804 resultados para Pixel-based Classification
Resumo:
We present a near-infrared (0.9-2.4 mu m) spectroscopic study of 73 field ultracool dwarfs having spectroscopic and/or kinematic evidence of youth (approximate to 10-300 Myr). Our sample is composed of 48 low-resolution (R approximate to 100) spectra and 41 moderate-resolution spectra (R greater than or similar to 750-2000). First, we establish a method for spectral typing M5-L7 dwarfs at near-IR wavelengths that is independent of gravity. We find that both visual and index-based classification in the near-IR provides consistent spectral types with optical spectral types, though with a small systematic offset in the case of visual classification at J and K band. Second, we examine features in the spectra of similar to 10 Myr ultracool dwarfs to define a set of gravity-sensitive indices based on FeH, VO, Ki, Nai, and H-band continuum shape. We then create an index-based method for classifying the gravities of M6-L5 dwarfs that provides consistent results with gravity classifications from optical spectroscopy. Our index-based classification can distinguish between young and dusty objects. Guided by the resulting classifications, we propose a set of low-gravity spectral standards for the near-IR. Finally, we estimate the ages corresponding to our gravity classifications.
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Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.
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Venous malformations (VMs) are the most common vascular developmental anomalies (birth defects) . These defects are caused by developmental arrest of the venous system during various stages of embryogenesis. VMs remain a difficult diagnostic and therapeutic challenge due to the wide range of clinical presentations, unpredictable clinical course, erratic response to the treatment with high recurrence/persistence rates, high morbidity following non-specific conventional treatment, and confusing terminology. The Consensus Panel reviewed the recent scientific literature up to the year 2013 to update a previous IUP Consensus (2009) on the same subject. ISSVA Classification with special merits for the differentiation between the congenital vascular malformation (CVM) and vascular tumors was reinforced with an additional review on syndrome-based classification. A "modified" Hamburg classification was adopted to emphasize the importance of extratruncular vs. truncular sub-types of VMs. This incorporated the embryological origin, morphological differences, unique characteristics, prognosis and recurrence rates of VMs based on this embryological classification. The definition and classification of VMs were strengthened with the addition of angiographic data that determines the hemodynamic characteristics, the anatomical pattern of draining veins and hence the risk of complication following sclerotherapy. The hemolymphatic malformations, a combined condition incorporating LMs and other CVMs, were illustrated as a separate topic to differentiate from isolated VMs and to rectify the existing confusion with name-based eponyms such as Klippel-Trenaunay syndrome. Contemporary concepts on VMs were updated with new data including genetic findings linked to the etiology of CVMs and chronic cerebrospinal venous insufficiency. Besides, newly established information on coagulopathy including the role of D-Dimer was thoroughly reviewed to provide guidelines on investigations and anticoagulation therapy in the management of VMs. Congenital vascular bone syndrome resulting in angio-osteo-hyper/hypotrophy and (lateral) marginal vein was separately reviewed. Background data on arterio-venous malformations was included to differentiate this anomaly from syndrome-based VMs. For the treatment, a new section on laser therapy and also a practical guideline for follow up assessment were added to strengthen the management principle of the multidisciplinary approach. All other therapeutic modalities were thoroughly updated to accommodate a changing concept through the years.
Resumo:
Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.
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n the framework of the FRUELA project, two oceanographic surveys were conducted by R/V Hespérides in the eastern Bellingshausen Sea, western basin of the Bransfield Strait and Gerlache Strait area during December 1995 and January 1996. The main hydrographic structures of the study domain were the Southern Boundary of the ACC and the Bransfield Front. The characteristics and zonation of local water masses are discussed in terms of temperature, salinity, dissolved oxygen, nutrient and inorganic carbon concentrations. Concentration intervals for water mass labelling, on the basis of chemical parameters in addition to the common theta/S-based classification, are defined. Silicate seems to be a very good discriminator for local water masses.
