Ultraviolet optical and microstructural properties of MgF2 and LaF3 coatings deposited by ion-beam sputtering and boat and electron-beam evaporation

Single layers of MgF2 and LaF3 were deposited upon superpolished fused-silica and CaF2 substrates by ion-beam sputtering (IBS) as well as by boat and electron beam (e-beam) evaporation and were characterized by a variety of complementary analytical techniques. Besides undergoing photometric and ellipsometric inspection, the samples were investigated at 193 and 633 nm by an optical scatter measurement facility. The structural properties were assessed with atomic-force microscopy, x-ray diffraction, TEM techniques that involved conventional thinning methods for the layers. For measurement of mechanical stress in the coatings, special silicon substrates were coated and analyzed. The dispersion behavior of both deposition materials, which was determined on the basis of various independent photometric measurements and data reduction techniques, is in good agreement with that published in the literature and with the bulk properties of the materials. The refractive indices of the MgF2 coatings ranged from 1.415 to 1.440 for the wavelength of the ArF excimer laser (193 nm) and from 1.435 to 1.465 for the wavelength of the F2 excimer laser (157 nm). For single layers of LaF3 the refractive indices extended from 1.67 to 1.70 at 193 nm to ~1.80 at 157 nm. The IBS process achieves the best homogeneity and the lowest surface roughness values (close to 1 nmrms) of the processes compared in the joint experiment. In contrast to MgF2 boat and e-beam evaporated coatings, which exhibit tensile mechanical stress ranging from 300 to 400 MPa, IBS coatings exhibit high compressive stress of as much as 910 MPa. A similar tendency was found for coating stress in LaF3 single layers. Experimental results are discussed with respect to the microstructural and compositional properties as well as to the surface topography of the coatings.

Deep GMRT radio observations and a multi-wavelength study of the region around HESS J1858+020

Context. There are a number of very high energy sources in the Galaxy that remain unidentified. Multi-wavelength and variability studies, and catalogue searches, are powerful tools to identify the physical counterpart, given the uncertainty in the source location and extension. Aims. This work carries out a thorough multi-wavelength study of the unidentified, very high energy source HESS J1858+020 and its environs. Methods. We have performed Giant Metrewave Radio Telescope observations at 610 MHz and 1.4 GHz to obtain a deep, low-frequency radio image of the region surrounding HESS J1858+020. We analysed archival radio, infrared, and X-ray data as well. This observational information, combined with molecular data, catalogue sources, and a nearby Fermi gamma-ray detection of unidentified origin, are combined to explore possible counterparts to the very high energy source. Results. We provide with a deep radio image of a supernova remnant that might be related to the GeV and TeV emission in the region. We confirm the presence of an H ii region next to the supernova remnant and coincident with molecular emission. A potential region of star formation is also identified. We identify several radio and X-ray sources in the surroundings. Some of these sources are known planetary nebulae, whereas others may be non-thermal extended emitters and embedded young stellar objects. Three old, background Galactic pulsars also neighbour HESS J1858+020 along the line of sight. Conclusions. The region surrounding HESS J1858+020 is rich in molecular structures and non-thermal objects that may potentially be linked to this unidentified very high energy source. In particular, a supernova remnant interacting with nearby molecular clouds may be a good candidate, but a star forming region, or a non-thermal radio source of yet unclear nature, may also be behind the gamma-ray source. The neighbouring pulsars, despite being old and distant, cannot be discarded as candidates. Further observational studies are needed, however, to narrow the search for a counterpart to the HESS source.

Scene classifier for real time road detection

L’objectiu principal del projecte és el de classificar escenes de carretera en funció del contingut de les imatges per així poder fer un desglossament sobre quin tipus de situació tenim en el moment. És important que fixem els paràmetres necessaris en funció de l’escenari en què ens trobem per tal de treure el màxim rendiment possible a cada un dels algoritmes. La seva funcionalitat doncs, ha de ser la d’avís i suport davant els diferents escenaris de conducció. És a dir, el resultat final ha de contenir un algoritme o aplicació capaç de classificar les imatges d’entrada en diferents tipus amb la màxima eficiència espacial i temporal possible. L’algoritme haurà de classificar les imatges en diferents escenaris. Els algoritmes hauran de ser parametritzables i fàcilment manejables per l’usuari. L’eina utilitzada per aconseguir aquests objectius serà el MATLAB amb les toolboxs de visió i xarxes neuronals instal·lades.

Intestinal content detection in capsule endoscopy using robust features

This work covers two aspects. First, it generally compares and summarizes the similarities and differences of state of the art feature detector and descriptor and second it presents a novel approach of detecting intestinal content (in particular bubbles) in capsule endoscopy images. Feature detectors and descriptors providing invariance to change of perspective, scale, signal-noise-ratio and lighting conditions are important and interesting topics in current research and the number of possible applications seems to be numberless. After analysing a selection of in the literature presented approaches, this work investigates in their suitability for applications information extraction in capsule endoscopy images. Eventually, a very good performing detector of intestinal content in capsule endoscopy images is presented. A accurate detection of intestinal content is crucial for all kinds of machine learning approaches and other analysis on capsule endoscopy studies because they occlude the field of view of the capsule camera and therefore those frames need to be excluded from analysis. As a so called “byproduct” of this investigation a graphical user interface supported Feature Analysis Tool is presented to execute and compare the discussed feature detectors and descriptor on arbitrary images, with configurable parameters and visualized their output. As well the presented bubble classifier is part of this tool and if a ground truth is available (or can also be generated using this tool) a detailed visualization of the validation result will be performed.

