Image Simulation in Remote Sensing

Remote sensing is being actively researched in the fields of environment, military and urban planning through technologies such as monitoring of natural climate phenomena on the earth, land cover classification, and object detection. Recently, satellites equipped with observation cameras of various resolutions were launched, and remote sensing images are acquired by various observation methods including cluster satellites. However, the atmospheric and environmental conditions present in the observed scene degrade the quality of images or interrupt the capture of the Earth's surface information. One method to overcome this is by generating synthetic images through image simulation. Synthetic images can be generated by using statistical or knowledge-based models or by using spectral and optic-based models to create a simulated image in place of the unobtained image at a required time. Various proposed methodologies will provide economical utility in the generation of image learning materials and time series data through image simulation. The 6 published articles cover various topics and applications central to Remote sensing image simulation. Although submission to this Special Issue is now closed, the need for further in-depth research and development related to image simulation of High-spatial and spectral resolution, sensor fusion and colorization remains.I would like to take this opportunity to express my most profound appreciation to the MDPI Book staff, the editorial team of Applied Sciences journal, especially Ms. Nimo Lang, the assistant editor of this Special Issue, talented authors, and professional reviewers

Journal of Telecommunications and Information Technology

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Infrared and visible image fusion with edge detail implantation

Infrared and visible image fusion aims to integrate complementary information from the same scene images captured by different types of sensors into one image to obtain a fusion image with richer information. Recently, deep learning-based infrared and visible image fusion methods have been widely used. However, it is still a difficult problem how to maintain the edge detail information in the source images more effectively. To address this problem, we propose a novel infrared and visible image fusion method with edge detail implantation. The proposed method no longer improves the performance of edge details in the fused image through making the extracted features contain edge detail information like traditional methods, but by processing source image information and edge detail information separately, and supplementing edge details to the main framework. Technically, we propose a two-branch feature representation framework. One branch is used to directly extract features from the input source image, while the other is utilized to extract features of edge map. The edge detail branch mainly provides edge detail features for the source image input branch, ensuring that the output features contain rich edge detail information. In the fusion of multi-source features, we respectively fuse the source image features and the edge detail features, and use the fusion results of edge details to guide and enhance the fusion results of source image features so that they contain richer edge detail information. A large number of experimental results demonstrate the effectiveness of the proposed method

Field Programmable Gate Arrays (FPGAs) II

This Edited Volume Field Programmable Gate Arrays (FPGAs) II is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Computer and Information Science. The book comprises single chapters authored by various researchers and edited by an expert active in the Computer and Information Science research area. All chapters are complete in itself but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on Computer and Information Science, and open new possible research paths for further novel developments

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

Most systematic reviews are retrospective and use aggregate data AD) from publications, meaning they can be unreliable, lag behind therapeutic developments and fail to influence ongoing or new trials. Commonly, the potential influence of unpublished or ongoing trials is overlooked when interpreting results, or determining the value of updating the meta-analysis or need to collect individual participant data (IPD). Therefore, we developed a Framework for Adaptive Metaanalysis (FAME) to determine prospectively the earliest opportunity for reliable AD meta-analysis. We illustrate FAME using two systematic reviews in men with metastatic (M1) and non-metastatic (M0)hormone-sensitive prostate cancer (HSPC)

Cold-Atom Loading of Hollow-Core Photonic Crystal Fibre for Quantum Technologies

Ultra-strong light-atom interaction is a key resource for numerous applications in quantum-information processing, nonlinear optics, and quantum sensing. Maximising the strength of the interaction requires optimising the combination of light-atom coherent interaction time, spatial overlap between the optical mode and the atomic cross section, and the number of participating atoms. An exciting approach to achieving these goals is to use a collection of laser-cooled atoms inside a hollow-core photonic crystal fibre. Here the tight transverse confinement provided by fibre guarantees overlap between the atomic sample and guided optical modes over an arbitrarily long distance. Laser cooling improves the effective atom number of the sample by increasing the fraction that participate in the interaction and significantly improves the coherent interaction time by reducing the spatial decoherence rate of the ensemble. This project focuses around the development of an apparatus that realises the lasercooling, trapping, and loading of atoms into a kagome-lattice hollow-core fibre. In this thesis we describe the development of the elements required to realise this task, including the vacuum system, laser sources, computer oversight, and theoretical models employed. The resulting platform is capable of achieving the ultra-high optical depths required for exciting quantum-optics applications such as long-lived coherent optical pulse storage. We have demonstrated high-efficiency transport of cold rubidium atoms from a magneto-optical trap into a hollow-core fibre, measuring a peak optical depth of 600 with only 3£106 atoms. These experiments were guided by a Monte-Carlo simulation that has been shown to have excellent agreement with the physical system. The results show that this platform is in an excellent position to investigate coherent optical phenomena at the few-photon level. Along the way we investigated the application of light-shift engineering to both measure and compensate for the perturbative effects the strong light fields present in the experiment have on atomic states. We extend the ‘magic-wavelength’ technique used in the atomic lattice clock community to nullify the lineshape broadening of the target ensemble by introducing an additional light field. This allows the technique to be implemented in a broad range of atomic species and transitions, where the original technique was only accessible for limited species with specific energy-level structures. We also take advantage of light-shift engineering to extract a detailed model of the spatial distribution of an optically-trapped ensemble through a simple spectroscopic technique. We use this model to infer the temperature, coherence time, and number of atoms in the trap in addition to the depth of the trap itself. Experimentally we demonstrate this on our cold-atom-filled fibre platform, showing that this information can be extracted from a system with limited optical access and where conventional techniques cannot be applied. The apparatus and experimental techniques we have developed place this project in an excellent position to perform cutting-edge research in the fields of quantum information processing and nonlinear optics.Thesis (Ph.D.) -- University of Adelaide, School of Physical Sciences, 202

