Feature selection, as a preprocessing step to machine learning, is effective in reducing di-mensionality, removing irrelevant data, in-creasing learning accuracy, and improving result comprehensibility. However, the re-cent increase of dimensionality of data poses a severe challenge to many

G). We describe a series of adaptations to the Par-allel Tracking and Mapping system to mitigate the impact of the device’s imaging deficiencies. Early results demonstrate a system capable of generating and augmenting small maps, albeit with re-duced accuracy and robustness compared to SLAM on a PC

behavior may fail to match an acceptable behavior of the SUT, leading to many false positives reported by the oracle. We propose an automated steering framework that can adjust the behavior of the model to better match the behavior of the SUT to re-duce the rate of false positives. This model steering

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The first re-duces parameter space by imposing long

interference, measurement noise, etc., and may not accurately characterize the true speech spectrum because of analysis model constraints. We have found that these undesirable spectral measurement variations can be partially controlled (i.e., re-duced in the level of variation) by appropriate signal

Homogeneous difference schemes, the general definition of which is given in [I], were considered from the point of view of their application to equations of the parabolic type with one space variable in [21-151. Since the problem of the convergence of difference schemes can be re-duced

of Horn clauses by repeated selection, mutation and optimization of more fit clauses. Its main novelty, with respect to previous approaches, is the use of stochastic search biases for re-ducing the complexity of the search process and of the clause fitness evaluation. An ex-perimental evaluation

ENDscript 2 is a friendly Web server for extracting and rendering a comprehensive analysis of primary to quaternary protein structure information in an au-tomated way. This major upgrade has been fully re-engineered to enhance speed, accuracy and usabil-ity with interactive 3D visualization

simple and stable im-plementation of the algorithm. Novel features of the approach in-clude the determination of the Laguerre parameter as a function of bandwidth and testing the accuracy of the results in terms of both amplitude and phase. Index Terms—Laguerre functions, Padé approximation, re-duced

This paper proposes a novel method to estimate and to re-duce redundant power of synchronous circuits at RT level design. Because much redundant power is caused by redun-dant clockings which activate registers unnecessarily, we de-tect these clockings. They are detected from the difference