1000 resultados para Imagens aéreas de pequeno formato


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While the carnivores are considered regulators and structuring of natural communities are also extremely threatened by human activities. Endangered little-spotted-cat (Leopardus tigrinus) is one of the lesser known species from the Neotropical cats. In this work we investigate the occupancy and the activity pattern of L. tigrinus in Caatinga of Rio Grande do Norte testing: 1) how environmental and anthropogenic factors influence their occupation and 2) how biotic and abiotic factors influence their activity pattern. For this we raised occurrence data of species in 10 priority areas for conservation. We built hierarchical models of occupancy based on maximum likelihood to represent biological hypotheses which were ranked using the Akaike Information Criterion (AIC). According to the results the feline occupancy is more likely away from rural settlements and in areas with a higher proportion of woody vegetation. The opportunistic killing of L. tigrinus and in retaliation for poultry predation close to residential areas can explain this result; as well as more complex vegetation structure can better serve as refuge and ensure more food. Analyzing the records of the species through circular statistics we conclude that the activity pattern is mostly nocturnal, although considerable crepuscular and a small diurnal activity. L. tigrinus activity was directly affected by the availability of small terrestrial mammals, which are essentially nocturnal. In addition, the temperatures recorded in the environment directly and indirectly affect the activity of the little-spotted-cat, as also influence the activity of their potential prey. Generally, the cats were more active when possible prey were active, and this happened at night when lower temperatures are recorded. Moreover, the different lunar phases did not affect the activity pattern. The results improve the understanding of an endangered feline inhabiting the Caatinga biome, and thus can help develop conservation and management strategies, as well as in planning future research in this semi-arid ecosystem.

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Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

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Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

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This work aims to develop a methodology for analysis of images using overlapping, which assists in identification of microstructural features in areas of titanium, which may be associated with its biological response. That way, surfaces of titanium heat treated for 08 (eight) different ways have been subjected to a test culture of cells. It was a relationship between the grain, texture and shape of grains of surface of titanium (attacked) trying to relate to the process of proliferation and adhesion. We used an open source software for cell counting adhered to the surface of titanium. The juxtaposition of images before and after cell culture was obtained with the aid of micro-hardness of impressions made on the surface of samples. From this image where there is overlap, it is possible to study a possible relationship between cell growth with microstructural characteristics of the surface of titanium. This methodology was efficient to describe a set of procedures that are useful in the analysis of surfaces of titanium subjected to a culture of cells

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Dissertação de Mestrado para obtenção do grau de Mestre em Arquitectura, apresentada na Universidade de Lisboa - Faculdade de Arquitectura.

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A Histologia, o estudo de tecidos, é uma das áreas fundamentais da Biologia que permitiu enormes avanços científicos. Sendo uma tarefa exigente, meticulosa e demorada, será importante aproveitar a existência de ferramentas e algoritmos computacionais no seu auxílio, tornando o processo mais rápido e possibilitando a descoberta de informação que poderá não estar visível à partida. Esta dissertação tem como principal objectivo averiguar se um animal foi ou não sujeito à ingestão de um xenobiótico. Com esse objectivo em vista, utilizaram-se técnicas de processamento e segmentação de imagem aplicadas a imagens de tecido renal de ratos saudáveis e ratos que ingeriram o xenobiótico. Destas imagens extraíram-se inúmeras características do corpúsculo renal que após serem analisadas através de vários algoritmos de classificação mostraram ser possível saber se o animal ingeriu ou não o xenobiótico, com um reduzido grau de incerteza. ABSTRACT: Histology, the study of tissues, is one of the key areas of Biology that has allowed huge advances in Science. Being a demanding, meticulous and time consuming task, it is important to use the existence of computational tools and algorithms in its aid, making the process faster and enabling the discovery of information that may not be initially visible. The main goal of this thesis is to ascertain if an animal was subjected or not to the ingestion of a xenobiotic. With this in mind, were used image processing and segmentation techniques applied on images of kidney tissue from healthy rats and rats that ingested the xenobiotic. From these images were extracted several features of renal glomeruli that after being analyzed by various classification algorithms had shown to be possible to know, with an acceptable degree of certainty, if the animal ingested or not the xenobiotic.

