2 resultados para Bootstrap truncated regression

em Universidade Federal do Rio Grande do Norte(UFRN)


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Due to its high resolution, Ground Penetrating Radar (GPR) has been used to image subsurface sedimentary deposits. Because GPR and Seismic methods share some principles of image construction, the classic seismostratigraphic interpretation method has been also applied as an attempt to interpret GPR data. Nonetheless some advances in few particular contexts, the adaptations from seismic to GPR of seismostratigraphic tools and concepts unsuitable because the meaning given to the termination criteria in seismic stratigraphy do not represent the adequate geologic record in the GPR scale. Essentially, the open question relies in proposing a interpretation method for GPR data which allow not only relating product and sedimentary process in the GPR scale but also identifying or proposing depositional environments and correlating these results with the well known Sequence Stratigraphy cornerstones. The goal of this dissertation is to propose an interpretation methodology of GPR data able to perform this task at least for siliciclastic deposits. In order to do so, the proposed GPR interpretation method is based both on seismostratigraphic concepts and on the bounding surface hierarchy tool from Miall (1988). As consequence of this joint use, the results of GPR interpretation can be associated to the sedimentary facies in a genetic context, so that it is possible to: (i) individualize radar facies and correlate them to the sedimentary facies by using depositional models; (ii) characterize a given depositional system, and (iii) determine its stratigraphic framework highligthing how it evolved through geologic time. To illustrate its use the proposed methodology was applied in a GPR data set from Galos area which is part of the Galinhos spit, located in Rio Grande do Norte state, Northeastern Brazil. This spit presents high lateral sedimentary facies variation, containing in its sedimentary record from 4th to 6th cicles caused by high frequency sea level oscillation. The interpretation process was done throughout the following phases: (i) identification of a vertical facies succession, (ii) characterization of radar facies and its associated sedimentary products, (iii) recognition of the associated sedimentary process in a genetic context, and finally (iv) proposal of an evolutionay model for the Galinhos spit. This model proposes that the Galinhos spit is a barrier island constituted, from base to top, of the following sedimentary facies: tidal channel facies, tidal flat facies, shore facies, and aeolic facies (dunes). The tidal channel facies, in the base, is constituted of lateral accretion bars and filling deposits of the channels. The base facies is laterally truncated by the tidal flat facies. In the foreshore zone, the tidal flat facies is covered by the shore facies which is the register of a sea transgression. Finally, on the top of the stratigraphic column, aeolic dunes are deposited due to areal exposition caused by a sea regression

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Foundations support constitute one of the types of legal entities of private law forged with the purpose of supporting research projects, education and extension and institutional, scientific and technological development of Brazil. Observed as links of the relationship between company, university, and government, foundations supporting emerge in the Brazilian scene from the principle to establish an economic platform of development based on three pillars: science, technology and innovation – ST&I. In applied terms, these ones operate as tools of debureaucratisation making the management between public entities more agile, especially in the academic management in accordance with the approach of Triple Helix. From the exposed, the present study has as purpose understanding how the relation of Triple Helix intervenes in the fund-raising process of Brazilian foundations support. To understand the relations submitted, it was used the interaction models University-Company-Government recommended by Sábato and Botana (1968), the approach of the Triple Helix proposed by Etzkowitz and Leydesdorff (2000), as well as the perspective of the national innovation systems discussed by Freeman (1987, 1995), Nelson (1990, 1993) and Lundvall (1992). The research object of this study consists of 26 state foundations that support research associated with the National Council of the State Foundations of Supporting Research - CONFAP, as well as the 102 foundations in support of IES associated with the National Council of Foundations of Support for Institutions of Higher Education and Scientific and Technological Research – CONFIES, totaling 128 entities. As a research strategy, this study is considered as an applied research with a quantitative approach. Primary research data were collected using the e-mail Survey procedure. Seventy-five observations were collected, which corresponds to 58.59% of the research universe. It is considering the use of the bootstrap method in order to validate the use of the sample in the analysis of results. For data analysis, it was used descriptive statistics and multivariate data analysis techniques: the cluster analysis; the canonical correlation and the binary logistic regression. From the obtained canonical roots, the results indicated that the dependency relationship between the variables of relations (with the actors of the Triple Helix) and the financial resources invested in innovation projects is low, assuming the null hypothesis of this study, that the relations of the Triple Helix do not have interfered positively or negatively in raising funds for investments in innovation projects. On the other hand, the results obtained with the cluster analysis indicate that entities which have greater quantitative and financial amounts of projects are mostly large foundations (over 100 employees), which support up to five IES, publish management reports and use in their capital structure, greater financing of the public department. Finally, it is pertinent to note that the power of the classification of the logistic model obtained in this study showed high predictive capacity (80.0%) providing to the academic community replication in environments of similar analysis.