Showing papers in "Journal of Computational Science in 2016"

TL;DR: Alya's main features are introduced and focus particularly on its solvers and the performance up to 100.000 processors in Blue Waters, the NCSA supercomputer with selected multi-physics tests that are representative of the engineering world.

TL;DR: A new well-optimized structure for three-input Exclusive-OR gate (TIEO) is proposed that is based on cell interaction and a low complexity and ultra-high speed QCA one-bit full-adder cell is designed employing this structure.

TL;DR: The role of uncertainty in the resource and service provisioning, privacy, etc, especially, in the presence of the risks of confidentiality, integrity, and availability is discussed, and fundamental approaches for scheduling under uncertainty are reviewed.

TL;DR: A new efficient global optimization method is proposed, referred to as multi-fidelity Gaussian process and radial basis function-model-assisted memetic differential evolution, which substantially improves reliability and efficiency of optimization compared to many existing methods.

TL;DR: GA-ETI is proved to reduce makespan of executing workflows between 11% and 85% when compared to three up-do-date scheduling algorithms without increasing the monetary cost.

TL;DR: Experimental results from a set of six stocks show the superiority of the hybrid VMD–PSO–BPNN predictive model over the baseline predictive model which is a PSO– BPNN model trained with past prices.

TL;DR: A multi-layer classifier ensemble framework is proposed based on the optimal combination of heterogeneous classifiers that overcomes the limitations of conventional performance bottlenecks by utilizing an ensemble of seven heterogeneousclassifiers.

TL;DR: The main contribution of this study is proposing extraordinary motion for particles in the PSO, so called extraordinariness particle swarm optimizer (EPSO) which outperforms than the standard PSO and its variants for benchmarks such as CEC 2015 benchmarks.

TL;DR: A powerful classification scheme that exclusively uses the natural language text from organic users to provide a criterion for identifying accounts posting automated messages, which is flexible and may be applied to any textual data beyond the Twitter-sphere.

TL;DR: A systematic quantitative performance study for large finite element computations on extreme scale computing systems and an all-at-once multigrid method for the saddle point system using an Uzawa-type smoother provides the best overall performance with respect to memory consumption and time-to-solution.

TL;DR: The primary conclusions were: Hydrogens do not require either polarization or diffuse functions, not even when the potential of interest is on the hydrogen, and Polarization functions are essential, for first-row as well as higher-row atoms; diffuse functions are less important.

TL;DR: A comparison between the results proves that the proposed nonlocal multiscale method can accurately predict the damage phenomena inside the clay/epoxy nanocomposites with minimal computational costs.

TL;DR: The empirical results obtained over a set of stock market indices from different international markets show that all hybrid models perform better than the individual PSVM prediction model, and suggest the superiority of a certain set of indicators over other indicators in achieving better results.

TL;DR: An effective cloud computing architecture is proposed which predicts H1N1 infected patients and provides preventions to control infection rate and the use of SNA graphs to calculate role of an infected user in spreading the outbreak known as Outbreak Role Index (ORI).

TL;DR: Numerical simulations using the Lattice Boltzmann Method show that non-equilibrium effects enhance the reactivity of the porous sample, in agreement with theoretical predictions, and provide a quantitative assessment of the reactsivity in terms of the thickness of the reactive layer inside the nanoporous catalytic sample.

TL;DR: This paper focuses on the searching for d -MPs by given MPs in terms of fast enumeration (FE), which was a recent advance in the integer programming problems in the literature.

TL;DR: It is found that increasing confinement ratio will enhance deformation, and the maximum deformation occurs at the viscosity ratio of unity, while the critical capillary number, above which the droplet breakup occurs, is found to be mildly affected by the confinement.

TL;DR: It is shown that the targeted immunization is better than the random immunization for controlling malware spreading in SFNs and the proposed model, which considers software diversity, is more effective than other existing epidemic models.

TL;DR: A survival prediction model to define three month mortality of patients after Liver Transplantation and compared with other classification models using various error performance measures is proposed.

TL;DR: A novel nanoscopic city-scale traffic simulation based method for determining charging infrastructure locations is proposed and its usefulness in spatio-temporal planning is demonstrated through a case-study of Singapore.

TL;DR: A solution strategy is developed and complete solutions for such optimization problem are obtained in one-, two-, and three-dimensions up to 9th order.

TL;DR: In this article, a kinetic mapping scheme between the Direct Simulation Monte Carlo (DSMC) and the Lattice Boltzmann Method (LBM) is proposed to simulate isothermal flows characterized by variable rarefaction effects.

TL;DR: By introducing a non-convex and non-differentiable loss function based on the ɛ-insensitive loss function, RLSSVM has several improved advantages compared with the plain LSSVM: firstly, it has the sparseness which is controlled by the ramp loss, leading to its better scaling properties.

TL;DR: It is demonstrated that current computing capabilities allow the direct pore-scale simulation of fluid flow in porous materials using system sizes far beyond what has been previously reported.

TL;DR: A new approach for solving RTE by LBM, referred to as RTLBM, is proposed for D 3 Q 7 grids, and it is shown by a Chapman–Enskog expansion, that the proposed RTLB equation solves the corresponding macroscopic target diffusion equation with additional sink term.

TL;DR: The developed method can be used to reveal the seismic mechanisms of concrete structures by considering the trans-level coupling process from meso-damage to local failure in vulnerable component and eventually to structural failure in a concurrent way and is reliable in simulation on the seismic performance of large scale concrete-based structures with the adaptive capability.

TL;DR: The results of the comparative studies reveal that the developed IRkFPCA method provides a better performance in terms of modeling and fault detection accuracies than the Iterated Robust Fuzzy Principal Component Analysis (IRFPC a) and Iterated kernel Principal Component analysis (IkPCA) methods; while both methods provide improved accuracy.

TL;DR: The reimplementation of four popular feature selection algorithms included in Weka is the focus of this work, with results obtained from tests on real-world datasets showing that the new versions offer significant reductions in processing times.

TL;DR: The proposed framework for a surrogate-based stochastic search algorithm for multi-objective and constrained black-box optimization where the objective and constraint function values are outputs of computationally expensive computer simulations is implemented using radial basis function (RBF) surrogate models and compared with alternative methods.

TL;DR: The study provides unprecedented insight into the interfacial regions between two colliding droplets and verified and extended the current gas film theory for the bounce regime through including the effects of evaporated water molecules (vapour).