The Inverse Ocean Modeling System. Part I: Implementation

2008 ◽  
Vol 25 (9) ◽  
pp. 1608-1622 ◽  
Author(s):  
A. F. Bennett ◽  
B. S. Chua ◽  
B. L. Pflaum ◽  
M. Erwig ◽  
Z. Fu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
User Interface ◽  
Data Assimilation ◽  
Graphical User Interface ◽  
Ocean Modeling ◽  
Dynamical Model ◽  
Interpolation Scheme ◽  
Fortran Code ◽  
System Part ◽  
The Many

Abstract The Inverse Ocean Modeling (IOM) system constructs and runs weak-constraint, four-dimensional variational data assimilation (W4DVAR) for any dynamical model and any observing array. The dynamics and the observing algorithms may be nonlinear but must be functionally smooth. The user need only provide the model and the observing algorithms, together with an interpolation scheme that relates the model numerics to the observer’s coordinates. All other model-dependent elements of the Inverse Ocean Modeling assimilation algorithm (see both Chua and Bennett), including adjoint generators and Monte Carlo estimates of posteriors, have been derived and coded as templates in Parametric FORTRAN (Erwig et al.). This language has been developed for the IOM but has wider application in scientific programming. Guided by the Parametric FORTRAN templates, and by model information entered via a graphical user interface (GUI), the IOM generates conventional FORTRAN code for each of the many algorithm elements, customized to the user’s model. The IOM also runs the various W4DVAR assimilations, which are monitored by the GUI. The system is supported by a Web site that includes interactive tutorials for the assimilation algorithm.

scholarly journals Excess Noise Factor in Avalanche Photodiodes with Dead Space Effect

2021 ◽  
Author(s):  
Vignesh Reddy Angadi
Keyword(s):  
Monte Carlo ◽  
User Interface ◽  
Graphical User Interface ◽  
Avalanche Photodiodes ◽  
Research Work ◽  
Noise Factor ◽  
Excess Noise ◽  
Excess Noise Factor ◽  
Monte Carlo Calculations ◽  
Space Effect

Abstract This project aims to produce a graphical user interface (GUI) for MATLAB programs written by J.S.Marsland as part of his research into the excess noise factor in avalanche photodiodes (APDs). The GUI will be produced using the GUIDE package supplied with the MATLAB software combined with the MATLAB programs. The GUI will then be used to compare this research work with the research work of others e.g. the Monte Carlo calculations made by the research group at the French Aerospace Laboratory (ONERA). Comparison with other research work will require the digitization of some graphs published in academic journals.

scholarly journals An update on the RTTOV fast radiative transfer model (currently at version 12)

2018 ◽  
Author(s):  
Roger Saunders ◽  
James Hocking ◽  
Emma Turner ◽  
Peter Rayer ◽  
David Rundle ◽  
...  
Keyword(s):  
User Interface ◽  
Radiative Transfer ◽  
Data Assimilation ◽  
Graphical User Interface ◽  
Jacobian Matrix ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Satellite Retrieval ◽  
Radiance Assimilation ◽  
Atmospheric State

Abstract. This paper gives an update of the RTTOV (Radiative Transfer for TOVS) fast radiative transfer model which is widely used in the satellite retrieval and data assimilation communities. RTTOV is a fast radiative transfer model for simulating top of atmosphere radiances from passive visible, infrared and microwave downward-viewing satellite radiometers. In addition to the forward model, it also optionally computes the tangent linear, adjoint and Jacobian matrix providing changes in radiances for profile variable perturbations assuming a linear relationship about a given atmospheric state. This makes it a useful tool for developing physical retrievals from satellite radiances, for direct radiance assimilation in NWP models, for simulating future instruments and for training or teaching with a graphical user interface. An overview of the RTTOV model is given highlighting the updates and increased capability of the latest versions and gives some examples of its current performance when compared with more accurate line by line radiative transfer models and a few selected observations. The improvement over the original version of the model released in 1999 is demonstrated.

