Abstract
This paper presents a new methodology for assessing both reliability and well-being indices for composite generation and transmission systems. Firstly, a transmission network reduction is applied to find an equivalent for assessing composite reliability for practical large power systems. After that, in order to classify the operating states, Artificial Neural Networks (ANNs) based on Group Method Data Handling (GMDH) techniques are used to capture the patterns of the operating states, during the beginning of the non-sequential Monte Carlo simulation (MCS). The idea is to provide the simulation process with an intelligent memory, based only on polynomial parameters, to speed up the evaluation of the operating states. For the conventional reliability assessment, the ANNs are used to classify the operating states into success and failure. However, for the well-being analysis, only success states are classified into healthy and marginal by the ANNs. The proposed methodology is applied to the IEEE Reliability Test System 1996 and to a configuration of the Brazilian South-Southeastern System.

Abstract
The design and implementation of multimedia signal processing systems is challenging especially when efficiency and real-time performance is desired. In many modern applications, software systems must be able to handle multiple flows of various types of multimedia data such as audio and video. Researchers frequently have to rely on a combination of different software tools for each modality to assemble proof-of-concept systems that are inefficient, brittle and hard to maintain. Marsyas is a software framework originally developed to address these issues in the domain of audio processing. In this paper we describe MarsyasX, a new open-source cross-modal analysis framework that aims at a broader score of applications. It follows a data ow architecture where complex networks of processing objects can be assembled to form systems that can handle multiple and different types of multimedia flows with expressiveness and efficiency. Copyright 2008 ACM.

Abstract
The performance of electrical devices, depending on the processes of the electrolytes, have been fully described and the physical origin of each parameter is well established. However, the influence of the irregularity of the electrodes was not a subject of study and only recently, this problem became relevant in the viewpoint of fractional calculus. This paper describes an electrolytic process in the perspective of fractional order capacitors. In this line of thought, are developed several experiments for measuring the electrical impedance of the devices. The results are analyzed through the frequency response, revealing capacitances of fractional order that can constitute an alternative to the classical integer order elements.

Abstract
Researchers are giving special attention to innovative healthcare projects in order to reduce medical service costs and to deal with the population ageing. The Virtual e-Care was born taking those goals in mind. An intelligent and proactive system has been prototyped, Supporting group decision making techniques, idea generation, argumentation and the quantification of the quality of information. In this paper it is simulated a virtual Assisted Living Environment, based in a solid agent-based architecture. Special attention is given to the monitoring system.

Abstract

Abstract
This work present and demonstrated an applications of artificial neural network approach in optical sensing. The conventional matrix method used in simultaneous measurement of strain and temperature with optical Bragg gratings is compared with artificial neural network approach. The alternative method is proposed for reduced the error.