31 resultados para Preferences and segmentation
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Pós-graduação em Alimentos e Nutrição - FCFAR
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Pós-graduação em Educação - FFC
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Pós-graduação em Matemática - IBILCE
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Educação - FFC
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Brazil is the world’s first chicken meat exporter nowadays. The maintenance of this position requires a constant quality attributes evolution. This work evaluated the chicken meat consumer profile in the northwest region of São Paulo state, the most important Brazilian poultry meat consumer market, in order to provide information to the productive sector. The data were collected using 482 interviews and questionnaires that were answered by e-mail. The questionnaires involved questions related to the consumer identification, habits and preferences and their knowledge about food safety, production system, sustainability and animal welfare. Most of the consumers, 62%, were female, with ages ranging from 20 to 50 years. Beef was preferred by the majority of the answerers and chicken and pork meat were together the second choice. Only 2% of the interviewed consumers mentioned not enjoying poultry meat. The main part of consumers, 67%, prefer to buy breast and leg cuts and only 11% are used to buy the whole poultry carcass. More than 60% of the interviewed have already eaten free range chicken meat, but the majority of them, 89%, are used to consume regular industrialized poultry. About 75% of the consumers believe hormones are used to grow the birds. Over 80% of people observe the expiration date before buying the product, but only 55% check if it has the stamp of the official inspection service. Color and appearance of meat are the most important factors that influence the consumer’s choice. The amount of water that drips on the tray is a rejection factor to 88% of answerers. Most of them, 66%, prefer lighter colored meat. Only 27% of them believe that chicken meat causes an environmental impact and 48% do not know the meaning of animal welfare. More than half of the interviewed do not consider animal welfare aspects before consuming any kind of meat. From these results obtained, it is possible to conclude that any effort to improve the product quality, mainly concerned to animal welfare and sustainability aspects, requires prior educational initiatives.
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Cassava is an important staple food for human and animal feeding in Cuba. Despite its importance, there is little or nonexistent information to diagnose preferences and frequency of consumption of cassava in that country. In this sense, the present article characterizes the preferences and frequency of consumption of cassava in the municipalities of Plaza de la Revolución-La Habana province, El Salvador–Guantanamo province and San José de Las Lajas–Mayabeque province in Cuba. A survey was conducted through a questionnaire containing twelve closed and two open questions. The sample was determined based on the number of total population of each municipality considering 95% as confidence interval and 5% as error margin. The results were statistically analyzed by calculating the absolute and the relative frequencies of each question. It was observed that the acquisition of cassava in the municipalities of Plaza de la Revolución, El Salvador and San José de las Lajas in Cuba is done by purchase small quantities of fresh cassava for home consumption within one week, due to the extreme perishability of cassava, which limits consumers' ability to store fresh roots at home. The choice of cassava is made based on both skin colour (light brown) and pulp (white) and empirical knowledge about its ease of cooking, and that cassava is mostly consumed in boiled and fried forms up to four times a week in times where there is root market supply with the desirable culinary characteristics (cooking facility), that is, from September to December.
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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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Two Aedes aegypti (L.) populations were studied in the laboratory regarding the preference for three types of breeding sites, i.e., flasks containing only water, flasks with a plant and flasks with a stick. Each of these breeding units was placed in one cage and the choice of the oviposition sites was determined for individual females and three females per experimental unit at two humidity levels. Preference for ovipositing on the water surface was observed and varied according to experimental unit and humidity. Mean hatching of eggs in water surface was 46.6%. Experiments with three females showed a more marked difference than when only one female was used. Inter and intrapopulation variability regarding oviposition sites was observed. The discrimination between the different oviposition substrates, hatching in water surface and its implication for mosquito control are discussed.
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Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.
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Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)