842 resultados para 3D Face Recognition, Feature Distribution Modelling, Pattern Recognition, Face Recognition
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From November 2004 to December 2007, size-segregated aerosol samples were collected all-year-round at Dome C (East Antarctica) by using PM10 and PM2.5 samplers, and multi-stage impactors. The data set obtained from the chemical analysis provided the longest and the most time-resolved record of sea spray aerosol (sea salt Na+) in inner Antarctica. Sea spray showed a sharp seasonal pattern. The highest values measured in winter (Apr-Nov) were about ten times larger than in summer (Dec-Mar). For the first time, a size-distribution seasonal pattern was also shown: in winter, sea spray particles are mainly submicrometric, while their summer size-mode is around 1-2 µm. Meteorological analysis on a synoptic scale allowed the definition of atmospheric conditions leading sea spray to Dome C. An extreme-value approach along with specific environmental based criteria was taken to yield stronger fingerprints linking atmospheric circulation (means and anomalies) to extreme sea spray events. Air mass back-trajectory analyses for some high sea spray events allowed the identification of two major air mass pathways, reflecting different size distributions: micrometric fractions for transport from the closer Indian-Pacific sector, and sub-micrometric particles for longer trajectories over the Antarctic Plateau. The seasonal pattern of the SO4**2- /Na+ ratio enabled the identification of few events depleted in sulphate, with respect to the seawater composition. By using methanesulphonic acid (MSA) profile to evaluate the biogenic SO4**2- contribution, a more reliable sea salt sulphate was calculated. In this way, few events (mainly in April and in September) were identified originating probably from the "frost flower" source. A comparison with daily-collected superficial snow samples revealed that there is a temporal shift between aerosol and snow sea spray trends. This feature could imply a more complex deposition processes of sea spray, involving significant contribution of wet and diamond dust deposition, but further work has to be carried out to rule out the effect of wind re-distribution and to have more statistic significance.
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The focus of this chapter is to study feature extraction and pattern classification methods from two medical areas, Stabilometry and Electroencephalography (EEG). Stabilometry is the branch of medicine responsible for examining balance in human beings. Balance and dizziness disorders are probably two of the most common illnesses that physicians have to deal with. In Stabilometry, the key nuggets of information in a time series signal are concentrated within definite time periods are known as events. In this chapter, two feature extraction schemes have been developed to identify and characterise the events in Stabilometry and EEG signals. Based on these extracted features, an Adaptive Fuzzy Inference Neural network has been applied for classification of Stabilometry and EEG signals.
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3D Reconstruction is the process used to obtain a detailed graphical model in three dimensions that represents some real objectified scene. This process uses sequences of images taken from the scene, so it can automatically extract the information about the depth of feature points. These points are then highlighted using some computational technique on the images that compose the used dataset. Using SURF feature points this work propose a model for obtaining depth information of feature points detected by the system. At the ending, the proposed system extract three important information from the images dataset: the 3D position for feature points; relative rotation and translation matrices between images; the realtion between the baseline for adjacent images and the 3D point accuracy error found.
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Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented landscapes, few studies have researched relevant ecological scales for organisms that also live in naturally fragmented landscapes. This situation is exemplified by the Australian rock-wallabies’ preference for rugged terrain and we addressed the issue of scale using the threatened brush-tailed rock-wallaby (Petrogale penicillata) in eastern Australia. We surveyed for brush-tailed rock-wallabies at 200 sites in southeast Queensland, collecting potentially influential site level and landscape level variables. We applied classification trees at either scale to capture a hierarchy of relationships between the explanatory variables and brush-tailed rock-wallaby presence/absence. Habitat complexity at the site level and geology at the landscape level were the best predictors of where we observed brush-tailed rock-wallabies. Our study showed that the distribution of the species is affected by both site scale and landscape scale factors, reinforcing the need for a multi-scale approach to understanding the relationship between a species and its environment. We demonstrate that careful design of data collection, using coarse scale spatial datasets and finer scale field data, can provide useful information for identifying the ecologically relevant scales for studying species–environment relationships. Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.
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In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.
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Although numerous genetic and acquired factors are appreciated as risk factors for venous thromboembolism (VTE) [1,2], only recently have male gender [3,4], dyslipoproteinemia [5], and silent atherosclerotic vascular disease [6] been linked to VTE. We recently found that high-density lipoprotein (HDL) deficiency is a key feature of a pattern of dyslipoproteinemia that is associated with VTE in males, and we found that the common TaqI B1 variation in the cholesteryl ester transfer protein (CETP) gene is significantly linked to VTE [5]. However, the TaqI B1/B2 single nucleotide polymorphism (SNP) itself is unlikely to affect directly CETP activity, but it is linked to nonsynonymous CETP SNPs Ala373Pro and Arg451Gln [7–9]. Here, we demonstrate that these two CETP variations are associated with VTE and low plasma HDL levels in males.
