55 resultados para Scenario Programming, Markup Languages, 3D Virtualworlds


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Magazine Digital eUAU - Março 2011

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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Dissertation to obtain master degree in Biotechnology

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Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

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Dissertação para obtenção do Grau de Mestre em Engenharia de Materiais

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

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Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

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Micro/nano wrinkled patterns on cross-linked urethane/urea polymeric flexible free standing films with two soft segments, polypropylene oxide and polybutadiene, can be induced by UV-irradiation. The ability to write/erase these 3D structures, in a controlled manner, is the main focus of this work. The imprinting of the wrinkled structures was accomplished by swelling in an appropriate solvent followed by drying the membranes after the cross-linking process and UV irradiation. The surface tailoring of the elastomeric membranes was imaged by optical microscopy, scanning electronic microscopy and by atomic force microscopy. To erase the wrinkled structures the elastomers were swollen. The swelling as well as the sol/gel fraction and the UV radiation were tuned in order to control the wrinkles characteristics. It was found that the wrinkles wavelength, in the order of microns (1±0,25μm), was stamped by the UV radiation intensity and exposure time while the wrinkles' amplitude, in the order of nanometers (150-450 nm), was highly dependent on the swelling and sol/gel fraction. A prototype for volatile organic compounds detection was developed taking advantage of the unique 3D micro/nano wrinkles features.

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This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

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The Intel R Xeon PhiTM is the first processor based on Intel’s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer’s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.

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A Engenharia de Tecidos surge da necessidade recorrente de regenerar ou recriar órgãos e tecidos danificados devido a vários tipos de trauma. A carência de funcionalidades resultante pode ser resolvida através da implantação de substitutos bio-sintéticos. O presente trabalho consiste na produção de matrizes porosas 3D baseadas em réplicas invertidas de cristais coloidais com futura aplicação em substituintes ósseos sintéticos para fraturas de não-união. O substituinte ósseo consiste numa estrutura denominada Inverse colloidal crystal (ICC), em que a sua organização singular resulta numa homogénea proliferação celular e num aumento das propriedades mecânicas, quando comparada com outros substituintes. O primeiro passo para a obtenção desta estrutura é a produção de microesferas de poliestireno, por uma técnica baseada em microfluídica. Posteriormente as microesferas são empacotadas resultando numa estrutura coesa com ligações entre microesferas vizinhas. O preenchimento dos espaços vazios entre microesferas pelo biomaterial pretendido e posterior remoção das microesferas dá origem à estrutura porosa do ICC. ICCs poliméricos (ϕCs = 1,00) e compósitos (ϕCs = 0,86 e ϕHA = 0,14; ϕCs = 0,67 e ϕHA = 0,33; ϕCs = ϕHA = 0,50) são produzidos e as suas propriedades mecânicas são testadas através de ensaios de compressão e comparadas com outros substituintes sintéticos. Para avaliação do comportamento dos materiais em contacto com meio biológico, foram realizados testes de citotoxicidade que revelaram uma viabilidade celular acima dos 80% em todos os ICCs.