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Dimitroulis C.,Applied Computational Technologies | Raptis T.,Applied Computational Technologies | Raptis V.,Greek National Center For Scientific Research
Computer Physics Communications | Year: 2015

We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules. Program summary: Program title: Polyana. Catalogue identifier: AEXP_v1_0. Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEXP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland. Licensing provisions: MIT License. No. of lines in distributed program, including test data, etc.: 33638. No. of bytes in distributed program, including test data, etc.: 574799. Distribution format: tar.gz. Programming language: Fortran. Computer: Any computer that can run a Fortran compiler. Operating system: Tested on CentOS 6.6, Ubuntu 12.04 and Ubuntu 15.04. RAM: Proportional to the size of the simulated system (number of atoms). Classification: 4.14, 7.7. Nature of problem: Computation of radial distribution functions of molecular centres of mass in systems subjected to Periodic Boundary Conditions. Solution method: Molecules of arbitrary topology are 'unfolded' using a generic algorithm and their centres of mass are computed; then, standard procedures are applied. Additional comments: The code has been designed with ease of use in mind; in most cases, no user input will be required, except the simulation input/output files. Abbreviations: RDF: Radial Distribution Function PBC: Periodic Boundary Conditions. Running time: Of the order of seconds to minutes, depending on platform and simulation size. © 2015 Elsevier B.V.


Koutroumbas K.,Institute for Space Applications and Remote Sensing | Bakopoulos Y.,Applied Computational Technologies
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

In this paper the problem of the approximation of decision regions bordered by (a) closed and/or (b) open and unbounded convex hypersurfaces using feedforward neural networks (FNNs) with hard limiter nodes is considered. Specifically, a constructive proof is given for the fact that a two or a three layer FNN with hard limiter nodes can approximate with arbitrary precision a given decision region of the above kind. This is carried out in three steps. First, each hypersurface is approximated by hyperplanes. Then each one of the regions formed by the hypersurfaces is appropriately approximated by regions defined via the previous hyperplanes. Finally, a feedforward neural network with hard limiter nodes is constructed, based on the previous hyperplanes and the regions defined by them. © Springer-Verlag Berlin Heidelberg 2010.


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