Fuzzy Logic and Geostatistical Techniques for Spatialization of Soil Texture in Region with Rough Terrains

From the geotechnical standpoint, it is interesting to analyse the soil texture in regions with rough terrain due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this paper is to present a methodology that provides the soil texture spatialization by using Fuzzy logic and Geostatistic. The results were correlated with maps drawn specifically for the study area. The knowledge of the spatialization of soil properties, such as the texture, can be an important tool for land use planning in order to reduce the potential soil losses during rain seasons. (c) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

Direct Esthetic Restorations Based on Translucency and Opacity of Composite Resins

Light dynamics is a relevant phenomenon with respect to esthetic restorations, as incorrect analysis of the optical behavior of natural dentition may lead to potential clinical failures. The nature of incident light plays a major role in determining the amount of light transmission or reflection, and how an object is perceived depends on the nature of the light source. Natural teeth demonstrate translucency, opalescence, and fluorescence, all of which must be replicated by restorative materials in order to achieve clinical success. Translucency is the intermediary between complete opacity and complete transparency, making its analysis highly subjective. In nature, the translucency of dental enamel varies from tooth to tooth, and from individual to individual. Therefore, four important factors must be considered when appraising translucency. Presence or absence of color, thickness of the enamel, degree of translucency, and surface texture are essential components when determining translucency. State-of-the-art resin composites provide varying shades and opacities that deliver a more faithful reproduction of the chromaticity and translucency/opacity of enamel and dentin. This enables the attainment of individualized and customized composite restorations. The objective of this article is to provide a review of the phenomena of translucency and opacity in the natural dentition and composite resins, under the scope of optics, and to describe how to implement these concepts in the clinical setting.CLINICAL SIGNIFICANCEChoosing composite resins, based on optical properties alone, in order to mimic the properties of natural tooth structures, does not necessarily provide a satisfactory esthetic outcome. In many instances, failure ensues from incorrect analysis of the optical behaviors of the natural dentition as well as the improper use of restorative materials. Therefore, it is necessary to implement a technique that enables a restorative material to be utilized to its full potential to correctly replicate the natural teeth.(J Esthet Restor Dent 23:73-88, 2011).

Corn texture and particle size in broiler diets

The objective of this study was to evaluate the effect of corn texture and the particle size on broiler performance, carcass yield, nutrient digestibility, and digestive organ morphometrics. In Experiment I, 720 male Cobb chicks were distributed in a completely randomized experimental design with a 2 x 3 factorial arrangement, consisting two corn textures (dented and hard) and three corn particle sizes, was applied, with four replicates of 30 birds each. Corn particle size was classified according to geometric mean diameter (GMD) as fine - 0.46 mm; medium - 0.73 mm, and coarse - 0.87 mm. In Experiment II, 120 broiler chicks were used to evaluate corn digestibility during the periods of 16 to 22 days and 35 to 41 days of age, using the method of total excreta collection. In Experiment I, corn particle size influenced body weight, average weight gain, feed intake and feed conversion ratio of 21-day-old birds. Corn texture and particle size did not affect the performance of 42-day-old broilers or carcass traits. In Experiment II, there was no influence of corn texture and particle size on digestive organ weights. Dented corn increased nitrogen excretion in the first trial, and hard corn improved dry matter digestibility in the second metabolic trial. Corn with fine particle size promotes better performance of broilers at 21 days of age. Hard corn results in higher dry matter digestibility and lower nitrogen excretion, and consequently higher production factor in 42-day-old broilers.

The effects of extrusion conditions and the addition of volatile compounds and flavour enhancers to corn grits on the retention of the volatile compounds and texture of the extrudates

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

Automatic estimation of crowd density using texture

This paper considers the role of automatic estimation of crowd density and its importance for the automatic monitoring of areas where crowds are expected to be present. A new technique is proposed which is able to estimate densities ranging from very low to very high concentration of people, which is a difficult problem because in a crowd only parts of people's body appear. The new technique is based on the differences of texture patterns of the images of crowds. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures. The image pixels are classified in different texture classes and statistics of such classes are used to estimate the number of people. The texture classification and the estimation of people density are carried out by means of self organising neural networks. Results obtained respectively to the estimation of the number of people in a specific area of Liverpool Street Railway Station in London (UK) are presented. (C) 1998 Elsevier B.V. Ltd. All rights reserved.

On the efficacy of texture analysis for crowd monitoring

The goal of this work is to assess the efficacy of texture measures for estimating levels of crowd densities ill images. This estimation is crucial for the problem of crowd monitoring. and control. The assessment is carried out oil a set of nearly 300 real images captured from Liverpool Street Train Station. London, UK using texture measures extracted from the images through the following four different methods: gray level dependence matrices, straight lille segments. Fourier analysis. and fractal dimensions. The estimations of dowel densities are given in terms of the classification of the input images ill five classes of densities (very low, low. moderate. high and very high). Three types of classifiers are used: neural (implemented according to the Kohonen model). Bayesian. and an approach based on fitting functions. The results obtained by these three classifiers. using the four texture measures. allowed the conclusion that, for the problem of crowd density estimation. texture analysis is very effective.

Genotypic evaluation of Dent composite (Zea mays L) half-sib progenies in late harvest crop conditions

The present work was conducted at FCAV-UNESP, Campus de Jaboticabal, in late harvest crop time of 1991. One hundred interpopulational hybrids obtained from a top-cross between Dent Composite and Flint Composite populations were evaluated. The analyzed characteristics were: Spodoptera frugiperda damages, lodging, damaged ears percentage, and productivity. Estimates of heritability, variance between progenies and genetical gain for each character of available population were determined. Estimates of the progenies variance, like those from heritability for the different analysed characters, indicate that there is an adequate genetical variance for the utilization of that material on subsequent genetic breeding programs, though allowing genetical gains, on the following selection cycles for the characteristics: grain weight, lodging and damages caused by armyworm larvae, whereas for the other characteristics the obtained results were not satisfactory.

Texture and Microstructure of Gelatin/Corn Starch-Based Gummy Confections

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

A regularized nonlinear diffusion approach for texture image denoising

In this paper a new partial differential equation based method is presented with a view to denoising images having textures. The proposed model combines a nonlinear anisotropic diffusion filter with recent harmonic analysis techniques. A wave atom shrinkage allied to detection by gradient technique is used to guide the diffusion process so as to smooth and maintain essential image characteristics. Two forcing terms are used to maintain and improve edges, boundaries and oscillatory features of an image having irregular details and texture. Experimental results show the performance of our model for texture preserving denoising when compared to recent methods in literature. © 2009 IEEE.

Potential use of the veris apparent EC sensor to predict soil texture under the semi-arid conditions of central Arizona

The operational details of the apparent electrical conductivity (ECa) sensor manufactured by Veris Technologies have been extensively documented in literature reports, but the geographical distribution of these research studies indicate a strong regional concentration in the US Mid-west and Southern states. The agricultural lands of these states diverge significantly to the soil conditions and water regime of irrigated land in the US South-western states such as Arizona where there is no previous research reports of the use of this particular sensor. The objectives of the present study were to analyze the performance of this sensor under the conditions of typical soils in irrigated farms of Central Arizona. We tested under static conditions the performance of the sensor on three soils of contrasting texture. Observations were collected as time series data as soil moisture changed from saturation to permanent wilting point. Observations were repeated at the hours of lowest and highest temperatures. In addition, this study included soil penetration resistance and salinity determinations. Preliminary results indicate that soil temperature of the upper layer caused the most dynamic change in the sensor output. The ECa curves of the three soil textures tested had well defined distinctive characteristics. Final multivariate analysis is pending.