scholarly journals A Simple Formula for the Hilbert Metric with Respect to a Sub-Gaussian Cone

Mathematics ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 35
Author(s):  
Stéphane Chrétien ◽  
Juan-Pablo Ortega
1997 ◽  
Vol 62 (3) ◽  
pp. 397-419 ◽  
Author(s):  
Ondřej Wein ◽  
Václav Sobolík

An exact theory is given of the voltage-step transient under limiting diffusion conditions for an electrodiffusion friction probe of arbitrary convex shape. The actual transient courses are given for the strip, circular, elliptic, triangular, and rectangular probes of any orientation with respect to the flow direction. A simple formula for any probe with a single working electrode of convex shape is suggested to facilitate the calibration of electrodiffusion probes based on the voltage-step transient.


2020 ◽  
Vol 70 (6) ◽  
pp. 1521-1537
Author(s):  
Feng Qi ◽  
Omran Kouba ◽  
Issam Kaddoura

AbstractIn the paper, employing methods and techniques in analysis and linear algebra, the authors find a simple formula for computing an interesting Hessenberg determinant whose elements are products of binomial coefficients and falling factorials, derive explicit formulas for computing some special Hessenberg and tridiagonal determinants, and alternatively and simply recover some known results.


1982 ◽  
Vol 25 (5) ◽  
pp. 2837-2840 ◽  
Author(s):  
A. Partensky ◽  
C. Quesne

The Lancet ◽  
1962 ◽  
Vol 280 (7263) ◽  
pp. 990
Author(s):  
J.E. Cullis

2016 ◽  
Vol 25 (6) ◽  
pp. 2704-2713 ◽  
Author(s):  
Giuseppe Rossi ◽  
Simone Del Sarto ◽  
Marco Marchi

To monitor a health event in patients with a specific risk of developing the event, a risk-adjusted cumulative sum chart is needed. The risk-adjusted cumulative sum chart proposed in the literature has some limitations. Setting appropriate control limits is not straightforward, there is no simple formula for constructing them, and they remain sensitive to changes in the underlying risk distribution and the baseline incidence rate. To overcome these limits, we propose a new risk-adjusted Bernoulli cumulative sum chart as a simple and efficient solution. Analyses of simulated and real data sets illustrate the performance and usefulness of the proposed procedure.


1987 ◽  
Vol 109 (4) ◽  
pp. 402-406 ◽  
Author(s):  
Go¨ran Gerbert ◽  
Jacques de Mare´

There are many applications in mechanical design where load distribution is modelled with parallel springs. Here random variation in spring length and spring stiffness is considered. Length variation is assumed to be the major influence and the case with uniform distribution is analyzed in detail. Small variations in spring stiffness are included. Numerical results are given. A simple formula is presented which gives the maximal length deviation as a function of the number of springs. The formula is based on a 10 percent failure risk which is a common number in practical mechanical design.


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