Influence of anatomical location on CT numbers in cone beam computed tomography

Objective: To assess the influence of anatomical location on computed tomography (CT) numbers in mid- and full field of view (FOV) cone beam computed tomography (CBCT) scans. Study Design: Polypropylene tubes with varying concentrations of dipotassium hydrogen phosphate (K2HPO4) solutions (50-1200 mg/mL) were imaged within the incisor, premolar, and molar dental sockets of a human skull phantom. CBCT scans were acquired using the NewTom 3G and NewTom 5G units. The CT numbers of the K2HPO 4 phantoms were measured, and the relationship between CT numbers and K2HPO4 concentration was examined. The measured CT numbers of the K2HPO4 phantoms were compared between anatomical sites. Results: At all six anatomical locations, there was a strong linear relationship between CT numbers and K2HPO4 concentration (R 2 > 0.93). However, the absolute CT numbers varied considerably with the anatomical location. Conclusion: The relationship between CT numbers and object density is not uniform through the dental arch on CBCT scans. © 2013 Elsevier Inc.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Evolução espaço-temporal do uso e cobertura do solo nas estâncias turísticas de Avaré e Paranapanema, no reservatório de Jurumirim (SP)

Pós-graduação em Geografia - IGCE

Lógica ANFIS aplicada na estimação da rugosidade e do desgaste da ferramenta de corte no processo de retificação plana de cerâmicas avançadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Determinação do conflito de uso e ocupação do solo em áreas de preservação permanente da microbacia do Ribeirão Água -Fria, Bofete(SP) visando a conservação dos recursos hídricos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Caracterização da cobertura vegetal na equação universal de perda de solos (fator C) por meio de geotecnologias

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Monitoramento da dressagem do processo de retificação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação de redes neurais artificiais no monitoramento da operação de dressagem

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Morfologia do relevo da porção sul do megaleque fluvial do Taquari, Pantanal da Nhecolândia, Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação de fração volumétrica de austenita retida e martensita em aço trip 800 utilizando três métodos diferentes

In the second half of the last century the automobile industries suffered from the petroleum crisis caused mainly by the wars in the Middle East. These crises led the automakers rethink their vehicles. One of the most important events after that was the adoption of new steels by the industry. One example is the TRIP steels (Transformationinduced plasticity). It is known that the macroscopic behavior of a material is strongly dependent on its microstructure and therefore the quantitative metallography is important to understand and relate the material properties to its microstructure. In this work, different specimens of TRIP steels were etched using LePera reagent. The obtained images were analyzed using digital processing. Using the ImageJ software the methods threshold and watershed were studied as well as a comparison with the ASTM E562 standard. The methods were compared and finally the morphological characteristics and volumetric fraction of the retained austenite and martensite phases were analyzed. The results showed that the threshold led to a higher number of identified grains with lower mean area and total area fraction than the watershed method and ASTM standard

Monitoramento da condição da ferramenta de dressagem usando sinais de vibração e modelos neurais

Pós-graduação em Engenharia Elétrica - FEB

Deriving vegetation indices for phenology analysis using genetic programming

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

Ridge-based fingerprint matching using hough transform

Despite the efficacy of minutia-based fingerprint matching techniques for good-quality images captured by optical sensors, minutia-based techniques do not often perform so well on poor-quality images or fingerprint images captured by small solid-state sensors. Solid-state fingerprint sensors are being increasingly deployed in a wide range of applications for user authentication purposes. Therefore, it is necessary to develop new fingerprint-matching techniques that utilize other features to deal with fingerprint images captured by solid-state sensors. This paper presents a new fingerprint matching technique based on fingerprint ridge features. This technique was assessed on the MSU-VERIDICOM database, which consists of fingerprint impressions obtained from 160 users (4 impressions per finger) using a solid-state sensor. The combination of ridge-based matching scores computed by the proposed ridge-based technique with minutia-based matching scores leads to a reduction of the false non-match rate by approximately 1.7% at a false match rate of 0.1%. © 2005 IEEE.

Caracterização geomorfológica do sistema deposicional do Rio Miranda (borda sul do Pantanal mato-grossense, MS) com base em dados orbitais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)