934 resultados para Computer-aided Translation (CAT)
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The aim of the present study was to evaluate the effect of disinfection and accelerated ageing on the dimensional stability and detail reproduction of a facial silicone with different types of nanoparticle. A total of 60 specimens were fabricated with Silastic MDX 4-4210 silicone and they were divided into three groups: colourless and pigmented with nanoparticles (make-up powder and ceramic powder). Half of the specimens of each group were disinfected with Efferdent tablets and half with neutral soap for 60 days. Afterwards, all specimens were subjected to accelerated ageing. Both dimensional stability and detail reproduction tests were performed after specimen fabrication (initial period), after chemical disinfection, and after accelerated ageing periods (252, 504 and 1008 hours). The dimensional stability test was conducted using AutoCAD software, while detail reproduction was analysed using a stereoscope magnifying glass. Dimensional stability values were statistically evaluated by analysis of variance (ANOVA) followed by Tukey's test (p < 0.01). Detail reproduction results were compared using a score. Chemical disinfection and also accelerated ageing affected the dimensional stability of the facial silicone with statistically significant results. The silicone's detail reproduction was not affected by these two factors regardless of nanoparticle type, disinfection and accelerated ageing. © 2012 Informa UK, Ltd.
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Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.
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Patients with congenital malformations, traumatic or pathological mutilation and maxillofacial developmental disorders can be restored aesthetically and emotionally by the production and use of facial prostheses. The aim of this study was to review the literature about the retention and processing methods of facial prostheses, and discuss their characteristics. A literature review on Medline (PubMed) database was performed by using the keywords maxillofacial prosthesis, silicone, resin, pigment, cosmetic, prosthetic nose, based on articles published from 1956 to 2010. Several methods of retention, from adhesives to the placement of implants, and different processing methods such as laser, CAD/CAM and rapid prototyping technologies have been reported. There are advantages and disadvantages of each procedure, and none can be classified as better compared to others.
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The aim of this study was to evaluate the influence of 2 different surface polishing procedures - glazing (GZ) and manual polishing (MP) - on the roughness of ceramics processed by computer-aided design/computer-aided manufacturing (CAD/CAM) and conventional systems (stratification technique). Eighty ceramic discs (diameter: 8 mm, thickness: 1 mm) were prepared and divided among 8 groups (n = 10) according to the type of ceramic disc and polishing method: 4 GZ and 4 MP. Specimens were glazed according to each manufacturer's recommendations. Two silicone polishing points were used on the ceramic surface for manual polishing. Roughness was measured using a surface roughness tester. The roughness measurements were made along a distance of 2 mm on the sample surface and the speed of reading was 0.1 mm/s. Three measurements were taken for each sample. The data (μm) were statistically analyzed using analysis of variance (ANOVA) and Tukey's test (α = 0.05). Qualitative analysis was performed using scanning electron microscopy (SEM). The mean (± SD) roughness values obtained for GZ were: 1.1 ± 0.40 μm; 1.0 ± 0.31 μm; 1.6 ± 0.31 μm; and 2.2 ± 0.73 μm. For MP, the mean values were: 0.66 ± 0.13 μm; 0.43 ± 0.14 μm; 1.6 ± 0.55 μm; and 2.0 ± 0.63 μm. The mean roughness values were significantly affected by the ceramic type (P = 0.0001) and polishing technique (P = 0.0047). The SEM images confirmed the roughness data. The manually polished glass CAD/CAM ceramics promoted lower surface roughness than did the glazed feldspathic dental ceramics.
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Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Geografia - IGCE
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Pós-graduação em Odontologia - FOA
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Pós-graduação em Odontologia Restauradora - ICT
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Geografia - IGCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)