A presente dissertação aborda a modelagem física de sistemas marinho profundo em escala reduzida, uma metodologia que vem contribuindo no entendimento dos processos sedimentares atuantes neste ambiente, principalmente as correntes de turbidez, fluxo gravitacional subaquoso responsável pela formação dos turbiditos, importantes reservatórios de hidrocarbonetos da costa brasileira. A modelagem física 3D empregada neste trabalho aborda a influência da autogênese no comportamento espacial e evolutivo de depósitos análogos gerados por simulações de correntes de turbidez em duas séries de 10 experimentos com parâmetros de controle constantes (vazão, concentração volumétrica de sedimentos, tipo e granulometria das partículas sedimentares), onde em cada série foi utilizada uma concentração de sedimentos diferente: uma com maior concentração – HDTC (high-density turbidity currents) e outra com menor concentração – LDTC (low-density turbidity currents) onde se buscou observar o efeito desta propriedade na construção dos depósitos. Para caracterizar o comportamento geométrico dos depósitos, uma nova abordagem estatística é utilizada a partir de uma análise de variância. Os resultados obtidos apontam que processos autogênicos locais puderam alterar a configuração global dos depósitos. A concentração de sedimentos teve influência direta nas características morfológicas e evolutivas dos depósitos, sendo os experimentos de HDTC os que apresentam uma evolução mais complexa, onde ocorreu um processo de auto-confinamento das correntes, gerando uma morfologia mais diversa. / Autogenic / allogenic controls have been discussed widely because they represent an important parameter in the constructive and evolutionary process of a sedimentary system. To evaluate these controls in submarine fans and analyse its capacity of selforganizing and creating depositional patterns, this work performed fully controlled 3D physical simulations of turbidity currents under ideal autogenic controls (no external influence) with detailed data for the generated deposits. Two series of 10 experiments of high-density turbidity currents (HDTC) and low-density turbidity currents (LDTC) were run, keeping all other input parameters (discharge, volumetric concentration, type and grain size) constant. From statistical and qualitative approach were characterised the geometric elements and morphodynamic behaviour of the deposits (centroid, Length/Width ratio, morphodynamic evolution). The results indicate local autogenic processes change the global setting of the flow evolution and deposits of submarine fans. A morphodynamic evolution generated by HDTC showed complex stages of filling and stacking caused by two types of flow self-channelling. Type I is characterised by flow channelling due to the elevation of levees without lateral avulsion and more efficient sediment transport (longer deposits, with terminal lobes well developed), and Type II is characterised by flow channelling but allows lateral avulsions and involves less efficient sediment transport (shorter deposits with terminal lobes undeveloped). The HDTC deposits showed random behaviour for the length/width ratio and for the centroid of sedimentary bodies and distinct morphological elements (elongated central deposit, fringes and distal lobes). By contrast, the LDTC morphodynamics were simplified without any self-confining process or distinct morphological elements. Finally, the statistical approach showed that the HDTC deposits had a greater variance of geometrical elements in relation to LDTC deposits. The experiments provided evidence that high rates of sediment supply decisively influenced the geometry and morphodynamic of the deposits, as well as they self-organizing capacity.

Made available in DSpace on 2014-06-11T19:32:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-05-24Bitstream added on 2014-06-13T21:04:42Z : No. of bitstreams: 1 matida_ck_dr_botfm.pdf: 889840 bytes, checksum: e2fb39fd0a8e59a674752ea187a4c74b (MD5) / A importância do estudo da trombose venosa profunda (TVP) em crianças e adolescentes reside no impacto desta doença sobre a qualidade de vida desta população, tendo em vista sua longa expectativa de vida e a morbidade associada ao tromboembolismo venoso. Com o passar dos anos, a síndrome pós-trombótica e a recorrência podem deixar sequelas que vão desde dor crônica nos membros, edema e até úlceras de difícil cicatrização. A TVP em crianças está sendo melhor estudada nos últimos anos. Até então, seu diagnóstico e tratamento eram baseados em experiências individuais, pequenas séries de casos ou extrapolados das recomendações para adultos. Realizamos a presente revisão para melhor compreensão da epidemiologia, fisiopatologia, etiologia, diagnóstico, tratamento desta doença / The study of deep vein thrombosis (DVT) in children and adolescents assesses the important impact of this disease on the quality of life of this population considering its long life expectancy and morbidity associated to venous thromboembolism. Within the years, the pos-thrombotic syndrome and recurrence can cause sequelae including chronic lower limb pain, edema and even hard cicatrization ulcer. Recently, DVT in children has been studied more appropriately. Previously, its diagnosis and treatment were based on individual experience, some serial cases or comparisons with recommendations to the adult treatments. This present study has been presented to better comprehend the epidemiology, physiopathology, etiology, diagnosis, treatment and prophylaxis of the deep vein thrombosis

