of engineering constraints of the design, including potential reduction of available solar energy, changes in thermal environment and background radiation, and vastly increased communications distances. The engineering tradespace analysis identified realistic COTS options that could satisfy mission objectives for the 6U cubesat bus while also accommodating a reasonable degree of risk. The exception was the communication subsystem, in which case suitable capability was restricted to one particular option. This analysis was used to support an additional trade investigation into the type of sensors that would be most suitable for building the red-edge hyperspectral payload. This was in part constrained by ensuring not only that readily available COTS sensors were used, but that affordability, particularly during a geopolitical environment that was affecting component supply surety and access to manufacturing facilities, was optimized. It was found that a number of sensor options were available for designing a useful instrument, although the rapid development and life-of-type issues with COTS sensors restricted the ability to obtain useful metrics on their performance in the space environment. Additional engineering testing was conducted by constructing hyperspectral sensors using sensors popular in science, technology, engineering and mathematics (STEM) contexts. Engineering and performance metrics of the payload containing the sensors was conducted; and performance of these sensors in relevant analogous environments. A selection of materials exhibiting spectral phenomenology in the red-edge portion of the spectrum was used to produce metrics on the performance of the sensors. It was found that low-cost cameras were able to distinguish between most minerals, although they required a wider spectral range to do so. Additionally, while Raspberry Pi cameras have been popular with scientific applications, a low-cost camera without a Bayer filter markedly improved spectral sensitivity. Consideration for space-environment testing was also trialed in additional experiments using high-altitude balloons to reach the near-space environment. The sensor payloads experienced conditions approximating the surface of Mars, and results were compared with Landsat 7, a heritage Earth sensing satellite, using a popular vegetation index. The selected Raspberry Pi cameras were able to provide useful results from near-space that could be compared with space imagery. Further testing incorporated comparative analysis of custom-built sensors using readily available Raspberry Pi and astronomy cameras, and results from Mastcam and Mastcam/z instruments currently on the surface of Mars. Two sensor designs were trialed in field settings possessing Mars-analogue materials, and a subset of these materials were analysed using a laboratory-grade spectro-radiometer. Results showed the Raspberry Pi multispectral camera would be best suited for broad-scale indications of mineralogy that could be targeted by the pushbroom sensor. This sensor was found to possess a narrower spectral range than the Mastcam and Mastcam/z but was sensitive to a greater number of bands within this range. The pushbroom sensor returned data on spectral phenomenology associated with attributes of Minerals of the type found on Mars. The actual performance of the payload in appropriate conditions was important to provide critical information used to risk reduce future designs. Additionally, the successful outcomes of the trials reduced risk for their application in a deep space environment. The SE and practical performance testing conducted in this thesis could be developed further to design, build and fly a hyperspectral sensor, sensitive to red-edge wavelengths, on a deep-space cubesat mission. Such a mission could be flown at reasonable cost yet return useful scientific and engineering data

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

    Principled methods for mixtures processing

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    This document is my thesis for getting the habilitation à diriger des recherches, which is the french diploma that is required to fully supervise Ph.D. students. It summarizes the research I did in the last 15 years and also provides the short­term research directions and applications I want to investigate. Regarding my past research, I first describe the work I did on probabilistic audio modeling, including the separation of Gaussian and α­stable stochastic processes. Then, I mention my work on deep learning applied to audio, which rapidly turned into a large effort for community service. Finally, I present my contributions in machine learning, with some works on hardware compressed sensing and probabilistic generative models.My research programme involves a theoretical part that revolves around probabilistic machine learning, and an applied part that concerns the processing of time series arising in both audio and life sciences

    Optical Fiber Interferometric Sensors

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    The contributions presented in this book series portray the advances of the research in the field of interferometric photonic technology and its novel applications. The wide scope explored by the range of different contributions intends to provide a synopsis of the current research trends and the state of the art in this field, covering recent technological improvements, new production methodologies and emerging applications, for researchers coming from different fields of science and industry. The manuscripts published in the Special issue, and re-printed in this book series, report on topics that range from interferometric sensors for thickness and dynamic displacement measurement, up to pulse wave and spirometry applications

