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Similarity solutions of partial differential equations using DESOLV  Original Research Article
Computer Physics Communications, Volume 176, Issues 11-12, June 2007, Pages 682-693
K.T. Vu, J. Butcher, J. Carminati
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36

A GUI application for creating macrofiles in GATE  Original Research Article
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Volume 569, Issue 2, 20 December 2006, Pages 378-380
S. Boukis N. Sakellios, G. Loudos, K. Nikita
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AbstractAbstract | Figures/TablesFigures/Tables | ReferencesReferences
Abstract
GEANT4 Application for Tomographic Emission (GATE) is a Monte Carlo simulation toolkit based on GEANT4 for PET and SPECT. GATE uses a high intuitive linear script language in a way that the code describing a system can be thought as a combination of separate objects, each one with certain parameters. The above structure of GATE's script language implies that by defining all the parameters involved in a certain implementation, the macrofiles can be created automatically, using appropriate software. The Gate Editor project, based on the above idea, aims the development of a homonym window application that exports GATE scripts based on easy to understand parameters given by the end user. Gate Editor is developed using the C++ program language in Linux environment. A WindowsXP version is also available. Object Oriented Programming allows the description of PET/SPECT system components with relative objects belonging to corresponding classes. Gate Editor is able to export macrofiles of low complicity (like the SPECT and PET benchmarks supplied with GATE). Objects such as collimator, crystal, detector blocks and sources can be described in the ‘real world’ and automatically constructed in ‘GATE world’. The relative position of these objects is adjusted as well, all under a user-friendly interface. The end user can create his own code without concerning for the exact syntax of GATE's script language. For more realistic and complicated implementations though, further development is required.
Article Outline
1. Introduction
1.1. GEANT4 Application for Tomographic Emission (GATE) simulation platform
1.2. Gate Editor
2. Materials and methods
3. Application environment
3.1. World definition
3.2. Inserting a new object
4. Discussion
References

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37

A real time collaboration system for teleradiology consultation  
International Journal of Medical Informatics, Volume 72, Issues 1-3, December 2003, Pages 73-79
Jiann-Shu Lee, Ching-Tsorng Tsai, Chen-Hsing Pen, Hui-Chieh Lu
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Abstract
Real time collaboration systems, in which participants share multimedia data and applications in real time, have attracted many researchers in recent years. A teleradiology consultation system based on the real time collaboration technology is presented in this paper. Under the platform-independence consideration, Java technologies are employed to construct the system. Applying this system, an off-duty on-call radiologist can make diagnoses and report easily by viewing the transferred images at home. Owing to the accessibility of image, all users can examine and manipulate images consistently such that a secluded hospital can be assisted to hold remote consultation. To reduce the network transmission time, the command-passing and local command execution techniques are utilized to achieve the screen synchronization. A pointer function is also developed to maintain the cursor consistency in a more efficient manner during consultation when a detail indication of the examined image is needed. Besides, a dialog window is also designed for on-line conversation. Since Java programs can run on heterogeneous platforms, the need for system maintenance and user training can be substantially reduced.
Article Outline
1. Introduction
2. Methods
2.1. System design
2.2. System operation
2.3. System implementation
3. Results
4. Discussion
5. Conclusions
Acknowledgements
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38