This thesis investigates the utility of sequence stratigraphy on a regional scale and the control of eustacy on basin infill in unprecedented detail. To achieve this, the thesis utilises a wealth of data, including a continuous 3D seismic MegaSurvey dataset covering 55,000 sq. km, combined with state of the art seismic interpretation software to interpret the basin infill of the Late Cenozoic southern North Sea. The prograding shelf-prism clinoforms of the Late Cenozoic are calibrated to high density borehole penetrations, high resolution chronostratigraphy and climate proxies. The chronostratigraphic control enables a correlation of geomorphology, seismic architectures and seismic facies with full 3D control to the global sea level curve, which enables an evaluation of the impact of eustatic change on sequence development. The control of eustacy and the limitations of sequence stratigraphy are highlighted by: 1) Investigating the regional expression of chronostratigraphically calibrated seismic units, which are linked to the global sea level curve. This was carried out by mapping across the region, the dominance of oblique or sigmoidal clinoform types and seismic features such as iceberg scours, terrestrial channels and submarine fans in order to evaluate the lateral variation of depositional systems and accommodation. 2) Investigating sediment partitioning basinwards of the shelf edge and how deposition basinwards can be predicted via observations of seismic facies and architecture. This was achieved by focusing on specific seismic architectures of forced regressive slope clinoforms and deep water sedimentary systems and the link updip to the shelf within the highly constrained chronostratigraphic framework. The thesis results suggest that sequence stratigraphic models do not represent lateral variation well or integrate other allocyclic forcings on sequence development. A holistic and observation based approach to understanding basin infill and recognising the importance of sediment supply, pre-existing geomorphology, process type of the feeder system, differential subsidence, as well as eustacy, is imperative.

abstract: Compressed sensing (CS) is a novel approach to collecting and analyzing data of all types. By exploiting prior knowledge of the compressibility of many naturally-occurring signals, specially designed sensors can dramatically undersample the data of interest and still achieve high performance. However, the generated data are pseudorandomly mixed and must be processed before use. In this work, a model of a single-pixel compressive video camera is used to explore the problems of performing inference based on these undersampled measurements. Three broad types of inference from CS measurements are considered: recovery of video frames, target tracking, and object classification/detection. Potential applications include automated surveillance, autonomous navigation, and medical imaging and diagnosis. Recovery of CS video frames is far more complex than still images, which are known to be (approximately) sparse in a linear basis such as the discrete cosine transform. By combining sparsity of individual frames with an optical flow-based model of inter-frame dependence, the perceptual quality and peak signal to noise ratio (PSNR) of reconstructed frames is improved. The efficacy of this approach is demonstrated for the cases of \textit{a priori} known image motion and unknown but constant image-wide motion. Although video sequences can be reconstructed from CS measurements, the process is computationally costly. In autonomous systems, this reconstruction step is unnecessary if higher-level conclusions can be drawn directly from the CS data. A tracking algorithm is described and evaluated which can hold target vehicles at very high levels of compression where reconstruction of video frames fails. The algorithm performs tracking by detection using a particle filter with likelihood given by a maximum average correlation height (MACH) target template model. Motivated by possible improvements over the MACH filter-based likelihood estimation of the tracking algorithm, the application of deep learning models to detection and classification of compressively sensed images is explored. In tests, a Deep Boltzmann Machine trained on CS measurements outperforms a naive reconstruct-first approach. Taken together, progress in these three areas of CS inference has the potential to lower system cost and improve performance, opening up new applications of CS video cameras. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

abstract: Light field imaging is limited in its computational processing demands of high sampling for both spatial and angular dimensions. Single-shot light field cameras sacrifice spatial resolution to sample angular viewpoints, typically by multiplexing incoming rays onto a 2D sensor array. While this resolution can be recovered using compressive sensing, these iterative solutions are slow in processing a light field. We present a deep learning approach using a new, two branch network architecture, consisting jointly of an autoencoder and a 4D CNN, to recover a high resolution 4D light field from a single coded 2D image. This network decreases reconstruction time significantly while achieving average PSNR values of 26-32 dB on a variety of light fields. In particular, reconstruction time is decreased from 35 minutes to 6.7 minutes as compared to the dictionary method for equivalent visual quality. These reconstructions are performed at small sampling/compression ratios as low as 8%, allowing for cheaper coded light field cameras. We test our network reconstructions on synthetic light fields, simulated coded measurements of real light fields captured from a Lytro Illum camera, and real coded images from a custom CMOS diffractive light field camera. The combination of compressive light field capture with deep learning allows the potential for real-time light field video acquisition systems in the future. / Dissertation/Thesis / Masters Thesis Computer Engineering 2017

abstract: Compressive sensing theory allows to sense and reconstruct signals/images with lower sampling rate than Nyquist rate. Applications in resource constrained environment stand to benefit from this theory, opening up many possibilities for new applications at the same time. The traditional inference pipeline for computer vision sequence reconstructing the image from compressive measurements. However,the reconstruction process is a computationally expensive step that also provides poor results at high compression rate. There have been several successful attempts to perform inference tasks directly on compressive measurements such as activity recognition. In this thesis, I am interested to tackle a more challenging vision problem - Visual question answering (VQA) without reconstructing the compressive images. I investigate the feasibility of this problem with a series of experiments, and I evaluate proposed methods on a VQA dataset and discuss promising results and direction for future work. / Dissertation/Thesis / Masters Thesis Computer Engineering 2017