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The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.
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As a Lecturer of Animation History and 3D Computer Animator, I received a copy of Moving Innovation: A History of Computer Animation by Tom Sito with an element of anticipation in the hope that this text would clarify the complex evolution of Computer Graphics (CG). Tom Sito did not disappoint, as this text weaves together the multiple development streams and convergent technologies and techniques throughout history that would ultimately result in modern CG. Universities now have students who have never known a world without computer animation and many students are younger than the first 3D CG animated feature film, Toy Story (1996); this text is ideal for teaching computer animation history and, as I would argue, it also provides a model for engaging young students in the study of animation history in general. This is because Sito places the development of computer animation within the context of its pre-digital ancestry and throughout the text he continues to link the discussion to the broader history of animation, its pioneers, technologies and techniques...
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Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.
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Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilised in everyday language. While the systematicity and productivity of language provide a strong argument in favour of assuming compositionality, this very assumption is still regularly questioned in both cognitive science and philosophy. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual combinations are compositional, and so can be considered as a function of the semantics of the constituent concepts, or not. Rather than adjudicating between different grades of compositionality, the framework presented here contributes formal methods for determining a clear dividing line between compositional and non-compositional semantics. Compositionality is equated with a joint probability distribution modelling how the constituent concepts in the combination are interpreted. Marginal selectivity is emphasised as a pivotal probabilistic constraint for the application of the Bell/CH and CHSH systems of inequalities (referred to collectively as Bell-type). Non-compositionality is then equated with either a failure of marginal selectivity, or, in the presence of marginal selectivity, with a violation of Bell-type inequalities. In both non-compositional scenarios, the conceptual combination cannot be modelled using a joint probability distribution with variables corresponding to the interpretation of the individual concepts. The framework is demonstrated by applying it to an empirical scenario of twenty-four non-lexicalised conceptual combinations.
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Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.
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A new geometry-independent state - a traveling-wave wall state - is proposed as the mechanism whereby which the experimentally observed wall-localized states in rotating Rayleigh-Bénard convection systems preempt the bulk state at large rotation rates. Its properties are calculated for the illustrative case of free-slip top and bottom boundary conditions. At small rotation rates, this new wall state is found to disappear. A detailed study of the dynamics of the wall state and the bulk state in the transition region where this disappearance occurs is conducted using a Swift-Hohenberg model system. The Swift-Hohenberg model, with appropriate reflection-symmetry- breaking boundary conditions, is also shown to exhibit traveling-wave wall states, further demonstrating that traveling-wave wall states are a generic feature of nonequilibrium pattern-forming systems. A numerical code for the Swift-Hohenberg model in an annular geometry was written and used to investigate the dynamics of rotating Rayleigh-Bénard convection systems.
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Os fatores que explicam a distribuição observada em plantas e animais é uma pergunta que intriga naturalistas, biogeógrafos e ecólogos há mais de um século. Ainda nos primórdios da disciplina de ecologia, as tolerâncias ambientais já haviam sido apontadas como as grandes responsáveis pelo padrão observado da distribuição dos seres vivos, o que mais tarde levou à concepção de nicho ecológico das espécies. Nos últimos anos, o estudo das distribuições dos organismos ganhou grande impulso e destaque na literatura. O motivo foi a maior disponibilidade de catálogos de presença de espécies, o desenvolvimento de bancos de variáveis ambientais de todo o planeta e de ferramentas computacionais capazes de projetar mapas de distribuição potencial de um dado organismo. Estes instrumentos, coletivamente chamados de Modelos de Distribuição de Espécies (MDEs) têm sido desde então amplamente utilizados em estudos de diferentes escopos. Um deles é a avaliação de potenciais áreas suscetíveis à invasão de organismos exóticos. Este estudo tem, portanto, o objetivo de compreender, através de MDEs, os fatores subjacentes à distribuição de duas espécies de corais escleractíneos invasores nativos do Oceano Pacífico e ambas invasoras bem sucedidas de diversas partes do Oceano Atlântico, destacadamente o litoral fluminense. Os resultados mostraram que os modelos preditivos da espécie Tubastraea coccinea (LESSON, 1829), cosmopolita amplamente difundida na sua região nativa pelo Indo- Pacífico demonstraram de maneira satisfatória suas áreas de distribuição nas áreas invadidas do Atlântico. Sua distribuição está basicamente associada a regiões com alta disponibilidade de calcita e baixa produtividade fitoplanctônica. Por outro lado, a aplicação de MDEs foi incapaz de predizer a distribuição de T. tagusensis (WELLS,1982) no Atlântico. Essta espécie, ao contrário de sua congênere, tem distribuição bastante restrita em sua região nativa, o arquipélago de Galápagos. Através de análises posteriores foi possível constatar a mudança no nicho observado durante o processo de invasão. Finalmente, o sucesso preditivo para T. coccinea e o fracasso dos modelos para T. tagusensis levantam importantes questões sobre quais os aspectos ecológicos das espécies são mais favoráveis à aplicação de MDEs. Adicionalmente, lança importantes ressalvas na utilização recentemente tão difundida destas ferramentas como forma de previsão de invasões biológicas e em estudos de efeitos de alterações climáticas sobre a distribuição das espécies.