The open source RFortran library for accessing R from Fortran, with applications in environmental modelling  Original Research Article
Environmental Modelling & Software, Volume 26, Issue 2, February 2011, Pages 219-234
Mark Thyer, Michael Leonard, Dmitri Kavetski, Stephen Need, Benjamin Renard
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Abstract
The open source RFortran library is introduced as a convenient tool for accessing the functionality and packages of the R programming language from Fortran programs. It significantly enhances Fortran programming by providing a set of easy-to-use functions that enable access to R′s very rapidly growing statistical, numerical and visualization capabilities, and support a richer and more interactive model development, debugging and analysis setup. RFortran differs from current approaches that require calling Fortran Dynamic link libraries (DLL) from R, and instead enables the Fortran program to transfer data to/from R and invoke R-based procedures via the R command interpreter. More generally, RFortran obviates the need to re-organize Fortran code into DLLs callable from R, or to re-write existing R packages in Fortran, or to jointly compile their Fortran code with the R language itself. Code snippets illustrate the basic transfer of data and commmands to and from R using RFortran, while two case studies discuss its advantages and limitations in realistic environmental modelling applications. These case studies include the generation of automated and interactive inference diagnostics in hydrological model calibration, and the integration of R statistical packages into a Fortran-based numerical quadrature code for joint probability analysis of coastal flooding using numerical hydraulic models. Currently, RFortran uses the Component Object Model (COM) interface for data/command transfer and is supported on the Microsoft Windows operating system and the Intel and Compaq Visual Fortran compilers. Extending its support to other operating systems and compilers is planned for the future. We hope that RFortran expedites method and software development for scientists and engineers with primary programming expertise in Fortran, but who wish to take advantage of R′s extensive statistical, mathematical and visualization packages by calling them from their Fortran code. Further information can be found at www.rfortran.org.
Article Outline
1. Background and motivation
1.1. Fortran
1.2. The R project
1.3. Current interoperability of R and Fortran
1.4. RFortran
1.5. Outline of the presentation
2. Using RFortran
2.1. Core functionality
2.2. Basic usage of RFortran
2.21. Example 1 – transferring data to R and plotting a simple graph
2.2.2. Example 2 – transferring data to R functions and returning results to Fortran
2.2.3. Example 3 – Using Fortran wrappers for a series of RFortran/R commands
2.2.4. Example 4 – using R scripts and Rcall for a series of RFortran/R commands
2.2.5. Example 5 – using RFortran for interactive debugging
2.3. Error handling and debugging
2.4. System requirements and installation
3. Structure and organization of RFortran
3.1. The COM architecture
3.2. Components of RFortran
3.3. Linking with RFortran
4. Summary of key capabilities of RFortran
5. Case study 1: diagnostics for Bayesian inference in hydrology
5.1. Background
5.2. Motivation for using Fortran and RFortran
5.2.1. Interactive MCMC convergence diagnostics
5.2.2. Automated Bayesian posterior diagnostics
5.3. Outline of BATEA diagnostics
5.4. Integration of R visualization into Fortran using RFortran
5.4.1. Interactive MCMC convergence diagnostics
5.4.2. Automated Bayesian posterior diagnostics
5.5. Benefits of using RFortran
5.5.1. Interactive MCMC convergence diagnostics
5.5.2. Automated generation of posterior diagnostics
6. Case study 2: exploiting R copula packages for flood modelling
6.1. Background
6.2. Motivation for using RFortran
6.3. Integration of R computation into Fortran using RFortran
6.4. Benefits of using RFortran
7. Comparison to alternatives: advantages and limitations
7.1. RFortran versus the “R calls Fortran DLLs” approach
7.2. Jointly compiling Fortran code with the R language
7.3. Alternative COM implementations
8. Towards a unified bi-directional interface between Fortran and R
9. Future work
10. Conclusions
Acknowledgements
References

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39

Object-oriented and distributed approach for programming robotic manufacturing cells  Original Research Article
Robotics and Computer-Integrated Manufacturing, Volume 16, Issue 1, February 2000, Pages 29-42
J. Norberto Pires, J. M. G. Sá da Costa
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AbstractAbstract
Abstract
Flexible manufacturing systems (FMS) are essential for small/medium batch and job shop manufacturing. These types of production systems are used to manufacture a considerable variety of products with medium/small production volumes. Therefore, the manufacturing platforms supporting these types of production must be flexible and organized in flexible manufacturing cells (FMC). Programming FMCs remains a difficult task and is an actual area of research and development. This paper reports an object-oriented approach developed for FMC programming. The work presented was first thought for application in industrial robot manipulators, and later extended to other FMC equipments just by putting the underlying ideas in a general framework. Initially, the motivation for this work was to develop means to add force control to a standard industrial robot manipulator. This problem requires remote access to the robot controller, remote programming and monitoring, as also is required to program and monitor any other FMC equipment. The proposed approach is distributed based on a client/server model and runs on Win32 platforms, i.e., Microsoft Windows and Windows NT. Implementation for the special case of industrial robot manipulators is presented, along with some application examples used for educational, research and industrial purposes.