Organismos de mar profundo encontram limitações na disponibilidade de alimentos e exploram enriquecimentos orgânicos esporádicos que chegam ao assoalho oceânico. O objetivo deste trabalho foi descrever a diversidade das comunidades bacterianas associadas a parcelas sintéticas e orgânicas (vértebras de baleia e blocos de madeira) no Espírito Santo, Rio de Janeiro e São Paulo a 3.300 m de profundidade, avaliando a influência dos substratos e da localização geográfica sobre essas comunidades. Foi realizada a extração de DNA e amplificação do gene RNAr 16S para sequenciamento por Illumina Miseq e análises estatísticas pelo Qiime. Os Gêneros dominantes nos substratos sintéticos, madeira e vértebras foram Psychroserpens (Flavobacteriia), Phaeobacter, (Alphaproteobacteria), Desulfobacter, (Deltaproteobacteria), respectivamente. Com base nos resultados obtidos, afirma-se que o tipo de substrato teve maior influência do que a localização geográfica sobre a estrutura das comunidades bacterianas. / Deep sea organisms found limitations in the availability of food and exploit sporadic organic enrichments that reach the ocean floor. The aim of this study was to describe the diversity of bacterial communities associated with synthetic and organic substrate (whale bone and wood blocks) in Espírito Santo, Rio de Janeiro and Sao Paulo to 3,300 m deep, assessing the influence of substrates and location geographical about these communities. 16S rRNA sequencing was performed by Illumina Miseq and statistical analysis by Qiime. The dominant genera in synthetic substrates, wood and vertebrae were Psychroserpens (Flavobacteriia), Phaeobacter (Alphaproteobacteria) and Desulfobacter, (Deltaproteobacteria), respectively. Based on these results, it is stated that the substrate type had greater influence than geographic location on the structure of bacterial communities.

Many real-world face recognition tasks are under unconstrained conditions such as off-angle pose variations, illumination variations, facial occlusion, facial expression, etc. In this work, we are focusing on the real-world scenarios where only the periocular region of a face is visible such as in the ISIS case. In Part I of the dissertation, we will showcase the face recognition capability based on the periocular region, which we call the periocular face recognition. We will demonstrate that face matching using the periocular region directly is more robust than the full face in terms of age-tolerant face recognition, expression-tolerant face recognition, pose-tolerant face recognition, as well as contains more cues for determining the gender information of a subject. In this dissertation, we will study direct periocular matching more comprehensively and systematically using both shallow and deep learning methods. Based on this, in Part II and Part III of the dissertation, we will continue to explore an indirect way of carrying out the periocular face recognition: periocular-based full face hallucination, because we want to capitalize on the powerful commercial face matchers and deep learning-based face recognition engines which are all trained on large-scale full face images. The reproducibility and feasibility of re-training for a proprietary facial region, such as the periocular region, is relatively low, due to the nonopen source nature of commercial face matchers as well as the amount of training data and computation power required by the deep learning based models. We will carry out the periocular-based full face hallucination based on two proposed reconstructive dictionary learning methods, including the dimensionally weighted K-SVD (DW-KSVD) dictionary learning approach and its kernel feature space counterpart using Fastfood kernel expansion approximation to reconstruct high-fidelity full face images from the periocular region, as well as two proposed generative deep learning approaches that build upon deep convolutional generative adversarial networks (DCGAN) to generate the full face from the periocular region observations, including the Gang of GANs (GoGAN) method and the discriminant nonlinear many-to-one generative adversarial networks (DNMM-GAN) for applications such as the generative open-set landmark-free frontalization (Golf) for faces and universal face optimization (UFO), which tackles an even broader set of problems than periocular based full face hallucination. Throughout Parts I-III, we will study how to handle challenging realworld scenarios such as unconstrained pose variations, unconstrained illumination conditions, and unconstrained low resolution of the periocular and facial images. Together, we aim to achieve unconstrained periocular face recognition through both direct periocular face matching and indirect periocular-based full face hallucination. In the final Part IV of the dissertation, we will go beyond and explore several new methods in deep learning that are statistically efficient for generalpurpose image recognition. Methods include the local binary convolutional neural networks (LBCNN), the perturbative neural networks (PNN), and the polynomial convolutional neural networks (PolyCNN).

