Comments on “Optimization of the decision threshold for single radioactive counting”

2010 ◽  
Vol 98 (6) ◽  
Author(s):  
S. Sterlinski
Keyword(s):  
Decision Threshold ◽  
Radioactive Counting

AbstractIt is argued that in the recent papers by A. Vivier and J. Aupiais (Radiochim. Acta

Optimization of the decision threshold for single radioactive counting

2008 ◽  
Vol 96 (6) ◽  
Author(s):  
V. Vivier ◽  
Jean Aupiais
Keyword(s):  
Decision Threshold ◽  
Correct Data ◽  
Radioactive Counting

SummaryIn the above mentioned paper several misprints and errors in the formulae have been noticed. In particular, several equations were not properly writtten in terms of variables of integration. We now present the correct data.

scholarly journals GHOST: Adjusting the Decision Threshold to Handle Imbalanced Data in Machine Learning

2021 ◽  
Author(s):  
Carmen Esposito ◽  
Gregory A. Landrum ◽  
Nadine Schneider ◽  
Nikolaus Stiefl ◽  
Sereina Riniker
Keyword(s):  
Machine Learning ◽  
Imbalanced Data ◽  
Decision Threshold

A critical decision threshold—the temperature: Reply of the authors

2002 ◽  
Vol 77 (3) ◽  
pp. 640-641
Author(s):  
Sharon J Paynter ◽  
Louise O’Neil ◽  
Barry J Fuller ◽  
Robert W Shaw
Keyword(s):  
Decision Threshold

Radioactive Counting Clocks

2006 ◽  
Author(s):  
Shankar Radhakrishnan ◽  
Amit Lal
Keyword(s):  
Radioactive Counting

Using the Kalman Filtering for the Fault Detection and Isolation (FDI) in the Nonlinear Dynamic Processes

2008 ◽  
Vol 6 (1) ◽  
Author(s):  
Yahya Chetouani
Keyword(s):  
Fault Detection ◽  
Nonlinear Dynamic ◽  
Nonlinear Dynamic System ◽  
Chemical Reactor ◽  
Fault Detection And Isolation ◽  
Decision Threshold ◽  
Normal Behaviour ◽  
Batch Mode ◽  
The Moment ◽  
Reactor Operating

This paper presents a Fault Detection and Isolation (FDI) method for stochastic nonlinear dynamic systems. First, the developed fault detection method is based on statistical information generated by the extended Kalman filter (EKF) and is intended to reveal any drift from the normal behaviour of the process. A fault of a chemical origin in a perfectly stirred batch chemical reactor, occurring at an unknown instant, is simulated. The purpose is to detect the presence of this abrupt change, and pinpoint the moment it occurred. It is also shown that the convergence of the EKF is accomplished more or less rapidly according to the nature of the noise generated by the measurement sensors. The state estimate is observed and discussed, as well as the time delay in detection according to the decision threshold. Then, this study shows another method of tackling the problem of the physical origin diagnosis of faults by combining the technique based on the standardized innovations and the technique using the multiple extended Kalman filters for a strongly non-stationary nonlinear dynamic system. The usefulness of this combination is the implementation of all the fault dynamics models if the decision threshold on the standardized innovation exceeds a determined threshold. In the other case, one EKF is enough to estimate all the process state. An algorithm is described and applied to a perfectly stirred chemical reactor operating in a semi-batch mode. The chemical reaction used is an exothermic second order one.

Decision threshold adjustment in class prediction

2006 ◽  
Vol 17 (3) ◽  
pp. 337-352 ◽  
Author(s):  
J. J. Chen ◽  
C.-A. Tsai ◽  
H. Moon ◽  
H. Ahn ◽  
J. J. Young ◽  
...  
Keyword(s):  
Decision Threshold ◽  
Class Prediction ◽  
Threshold Adjustment
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