20 resultados para binary to multi-class classifiers
Resumo:
Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.
Resumo:
Social businesses present a new paradigm to capitalism, in which private companies, non-profit organizations and civil society create a new type of business with the main objective of solving social problems with financial sustainability and efficiency through market mechanisms. As any new phenomenon, different authors conceptualize social businesses with distinct views. This article aims to present and characterize three different perspectives of social business definitions: the European, the American and that of the emerging countries. Each one of these views was illustrated by a different Brazilian case. We conclude with the idea that all the cases have similar characteristics, but also relevant differences that are more than merely geographical. The perspectives analyzed in this paper provide an analytical framework for understanding the field of social businesses. Moreover, the cases demonstrate that in the Brazilian context the field of social business is under construction and that as such it draws on different conceptual influences to deal with a complex and challenging reality.
Resumo:
Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.
Resumo:
It has been shown that HLA class I molecules play a significant role in the regulation of the proliferation of T cells activated by mitogens and antigens. We evaluated the ability of mAb to a framework determinant of HLA class I molecules to regulate T cell proliferation and interferon gamma (IFN-g) production against leishmania, PPD, C. albicans and tetanus toxoid antigens in patients with tegumentary leishmaniasis and healthy subjects. The anti-major histocompatibility complex (MHC) mAb (W6/32) suppressed lymphocyte proliferation by 90% in cultures stimulated with aCD3, but the suppression was variable in cultures stimulated with leishmania antigen. This suppression ranged from 30-67% and was observed only in 5 of 11 patients. IFN-g production against leishmania antigen was also suppressed by anti-HLA class I mAb. In 3 patients IFN-g levels were suppressed by more than 60%, while in the other 2 cultures IFN-g levels were 36 and 10% lower than controls. The suppression by HLA class I mAb to the proliferative response in leishmaniasis patients and in healthy controls varied with the antigens and the patients or donors tested. To determine whether the suppression is directed at antigen presenting cells (APCs) or at the responding T cells, experiments with antigen-primed non-adherent cells, separately incubated with W6/32, were performed. Suppression of proliferation was only observed when the W6/32 mAb was added in the presence of T cells. These data provide evidence that a mAb directed at HLA class I framework determinants can suppress proliferation and cytokine secretion in response to several antigens.