This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Scientific experiments produce large volumes of data represented as complex objects that describe independent events such as particle collisions. Scientific analyses can be express...
A simple, tunable, synthetic benchmark with a performance directly related to applications would be of great benefit to the scientific computing community. In this paper, we prese...
Efficient data management is a key component in achieving good performance for scientific workflows in distributed environments. Workflow applications typically communicate data be...
In physics, structure of glass and ion trajectories are essentially based on statistical analysis of data acquired through experimental measurement and computer simulation [1, 2]. ...
J. M. Sharif, M. Mahadi Abdul Jamil, Md. Asri Ngad...