In the analysis of combustion processes, simulation is a costefficient tool that complements experimental testing. The simulation models must be precise if subtle differences are to be detected. On the other hand, computational evaluation of precise models typically requires substantial effort. To escape the computational bottleneck, reduced chemical schemes, for example, ILDM-based methods or ...

Template Construction Grammar (TCG) was developed as part of an effort to build a system-level neuro-computational model simulating the dynamics at play during languagevision interactions. This paper presents TCG as a computational framework designed to model the human brain’s capacity to dynamically coordinate two concurrent incremental processes, one generating a message and the other organiz...

We propose a new computational scheme of the Celada-Seiden model (CSmodel) for the simulation of the Immune System response. This new approach is closer to the classical definition of cellular automata than the previous. It has the advantage to achieve the same results obtained with the CSmodel (IMMSIM) with a lower computational effort. keywords: Immune System, CSmodel, Stochastic Cellular Aut...

We use stochastic kriging, a metamodeling technique, to speed up nested simulation of expected shortfall, a portfolio risk measure. Evaluating a risk measure of a portfolio that includes derivative securities may require nested Monte Carlo simulation. The outer level simulates financial scenarios and the inner level of simulation estimates the portfolio value given a scenario. Spatial metamodel...

This paper presents POD-based reduction approach for structural optimization design considering microscopic material nonlinear microstructures. This work introduces Reduced Order Model (ROM) to alleviate the heavy computational demand of nonlinear nested multiscale procedures, particularly in an optimization framework which requires multiple loops involving similar computations. The surrogate m...

Many knowledge acquisition approaches have been proposed to minimize the cognitive effort in knowledgebased system construction. The knowledge acquisition approach proposed here put together the user interaction benefits of semiformal modeling and the computational benefits of formal modeling. Our approach defines a method where the designer first constructs a semiformal model of the design pro...

Test Effort Estimation is an important activity in software development. The test effort can be calculated on the basis of effort cost and time required for testing. Several studies have been done for developing test effort estimation models but to some extent only, most of these models result in erroneous results. So there is a strong need to optimize the efforts estimated. Meta heuristic tech...

We demonstrate that substantial computational savings are attainable in electronic structure calculations using a Cholesky decomposition of the two-electron integral matrix. In most cases, the computational effort involved calculating the Cholesky decomposition is less than the construction of one Fock matrix using a direct O(N) procedure. © 2003 American Institute of Physics. @DOI: 10.1063/1.1...

According to prominent models in cognitive psychology, neuroscience, and economics, effort (be it physical or mental) is costly: when given a choice, humans and non-human animals alike tend to avoid effort. Here, we suggest that the opposite is also true and review extensive evidence that effort can also add value. Not only can the same outcomes be more rewarding if we apply more (not less) eff...

We analyze general model selection procedures using penalized empirical loss minimization under computational constraints. While classical model selection approaches do not consider computational aspects of performing model selection, we argue that any practical model selection procedure must not only trade off estimation and approximation error, but also the computational effort required to co...