Abstract

Abstract
The Internet is characterized by the coexistence of two Internet Protocol (IP) versions and multiple autoconfiguration mechanisms which are deployed targeting specific communication scenarios. This heterogeneity requires user pre-configurations, namely with respect to the proper autoconfiguration mechanism to be used at each time. On the other hand, future networks may imply that users own personal networks demanding self-configuration and self-management, and being part of very dynamic scenarios. In this paper we make a survey of the autoconfiguration mechanisms available for IP networks, and argue that a new solution is needed, so that the proper autoconfiguration mechanism can be selected automatically, dynamically and efficiently, and future communication paradigms can be properly addressed. Copyright 2005 ACM.

Abstract
This paper proposes and analyses the performance of a Genetic Algorithm (GA) using two new concepts, namely a static fitness function including a discontinuity measure and a fractional-order dynamic fitness function. The GA is adopted for the synthesis of combinational logic circuits. In both cases, experiments reveal superior results in terms of speed and convergence to achieve a solution.

Abstract
Recent investigations suggest that there are differences between the characteristics of EEG and MEG epileptiform spikes. The authors performed an objective characterization of the morphology of epileptiform spikes recorded simultaneously in both EEG and MEG to determine whether they present the same morphologic characteristics. Based on a stepwise approach, the authors performed a computer analysis of EEG and MEG of a set of coincident epileptiform transients selected by a senior clinical neurophysiologist in recordings of three patients with drug-resistant epilepsy. A computer-based algorithm was applied to extract parameters that could be used to describe quantitatively the morphology of the transients, followed by a statistical comparison over the extracted metrics of the EEG and MEG waveforms. EEG and MEG coincident events were statistically different with respect to several morphologic characteristics, such as duration, sharpness, and shape. The differences found appear to be a consequence of MEG signals not being influenced by volume propagation through the tissues with different conductivities that surround the brain, compared with EEG, and of the different orientation of the underlying dipolar sources. The results indicate that visual inspection of MEG spikes and automatic spike-detector algorithms should use criteria adapted to the specific characteristics of the MEG, and not simply those used on conventional EEG.

Abstract
Cosmetic assessment or conservative breast cancer treatment plays a major role in the study of breast cancer techniques. Objective assessment methods are being preferred to overcome the drawbacks of subjective evaluation. In this paper a methodology for the objective assessment of conservative breast cancer treatment is proposed. The quantitative measures used in this research provide an objective way to calculate the overall cosmetic result. We report experiments using support vector machines to derive an optimal assessment rule. The results seem to indicate that it is possible to construct an algorithm for a complete objective classification of the aesthetic result of breast conservative treatment.

Abstract
The paper proposes a dependability model to evaluate the behavior of a CAN network in scenarios of transient faults which affect data communications. Fault occurrence is modeled by a Markov Modulated Poisson Process (MMPP) which is capable to describe the typical behavior of electromagnetic interferences (EMI) that occur in industrial environments. An accurate and efficient representation of the network behavior is achieved by adopting a set of assumptions that reduce the pessimism level and which are closer to the real operating conditions. The model is based on Stochastic Petri Nets, which are a high-level modeling formalism able to produce very compact and efficient models, supporting both analytical and simulation solutions. Dependability measures are established from the fulfillment of the real-time constraints (deadlines) defined on messages exchanged between network nodes. Analytical and simulation solutions are both investigated. A case study is proposed to asses both model performance and network dependability. Copyright © 2005 IFAC.