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A importância que a vegetação de margem de rios representa para o meio ambiente exercendo funções tais como proteção de mananciais e do solo e manutenção do equilíbrio ecológico do ecossistema, faz com que seja fundamental a sua conservação. Este trabalho tem por objetivo identificar padrões de vegetação ciliar em imagens CBERS do Mato Grosso do Sul e seu respectivo estado de conservação. Foram utilizadas imagens do sensor CCD do satélite CBERS-2B do ano de 2007 e informações de campo, coletadas em 368 pontos de imagem referentes a 14 desses 368 pontos que representam áreas de vegetação ciliar ocupadas por campos úmidos, vegetação arbustiva e vegetação arbórea, além de áreas impactadas por cultivo de arroz, desmatamentos, implantação de pasto exótico, erosão e assoreamento de cursos d'água. De maneira geral, a vegetação ciliar do Estado encontra-se impactada ou ausente na maior parte das áreas observadas.

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deo produzido com o GoAnimate! em que Maria Teresa leva seu filho, Pedro, para se consultar com Dra. Fátima, pois ele tem apresentado tosse, dificuldade para respirar e febre. Após avaliação a Dra. Fátima concluiu que Pedro apresenta infecção das vias aéreas.

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Prosopis rubriflora and Prosopis ruscifolia are important species in the Chaquenian regions of Brazil. Because of the restriction and frequency of their physiognomy, they are excellent models for conservation genetics studies. The use of microsatellite markers (Simple Sequence Repeats, SSRs) has become increasingly important in recent years and has proven to be a powerful tool for both ecological and molecular studies. In this study, we present the development and characterization of 10 new markers for P. rubriflora and 13 new markers for P. ruscifolia. The genotyping was performed using 40 P. rubriflora samples and 48 P. ruscifolia samples from the Chaquenian remnants in Brazil. The polymorphism information content (PIC) of the P. rubriflora markers ranged from 0.073 to 0.791, and no null alleles or deviation from Hardy-Weinberg equilibrium (HW) were detected. The PIC values for the P. ruscifolia markers ranged from 0.289 to 0.883, but a departure from HW and null alleles were detected for certain loci; however, this departure may have resulted from anthropic activities, such as the presence of livestock, which is very common in the remnant areas. In this study, we describe novel SSR polymorphic markers that may be helpful in future genetic studies of P. rubriflora and P. ruscifolia.

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An unfavorable denture-bearing area could compromise denture retention and stability, limit mastication, and possibly alter masticatory motion. The purpose of this study was to evaluate the masticatory movements of denture wearers with normal and resorbed denture-bearing areas. Completely edentulous participants who received new complete dentures were selected and divided into 2 groups (n=15) according to the condition of their denture-bearing areas as classified by the Kapur method: a normal group (control) (mean age, 65.9 ± 7.8 years) and a resorbed group (mean age, 70.2 ± 7.6 years). Masticatory motion was recorded and analyzed with a kinesiographic device. The patients masticated peanuts and Optocal. The masticatory movements evaluated were the durations of opening, closing, and occlusion; duration of the masticatory cycle; maximum velocities and angles of opening and closing; total masticatory area; and amplitudes of the masticatory cycle. The data were analyzed by 2-way ANOVA and the Tukey honestly significant difference post hoc test (α=.05). The group with a resorbed denture-bearing area had a smaller total masticatory area in the frontal plane and shorter horizontal masticatory amplitude than the group with normal denture-bearing area (P<.05). Denture wearers with resorbed denture-bearing areas showed reduced jaw motion during mastication.

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Abstract Introduction: Hypertension (HTN) is a preventable cause of cardiovascular morbidity and mortality. To compare the prevalence, awareness, treatment, and control of HTN among urban and riverside populations in Porto Velho, Amazon region. We conducted a cross-sectional study between July and December 2013 based on a household survey of individuals aged 35-80 years. Interviews by using a standardized questionnaire, and blood pressure (BP), weight, height, and waist circumference measurements were performed. HTN was defined when individuals reported having the disease, received antihypertensive medications, or had a systolic BP ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg. Awareness was based on self-reports and the use of antihypertensive medications. Control was defined as a BP ≤ 140/90 mm Hg. Among the 1410 participants, 750 (53.19%) had HTN and 473 (63.06%) had diagnosis awareness, of whom 404 (85.41%) received pharmacological treatment but with low control rate. The prevalence and treatment rates were higher in the urban areas (55.48% vs. 48.87% [p = 0.02] and 61.25% vs. 52.30% [p < 0.01], respectively). HTN awareness was higher in the riverside area (61.05% vs. 67.36% ; p < 0.01), but the control rates showed no statistically significant difference (22.11% vs. 23.43% ; p = 0.69). HTN prevalence was higher in the urban population than in the riverside population. Of the hypertensive individuals in both areas, <25% had controlled HTN. Comprehensive public health measures are needed to improve the prevention and treatment of systemic arterial HTN and prevent other cardiovascular diseases.