Orientador: Maurício Tatsuei Sakima / Banca: Ary dos Santos Pinto / Banca: Luiz Gonzaga Gandini Junior / Banca: Júlio de Araújo Gurgel / Banca: Arno Locks / Resumo: Este estudo cefalométrico prospectivo foi desenvolvido com o propósito de descrever os resultados de uma das estratégias de correção da mordida profunda. Foram selecionados 19 indivíduos, com faixa etária entre 11 e 15 anos, apresentando más-oclusões de Classe II, Divisão 1, com mordida profunda de no mínimo 4 milímetros. Desses, 9 indivíduos serviram como grupo controle e os outros 10 foram tratados com a mecânica de intrusão da técnica de Ricketts (arco base). Foram colocados implantes metálicos de referência intra-mandibulares, para sobreposições de traçados, em todos os componentes da amostra. Telerradiografias cefalométricas, em norma lateral, para a avaliação do comportamento dos incisivos inferiores, e em 45 graus, para a avaliação dos primeiros pré-molares e primeiros molares inferiores, foram tomadas no início do tratamento e após o nivelamento da curva de Spee do arco inferior para o grupo experimental, e após aproximadamente 6 meses no grupo controle. Os resultados na região de incisivos inferiores indicaram que houve intrusão dos incisivos inferiores e também um deslocamento horizontal para lingual dos três pontos estudados (borda incisal, centro de resistência e ápice radicular). Não houve deslocamento vertical (extrusivo) nos primeiros pré-molares e nos primeiros molares causados pelo tratamento. Os primeiros pré-molares demonstraram uma inclinação para distal com o fulcro próximo ao ápice, apesar de nenhum acessório ter sido colocado nesses dentes. Na região de molares, houve uma inclinação distal da coroa e mesial de raiz, com o fulcro desse movimento próximo ao centro de resistência. / Abstract: The purpose of this prospective study was to avaliate the results of treatment strategie for deep overbite correction. Nineteen Class II, Division 1, with deep overbite individuals (age 11 to 15 years) were selected. Nine cases were used as a control group and the others were trated with the bioprogressive technique (Ricketts) for correction of vertical malocclusion. Metallic implants were used for superimpositions. Lateral cephalometric radiographs were used for evaluation of lower incisors. Forty five degrees cephalometric radiographs were used for evaluation of lower first bicuspids and first molars. These radiographs were taken before and immediately after leveling of lower arch and about 6 months later for the control group. The results showed that the technique produced highly significant incisor intrusion and a lingual movement of three points inverstigated (incisal edge, center of resistence and root apex). There was no vertical displacement (extrusion) on lower first bicuspid and first molar. A distal inclination was observed on lower first bicuspid, despite of any bracket has been fixed on it. Lower first molars crowns showed a distal movement and the root showed a mesial movement, with center of rotation near the fulcrum. / Doutor

Thesis (MTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2017. / In South Africa, squid fishing vessels need to find and then anchor above benthic squid egg beds to effect viable catches. However, waves acting on the vessel produce a dynamic response on the anchor line. These oscillatory motions produce impact forces of the chain striking the seabed. It is hypothesised that this causes damage to the squid egg bed beneath the vessels. Different mooring systems may cause more or less damage and this is what is investigated in this research. The effect of vessel mooring lines impact on the seabed during squid fishing is investigated using a specialised hydrodynamic tool commercial package ANSYS AQWA models. This study analysed the single-point versus the two-point mooring system’s impact on the seabed. The ANSYS AQWA models were developed for both mooring systems under the influence of the wave and current loads using the 14 and 22 m vessels anchored with various chain sizes. The effect of various wave conditions was investigated as well as the analysis of three mooring line configurations. The mooring chain contact pressure on the seabed is investigated beyond what is output from ANSYS AQWA using ABAQUS finite element analysis. The real-world velocity of the mooring chain underwater was obtained using video analysis. The ABAQUS model was built by varying chain sizes at different impact velocities. The impact pressure and force due to this velocity was related to mooring line impact velocity on the seabed in ANSYS AQWA. Results show the maximum impact pressure of 191 MPa when the 20 mm diameter chain impacts the seabed at the velocity of 8 m/s from video analysis. It was found that the mooring chain impact pressure on the seabed increased with an increase in the velocity of impact and chain size. The ANSYS AQWA impact pressure on the seabed was found to be 170.86 MPa at the impact velocity of 6.4 m/s. The two-point mooring system was found to double the seabed mooring chain contact length compared to the single-point mooring system. Both mooring systems showed that the 14 m vessel mooring line causes the least seabed footprint compared to the 22 m vessel.