scholarly journals A tool for precise calculation of organ doses in voxelised geometries using GAMOS/Geant4 with a graphical user interface

2021 ◽  
Vol 27 (1) ◽  
pp. 31-40
Author(s):  
Pedro Arce Dubois ◽  
Nguyen Thi Phuong Thao ◽  
Nguyen Thien Trung ◽  
Juan Diego Azcona ◽  
Pedro-Borja Aguilar-Redondo
Keyword(s):  
Monte Carlo ◽  
User Interface ◽  
Graphical User Interface ◽  
Dose Calculation ◽  
Medical Personnel ◽  
Ease Of Use ◽  
Simulation Code ◽  
Organ Doses ◽  
Precise Calculation ◽  
Parallel Geometry

Abstract Introduction: The limit of the method of calculating organ doses using voxelised phantoms with a Monte Carlo simulation code is that dose calculation errors in the boundaries of the organs are especially relevant for thin, small or complex geometries. In this report, we describe a tool that helps overcome this problem, accurately calculating organ doses by applying the “parallel geometry” utility feature of Geant4 through the GAMOS framework. Methods and methods: We have tried to simplify the use of this tool by automatically processing the different DICOM image modalities (CT, PT, ST, NM), and by including the automatic conversion of the structures found in a DICOM RTSTRUCT file into Geant4 volumes that build the parallel geometry. For Nuclear Medicine applications, the DICOM PT, ST or NM images are converted into probabilities of generation of primary particles in each voxel, and the DICOM CT images into materials and material densities. For radiotherapy treatments, the DICOM RTPlan or RTIonPlan may also be used, hence the user only needs to describe the accelerator geometry. We also provide a Graphical User Interface for ease of use by for inexperienced users in Monte Carlo. Results: We have tested the functionality of the tool with an I-131 thyroid cancer treatment, and obtained the expected energy deposition and dose differences, given that the particle source, geometry and structures are defined. Conclusions: In summary, we provide an easy-to-use tool to calculate, with high accuracy, organ doses, taking into account their exact geometry as painted by the medical personnel on a voxelised phantom.

scholarly journals Excess Noise Factor in Avalanche Photodiodes with Dead Space Effect

2021 ◽  
Author(s):  
Vignesh Reddy Angadi
Keyword(s):  
Monte Carlo ◽  
User Interface ◽  
Graphical User Interface ◽  
Avalanche Photodiodes ◽  
Research Work ◽  
Noise Factor ◽  
Excess Noise ◽  
Excess Noise Factor ◽  
Monte Carlo Calculations ◽  
Space Effect

Abstract This project aims to produce a graphical user interface (GUI) for MATLAB programs written by J.S.Marsland as part of his research into the excess noise factor in avalanche photodiodes (APDs). The GUI will be produced using the GUIDE package supplied with the MATLAB software combined with the MATLAB programs. The GUI will then be used to compare this research work with the research work of others e.g. the Monte Carlo calculations made by the research group at the French Aerospace Laboratory (ONERA). Comparison with other research work will require the digitization of some graphs published in academic journals.

scholarly journals Why scientists should learn to program in Python

2014 ◽  
Vol 29 (S2) ◽  
pp. S48-S64 ◽  
Author(s):  
Vidya M. Ayer ◽  
Sheila Miguez ◽  
Brian H. Toby
Keyword(s):  
User Interface ◽  
Programming Languages ◽  
Powder Diffraction ◽  
Graphical User Interface ◽  
Scientific Research ◽  
Numerical Computations ◽  
Knowing How ◽  
Python Scripting ◽  
Scripting Language ◽  
The Many

The importance of software continues to grow for all areas of scientific research, no less for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. This paper explains the three approaches for programming languages and why scripting languages are preferred for non-expert programmers. The Python-scripting language is extremely efficient for science and its use by scientists is growing. Python is also one of the easiest languages to learn. The language is introduced, as well as a few of the many add-on packages available that extend its capabilities, for example, for numerical computations, scientific graphics, and graphical user interface programming. Resources for learning Python are also provided.

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