Determination of resonant frequencies of triangular and rectangular microstrip antennas, using artificial neural networks

This paper presents models that can be used in the design of microstrip antennas for mobile communications. The antennas can be triangular or rectangular. The presented models are compared with deterministic and empirical models based on artificial neural networks (ANN) presented in the literature. The models are based on Perceptron Multilayer (PML) and Radial Basis Function (RBF) ANN. RBF based models presented the best results. Also, the models can be embedded in CAD systems, in order to design microstrip antennas for mobile communications.

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.

Determinação da freqüência de ressonância de antenas tipo microfita triangular e retangular utilizando redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optical Impression Systems for CAD-CAM Restorations

Computer-aided design/computer-aided manufacturing images can be taken through either direct or indirect imaging. For the indirect systems, the digitalization is obtained from the impression material or cast, and for the direct ones the image is taken directly from the mouth using intraoral scanners.The direct acquisition systems have been constantly improved because these are less invasive, quicker, and more precise than the conventional method. Besides, the digital images can be easily stored for a long time. Therefore, the aim of this paper was to describe and discuss based on the literature the main direct image acquisition systems available on the market: CEREC Bluecam (Sirona), Lava C.O.S. System (3M ESPE), iTero System (Cadent/Straumann), and E4D System (D4D Technologies).

GRIOT - sistema CAD inteligente para design de calçados

O presente trabalho é o estudo dos aspectos da metodologia projetual, face às novas tecnologias da informática, Inteligência Artificial (Sistemas Especialistas) e CAD, consideradas as reais possibilidades de automatização no processo de concepção em Design. Esse artigo propõe uma metodologia para a construção de sistema inteligente capaz de auxiliar o designer nas tarefas projetuais. A indústria de calçados foi utilizada como estudo de caso para a aplicação da metodologia, onde as reais possibilidades de automação são verificadas.

Current status of pulp capping with dentin adhesive systems: a review

Several studies have assessed the morphology and thickness of hybrid layer, the dentin bend strengths as well as sealing ability of dentin adhesive systems. However, few in vivo studies have evaluated the biocompatibility of the adhesive systems following application to deep dentin or directly to the pulp of human teeth. Many studies performed in non-human primate teeth or teeth of rats have reported pulp healing and dentin bridging following pulp capping with bonding agents. In addition, a few clinical and radiographical reports of the success of resin pulp capping have been described in the dental literature.Objectives: the aim of this review was to evaluate the literature on pulp responses following total acid etching and application of adhesive resins on deep cavities or pulp exposures. In addition, the clinical/radiographical evidence for the apparent success of vital pulp therapy and results obtained from animal and human studies were compared and discussed.Significance and conclusions: the self-etching adhesive systems may be useful and safe when applied on dentin, In contrast, persistent inflammatory reactions as well as delay in pulpal healing and failure of dentin bridging were seen in human pulps capped with bonding agents. The results observed in animal teeth cannot be directly extrapolated to human clinical conditions. Consequently, vital pulp therapy using acidic agents and adhesive resins seems to be contraindicated. (C) 2000 Academy of Dental Materials. Published by Elsevier B.V. Ltd. All rights reserved.

Geometric modeling from the medical images in the CAD system to support prosthesis design

This paper presents an individual designing prosthesis for surgical use and proposes a methodology for such design through mathematical extrapolation of data from digital images obtained via tomography of individual patient's bones. Individually tailored prosthesis designed to fit particular patient requirements as accurately as possible should result in more successful reconstruction, enable better planning before surgery and consequently fewer complications during surgery. Fast and accurate design and manufacture of personalized prosthesis for surgical use in bone replacement or reconstruction is potentially feasible through the application and integration of several different existing technologies, which are each at different stages of maturity. Initial case study experiments have been undertaken to validate the research concepts by making dimensional comparisons between a bone and a virtual model produced using the proposed methodology and a future research directions are discussed.

Sistemas CAD/CAM: avaliação da precisão de aquisição de dados

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.

Avaliação da precisão de aquisição de dados nos Sistemas CAD/CAM: desadaptação marginal horizontal

Pós-graduação em Odontologia - FOA