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The important technological advances experienced along the last years have resulted in an important demand for new and efficient computer vision applications. On the one hand, the increasing use of video editing software has given rise to a necessity for faster and more efficient editing tools that, in a first step, perform a temporal segmentation in shots. On the other hand, the number of electronic devices with integrated cameras has grown enormously. These devices require new, fast, and efficient computer vision applications that include moving object detection strategies. In this dissertation, we propose a temporal segmentation strategy and several moving object detection strategies, which are suitable for the last generation of computer vision applications requiring both low computational cost and high quality results. First, a novel real-time high-quality shot detection strategy is proposed. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that allows to detect and discard false detections. This analysis is carried out exclusively over a reduced amount of candidate transitions, thus maintaining the computational requirements. On the other hand, a moving object detection strategy, which is based on the popular Mixture of Gaussians method, is proposed. This strategy, taking into account the recent history of each image pixel, adapts dynamically the amount of Gaussians that are required to model its variations. As a result, we improve significantly the computational efficiency with respect to other similar methods and, additionally, we reduce the influence of the used parameters in the results. Alternatively, in order to improve the quality of the results in complex scenarios containing dynamic backgrounds, we propose different non-parametric based moving object detection strategies that model both background and foreground. To obtain high quality results regardless of the characteristics of the analyzed sequence we dynamically estimate the most adequate bandwidth matrices for the kernels that are used in the background and foreground modeling. Moreover, the application of a particle filter allows to update the spatial information and provides a priori knowledge about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results. Additionally, we propose the use of an innovative combination of chromaticity and gradients that allows to reduce the influence of shadows and reflects in the detections.
Resumo:
The increasing use of video editing software requires faster and more efficient editing tools. As a first step, these tools perform a temporal segmentation in shots that allows a later building of indexes describing the video content. Here, we propose a novel real-time high-quality shot detection strategy, suitable for the last generation of video editing software requiring both low computational cost and high quality results. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that helps to detect and discard false detections. This motion analysis is carried out exclusively over a reduced set of candidate transitions, thus maintaining the computational requirements demanded by new applications to fulfill user needs.
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Video Quality Assessment needs to correspond to human perception. Pixel-based metrics (PSNR or MSE) fail in many circumstances for not taking into account the spatio-temporal property of human's visual perception. In this paper we propose a new pixel-weighted method to improve video quality metrics for artifacts evaluation. The method applies a psychovisual model based on motion, level of detail, pixel location and the appearance of human faces, which approximate the quality to the human eye's response. Subjective tests were developed to adjust the psychovisual model for demonstrating the noticeable improvement of an algorithm when weighting the pixels according to the factors analyzed instead of treating them equally. The analysis developed demonstrates the necessity of models adapted to the specific visualization of contents and the model presents an advance in quality to be applied over sequences when a determined artifact is analyzed.
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Structural genomics aims to solve a large number of protein structures that represent the protein space. Currently an exhaustive solution for all structures seems prohibitively expensive, so the challenge is to define a relatively small set of proteins with new, currently unknown folds. This paper presents a method that assigns each protein with a probability of having an unsolved fold. The method makes extensive use of protomap, a sequence-based classification, and scop, a structure-based classification. According to protomap, the protein space encodes the relationship among proteins as a graph whose vertices correspond to 13,354 clusters of proteins. A representative fold for a cluster with at least one solved protein is determined after superposition of all scop (release 1.37) folds onto protomap clusters. Distances within the protomap graph are computed from each representative fold to the neighboring folds. The distribution of these distances is used to create a statistical model for distances among those folds that are already known and those that have yet to be discovered. The distribution of distances for solved/unsolved proteins is significantly different. This difference makes it possible to use Bayes' rule to derive a statistical estimate that any protein has a yet undetermined fold. Proteins that score the highest probability to represent a new fold constitute the target list for structural determination. Our predicted probabilities for unsolved proteins correlate very well with the proportion of new folds among recently solved structures (new scop 1.39 records) that are disjoint from our original training set.
