A Small Baseline DIFSAR Approach for Investigating Deformations on Full Resolution SAR Interferograms

This paper presents a differential synthetic apertureradar (SAR) interferometry (DIFSAR) approach for investigatingdeformation phenomena on full-resolution DIFSAR interferograms.In particular, our algorithm extends the capabilityof the small-baseline subset (SBAS) technique that relies onsmall-baseline DIFSAR interferograms only and is mainly focusedon investigating large-scale deformations with spatial resolutionsof about 100 100 m. The proposed technique is implemented byusing two different sets of data generated at low (multilook data)and full (single-look data) spatial resolution, respectively. Theformer is used to identify and estimate, via the conventional SBAStechnique, large spatial scale deformation patterns, topographicerrors in the available digital elevation model, and possibleatmospheric phase artifacts; the latter allows us to detect, onthe full-resolution residual phase components, structures highlycoherent over time (buildings, rocks, lava, structures, etc.), as wellas their height and displacements. In particular, the estimation ofthe temporal evolution of these local deformations is easily implementedby applying the singular value decomposition technique.The proposed algorithm has been tested with data acquired by theEuropean Remote Sensing satellites relative to the Campania area(Italy) and validated by using geodetic measurements.

Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR)

Interferometric synthetic aperture radar (InSAR) techniques can successfully detect phase variations related to the water level changes in wetlands and produce spatially detailed high-resolution maps of water level changes. Despite the vast details, the usefulness of the wetland InSAR observations is rather limited, because hydrologists and water resources managers need information on absolute water level values and not on relative water level changes. We present an InSAR technique called Small Temporal Baseline Subset (STBAS) for monitoring absolute water level time series using radar interferograms acquired successively over wetlands. The method uses stage (water level) observation for calibrating the relative InSAR observations and tying them to the stage's vertical datum. We tested the STBAS technique with two-year long Radarsat-1 data acquired during 2006–2008 over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). The InSAR-derived water level data were calibrated using 13 stage stations located in the study area to generate 28 successive high spatial resolution maps (50 m pixel resolution) of absolute water levels. We evaluate the quality of the STBAS technique using a root mean square error (RMSE) criterion of the difference between InSAR observations and stage measurements. The average RMSE is 6.6 cm, which provides an uncertainty estimation of the STBAS technique to monitor absolute water levels. About half of the uncertainties are attributed to the accuracy of the InSAR technique to detect relative water levels. The other half reflects uncertainties derived from tying the relative levels to the stage stations' datum.

Large slope deformations detection and monitoring along shores of the Potrerillos dam reservoir, Argentina, based on a small-baseline InSAR approach

The Argentina National Road 7 that crosses the Andes Cordillera within the Mendoza province to connect Santiago de Chile and Buenos Aires is particularly affected by natural hazards requiring risk management. Integrated in a research plan that intends to produce landslide susceptibility maps, we aimed in this study to detect large slope movements by applying a satellite radar interferometric analysis using Envisat data, acquired between 2005 and 2010. We were finally able to identify two large slope deformations in sandstone and clay deposits along gentle shores of the Potrerillos dam reservoir, with cumulated displacements higher than 25mm in 5years and towards the reservoir. There is also a body of evidences that these large slope deformations are actually influenced by the seasonal reservoir level variations. This study shows that very detailed information, such as surface displacements and above all water level variation, can be extracted from spaceborne remote sensing techniques; nevertheless, the limitations of InSAR for the present dataset are discussed here. Such analysis can then lead to further field investigations to understand more precisely the destabilising processes acting on these slope deformations.

Analisi dei fenomeni franosi lenti nell'abitato di Gaggio Montano mediante interferometria radar

I movimenti lenti delle colate in terra sono una caratteristica geomorfologica comune nell’Appennino settentrionale e sono uno dei principali agenti di modellazione del paesaggio. Spesso case e piccoli centri abitati sorgono in zone affette da questo tipo di movimento franoso e di conseguenza subiscono danni causati da piccoli spostamenti. In questo lavoro di Tesi vengono presentati i risultati ottenuti dall’interferometria radar ad apertura sintetica (InSAR) mediante elaborazione tramite StaMPS (Stanford Method of Persistent Scatterers), utilizzando la tecnica avanzata Small Baseline Subset (Berardino et al., 2002). Questo metodo informatico è applicato alle acquisizioni rilevate dai satelliti Envisat e COSMO-SkyMed in orbita ascendente e discendente, ottenendo una copertura di dati che va dal 2004 al 2015, oltre ad un rilevamento geologico-geomorfologico in dettaglio eseguito nell’area di studio. Questa tecnica di telerilevamento è estremamente efficace per il monitoraggio dei fenomeni di deformazione millimetrica che persistono sulla superficie terrestre, basata sull'impiego di serie temporali d’immagini radar satellitari (Ferretti et al., 2000). Lo studio è stato realizzato nel paese di Gaggio Montano nell’Appennino bolognese. In questa zona sono stati identificati diversi corpi di frana che si muovono con deformazioni costanti durante il tempo di investigazione e grazie ai risultati ottenuti dai satelliti è possibile confrontare tale risultato. Gli spostamenti misurati con il metodo InSAR sono dello stesso ordine di grandezza dei movimenti registrati dai sondaggi inclinometrici. Le probabili cause dell’instabilità di versante a Gaggio Montano sono di natura antropica, in quanto alti tassi di deformazione sono presenti nelle zone dove sorgono case di recente costruzione e complessi industriali. Un’altra plausibile spiegazione potrebbe essere data dalla ricarica costante d’acqua, proveniente dagli strati dei Flysch verso l’interno del complesso caotico sottostante, tale dinamica causa un aumento della pressione dell’acqua nelle argille e di conseguenza genera condizioni d’instabilità sul versante. Inoltre, i depositi franosi rilevati nell’area di studio non mostrano nessun tipo di variazione dovuta ad influenze idrologiche. Per questo motivo le serie temporali analizzare tendo ad essere abbastanza lineari e costanti nel tempo, non essendo influenzate da cicli stagionali.