Commissioning of the tracking system in the ATLAS detector

ATLAS is one of the four experiments that will analyze the p-p collisions at LHC. It consists of several subsystems: the Inner Detector is devoted to the measurement of the charged particle tracks in the interaction point region and the Pixel Detector is its innermost component. Both have been commissioned by using cosmic rays collected by the ATLAS detector in 2009. In the first part of the thesis, the spatial resolution of the Pixel Detector is studied and optimized. When a charged particle traverses the Pixel Detector, charges released in the sensors are collected by segmented electrodes, the pixels. The charge of each pixel is read out by the Time-over-Threshold technique and adjacent pixels are grouped into clusters. Cluster position can be computed by considering its geometrical center, but spatial resolution can be optimized if using charge information to improve position determination. In the second part of the thesis, the Inner Detector resolution in all track parameters has been studied by splitting each cosmic ray track into two halves. Since both halves stem from the same particle, they should be described by the same parameters. At the same time, the two tracks are fitted independently and can be compared to study the resolution of the tracking system. Resolution been studied as a function of track direction and distance from the beam axis. The multiple scattering contribution and several systematic effects due to residual misalignments have been evaluated

Carbon Nano Tubes (CNTS) for the development of high-performance and smart composites.

Los nanotubos de carbono han atraído una enorme atención en los últimos años debido a sus propiedades multifuncionales sobresalientes. Un número cada vez mayor de trabajos de investigación de primera línea centran su interés en la búsqueda de aplicaciones prácticas que den uso de las notables propiedades de los nanotubos de carbono, incluyendo una elevada resistencia mecánica, propiedades piezorestivas, alta conductividad eléctrica, ligereza, excelente estabilidad química y térmica. En concreto, los estudios más recientes plantean dos grandes ramas de aplicación: fabricación de estructuras aligeradas de alta resistencia, y desarrollo de estructuras inteligentes. Con respecto a la primera línea de aplicación, el desarrollo de materiales compuestos ligeros de alta resistencia conecta con la creciente tendencia de la ingeniería estructural a incorporar materiales compuestos innovadores. Ejemplos recientes como el avión comercial Boeing 787, en el que la mitad del peso fue diseñado con materiales compuestos, predicen un futuro auspicioso para los nanotubos de carbono en la ingeniería aeronáutica. Sin embargo, aún resulta más interesante el comportamiento piezorresistivo de los compuestos reforzados con nanotubos de carbono, ya que posibilita la creación de estructuras que no sólo presentan altas capacidades portantes y reducido peso específico, sino que también ofrecen capacidades de auto-detección de deformaciones. Cuando el material se ve sometido a una deformación externa, en virtud de dicha propiedad piezoresistiva, la conductividad eléctrica varía de modo que es posible correlacionar su respuesta eléctrica con el campo deformacional aplicado. Estas propiedades multifuncionales entroncan con el nuevo paradigma de la Vigilancia de la Salud Estructural el cual aboga por el uso de materiales/estructuras inteligentes para resolver el problema de escalabilidad. En este contexto, la estructura o parte de ella presenta capacidades de auto-detección de tal manera que el mantenimiento basado en la condición puede llevarse a cabo sin necesidad de incluir sensores externos. En ambas líneas, la mayoría de las investigaciones han centrado el estudio en la experimentación, siendo mucho menor el número de trabajos que plantean modelos teóricos capaces de simular las propiedades mecánicas, eléctricas y electromecánicas de estos compuestos. Desde un punto de vista mecánico, existen estudios experimentales que informan acerca de los efectos perjudiciales sobre la respuesta macroscópica de aspectos micromecánicos tales como la tendencia a formar aglomerados, así como la curvatura de los nanotubos de carbono. Es por ello esencial desarrollar modelos teóricos que incorporen estos efectos y asistan al diseño de elementos estructurales reforzados con nanotubos de carbono. Respecto al estudio de las propiedades de conductividad y piezoresistividad, es esencial desarrollar formulaciones teóricas capaces de abordar la optimización de las propiedades de autodetección de deformaciones. Asimismo, es crucial comprender los diferentes mecanismos físicos que rigen la conductividad eléctrica de estos compuestos, de modo que sea posible incorporar su efecto diferencial dentro de un marco teórico. Por último, también es fundamental avanzar hacia el dominio del tiempo con el fin de desarrollar aplicaciones de vigilancia de la salud estructural basada en vibraciones. Con todo ello, los esfuerzos de esta tesis se han centrado en el modelado de las propiedades mecánicas, conductivas