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The creation of the Brazilian Program for the Modernization of the Horticulture by the Secretariat of Agriculture and Supplying of the State of São Paulo at CEAGESP, determined the standardization of fruit and vegetables in the follow aspects: degree of coloration, format, calibers, defects and packing. Therefore, the main goal of this research is to correlate the classification given by the Brazilian Program with the one used by the wholesalers at CEAGESP, verifying if the established norms are being fulfilled for cultivar Carmen and Debora (SAKATA SEED). The results showed, that for cultivar Carmem, for the averages of the observed values it does not move away from the norms created by the Program for sizes small and medium. However, for the case of cultivar Debora, the results showed differences between the adopted classifications. The tomatoes were devaluated, because had been commercialized below of the standardization indicated for the Brazilian Program.

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The objective of this study was to analyze changes in the spectral behavior of the soybean crop through spectral profiles of the vegetation indexes NDVI and GVI, expressed by different physical values such as apparent bi-directional reflectance factor (BRF), surface BRF, and normalized BRF derived from images of the Landsat 5/TM. A soybean area located in Cascavel, Paraná, was monitored by using five images of Landsat 5/TM during the 2004/2005 harvesting season. The images were submitted to radiometric transformation, atmospheric correction and normalization, determining physical values of apparent BRF, surface BRF and normalized BRF. NDVI and GVI images were generated in order to distinguish the soybean biomass spectral response. The treatments showed different results for apparent, surface and normalized BRF. Through the profiles of average NDVI and GVI, it was possible to monitor the entire soybean cycle, characterizing its development. It was also observed that the data from normalized BRF negatively affected the spectral curve of soybean crop, mainly, during the phase of vegetative growth, in the 12-9-2004 image.

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Remote sensing data are each time more available and can be used to monitor the vegetal development of main agricultural crops, such as the Arabic coffee in Brazil, since that the relationship between spectral and agronomical data be well known. Therefore, this work had the main objective to assess the use of Quickbird satellite images to estimate biophysical parameters of coffee crop. Test area was composed by 25 coffee fields located between the cities of Ribeirão Corrente, Franca and Cristais Paulista (SP), Brazil, and the biophysical parameters used were row and between plants spacing, plant height, LAI, canopy diameter, percentage of vegetation cover, roughness and biomass. Spectral data were the reflectance of four bands of QUICKBIRD and values of four vegetations indexes (NDVI, GVI, SAVI and RVI) based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.

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Understanding the flow of diaspores is fundamental for determining plant population dynamics in a particular habitat, and a lack of seeds is a limiting factor in forest regeneration, especially in isolated forest fragments. Bamboo dominance affects forest structure and dynamics by suppressing or delaying the recruitment of and colonization by tree species as well as by inhibiting the survival and growth of adult trees. The goal of the present study was to determine whether dominance of the bamboo species Aulonemia aristulata (Döll) McClure in the forest understory influences species abundance and composition. We examined the seed rain at two noncontiguous sites (1.5 km apart) within an urban forest fragment, with and without bamboo dominance (BD+ and BD- areas, respectively). Sixty seed traps (0.5 m², with a 1-mm mesh) were set in the BD+ and BD- areas, and the seed rain was sampled from January to December 2007. Diaspores were classified according to dispersal syndrome, growth form and functional type of the species to which they belonged. There were significant differences between the two areas in terms of seed density, species diversity and dispersal syndrome. The BD+ area showed greater seed density and species diversity. In both areas, seed distribution was limited primarily by impaired dispersal. Bamboo dominance and low tree density resulted in fewer propagules in the seed rain. Our results suggest that low availability of seeds in the rain does not promote the maintenance of a degraded state, characterized by the presence of bamboo.