Sistemes lidar (radar laser) d'ona contínua i baixa potència per a la detecció i mesura de concentració de gasos amb resolució espacial

The present project has performed the study and development of a new technique for the detection of gases with range resolution. This technique called FMCW-lidar is a technique that evolves from the FMCW-radar technique to be applied to lidar systems. Moreover, it takes advantage of the appearance of spectral absorption lines because of the interaction between light and gases to tune the light wavelength of a laser emitter with one of this spectral lines and then detects the backscattered light and analyzes it in order to obtain gas concentration measurements. The first part of the project consisted in the analysis of the WMS technique which is a technique for the in-situ measurement of gases. A complete theoretical analysis has been performed and some experiments have been carried out in order to test the technique and to validate its application to an FMCW-modulated system for the detection of gases. The second part of the project consisted in the analysis of the lidar FMCW technique for solid target detection and its extension to continuous media. The classical form of this technique has been analyzed for a distributed medium and a filtering effect has been found which prevents the accurate acquisition of the medium response. A modification of the technique has been proposed and a validation via simulations and some experiments has been carried on. After performing these tests, a novel system is proposed to be developed and tested in order to perform the indicated gas detection with range resolution.

Evaluation of detection methods for Virus, Viroids and Phytoplasmas affecting pear and apple

The RT-PCR technique for the detection of apple stem grooving virus (ASGV), apple stem pitting virus (ASPV), apple chlorotic leaf spot virus (ACLSV), apple mosaic virus (ApMV) and pear blister canker viroid (PBCV) was evaluated for health control of fruit plants from nurseries. The technique was evaluated in purified RNA and crude extracts and also in phloem collected in autumn and from young spring shoots. The results obtained for phytoplasma detection with ribosomal and non-ribosomal primers are also presented.

Detection of matchings in a sequence of underwater images through texture analysis

This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions

GNSS signal detection based on first-order absolute statistics

Aquest projecte es centra principalment en el detector no coherent d’un GPS. Per tal de caracteritzar el procés de detecció d’un receptor, es necessita conèixer l’estadística implicada. Pel cas dels detectors no coherents convencionals, l’estadística de segon ordre intervé plenament. Les prestacions que ens dóna l’estadística de segon ordre, plasmada en la ROC, són prou bons tot i que en diferents situacions poden no ser els millors. Aquest projecte intenta reproduir el procés de detecció mitjançant l’estadística de primer ordre com a alternativa a la ja coneguda i implementada estadística de segon ordre. Per tal d’aconseguir-ho, s’usen expressions basades en el Teorema Central del Límit i de les sèries Edgeworth com a bones aproximacions. Finalment, tant l’estadística convencional com l’estadística proposada són comparades, en termes de la ROC, per tal de determinar quin detector no coherent ofereix millor prestacions en cada situació.

Unusual voltage sag event detection in power systems

Three multivariate statistical tools (principal component analysis, factor analysis, analysis discriminant) have been tested to characterize and model the sags registered in distribution substations. Those models use several features to represent the magnitude, duration and unbalanced grade of sags. They have been obtained from voltage and current waveforms. The techniques are tested and compared using 69 registers of sags. The advantages and drawbacks of each technique are listed

Modelling of Mercury’s surface composition and remote detection from the orbit with the BepiColombo Mercury Planetary Orbiter

It can be assumed that the composition of Mercury’s thin gas envelope (exosphere) is related to thecomposition of the planets crustal materials. If this relationship is true, then inferences regarding the bulkchemistry of the planet might be made from a thorough exospheric study. The most vexing of allunsolved problems is the uncertainty in the source of each component. Historically, it has been believedthat H and He come primarily from the solar wind, while Na and K originate from volatilized materialspartitioned between Mercury’s crust and meteoritic impactors. The processes that eject atoms andmolecules into the exosphere of Mercury are generally considered to be thermal vaporization, photonstimulateddesorption (PSD), impact vaporization, and ion sputtering. Each of these processes has its owntemporal and spatial dependence. The exosphere is strongly influenced by Mercury’s highly ellipticalorbit and rapid orbital speed. As a consequence the surface undergoes large fluctuations in temperatureand experiences differences of insolation with longitude. We will discuss these processes but focus moreon the expected surface composition and solar wind particle sputtering which releases material like Caand other elements from the surface minerals and discuss the relevance of composition modelling

alr approach for replacing values below the detection limit

All of the imputation techniques usually applied for replacing values below thedetection limit in compositional data sets have adverse effects on the variability. In thiswork we propose a modification of the EM algorithm that is applied using the additivelog-ratio transformation. This new strategy is applied to a compositional data set and theresults are compared with the usual imputation techniques