Automatic code generation for microcontrollers from place-transition Petri net models

This paper describes a program for the automatic generation of code for Intel's 8051 microcontroller. The code is generated from a place-transition Petri net specification. Our goal is to minimize programming time. The code generated by our program has been observed to exactly match the net model. It has also been observed that no change is needed to be made to the generated code for its compilation to the target architecture. © 2011 IFAC.

Effect of disinfection and accelerated ageing on dimensional stability and detail reproduction of a facial silicone with nanoparticles

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.

Retention and processing methods of nasal prosthesis

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.

Influence of polishing procedures on the surface roughness of dental ceramics made by different techniques

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.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

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.

Quantificação de fibrose e enfisema em pacientes com paracoccidioidomicose (PCM) pulmonar, através de imagens de tomografia computadorizada de alta resolução (TCAR)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mudanças morfológicas na evolução do megaleque do Taquari: uma análise com base em dados orbitais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação da influência de diferentes materiais oclusais na confecção de próteses fixas implantossuportadas unitárias com diferentes diâmetros dos implantes osseointegrados: estudo pelo método dos elementos finitos tridimensionais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influência de diferentes pilares e materiais de recobrimento estético na manutenção da pré-carga do parafuso de retenção de coroas implantosuportadas

Pós-graduação em Odontologia - FOA

Avaliação da adaptação marginal de restaurações cerâmicas inlay após a cimentação

Pós-graduação em Odontologia Restauradora - ICT

Método para extração e caracterização de lesões de pele usando difusão anisotrópica, crescimento de regiões, watersheds e contornos ativos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geotecnologias digitais no ensino médio: avaliação prática de seu potencial

Pós-graduação em Geografia - IGCE

Estudo das características morfométricas de diferentes regiões do intestino delgado e índices zootécnicos em quatro linhagens de frangos de corte

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of a CAD system for automatic classification of microcalcifications based on FPGA

This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

Optimum-Path Forest Applied for Breast Masses Classification

In Computer-Aided Diagnosis-based schemes in mammography analysis each module is interconnected, which directly affects the system operation as a whole. The identification of mammograms with and without masses is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest for further image segmentation. This study aims to evaluate the performance of three techniques in classifying regions of interest as containing masses or without masses (without clinical findings), as well as the main contribution of this work is to introduce the Optimum-Path Forest (OPF) classifier in this context, which has never been done so far. Thus, we have compared OPF against with two sorts of neural networks in a private dataset composed by 120 images: Radial Basis Function and Multilayer Perceptron (MLP). Texture features have been used for such purpose, and the experiments have demonstrated that MLP networks have been slightly better than OPF, but the former is much faster, which can be a suitable tool for real-time recognition systems.