947 resultados para Use-wear analysis


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The most common techniques for stress analysis/strength prediction of adhesive joints involve analytical or numerical methods such as the Finite Element Method (FEM). However, the Boundary Element Method (BEM) is an alternative numerical technique that has been successfully applied for the solution of a wide variety of engineering problems. This work evaluates the applicability of the boundary elem ent code BEASY as a design tool to analyze adhesive joints. The linearity of peak shear and peel stresses with the applied displacement is studied and compared between BEASY and the analytical model of Frostig et al., considering a bonded single-lap joint under tensile loading. The BEM results are also compared with FEM in terms of stress distributions. To evaluate the mesh convergence of BEASY, the influence of the mesh refinement on peak shear and peel stress distributions is assessed. Joint stress predictions are carried out numerically in BEASY and ABAQUS®, and analytically by the models of Volkersen, Goland, and Reissner and Frostig et al. The failure loads for each model are compared with experimental results. The preparation, processing, and mesh creation times are compared for all models. BEASY results presented a good agreement with the conventional methods.

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Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

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

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

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The action of fenthion was studied in a 15% epicutaneous formulation upon Rhipicephalus sanguineus, which may transmit pathogens to men and other animals, such as Ehrlichia, Babesia and Ricketsia. Dogs were artificially infected for the trial. The fenthion bioassays were begun four months after artificial infestation. The test group, having a mean of 186 ticks per dog, received the formulation dosage according to body weight on the neck region. Tick counts were performed, considering diameters > or = 2mm, during 11 days of treatment, in the most affected body areas: back, ears and paws. Before the application of fenthion in the dogs, it were observed an average 43.3% ticks in the ears, 38.1% in the back area and 17.6% in the paws. The number of ticks in dogs decreased by 36.2%, 63.8%, 82.7%, 67%, 40% and 4.9%, respectively on days 1, 2, 3, 5, 7, 9 and 11 after treatment. R. sanguineus anti-tick activity, lower than that officially recommended, was verified. The number of ticks increased progressively after the 5th day, demonstrating residual insecticide inefficacy. The results obtained did not indicate the use of this formulation, at the tested dosage, as an elective measure for R. sanguineus control.

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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

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We analyzed 37 patients who underwent segmental wide resection of bone tumors and reconstruction with a modular titanium endoprosthesis at the Orthopaedic Oncology Group, between 1992 and 1998. Twelve patients were male and 25 were female, with a mean age of 30 years (9 - 81). The mean follow-up was 14 months (2 - 48). The diagnoses were: osteosarcoma (14 cases), metastatic carcinoma (10), Ewing's sarcoma (4), giant cell tumor (4), malignant fibrous histiocytoma (3), chondrosarcoma (1), and aneurysmal bone cyst (1). Eleven articulated total knee, 8 partial proximal femur with bipolar acetabulum, 8 partial proximal humerus, 3 total femur, 2 partial proximal tibia, 2 diaphyseal femur, 2 diaphyseal humerus, and 1 total proximal femur with cementless acetabulum endoprosthesis implant procedures were done. The complications related to the procedure included: infection (5 cases), dislocation (3), module loosening (1), and ulnar nerve paresthesia (1). We used the following criteria for the clinical evaluation: presence of pain, range of motion, reconstruction stability, surgical and oncologic complications, and patient acceptance. The results were good in 56.8% of the cases, regular in 32.4% and poor in 10.8%.

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Tese de Doutoramento Engenharia Mecânica

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Executive functioning (EF), which is considered to govern complex cognition, and verbal memory (VM) are constructs assumed to be related. However, it is not known the magnitude of the association between EF and VM, and how sociodemographic and psychological factors may affect this relationship, including in normal aging. In this study, we assessed different EF and VM parameters, via a battery of neurocognitive/psychological tests, and performed a Canonical Correlation Analysis (CCA) to explore the connection between these constructs, in a sample of middle- aged and older healthy individuals without cognitive impairment (N = 563, 50+ years of age). The analysis revealed a positive and moderate association between EF and VM independently of gender, age, education, global cognitive performance level, and mood. These results confirm that EF presents a significant association with VM performance.

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This study utilised recent developments in forensic aromatic hydrocarbon fingerprint analysis to characterise and identify specific biogenic, pyrogenic and petrogenic contamination. The fingerprinting and data interpretation techniques discussed include the recognition of: The distribution patterns of hydrocarbons (alkylated naphthalene, phenanthrene, dibenzothiophene, fluorene, chrysene and phenol isomers), • Analysis of “source-specific marker” compounds (individual saturated hydrocarbons, including n-alkanes (n-C5 through 0-C40) • Selected benzene, toluene, ethylbenzene and xylene isomers (BTEX), • The recalcitrant isoprenoids; pristane and phytane and • The determination of diagnostic ratios of specific petroleum / non-petroleum constituents, and the application of various statistical and numerical analysis tools. An unknown sample from the Irish Environmental Protection Agency (EPA) for origin characterisation was subjected to analysis by gas chromatography utilising both flame ionisation and mass spectral detection techniques in comparison to known reference materials. The percentage of the individual Polycyclic Aromatic Hydrocarbons (PAIIs) and biomarker concentrations in the unknown sample were normalised to the sum of the analytes and the results were compared with the corresponding results with a range of reference materials. In addition, to the determination of conventional diagnostic PAH and biomarker ratios, a number of “source-specific markers” isomeric PAHs within the same alkylation levels were determined, and their relative abundance ratios were computed in order to definitively identify and differentiate the various sources. Statistical logarithmic star plots were generated from both sets of data to give a pictorial representation of the comparison between the unknown sample and reference products. The study successfully characterised the unknown sample as being contaminated with a “coal tar” and clearly demonstrates the future role of compound ratio analysis (CORAT) in the identification of possible source contaminants.

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This study analyses the area of construction and demolition waste (C & D W) auditing. The production of C&DW has grown year after year since the Environmental Protection Agency (EPA) first published a report in 1996 which provided data for C&D W quantities for 1995 (EPA, 1996a). The most recent report produced by the EPA is based on data for 2005 (EPA, 2006). This report estimated that the quantity of C&DW produced for that period to be 14 931 486 tonnes. However, this is a ‘data update’ report containing an update on certain waste statistics so any total provided would not be a true reflection of the waste produced for that period. This illustrates that a more construction site-specific form of data is required. The Department of Building and Civil Engineering in the Galway-Mayo Institute of Technology have carried out two recent research projects (Grimes, 2005; Kelly, 2006) in this area, which have produced waste production indicators based on site-specific data. This involved the design and testing of an original auditing tool based on visual characterisation and the application of conversion factors. One of the main recommendations of these studies was to compare this visual characterisation approach with a photogrammetric sorting methodology. This study investigates the application of photogrammetric sorting on a residential construction site in the Galway region. A visual characterisation study is also carried out on the same project to compare the two methodologies and assess the practical application in a construction site environment. Data collected from the waste management contractor on site was also used to provide further evaluation. From this, a set of waste production indicators for new residential construction was produced: □ 50.8 kg/m2 for new residential construction using data provided by the visual characterisation method and the Landfill Levy conversion factors. □ 43 kg/m2 for new residential construction using data provided by the photogrammetric sorting method and the Landfill Levy conversion factors. □ 23.8 kg/m2 for new residential construction using data provided by Waste Management Contractor (WMC). The acquisition of the data from the waste management contractor was a key element for testing of the information produced by the visual characterisation and photogrammetric sorting methods. The actual weight provided by the waste management contractor shows a significant difference between the quantities provided.