scholarly journals Preliminary evaluation of the BIODOSE computer program. [For simulating radionuclide transport through aquatic ecosystems and predicting the dose to humans]

1979 ◽  
Author(s):  
N.A. Bonner ◽  
Y.C. Ng
1993 ◽  
Vol 20 (3) ◽  
pp. 186-187 ◽  
Author(s):  
Thomas Brothen ◽  
Janet Schneider

This article describes a computer-assisted study exercise for introductory psychology classes adapted from Boneau's (1990) list of the top 100 terms and concepts. We discuss alternative uses for the list, computer program development, and student use of the program in studying for the final examination. Preliminary evaluation suggests that the exercise increases student knowledge of introductory psychology.


Author(s):  
Richard A. Riemke ◽  
Cliff B. Davis ◽  
Richard R. Schultz

The hydrodynamics section of the RELAP5-3D computer program has been recently improved. Changes were made as follows: (1) improved turbine model, (2) spray model for the pressurizer model, (3) feedwater heater model, (4) radionuclide transport model, (5) improved pump model, and (6) compressor model. These changes will be discussed.


AMBIO ◽  
2013 ◽  
Vol 42 (4) ◽  
pp. 464-475 ◽  
Author(s):  
Anders Christian Erichsen ◽  
Lena Konovalenko ◽  
Flemming Møhlenberg ◽  
Rikke Margrethe Closter ◽  
Clare Bradshaw ◽  
...  

1978 ◽  
Vol 48 ◽  
pp. 287-293 ◽  
Author(s):  
Chr. de Vegt ◽  
E. Ebner ◽  
K. von der Heide

In contrast to the adjustment of single plates a block adjustment is a simultaneous determination of all unknowns associated with many overlapping plates (star positions and plate constants etc. ) by one large adjustment. This plate overlap technique was introduced by Eichhorn and reviewed by Googe et. al. The author now has developed a set of computer programmes which allows the adjustment of any set of contemporaneous overlapping plates. There is in principle no limit for the number of plates, the number of stars, the number of individual plate constants for each plate, and for the overlapping factor.


Author(s):  
Makoto Shiojiri ◽  
Toshiyuki Isshiki ◽  
Tetsuya Fudaba ◽  
Yoshihiro Hirota

In hexagonal Se crystal each atom is covalently bound to two others to form an endless spiral chain, and in Sb crystal each atom to three others to form an extended puckered sheet. Such chains and sheets may be regarded as one- and two- dimensional molecules, respectively. In this paper we investigate the structures in amorphous state of these elements and the crystallization.HRTEM and ED images of vacuum-deposited amorphous Se and Sb films were taken with a JEM-200CX electron microscope (Cs=1.2 mm). The structure models of amorphous films were constructed on a computer by Monte Carlo method. Generated atoms were subsequently deposited on a space of 2 nm×2 nm as they fulfiled the binding condition, to form a film 5 nm thick (Fig. 1a-1c). An improvement on a previous computer program has been made as to realize the actual film formation. Radial distribution fuction (RDF) curves, ED intensities and HRTEM images for the constructed structure models were calculated, and compared with the observed ones.


1989 ◽  
Vol 32 (3) ◽  
pp. 681-687 ◽  
Author(s):  
C. Formby ◽  
B. Albritton ◽  
I. M. Rivera

We describe preliminary attempts to fit a mathematical function to the slow-component eye velocity (SCV) over the time course of caloric-induced nystagmus. Initially, we consider a Weibull equation with three parameters. These parameters are estimated by a least-squares procedure to fit digitized SCV data. We present examples of SCV data and fitted curves to show how adjustments in the parameters of the model affect the fitted curve. The best fitting parameters are presented for curves fit to 120 warm caloric responses. The fitting parameters and the efficacy of the fitted curves are compared before and after the SCV data were smoothed to reduce response variability. We also consider a more flexible four-parameter Weibull equation that, for 98% of the smoothed caloric responses, yields fits that describe the data more precisely than a line through the mean. Finally, we consider advantages and problems in fitting the Weibull function to caloric data.


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