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Of the approximately 380 families of angiosperms, representatives of only 10 are known to form symbiotic associations with nitrogen-fixing bacteria in root nodules. The morphologically based classification schemes proposed by taxonomists suggest that many of these 10 families of plants are only distantly related, engendering the hypothesis that the capacity to fix nitrogen evolved independently several, if not many, times. This has in turn influenced attitudes toward the likelihood of transferring genes responsible for symbiotic nitrogen fixation to crop species lacking this ability. Phylogenetic analysis of DNA sequences for the chloroplast gene rbcL indicates, however, that representatives of all 10 families with nitrogen-fixing symbioses occur together, with several families lacking this association, in a single clade. This study therefore indicates that only one lineage of closely related taxa achieved the underlying genetic architecture necessary for symbiotic nitrogen fixation in root nodules.
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An approach and strategy for automatic detection of buildings from aerial images using combined image analysis and interpretation techniques is described in this paper. It is undertaken in several steps. A dense DSM is obtained by stereo image matching and then the results of multi-band classification, the DSM, and Normalized Difference Vegetation Index (NDVI) are used to reveal preliminary building interest areas. From these areas, a shape modeling algorithm has been used to precisely delineate their boundaries. The Dempster-Shafer data fusion technique is then applied to detect buildings from the combination of three data sources by a statistically-based classification. A number of test areas, which include buildings of different sizes, shape, and roof color have been investigated. The tests are encouraging and demonstrate that all processes in this system are important for effective building detection.
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It is often debated whether migraine with aura (MA) and migraine without aura (MO) are etiologically distinct disorders. A previous study using latent class analysis (LCA) in Australian twins showed no evidence for separate subtypes of MO and MA. The aim of the present study was to replicate these results in a population of Dutch twins and their parents, siblings and partners (N = 10,144). Latent class analysis of International Headache Society (IHS)-based migraine symptoms resulted in the identification of 4 classes: a class of unaffected subjects (class 0), a mild form of nonmigrainous headache (class 1), a moderately severe type of migraine (class 2), typically without neurological symptoms or aura (8% reporting aura symptoms), and a severe type of migraine (class 3), typically with neurological symptoms, and aura symptoms in approximately half of the cases. Given the overlap of neurological symptoms and nonmutual exclusivity of aura symptoms, these results do not support the MO and MA subtypes as being etiologically distinct. The heritability in female twins of migraine based on LCA classification was estimated at .50 (95% confidence intervals [0CI} .27 -.59), similar to IHS-based migraine diagnosis (h(2) = .49, 95% Cl .19-.57). However, using a dichotomous classification (affected-unaffected) decreased heritability for the IHS-based classification (h(2) = .33, 95% Cl .00-.60), but not the LCA-based classification (h(2) = .51, 95% Cl. 23-.61). Importantly, use of the LCA-based classification increased the number of subjects classified as affected. The heritability of the screening question was similar to more detailed LCA and IHS classifications, suggesting that the screening procedure is an important determining factor in genetic studies of migraine.
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This thesis presents a new approach to designing large organizational databases. The approach emphasizes the need for a holistic approach to the design process. The development of the proposed approach was based on a comprehensive examination of the issues of relevance to the design and utilization of databases. Such issues include conceptual modelling, organization theory, and semantic theory. The conceptual modelling approach presented in this thesis is developed over three design stages, or model perspectives. In the semantic perspective, concept definitions were developed based on established semantic principles. Such definitions rely on meaning - provided by intension and extension - to determine intrinsic conceptual definitions. A tool, called meaning-based classification (MBC), is devised to classify concepts based on meaning. Concept classes are then integrated using concept definitions and a set of semantic relations which rely on concept content and form. In the application perspective, relationships are semantically defined according to the application environment. Relationship definitions include explicit relationship properties and constraints. The organization perspective introduces a new set of relations specifically developed to maintain conformity of conceptual abstractions with the nature of information abstractions implied by user requirements throughout the organization. Such relations are based on the stratification of work hierarchies, defined elsewhere in the thesis. Finally, an example of an application of the proposed approach is presented to illustrate the applicability and practicality of the modelling approach.
Resumo:
Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.
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Thesis (Ph.D.)--University of Washington, 2016-08