Evaluation of steroidomics by liquid chromatography hyphenated to mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations.

This review presents the evolution of steroid analytical techniques, including gas chromatography coupled to mass spectrometry (GC-MS), immunoassay (IA) and targeted liquid chromatography coupled to mass spectrometry (LC-MS), and it evaluates the potential of extended steroid profiles by a metabolomics-based approach, namely steroidomics. Steroids regulate essential biological functions including growth and reproduction, and perturbations of the steroid homeostasis can generate serious physiological issues; therefore, specific and sensitive methods have been developed to measure steroid concentrations. GC-MS measuring several steroids simultaneously was considered the first historical standard method for analysis. Steroids were then quantified by immunoassay, allowing a higher throughput; however, major drawbacks included the measurement of a single compound instead of a panel and cross-reactivity reactions. Targeted LC-MS methods with selected reaction monitoring (SRM) were then introduced for quantifying a small steroid subset without the problems of cross-reactivity. The next step was the integration of metabolomic approaches in the context of steroid analyses. As metabolomics tends to identify and quantify all the metabolites (i.e., the metabolome) in a specific system, appropriate strategies were proposed for discovering new biomarkers. Steroidomics, defined as the untargeted analysis of the steroid content in a sample, was implemented in several fields, including doping analysis, clinical studies, in vivo or in vitro toxicology assays, and more. This review discusses the current analytical methods for assessing steroid changes and compares them to steroidomics. Steroids, their pathways, their implications in diseases and the biological matrices in which they are analysed will first be described. Then, the different analytical strategies will be presented with a focus on their ability to obtain relevant information on the steroid pattern. The future technical requirements for improving steroid analysis will also be presented.

Sparse kernel density estimation technique based on zero-norm constraint

A sparse kernel density estimator is derived based on the zero-norm constraint, in which the zero-norm of the kernel weights is incorporated to enhance model sparsity. The classical Parzen window estimate is adopted as the desired response for density estimation, and an approximate function of the zero-norm is used for achieving mathemtical tractability and algorithmic efficiency. Under the mild condition of the positive definite design matrix, the kernel weights of the proposed density estimator based on the zero-norm approximation can be obtained using the multiplicative nonnegative quadratic programming algorithm. Using the -optimality based selection algorithm as the preprocessing to select a small significant subset design matrix, the proposed zero-norm based approach offers an effective means for constructing very sparse kernel density estimates with excellent generalisation performance.

Massively parallelizable list-mode reconstruction using a Monte Carlo-based elliptical Gaussian model

Purpose: A fully three-dimensional (3D) massively parallelizable list-mode ordered-subsets expectation-maximization (LM-OSEM) reconstruction algorithm has been developed for high-resolution PET cameras. System response probabilities are calculated online from a set of parameters derived from Monte Carlo simulations. The shape of a system response for a given line of response (LOR) has been shown to be asymmetrical around the LOR. This work has been focused on the development of efficient region-search techniques to sample the system response probabilities, which are suitable for asymmetric kernel models, including elliptical Gaussian models that allow for high accuracy and high parallelization efficiency. The novel region-search scheme using variable kernel models is applied in the proposed PET reconstruction algorithm. Methods: A novel region-search technique has been used to sample the probability density function in correspondence with a small dynamic subset of the field of view that constitutes the region of response (ROR). The ROR is identified around the LOR by searching for any voxel within a dynamically calculated contour. The contour condition is currently defined as a fixed threshold over the posterior probability, and arbitrary kernel models can be applied using a numerical approach. The processing of the LORs is distributed in batches among the available computing devices, then, individual LORs are processed within different processing units. In this way, both multicore and multiple many-core processing units can be efficiently exploited. Tests have been conducted with probability models that take into account the noncolinearity, positron range, and crystal penetration effects, that produced tubes of response with varying elliptical sections whose axes were a function of the crystal's thickness and angle of incidence of the given LOR. The algorithm treats the probability model as a 3D scalar field defined within a reference system aligned with the ideal LOR. Results: This new technique provides superior image quality in terms of signal-to-noise ratio as compared with the histogram-mode method based on precomputed system matrices available for a commercial small animal scanner. Reconstruction times can be kept low with the use of multicore, many-core architectures, including multiple graphic processing units. Conclusions: A highly parallelizable LM reconstruction method has been proposed based on Monte Carlo simulations and new parallelization techniques aimed at improving the reconstruction speed and the image signal-to-noise of a given OSEM algorithm. The method has been validated using simulated and real phantoms. A special advantage of the new method is the possibility of defining dynamically the cut-off threshold over the calculated probabilities thus allowing for a direct control on the trade-off between speed and quality during the reconstruction.

Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.

Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry

Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.

Submodular Optimization and Data Processing

Thesis (Ph.D.)--University of Washington, 2016-06

Fitness assessment of document model

Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

FILTERING TECHNIQUES APPLIED ON RAW CARRIER PHASE FOR GPS DETECTING SMALL DYNAMIC DISPLACEMENTS

This work is part of a research under construction since 2000, in which the main objective is to measure small dynamic displacements by using L1 GPS receivers. A very sensible way to detect millimetric periodic displacements is based on the Phase Residual Method (PRM). This method is based on the frequency domain analysis of the phase residuals resulted from the L1 double difference static data processing of two satellites in almost orthogonal elevation angle. In this article, it is proposed to obtain the phase residuals directly from the raw phase observable collected in a short baseline during a limited time span, in lieu of obtaining the residual data file from regular GPS processing programs which not always allow the choice of the aimed satellites. In order to improve the ability to detect millimetric oscillations, two filtering techniques are introduced. One is auto-correlation which reduces the phase noise with random time behavior. The other is the running mean to separate low frequency from the high frequency phase sources. Two trials have been carried out to verify the proposed method and filtering techniques. One simulates a 2.5 millimeter vertical antenna displacement and the second uses the GPS data collected during a bridge load test. The results have shown a good consistency to detect millimetric oscillations.

Latin American Consensus: Children Born Small for Gestational Age

Background: Children born small for gestational age (SGA) experience higher rates of morbidity and mortality than those born appropriate for gestational age. In Latin America, identification and optimal management of children born SGA is a critical issue. Leading experts in pediatric endocrinology throughout Latin America established working groups in order to discuss key challenges regarding the evaluation and management of children born SGA and ultimately develop a consensus statement. Discussion: SGA is defined as a birth weight and/or birth length greater than 2 standard deviations (SD) below the population reference mean for gestational age. SGA refers to body size and implies length-weight reference data in a geographical population whose ethnicity is known and specific to this group. Ideally, each country/region within Latin America should establish its own standards and make relevant updates. SGA children should be evaluated with standardized measures by trained personnel every 3 months during year 1 and every 6 months during year 2. Those without catch-up growth within the first 6 months of life need further evaluation, as do children whose weight is <= -2 SD at age 2 years. Growth hormone treatment can begin in SGA children > 2 years with short stature (< -2.0 SD) and a growth velocity < 25th percentile for their age, and should continue until final height (a growth velocity below 2 cm/year or a bone age of > 14 years for girls and > 16 years for boys) is reached. Blood glucose, thyroid function, HbA1c, and insulin-like growth factor-1 (IGF-1) should be monitored once a year. Monitoring insulin changes from baseline and surrogates of insulin sensitivity is essential. Reduced fetal growth followed by excessive postnatal catch-up in height, and particularly in weight, should be closely monitored. In both sexes, gonadal function should be monitored especially during puberty. Summary: Children born SGA should be carefully followed by a multidisciplinary group that includes perinatologists, pediatricians, nutritionists, and pediatric endocrinologists since 10% to 15% will continue to have weight and height deficiency through development and may benefit from growth hormone treatment. Standards/guidelines should be developed on a country/region basis throughout Latin America.

The role of interleukin-6, endothelins, and apoptotic genes in small bowel transplantation, in a swine model of ischemia and reperfusion injury

IRI is closely related to sepsis in ITx setting. Complete understanding of the mechanisms involved in IRI development may improve outcomes. Ortothopic ITx without immunosuppression was performed in order to characterize IRI-associated mucosal damage. Twenty pigs underwent ITx. Two groups were assigned to different CI times: G1: 90 min and, G2: 180 min. Euro-Collins was used as preservation solution. Jejunal fragments were collected at donor laparotomy, 30 min, and 3 days after reperfusion. IRI assessment involved: histopathologic analysis, quantification of MPO-positive cells through immunohistochemical studies, quantification of epithelial apoptotic cells using TUNEL staining, and quantification of IL-6, ET-1, Bak, and Bcl-XL genes expression by RT-PCR. Neutrophilic infiltration increased in a similar fashion in both groups, but lasted longer in G2. Apoptosis detected by TUNEL staining increased and anti-apoptotic gene Bcl-XL expression decreased significantly in G1, 3 days after surgery. Endothelin-1 and IL-6 genes expression increased 30 min after the procedure and returned to baseline 3 days after surgery. In conclusion, IL-6 and ET-1 are involved precociously in the development of intestinal IRI. Apoptosis was more frequently detected in G1 grafts by TUNEL-staining and by RT-PCR.