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A demarcação de Unidades de Conservação é uma forma supostamente eficaz para a conservação da biodiversidade. A Mata Atlântica é caracterizada por apresentar uma elevada biodiversidade e altos níveis de ameaça. O estado do Rio de Janeiro encontra-se totalmente inserido nesse bioma e seus remanescentes florestais são considerados um hotspot dentro de outro hotspot. O Rio de Janeiro pode ser considerado um dos estados melhor amostrados, porém ainda existem lacunas de conhecimentos geográficos sobre a ocorrência de morcegos. Esta tese foi desenvolvida em três capítulos com o objetivo de contribuir com conservação de morcegos no estado do Rio de Janeiro, focando em como e onde eles já foram amostrados e que locais ainda carecem de atenção. Para este estudo foram utilizados dados referentes a buscas bibliográficas e dados de amostragens do Laboratório de Diversidade de Morcegos da Universidade Federal Rural do Rio de Janeiro. No primeiro capítulo pode-se observar que as localidades com mais de 30 espécies de morcegos são resultado de grande esforço de captura e amostragens usando diversas metodologias. Para uma melhor amostragem da riqueza local, devem-se armar redes não somente em trilhas e próximas a árvores em frutificação, mas também sobre corpos de água. Fazer busca em refúgios diurnos também é aconselhável. Devem ser realizadas amostragens durante a noite toda e variar a fase do ciclo lunar, não restringindo a apenas uma ou partes das fases do ciclo lunar. No segundo capítulo observou-se que 43% das Unidades de Conservação aqui estudadas apresentam 20 ou mais espécies. Localidades que apresentam de 20 a 40 espécies de morcegos na Mata Atlântica podem ser consideradas bem amostradas. Isso demonstra que mais da metade das Unidades de Conservação não podem ser consideradas bem inventariadas. Muitos projetos de pesquisas dão prioridade para a localidade estudada ser uma Unidade de Conservação, porém existem poucos trabalhos de longa duração. No Rio de Janeiro ainda existem diversas Unidades de Conservação não amostradas, principalmente aquelas de difícil acesso e em altitudes elevadas. No terceiro capítulo foi possível observar que há uma maior proporção de espécies que apresentam distribuição geográfica restrita. Esse padrão constitui uma informação importante em termos de conservação, visto que indiretamente poderia indicar uma menor capacidade de dispersão desses animais em médias e grandes distâncias. Entretanto existem lacunas de conhecimento em decorrência da falta de amostragem em algumas regiões, sendo imperativos maiores esforços de captura. Importantes municípios para a conservação e/ou preservação de morcegos como Varre-Sai, Cambuci, Miracema, Carmo, Cantagalo, Valença, Barra do Piraí e Piraí não estão sob proteção legal, mesmo constituindo possíveis corredores entre Unidades de Conservação ou mesmo fragmentos importantes que ainda detém espécies que não estão representadas em Unidades de Conservação já estabelecidas. É imperativo que mais estudos e esforços de conservação sejam direcionados para essas áreas
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In microelectronics, the increase in complexity and the reduction of devices dimensions make essential the development of new characterization tools and methodologies. Indeed advanced characterization methods with very high spatial resolution are needed to analyze the redistribution at the nanoscale in devices and interconnections. The atom probe tomography has become an essential analysis to study materials at the nanometer scale. This instrument is the only analytical microscope capable to produce 3D maps of the distribution of the chemical species with an atomic resolution inside a material. This technique has benefit from several instrumental improvements during last years. In particular, the use of laser for the analysis of semiconductors and insulating materials offers new perspectives for characterization. The capability of APT to map out elements at the atomic scale with high sensitivity in devices meets the characterization requirements of semiconductor devices such as the determination of elemental distributions for each device region. In this paper, several examples will show how APT can be used to characterize and understand materials and process for advanced metallization. The possibilities and performances of APT (chemical analysis of all the elements, atomic resolution, planes determination, crystallographic information...) will be described as well as some of its limitations (sample preparation, complex evaporation, detection limit, ...). The examples illustrate different aspect of metallization: dopant profiling and clustering, metallic impurities segregation on dislocation, silicide formation and alloying, high K/metal gate optimization, SiGe quantum dots, as well as analysis of transistors and nanowires. © 2013 Elsevier B.V. All rights reserved.