    Lensless Single-shot Pixel Super-resolution Phase Microscopy

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    This doctoral thesis is dedicated to the development of a mini phase microscope capable of subpixel resolution without using lenses. Instead of lenses, a custom-made diffractive element, a small-pixeled binary phase mask is used along with state-of-the-art phase retrieval-based algorithms to achieve high-resolution reconstruction of complex-valued objects. In phase retrieval, the test object is illuminated by coherent light source, which changes depending on the object’s characteristics. From this diffracted intensity pattern captured by the sensor a complex wavefront is reconstructable. Although, it is an ill-posed problem, since the traditional sensors can capture only the intensity of the light radiation, while the phase is in invisible range. Moreover, the scheme is in-line therefore, the pattern will result in several overlapping diffraction orders. The overlapping images and the ill-posedness make the reconstruction from the diffraction patterns challenging. Most methods provided by the literature try to solve this problem by registering several decorrelated diffraction patterns on the sensor – with a so-called multi-exposure method. Contrary to those techniques, the first contribution of the thesis is the development of a single-exposure approach for phase retrieval using lensless wavefront modulation. The modulation is achieved by a single random binary phase mask positioned between the object and the sensor. The second contribution of the thesis is an optical system design for the proposed algorithm to achieve super-resolution reconstruction. The system design includes the investigation of the system parameters, like distance tuning, noise-influence analysis, and modulation mask selection. The third contribution of the thesis is a novel approach based on wavefront separation to further reduce the appearing noises and enhance the resolving power. We computationally separated the carrying and objects’ wavefronts, which was not considered before. The performance of the novel approach and algorithm is demonstrated in simulations and physical experiments. We report an experimental computational super-resolution of 2um lines of USAF phase target, which is 3.45x smaller than the resolution following from the Nyquist-Shannon sampling theorem for used camera pixel size 3.45um. To the best of our knowledge, the 2um resolution is beyond the state-of-the-art resolution for single-shot phase retrieval techniques reported so far, even with lens configurations

    Reconstruction from Spatio-Spectrally Coded Multispectral Light Fields

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    In dieser Arbeit werden spektral codierte multispektrale Lichtfelder, wie sie von einer Lichtfeldkamera mit einem spektral codierten Mikrolinsenarray aufgenommen werden, untersucht. Für die Rekonstruktion der codierten Lichtfelder werden zwei Methoden entwickelt und im Detail ausgewertet. Zunächst wird eine vollständige Rekonstruktion des spektralen Lichtfelds entwickelt, die auf den Prinzipien des Compressed Sensing basiert. Um die spektralen Lichtfelder spärlich darzustellen, werden 5D-DCT-Basen sowie ein Ansatz zum Lernen eines Dictionary untersucht. Der konventionelle vektorisierte Dictionary-Lernansatz wird auf eine tensorielle Notation verallgemeinert, um das Lichtfeld-Dictionary tensoriell zu faktorisieren. Aufgrund der reduzierten Anzahl von zu lernenden Parametern ermöglicht dieser Ansatz größere effektive Atomgrößen. Zweitens wird eine auf Deep Learning basierende Rekonstruktion der spektralen Zentralansicht und der zugehörigen Disparitätskarte aus dem codierten Lichtfeld entwickelt. Dabei wird die gewünschte Information direkt aus den codierten Messungen geschätzt. Es werden verschiedene Strategien des entsprechenden Multi-Task-Trainings verglichen. Um die Qualität der Rekonstruktion weiter zu verbessern, wird eine neuartige Methode zur Einbeziehung von Hilfslossfunktionen auf der Grundlage ihrer jeweiligen normalisierten Gradientenähnlichkeit entwickelt und gezeigt, dass sie bisherige adaptive Methoden übertrifft. Um die verschiedenen Rekonstruktionsansätze zu trainieren und zu bewerten, werden zwei Datensätze erstellt. Zunächst wird ein großer synthetischer spektraler Lichtfelddatensatz mit verfügbarer Disparität Ground Truth unter Verwendung eines Raytracers erstellt. Dieser Datensatz, der etwa 100k spektrale Lichtfelder mit dazugehöriger Disparität enthält, wird in einen Trainings-, Validierungs- und Testdatensatz aufgeteilt. Um die Qualität weiter zu bewerten, werden sieben handgefertigte Szenen, so genannte Datensatz-Challenges, erstellt. Schließlich wird ein realer spektraler Lichtfelddatensatz mit einer speziell angefertigten spektralen Lichtfeldreferenzkamera aufgenommen. Die radiometrische und geometrische Kalibrierung der Kamera wird im Detail besprochen. Anhand der neuen Datensätze werden die vorgeschlagenen Rekonstruktionsansätze im Detail bewertet. Es werden verschiedene Codierungsmasken untersucht -- zufällige, reguläre, sowie Ende-zu-Ende optimierte Codierungsmasken, die mit einer neuartigen differenzierbaren fraktalen Generierung erzeugt werden. Darüber hinaus werden weitere Untersuchungen durchgeführt, zum Beispiel bezüglich der Abhängigkeit von Rauschen, der Winkelauflösung oder Tiefe. Insgesamt sind die Ergebnisse überzeugend und zeigen eine hohe Rekonstruktionsqualität. Die Deep-Learning-basierte Rekonstruktion, insbesondere wenn sie mit adaptiven Multitasking- und Hilfslossstrategien trainiert wird, übertrifft die Compressed-Sensing-basierte Rekonstruktion mit anschließender Disparitätsschätzung nach dem Stand der Technik
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