We study a multiscale discontinuous Galerkin method introduced in [10] that reduces the computational complexity of the discontinuous Galerkin method, seemingly without adversely affecting the quality of results. For a stabilized variant we are able to obtain the same error estimates for the advection-diffusion equation as for the usual discontinuous Galerkin method. We assess the stability of ...

Evolutionary design of time series predictors is a field that has been explored for several years now. The levels of design vary in the many works reported in the field. We decided to perform a complete design and training of ARIMA models using Evolutionary Computation. This decision leads to high dimensional search spaces, whose size increases exponentially with dimensionality. In order to red...

We compare the performance of an intensity based nonparametric image registration algorithm and extensions applied to frame interpolation of mouth images. The mouth exhibits large deformations due to different shapes, additionally some facial features occlude others, e.g. the lips cover the teeth. The closures and disclosures represent a challenging problem, which cannot be solved by the tradit...

India gives utmost importance to alleviate malnourishment, health problems in order to reach low Infant Mortality Rate (IMR) & Maternal Mortality Rate (MMR) as indicated in Millennium Development Goals (MDGs) by 2015. Society for Elimination of Rural Poverty (SERP), Andhra Pradesh with the support of World Bank has brought a unique model namely Community Managed Nutrition cum Day Care Centres (...

The combination of multiple classifiers to generate a single classifier has been shown to be very useful in practice. Similarly, several efforts have shown that cluster ensembles can improve the quality of results as compared to a single clustering solution. These observations suggest that ensembles containing both classifiers and clusterers are potentially useful as well. Specifically, cluster...

Deformable models are by their formulation able to solve surface extraction problem from noisy volumetric images. This is since they use image independent information, in form of internal energy or internal forces, in addition to image data to achieve the goal. However, it is not a simple task to deform initially given surface meshes to a good representation of the target surface in the presenc...

In this work, we consider the problem to personalize user’s Web searches for improving the quality of results. To this aim, we propose a preliminary methodology that allows to define a conceptual user profile based on the YAGO ontology.

Modern logic and physical synthesis tools provide numerous options and parameters that can drastically impact design quality; however the large number of options leads to a complex design space difficult for human circuit designers to navigate. We tackle this parameter tuning problem with a novel system employing intelligent search strategies and parallel computing, thus automating one of the k...

We propose an approach to semantic (image) segmentation that reduces the computational costs by a factor of 25 with limited impact on the quality of results. Semantic segmentation has a number of practical applications, and for most such applications the computational costs are critical. The method follows a typical two-column network structure, where one column accepts an input image, while th...

While most knowledge engineers believe that the quality of results obtained by means of Bayesian networks is not too sensitive to imprecision in probabilities, this remains a conjecture with only modest empirical support. We summarize the results of several previously presented experiments involving Hepar II model, in which we manipulated the quality of the model’s numerical parameters and chec...