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A computer program for two-particle generalized coefficients of fractional parentage  Original Research Article
Computer Physics Communications, Volume 179, Issue 8, 15 October 2008, Pages 607-613
A. Deveikis, A. Juodagalvis
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Abstract
We present a FORTRAN90 program GCFP for the calculation of the generalized coefficients of fractional parentage (generalized CFPs or GCFP). The approach is based on the observation that the multi-shell CFPs can be expressed in terms of single-shell CFPs, while the latter can be readily calculated employing a simple enumeration scheme of antisymmetric A-particle states and an efficient method of construction of the idempotent matrix eigenvectors. The program provides fast calculation of GCFPs for a given particle number and produces results possessing numerical uncertainties below the desired tolerance. A single j-shell is defined by four quantum numbers, (e,l,j,t).
A supplemental C++ program parGCFP allows calculation to be done in batches and/or in parallel.
Program summary
Program title: GCFP, parGCFP
Catalogue identifier: AEBI_v1_0
Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEBI_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html
No. of lines in distributed program, including test data, etc.: 17 199
No. of bytes in distributed program, including test data, etc.: 88 658
Distribution format: tar.gz
Programming language: FORTRAN 77/90 (GCFP), C++ (parGCFP)
Computer: Any computer with suitable compilers. The program GCFP requires a FORTRAN 77/90 compiler. The auxiliary program parGCFP requires GNU-C++ compatible compiler, while its parallel version additionally requires MPI-1 standard libraries
Operating system: Linux (Ubuntu, Scientific) (all programs), also checked on Windows XP (GCFP, serial version of parGCFP)
RAM: The memory demand depends on the computation and output mode. If this mode is not 4, the program GCFP demands the following amounts of memory on a computer with Linux operating system. It requires around 2 MB of RAM for the A=12 system at Ex2. Computation of the A=50 particle system requires around 60 MB of RAM at Ex=0 and 70 MB at Ex=2 (note, however, that the calculation of this system will take a very long time). If the computation and output mode is set to 4, the memory demands by GCFP are significantly larger. Calculation of GCFPs of A=12 system at Ex=1 requires 145 MB. The program parGCFP requires additional 2.5 and 4.5 MB of memory for the serial and parallel version, respectively.
Classification: 17.18
Nature of problem: The program GCFP generates a list of two-particle coefficients of fractional parentage for several j-shells with isospin.
Solution method: The method is based on the observation that multishell coefficients of fractional parentage can be expressed in terms of single-shell CFPs [1]. The latter are calculated using the algorithm [2,3] for a spectral decomposition of an antisymmetrization operator matrix Y. The coefficients of fractional parentage are those eigenvectors of the antisymmetrization operator matrix Y that correspond to unit eigenvalues. A computer code for these coefficients is available [4]. The program GCFP offers computation of two-particle multishell coefficients of fractional parentage. The program parGCFP allows a batch calculation using one input file. Sets of GCFPs are independent and can be calculated in parallel.
Restrictions: A<86 when Ex=0 (due to the memory constraints); small numbers of particles allow significantly higher excitations, though the shell with j11/2 cannot get full (it is the implementation constraint).
Unusual features: Using the program GCFP it is possible to determine allowed particle configurations without the GCFP computation. The GCFPs can be calculated either for all particle configurations at once or for a specified particle configuration. The values of GCFPs can be printed out with a complete specification in either one file or with the parent