Abstract
The multi-stream based automatic speech recognisers can obtain higher recognition rates than the conventional systems. This advantage is particularly evident on recognition tasks where the robustness to certain types of noise is critical, which is a very important issue in real-world applications. However most of the multi-stream based approaches remain limited to a research topic due to their higher computation complexity. The fact of this problem has not been addressed satisfactorily in the literature is the main motivation for this study. In our work we investigated the acceleration of the acoustic likelihoods computation, the most time consuming part of the whole recogniser. This paper presents results on the computational complexity of the Gaussian mixture emissions estimation in a multi-stream statistical framework. Some results concerning the recognition performance dependence on the numeric precision at different stages of that process are presented too. In order to achieve a higher acceleration of some critical computation blocks, a hardware implementation is proposed, based on the Field Programmable Gate Array (FPGA) technology.

Abstract
The emerging standard for the platform- and system-independent representation of data mining models PMML (Predictive Model Markup Language) is currently supported by a number of knowledge discovery support engines. The primary purpose of the PMML standard is to separate model generation from model storage in order to enable users to view, post-process, and utilize data mining models independently of the tool that generated the model. In this paper two systems, called VizWiz and PEAR, are described. These software packages allow for the visualization and evaluation of data mining models that are specified in PMML. They can be viewed. as decision support systems, since they enable non-expert users of data mining results to interactively inspect and evaluate these results.

Abstract
In this paper we report the implementation of fiber Bragg gratings with variable negative mean refractive index perturbation, in a highly germanium-doped fiber, resultant from a type IIa exposition regime. The obtained grating presents a favorable group delay characteristic for dispersion compensation applications with reduced bandwidth.

Abstract
In this paper, we describe an integrated methodology to compute long-term marginal prices in distribution networks. Long-term marginal prices are considered the most interesting and economically sound way of allocating network costs to users. Additionally, they inherently deal with the revenue reconciliation problem, as they generally do not require other large supplementary tariff terms. The proposed methodology uses fuzzy sets to model uncertainties in load forecasts and considers several criteria to guide the identification of solutions. At the end, there is a final decision-making step to select the most adequate expansion plan according to the preferences of the decision maker.

Abstract

Abstract
In this paper a new method of estimation of the induction motor electric parameters is presented and discussed. The proposed method uses the indirect approach that consists in estimating the continuous-time parameters by first fitting a discrete-time model to the data and then converting this model to a continuous-time version. The main contribution is that by using a polynomial pre-filter it is possible to compute the induction motor equivalent circuit parameters via an inverse transformation between the discrete-time and the continuous-time models. The procedure is potentially useful for the design of self-commissioning drives and may provide initial estimates to extended Kalman filtering type of procedures. The effectiveness of the proposed method is verified by simulated tests and results of the method are discussed.