Proposta para classificação, segundo a severidade, dos indivíduos portadores de más oclusões do Padrão Face Longa

OBJETIVO: o presente estudo teve como objetivo propor um método para classificação, segundo a severidade, dos indivíduos Padrão Face Longa, avaliando sua confiabilidade e reprodutibilidade. METODOLOGIA: foram utilizadas fotografias faciais (frontal, perfil e frontal sorrindo) de 125 crianças Padrão Face Longa (54 do gênero feminino e 71 do gênero masculino), selecionadas apenas considerando-se a morfologia facial, com idades entre 10 anos e 6 meses e 15 anos e 2 meses. As fotografias foram avaliadas, separadamente, por três examinadores, sendo reavaliadas após três semanas, em uma nova disposição aleatória. Os indivíduos foram graduados em três subtipos, de acordo com a severidade: moderado, médio e severo. Para avaliar as concordâncias intra e interexaminadores, foi utilizada a estatística Kappa (k). RESULTADOS: na avaliação intra-examinador, todos os examinadores obtiveram concordâncias substanciais, com o valor de Kappa variando de 0,64 a 0,66, havendo em todos os examinadores 80% ou mais de concordância. Quando comparadas as avaliações interexaminadores, as freqüências de concordância diminuíram, variando de 67,2% a 70,4%. A partir dos valores de Kappa, que variaram de 0,41 a 0,46, a interpretação foi considerada moderada. CONCLUSÕES: com base nesses resultados, o método foi considerado aplicável, com necessidade de complemento de informações provenientes de outros exames rotineiramente aplicados em Ortodontia. A aplicação clínica será demonstrada com intuito de evidenciar os níveis diferentes de severidade das más oclusões do Padrão Face Longa e as características do protocolo de tratamento recomendado.

Infrared face recogniton by optimum-path forest

This paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.

A dupla face da bola: as estratégias de comunicação do Portal da Copa 2014 e o site De olho no cofre do portal UOL

Pós-graduação em Comunicação - FAAC

Estudo da associaçao entre o Padrão face longa, o hábito de respiração bucal e as características intrabucais

Aim: to evaluate the association of the long face pattern and the mouth breathing, correlating them with the intraoral characteristics. Methods: the sample was composed of 60 Caucasian Brazilian descendents patients, divided in two groups according to the subjective of their facial pattern. The patients were clinically evaluated to determine their respiratory pattern and the diagnosed of malocclusion. The lateral teleradiographies were drawn in standard to verification facial cephalometric pattern. Chi-Square analysis evaluated the association between subjective facial pattern and type of breathing; facial pattern subjective and cephalometric facial pattern. It was also the chi-square with yates correction to evaluate the associations between subjective facial pattern, type of breathing and posterior cross bite; facial subjective standard, type of breathing and anterior open bite; facial pattern between subjective, type breathing and type of Angle´s malocclusion. Results: it showed that long face pattern (group 1) was associated with mouth breathing habit and facial cephalometric standard. Moreover, the long-face pattern (group 1) presented that mouth breathing was associated with a posterior crossbite and Angle Class II malocclusion. Conclusion: the long face pattern - evaluated with subjective facial analyses - was associated with mouth breathing. The long face pattern and patients with mouth breathing was associated with a posterior crossbite and Class II Angle's malocclusion.

Ultra-precision face grinding with constant pressure, lapping kinematics, and SiC grinding wheels dressed with overlap factor

Several machining processes have been created and improved in order to achieve the best results ever accomplished in hard and difficult to machine materials. Some of these abrasive manufacturing processes emerging on the science frontier can be defined as ultra-precision grinding. For finishing flat surfaces, researchers have been putting together the main advantages of traditional abrasive processes such as face grinding with constant pressure, fixed abrasives for two-body removal mechanism, total contact of the part with the tool, and lapping kinematics as well as some specific operations to keep grinding wheel sharpness and form. In the present work, both U d-lap grinding process and its machine tool were studied aiming nanometric finishing on flat metallic surfaces. Such hypothesis was investigated on AISI 420 stainless steel workpieces U d-lap ground with different values of overlap factor on dressing (Ud=1, 3, and 5) and grit sizes of conventional grinding wheels (silicon carbide (SiC)=#800, #600, and #300) applying a new machine tool especially designed and built for such finishing. The best results, obtained after 10 min of machining, were average surface roughness (Ra) of 1.92 nm, 1.19-μm flatness deviation of 25.4-mm-diameter workpieces, and mirrored surface finishing. Given the surface quality achieved, the U d-lap grinding process can be included among the ultra-precision abrasive processes and, depending on the application, the chaining steps of grinding, lapping, and polishing can be replaced by the proposed abrasive process.