41 resultados para 3D shape detection

em Universidade do Minho


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The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

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

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Dissertation for Ph.D. degree in Biomedical Engineering.

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Bone tissue engineering requires a biocompatible scaffold that supports cell growth and enhances the native repair process. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHB-HV) is a biodegradable 3D scaffold with 88.1 â 0.3% porosity and pore size of 163.5 â 0.1 mm. Previous studies demonstrated the potential of PHB-HV as a scaffold in spinal cord repair. The aim of this study was to evaluate PHB-HV as a scaffold for bone regeneration by assessing the cytocompatability of this scaffold.

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Cell encapsulation within hydrogel microspheres shows great promise in the field of tissue engineering and regenerative medicine (TERM). However, the assembling of microspheres as building blocks to produce complex tissues is a hard task because of their inability to place along length scales in space. We propose a proof-of-concept strategy to produce 3D constructs using cell encapsulated as building blocks by perfusion based LbL technique. This technique exploits the â bindingâ potential of multilayers apart from coating

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Bioactive glass nanoparticles (BGNPs) promote an apatite surface layer in physiologic conditions that lead to a good interfacial bonding with bone.1 A strategy to induce bioactivity in non-bioactive polymeric biomaterials is to incorporate BGNPs in the polymer matrix. This combination creates a nanocomposite material with increased osteoconductive properties. Chitosan (CHT) is a polymer obtained by deacetylation of chitin and is biodegradable, non-toxic and biocompatible. The combination of CHT and the BGNPs aims at designing biocompatible spheres promoting the formation of a calcium phosphate layer at the nanocomposite surface, thus enhancing the osteoconductivity behaviour of the biomaterial. Shape memory polymers (SMP) are stimuli-responsive materials that offer mechanical and geometrical action triggered by an external stimulus.2 They can be deformed and fixed into a temporary shape which remains stable unless exposed to a proper stimulus that triggers recovery of their original shape. This advanced functionality makes such SMPs suitable to be implanted using minimally invasive surgery procedures. Regarding that, the inclusion of therapeutic molecules becomes attractive.  We propose the synthesis of shape memory bioactive nanocomposite spheres with drug release capability.3   1.  L. L. Hench, Am. Ceram. Soc. Bull., 1993, 72, 93-98. 2.  A. Lendlein and S. Kelch, Angew Chem Int Edit, 2002, 41, 2034-2057. 3.  Ã . J. Leite, S. G. Caridade and J. F. Mano, Journal of Non-Crystalline Solids (in Press)

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Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome.

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Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

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Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

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Human activity is very dynamic and subtle, and most physical environments are also highly dynamic and support a vast range of social practices that do not map directly into any immediate ubiquitous computing functionally. Identifying what is valuable to people is very hard and obviously leads to great uncertainty regarding the type of support needed and the type of resources needed to create such support. We have addressed the issues of system development through the adoption of a Crowdsourced software development model [13]. We have designed and developed Anywhere places, an open and flexible system support infrastructure for Ubiquitous Computing that is based on a balanced combination between global services and applications and situated devices. Evaluation, however, is still an open problem. The characteristics of ubiquitous computing environments make their evaluation very complex: there are no globally accepted metrics and it is very difficult to evaluate large-scale and long-term environments in real contexts. In this paper, we describe a first proposal of an hybrid 3D simulated prototype of Anywhere places that combines simulated and real components to generate a mixed reality which can be used to assess the envisaged ubiquitous computing environments [17].

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The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

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[Excerpt] The advantages resulting from the use of numerical modelling tools to support the design of processing equipment are almost consensual. The design of calibration systems in profile extrusion is not an exception . H owever , the complex geome tries and heat exchange phenomena involved in this process require the use of numerical solvers able to model the heat exchange in more than one domain ( calibrator and polymer), the compatibilization of the heat transfer at the profile - calibrator interface and with the ability to deal with complex geometries. The combination of all these features is usually hard to find in commercial software. Moreover , the dimension of the meshes required to ob tain accurate results, result in computational times prohibitive for industrial application. (...)

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Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.

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The free volume holes of a shape memory polymer have been analysed considering that the empty space between molecules is necessary for the molecular motion, and the shape memory response is based on polymer segments acting as molecular switches through variable flexibility with temperature or other stimuli. Therefore, thermomechanical analysis (TMA) and positron annihilation lifetime spectroscopy (PALS) have been applied to analyse shape recovery and free volume hole sizes in gamma irradiated polycyclooctene (PCO) samples, as a non-cytotoxic alternative to more conventional PCO crosslinked via peroxide for future applications in medicine. Thus, a first approach relating structure, free volume holes and shape memory properties in gamma irradiated PCO is presented. The results suggest that free volume holes caused by gamma irradiation in PCO samples facilitate the recovery process by improving movement of polymer chains and open t possibilities for the design and control of the macroscopic response.