19 resultados para Machine components

em Universidade do Minho


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Doctoral Program in Computer Science

Relevância:

20.00% 20.00%

Publicador:

Resumo:

The bond behavior between Fiber Reinforced Polymers (FRPs) and masonry substrates has been the subject of many studies during the last years. Recent accelerated aging tests have shown that bond degradation and FRP delamination are likely to occur in FRP-strengthened masonry components under hygrothermal conditions. While an investigation on the possible methods to improve the durability of these systems is necessary, the applicability of different bond repair methods should also be studied. This paper aims at investigating the debonding mechanisms after repairing delaminated FRP-strengthened masonry components. FRP-strengthened brick specimens, after being delaminated, are repaired with two different adhesives: a conventional epoxy resin and a highly flexible polymer. The latter is used as an innovative adhesive in structural applications. The bond behavior in the repaired specimens is investigated by performing single-lap shear bond tests. Digital image correlation (DIC) is used for deeper investigation of the surface deformation and strains development. The effectiveness of the repair methods is discussed and compared with the strengthened specimens.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Eye tracking as an interface to operate a computer is under research for a while and new systems are still being developed nowadays that provide some encouragement to those bound to illnesses that incapacitates them to use any other form of interaction with a computer. Although using computer vision processing and a camera, these systems are usually based on head mount technology being considered a contact type system. This paper describes the implementation of a human-computer interface based on a fully non-contact eye tracking vision system in order to allow people with tetraplegia to interface with a computer. As an assistive technology, a graphical user interface with special features was developed including a virtual keyboard to allow user communication, fast access to pre-stored phrases and multimedia and even internet browsing. This system was developed with the focus on low cost, user friendly functionality and user independency and autonomy.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Masonry is a non-homogeneous material, composed of units and mortar, which can be of different types, with distinct mechanical properties. The design of both masonry units and mortar is based on the role of the walls in the building. Load-bearing walls relate to structural elements that bear mainly vertical loads, but can serve also to resist to horizontal loads. When a structural masonry building is submitted to in-plane and out-of-plane loadings induced by an earthquake for example, the masonry walls are the structural elements that ensure the global stability of the building. This means that the walls should have adequate mechanical properties that enable them to resist to different combinations of compressive, shear and tensile stresses.The boundary conditions influence the resisting mechanisms of the structural walls under in-plane loading and in a buildings the connection at the intersection walls are of paramount importance for the out-of-plane resisting mechanism. However, it is well established that the masonry mechanical properties are also relevant for the global mechanical performance of the structural masonry walls. Masonry units for load-bearing walls are usually laid so that their perforations are vertically oriented, whereas for partition walls, brick units with horizontal perforation are mostly adopted.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Tese de Doutoramento - Leaders for Technical Industries (LTI) - MIT Portugal

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

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

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Dissertação de mestrado em Engenharia Industrial

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Dissertação de mestrado em Engenharia Mecânica

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Tese de Doutoramento em Engenharia Química e Biológica (área de conhecimento em Engenharia Enzimática e das Fermentações)

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Dissertação de mestrado integrado em Engenharia Mecânica

Relevância:

20.00% 20.00%

Publicador:

Resumo:

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.