error condition statement

2011 ◽  
Keyword(s):  
Error Condition

scholarly journals A mean-squared-error condition for weighting ionospheric delays in GNSS baselines

2021 ◽  
Vol 95 (11) ◽  
Author(s):  
P. J. G. Teunissen ◽  
A. Khodabandeh
Keyword(s):  
Parameter Estimation ◽  
Mean Squared Error ◽  
Present Contribution ◽  
Squared Error ◽  
Fixed Solution ◽  
Error Condition

AbstractAlthough ionosphere-weighted GNSS parameter estimation is a popular technique for strengthening estimator performance in the presence of ionospheric delays, no provable rules yet exist that specify the needed weighting in dependence on ionospheric circumstances. The goal of the present contribution is therefore to develop and present the ionospheric conditions that need to be satisfied in order for the ionosphere-weighted solution to be mean squared error (MSE) superior to the ionosphere-float solution. When satisfied, the presented conditions guarantee from an MSE performance view, when (a) the ionosphere-fixed solution can be used, (b) the ionosphere-float solution must be used, or (c) an ionosphere-weighted solution can be used.

The Error Condition

2019 ◽  
Vol 50 (1) ◽  
pp. 34-48 ◽  
Author(s):  
Jeremy David Fix
Keyword(s):  
Error Condition

AbstractThe possibility of error conditions the possibility of normative principles. I argue that extant interpretations of this condition undermine the possibility of normative principles for our action because they implicitly treat error as a perfection of an action. I then explain how a constitutivist metaphysics of capacities explains why error is an imperfection of an action. Finally, I describe and defend the interpretation of the error condition which follows.

scholarly journals Effect of analytical run length on quality-control (QC) performance and the QC planning process

1997 ◽  
Vol 43 (11) ◽  
pp. 2149-2154 ◽  
Author(s):  
Curtis A Parvin ◽  
Ann M Gronowski
Keyword(s):  
Quality Control ◽  
Error Detection ◽  
Planning Process ◽  
Performance Measure ◽  
Major Influence ◽  
Expected Number ◽  
Control Error ◽  
Allowable Error ◽  
The Impact ◽  
Error Condition

Abstract The performance measure traditionally used in the quality-control (QC) planning process is the probability of rejecting an analytical run when an out-of-control error condition exists. A shortcoming of this performance measure is that it doesn’t allow comparison of QC strategies that define analytical runs differently. Accommodating different analytical run definitions is straightforward if QC performance is measured in terms of the average number of patient samples to error detection, or the average number of patient samples containing an analytical error that exceeds total allowable error. By using these performance measures to investigate the impact of different analytical run definitions on QC performance demonstrates that during routine QC monitoring, the length of the interval between QC tests can have a major influence on the expected number of unacceptable results produced during the existence of an out-of-control error condition.

Observing Errors in a Combination of Error and Correct Models Favors Observational Motor Learning

2021 ◽  
Author(s):  
Zhi-Ming Tang ◽  
Yutaka Oouchida ◽  
Meng-Xin Wang ◽  
Zu-Lin Dou ◽  
Shin-Ichi Izumi
Keyword(s):  
Motor Learning ◽  
Auditory Feedback ◽  
Training Session ◽  
Learning Performance ◽  
Mixed Condition ◽  
Average Force ◽  
Imitative Learning ◽  
Correct Condition ◽  
Target Force ◽  
Error Condition

Abstract Background:Imitative learning is highly effective from infancy to old age, but little is known about the effects of observing errors during imitative learning. This study aims to examine how observing errors affect imitative learning performance, to maximize the effects of imitative learning. Method：In the pre-training session, participants were instructed to pinch at the target force (8 N) with auditory feedback about generated force while watching videos of someone pinching a sponge at the target force. In the pre-test, participants pinched at the target force without viewing a model or receiving auditory feedback. In Experiment 1, in the main training session, participants imitated models while watching videos of pinching at either the incorrect force (error-mixed condition) or the target force (all-correct condition). Then, the exact force they generated in pinching was measured without receiving auditory feedback or viewing a model. In Experiment 2, using the same procedure in the pre-training and pre-test sessions, newly recruited participants watched pinching at incorrect forces (4 and 24 N) as the all-error condition and the correct force as the correct condition. Results: In Experiment 1, the average force was better in the error-mixed condition than in the correct condition. In Experiment 2, the average force in the correct condition was better than that in the error condition.Conclusion: Our findings indicate that observing error actions combined with correct actions affected imitation motor learning positively, because error actions contain what-not-to-do information about the target action, unlike correct actions, which provide more information to enhance imitative learning.

Error, Falsification and Scientific Inference: An Experimental Investigation

1989 ◽  
Vol 41 (2) ◽  
pp. 385-412 ◽  
Author(s):  
Michael E. Gorman
Keyword(s):  
Experimental Investigation ◽  
Scientific Reasoning ◽  
Experimental Results ◽  
Current Trial ◽  
Control Subjects ◽  
Scientific Inference ◽  
Actual Error ◽  
Error Condition

This paper reports the results of four experiments designed to test the methodological falsificationist's assumption that replication is sufficient to prevent the possibility of error from being used to immunize hypotheses against disconfirmation. The first three experiments compare the performance of subjects on tasks that simulate scientific reasoning under two conditions: (1) where there is a 0–20% possibility of error in experimental results, but no actual error; and (2) a control condition. All experiments used Wason's 2–4–6 task, in which subjects propose triples and are told whether each corresponds to a rule. In Experiment 1, subjects in the possible-error condition proposed significantly more triples than control subjects. Experiment 2 added colour and letter dimensions to the 2–4–6 task; possible-error subjects proposed significantly more triples and replicated the same triple more often than control subjects. Experiment 3 made replication more difficult by limiting the number of experiments subjects could perform and by altering the rule to make the results of the current trial dependent on previous ones. Control subjects solved this problem significantly more often than possible-error subjects. Experiment 4 was run in a manner very similar to Experiment 1, except that an actual 20% error condition was added. Subjects in this condition solved the rule significantly less often than subjects in other conditions, and also took more time and replicated more often. Implications of these results for the methodological falsificationist's position are discussed.

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