13 resultados para image reconstruction

em Universidade do Minho


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This article presents an experimental and numerical study for the mechanical characterization under uniaxial compressive loading of the adobe masonry of one of the most emblematic archaeological complex in Peru, 'Huaca de la Luna' (100-650AD). Compression tests of prisms were carried out with original material brought to the laboratory. For measuring local deformations in the tests, displacement transducers were used which were complemented by a digital image correlation system which allowed a better understanding of the failure mechanism. The tests were then numerically simulated by modelling the masonry as a continuum media. Several approaches were considered concerning the geometrical modelling, namely 2D and 3D simplified models, and 3D refined models based on a photogrammetric reconstruction. The results showed a good approximation between the numerical prediction and the experimental response in all cases. However, the 3D models with irregular geometries seem to reproduce better the cracking pattern observed in the tests.

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The number of houses damaged or destroyed after disasters is frequently large, and re-housing of homeless people is one of the most important tasks of reconstruction programmes. Reconstruction works often last long and during that time, it is essential to provide victims with the minimum conditions to live with dignity, privacy, and protection. This research intends to demonstrate the crucial role of temporary accommodation buildings to provide spaces where people can live and gradually resume their life until they have a permanent house. The study also aims to identify the main problems of temporary accommodation strategies and to discuss some principles and guidelines in order to reach better design solutions. It is found that temporary accommodation is an issue that goes beyond the simple provision of buildings, since the whole space for temporary settlement is important. Likewise, temporary accommodation is a process that should start before a disaster occurs, as a preventive pre-planning. In spite of being temporary constructions, these housing buildings are one of the most important elements to provide in emergency scenarios, contributing for better recovery and reconstruction actions.

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Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

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Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

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PhD Thesis in Bioengineering

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Objective: The aim of this study is to improve the understanding of self-changes after an intervention for depression focused on implicative dilemmas, a type of cognitive conflict related to identity. As recent research has highlighted the relevance of identity-related dilemmas in clients with depression, we sought to assess the way in which clients resolve such inner conflicts after a tailored dilemma-focused intervention and how this is reflected in the clients’ self-narratives. Method: We used three instruments to observe differences between good (n = 5) and poor (n = 5) outcome cases: (i) the Repertory Grid Technique to track the resolution of dilemmas, (ii) the Change Interview to compile clients’ accounts of changes at posttreatment, and (iii) the Innovative Moments Coding System to examine the emergence of clients’ novelties at the Change Interview. Results: Groups did not differ in terms of the number and relevance of client-identified significantly helpful events. However, between-group differences were found for the resolution of dilemmas and for the proportion of high-level innovative moment (IM) types. Furthermore, a greater self-narrative reconstruction was associated with higher levels of symptom improvement. Conclusions: Good outcome cases seem to be associated with the resolution of conflicts and high-level IMs.

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Dissertação de mestrado em Design de Comunicação de Moda

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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

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The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275

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Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

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Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

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Dissertação de mestrado integrado em Arquitectura (área de especialização de Cultura Arquitectónica)