14 resultados para Object Localization


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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

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Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Dissertação de Mestrado em Engenharia Informática

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertation presented at Faculty of Sciences and Technology of the New University of Lisbon to attain the Master degree in Electrical and Computer Science Engineering

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Degree of Master in Biotecnology

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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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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This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

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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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Part of the work described in this chapter, was the subject of the following publication: D. Vieira, T. a. Figueiredo, A. Verma, R. G. Sobral, A. M. Ludovice, H. de Lencastre, and J. Trincao, “Purification, crystallization and preliminary X-ray diffraction analysis of GatD, a glutamine amidotransferase-like protein from Staphylococcus aureus peptidoglycan,” Acta Crystallogr. Sect. F Struct. Biol. Commun., vol. 70, no. 5, pp. 1–4, Apr. 2014.

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The cell wall of Staphylococcus aureus is a highly complex network mainly composed of highly cross-linked peptidoglycan (PG) and teichoic acids (TAs), both important for the maintenance of the integrity and viability of bacteria. The penicillin binding proteins (PBPs), which catalyse the final stage of PG biosynthesis, are targets of β-lactam antibiotics and have been a key focus of antibacterial research. S. aureus has four native PBPs, PBP1-4 carried by both methicillin-sensitive (MSSA) and –resistant (MRSA) strains. PBP4 is required for the synthesis of the highly cross-linked PG and, as shown in recent studies, is essential for the expression of β-lactam resistance in community-acquired strains (CA-MRSA). This protein has a septal localization that seems to be spatially and temporally regulated by an unknown intermediate of the wall teichoic acids (WTA) biosynthesis pathway. Therefore, if WTA synthesis is compromised, PBP4 becomes dispersed throughout the entire cell membrane. The aim of this project was to identify the WTA precursor responsible for the septal recruitment of PBP4. In order to do so, inducible mutants of tarB and tarL genes in the background of NCTCPBP4-YFP were constructed allowing for the study of PBP4 localization in the presence and absence of these specific tar genes.With this work we were able to show that the absence of TarB or TarL leads to the delocalization of PBP4, indicating that TarL or a protein/WTA precursor whose localization/synthesis is dependent on TarL is responsible for the recruitment of PBP4.

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Endospores, or spores for simplicity, are a highly resistant cell type produced by some bacterial species under adverse conditions. Two main protective layers contribute to the resilience of spores: the cortex, composed of peptidoglycan, and the outermost proteinaceous coat. In Bacillus subtilis, the coat comprises up to 80 different proteins, organized into four sublayers: the basement layer, the inner coat, the outer coat and the crust. These proteins are synthesized at different times during sporulation and deposited at the spore surface in multiple coordinated waves. Central to coat formation is a group of morphogenetic proteins that guide the assembly of the coat components. Targeting of the coat proteins to the surface of the developing spore is mainly controlled by the SpoIVA morphogenetic ATPase. In a second stage, the coat proteins fully encircle the spore, a process termed encasement that requires the morphogenetic protein SpoVID. Assembly of the inner coat requires SafA, whereas formation of the outer coat and the crust requires CotE. SafA interacts directly with the N terminus of SpoVID. (...)