2 resultados para domain analysis
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
This work presents a theoretical analysis and numerical and experimental results of the scattering characteristics of frequency selective surfaces, using elements of type patch perfectly conductor. The structures are composed of two frequency selective surfaces on isotropic dielectric substrates cascaded, separated by a layer of air. The analysis is performed using the method of equivalent transmission line in combination with the Galerkin method, to determine the transmission and reflection characteristics of the structures analyzed. Specifically, the analysis uses the impedance method, which models the structure by an equivalent circuit, and applies the theory of transmission lines to determine the dyadic Green's function for the cascade structure. This function relates the incident field and surface current densities. These fields are determined algebraically by means of potential incidents and the imposition of the continuity of the fields in the dielectric interfaces. The Galerkin method is applied to the numerical determination of the unknown weight coefficients and hence the unknown densities of surface currents, which are expanded in terms of known basis functions multiplied by these weight coefficients. From the determination of these functions, it becomes possible to obtain numerical scattered fields at the top and bottom of the structures and characteristics of transmission and reflection of these structures. At work, we present numerical and experimental results for the characteristics of transmission and reflection. Comparisons were made with other results presented in literature, and it was observed a good agreement in the cases presented suggestions continuity of the work are presented
Resumo:
Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.