Analyzing the degree of conflict among belief functions.

The study of alternative combination rules in DS theory when evidence is in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. These studies have mainly focused on investigating which alternative would be appropriate for which conflicting situation, under the assumption that a conflict is identified. The issue of detection (or identification) of conflict among evidence has been ignored. In this paper, we formally define when two basic belief assignments are in conflict. This definition deploys quantitative measures of both the mass of the combined belief assigned to the emptyset before normalization and the distance between betting commitments of beliefs.We argue that only when both measures are high, it is safe to say the evidence is in conflict. This definition can be served as a prerequisite for selecting appropriate combination rules.

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

Gender influences the detection of spatial working memory deficits in bipolar disorder.

Objective: Despite evidence that gender may influence neurocognitive functioning, few studies have examined its effects in bipolar disorder (BD) a priori. The aim of this study was to examine how gender influences executive-type functions, which are potentially useful as endophenotypes for BD. Methods: The performance of 26 euthymic patients(12 males, 14 females) with DSM-IV BD (20 BD type I and six BD type II) was compared to that of 26 controls (12 males, 14 females) on tests of executive function. Controls were matched to patients on an individual basis for sex, age and premorbid IQ. Tests assessed spatial working memory (SWM), planning, attentional set-shifting and verbal fluency. Results: Overall, patients showed deficits in SWM strategy (p < 0.001) and made more SWM errors relative to controls (p < 0.001). These deficits were more apparent in male-only comparisons (both p < 0.001) than in female-only comparisons (both p < 0.05). When examined in isolation, male controls were significantly better at performing the SWM task than female controls (both p < 0.05). This pattern was not observed in the patient cohort: male patients had poorer strategy scores than female patients (p < 0.05), but made a similar number of SWM errors. Conclusions: These findings provide evidence that gender can influence the detection of SWM deficits in the euthymic phase of BD, as the sex-related disequilibrium in SWM identified in healthy controls was disrupted in BD. © 2008 The Authors Journal compilation © 2008 Blackwell Munksgaard.

The role of Mittag-Leffler functions in anomalous relaxation

The inertia-corrected Debye model of rotational Brownian motion of polar molecules was generalized by Coffey et al. [Phys. Rev. E, 65, 32 102 (2002)] to describe fractional dynamics and anomalous rotational diffusion. The linear- response theory of the normalized complex susceptibility was given in terms of a Laplace transform and as a function of frequency. The angular-velocity correlation function was parametrized via fractal Mittag-Leffler functions. Here we apply the latter method and complex-contour integral- representation methods to determine the original time-dependent amplitude as an inverse Laplace transform using both analytical and numerical approaches, as appropriate. (C) 2004 Elsevier B.V. All rights reserved.

Spectroscopic measurements of phase-resolved electron energy distribution functions in RF-excited discharges

The reliable measurement of the electron energy distribution function (EEDF) of plasmas is one of the most important subjects of plasma diagnostics, because this piece of information is the key to understand basic discharge mechanisms. Specific problems arise in the case of RF-excited plasmas, since the properties of electrons are subject to changes on a nanosecond time scale and show pronounced spatial anisotropy. We report on a novel spectroscopic method for phase- and space-resolved measurements of the electron energy distribution function of energetic (> 12 eV) electrons in RF discharges. These electrons dominate excitation and ionization processes and are therefore of particular interest. The technique is based on time-dependent measurements during the RF cycle of excited-state populations of rare gases admixed in small fractions. These measurements yield � in combination with an analytical model � detailed information on the excitation processes. Phase-resolved optical emission spectroscopy allows us to overcome the difficulties connected with the very low densities (107�109 cm�3) and the transient character of the electrons in the sheath region. The EEDF of electrons accelerated in the sheath region can be described by a shifted Maxwellian with a drift velocity component in direction of the electric field. The method yields the high-energy tail of the EEDF on an absolute scale. The applicability of the method is demonstrated at a capacitively coupled RF discharge in hydrogen.