y electromecánicas de los compuestos reforzados con nanotubos de carbono para el desarrollo de estructuras inteligentes y de alta resistencia. Estas dos aplicaciones, a saber, compuestos de alta resistencia e inteligentes, han sido enmarcadas en el ámbito de los materiales poliméricos y de cemento, respectivamente. La razón de esta distinción se debe a la presunción de que los compuestos poliméricos pueden encontrar aplicaciones directas como paneles de fuselaje para estructuras de aeronaves, así como refuerzos mecánicos sobre estructuras pre-existentes. En cuanto al uso de nanotubos de carbono como inclusiones multifuncionales para compuestos inteligentes, tanto los materiales poliméricos como los de base cemento ofrecen una amplia gama de aplicaciones potenciales. Sin embargo, la similitud entre los compuestos de base cemento y el hormigón estructural convencional sugiere la idea de desarrollar sensores embebidos que ofrezcan una monitorización continua integrada sin comprometer a priori la durabilidad de la estructura huésped. Tanto las propiedades mecánicas como las conductivas han sido estudiadas mediante métodos de homogeneización de campo medio. Aspectos micromecánicos tales como la relación de aspecto, el contenido, la distribución de la orientación, la ondulación o la aglomeración de los nanotubos se han estudiado en detalle e incorporado al análisis de diferentes elementos estructurales. De manera similar, se han estudiado las propiedades de conductividad eléctrica y auto-detección de deformaciones bajo cargas cuasi-estáticas mediante modelos mixtos de homogenización micromecánica de Mori-Tanaka. Los principales mecanismos que gobiernan las propiedades de transporte eléctrico de estos compuestos, a saber, los efectos de túnel cuántico y la formación de canales conductores, se han incorporado por separado en las simulaciones a través de la teoría de percolación de fibras conductoras. Los resultados teóricos han sido validados con éxito mediante experimentos en condiciones de laboratorio. Finalmente, se ha desarrollado un nuevo circuito equivalente piezorresistivo/piezoeléctrico para el modelado electromecánico de materiales de base cemento reforzado con nanotubos de carbono en el dominio del tiempo. Con los experimentos como base de validación, se ha demostrado que el enfoque propuesto proporciona resultados precisos y ofrece un marco teórico apto para aplicaciones de procesamiento de señales y monitorización de la salud estructural. Se espera que el trabajo desarrollado en esta tesis pueda proporcionar herramientas valiosas que permitan profundizar en la comprensión de los principales aspectos físicos que controlan las propiedades mecánicas, eléctricas y electromecánicas de los compuestos reforzados con nanotubos de carbono. Además, se espera que los resultados presentados en esta tesis impulsen el desarrollo de materiales compuestos auto-sensibles embebidos para aplicaciones de vigilancia de la salud estructural.Carbon nanotubes have drawn enormous attention in recent years due to their outstanding multifunctional properties. A constantly growing number of works at the front line of research pursue potential applications of their remarkable physical properties, including elevated load-bearing capacity, piezoresistive properties, high electrical conductivity, lightness, and excellent chemical and thermal stability. In particular, most recent works contemplate two different application branches: manufacture of light-weight high-strength structures, and development of smart structures. With regard to the first line of application, the development of high-strength lightweight composites connects with the growing tendency of structural engineering to incorporate advanced composite materials. Recent noticeable examples such as the commercial aircraft Boeing 787, in which half of the total weight was designed with composite materials, predict an auspicious future for carbon nanotubes in aircraft structures. Nonetheless, what is even more interesting is the piezoresistive behavior of carbon nanotube-reinforced composites, which allows us to create structures that are not only high-strength and lightweight but also strain-sensitive. When the composites are subjected to external strain fields, in virtue of such piezoresistive properties, the overall electrical conductivity varies in such a way that it is possible to correlate the electrical response with the deformational state of the material. These multifunctional properties are in line with the new paradigm of Structural Health Monitoring which advocates the use of smart materials/structures to solve the scalability issue. In this context, the structure or part of it presents self-sensing capabilities in such a way that the condition-based maintenance can be conducted without necessitating external off-the-shelf sensors. In both lines, most investigations have focused on experimentation. Conversely, the number of theoretical models capable of simulating the mechanical, electrical, and electromechanical properties of these composites is still scarce. From a mechanical point of view, experiments have reported about the detrimental effects of micromechanical aspects such as agglomeration of fillers and curviness on the macroscopic properties. Hence, it is essential to develop theoretical models that allow us to include these effects and assist the design of composite structural elements. With regard to the study of the conductivity and piezoresistivity of carbon nanotube-reinforced composites, it is essential to develop theoretical formulations capable of tackling the optimization of their strain sensitivity. In addition, it is crucial to understand the different physical mechanisms that govern the electrical conductivity of these composites and include them separately in the theoretical framework. Finally, it is also fundamental to move towards the time domain in order to develop applications for vibration-based structural health monitoring. Overall, all the efforts of this thesis have been put into the modeling of the mechanical, conductive and electromechanical properties of carbon nanotube-reinforced composites for the development of high-strength and smart structures. These two applications, namely high-strength and smart composites, have been framed in the realm of polymeric and cement-based materials, respectively. The reason for this distinction is the idea that polymer composites with high load-bearing capacity can find direct applications as fuselage panels for aircraft structures, as well as mechanical reinforcements attached to pre-existing structures. With regard to the use of carbon nanotubes as fillers for smart composites, both polymer and cement-based materials offer an enormous range of potential applications. Nonetheless, the similarity between cement-based composites and regular structural concrete suggests the idea of developing continuous embedded monitoring systems without compromising the durability of the hosting structure a priori. Both mechanical and conductive properties have been studied by means of mean-field homogenization methods. Micromechanical aspects such as filler aspect ratio, content, orientation distribution, waviness or agglomeration have been studied in detail and incorporated to the analysis of different structural elements. Similarly, the electrical conductivity and strain-sensing properties of these composites under quasi-static loadings have been studied by means of mixed Mori-Tanaka micromechanics models. The main mechanisms that underlie the electrical conduction of these composites, namely quantum tunneling effects and conductive networks, have been distinguished by a percolative-type behavior. The theoretical results have been successfully validated by means of experiments under laboratory conditions. Finally, a novel piezoresistive/piezoelectric equivalent lumped circuit has been developed for the electromechanical modeling of carbon nanotube-reinforced cement-based materials in the time domain. With experiments as validating basis, the proposed approach has been shown to provide accurate results and offers a theoretical framework readily applicable to signal processing applications and structural health monitoring. The work developed in this thesis is envisaged to provide valuable tools to further the understanding of the main physical aspects that control the mechanical, electrical and electromechanical properties of composites doped with carbon nanotubes. Furthermore, it is expected to boost the development of embedded self-sensing carbon nanotube-reinforced composites for structural health monitoring applications.Premio Extraordinario de Doctorado U

Commissioning of the tracking system in the ATLAS detector

ATLAS is one of the four experiments that will analyze the p-p collisions at LHC. It consists of several subsystems: the Inner Detector is devoted to the measurement of the charged particle tracks in the interaction point region and the Pixel Detector is its innermost component. Both have been commissioned by using cosmic rays collected by the ATLAS detector in 2009. In the first part of the thesis, the spatial resolution of the Pixel Detector is studied and optimized. When a charged particle traverses the Pixel Detector, charges released in the sensors are collected by segmented electrodes, the pixels. The charge of each pixel is read out by the Time-over-Threshold technique and adjacent pixels are grouped into clusters. Cluster position can be computed by considering its geometrical center, but spatial resolution can be optimized if using charge information to improve position determination. In the second part of the thesis, the Inner Detector resolution in all track parameters has been studied by splitting each cosmic ray track into two halves. Since both halves stem from the same particle, they should be described by the same parameters. At the same time, the two tracks are fitted independently and can be compared to study the resolution of the tracking system. Resolution been studied as a function of track direction and distance from the beam axis. The multiple scattering contribution and several systematic effects due to residual misalignments have been evaluated