A novel test methodology based on error-rate to support error-tolerance

Author(s):  
Kuen-Jong Lee ◽  
Tong-Yu Hsieh ◽  
M.A. Breuer
2008 ◽  
Vol 57 (1) ◽  
pp. 204-214 ◽  
Author(s):  
Tong-Yu Hsieh ◽  
Kuen-Jong Lee ◽  
M.A. Breuer

2010 ◽  
Vol 121-122 ◽  
pp. 87-92
Author(s):  
Chang Hong Yu

As the transistor sizes continue to shrink, quantum effects will significantly affect the circuit behavior. The inherent unreliability of nano-electronics will have significantly impact on the way of circuits design, so defects and faults of nano-scale circuit technologies have to be taken into account early in the design of digital systems. Fault-tolerant architectures may become a necessity to ensure that the underlying circuit could function properly. In CAD software, a same logic can be made out with different circuits but different design methodology can reach different soft error tolerance ability, so we must find a way to estimate the error rate of the circuit efficiently to make the design more fault tolerant. In this paper, a new way to fault tolerance design in nano-scale circuit by accurate soft error rate (SER) estimation is proposed. Transform matrix is used for SER computation and a design criteria is then proposed. Simulation results show that the proposed transform matrix model is effective for nano-scale circuits and the criteria delivered is suitable CAD tools development in nano-system design.


2019 ◽  
Vol 28 (4) ◽  
pp. 1411-1431 ◽  
Author(s):  
Lauren Bislick ◽  
William D. Hula

Purpose This retrospective analysis examined group differences in error rate across 4 contextual variables (clusters vs. singletons, syllable position, number of syllables, and articulatory phonetic features) in adults with apraxia of speech (AOS) and adults with aphasia only. Group differences in the distribution of error type across contextual variables were also examined. Method Ten individuals with acquired AOS and aphasia and 11 individuals with aphasia participated in this study. In the context of a 2-group experimental design, the influence of 4 contextual variables on error rate and error type distribution was examined via repetition of 29 multisyllabic words. Error rates were analyzed using Bayesian methods, whereas distribution of error type was examined via descriptive statistics. Results There were 4 findings of robust differences between the 2 groups. These differences were found for syllable position, number of syllables, manner of articulation, and voicing. Group differences were less robust for clusters versus singletons and place of articulation. Results of error type distribution show a high proportion of distortion and substitution errors in speakers with AOS and a high proportion of substitution and omission errors in speakers with aphasia. Conclusion Findings add to the continued effort to improve the understanding and assessment of AOS and aphasia. Several contextual variables more consistently influenced breakdown in participants with AOS compared to participants with aphasia and should be considered during the diagnostic process. Supplemental Material https://doi.org/10.23641/asha.9701690


1978 ◽  
Vol 11 (3) ◽  
pp. 150-154
Author(s):  
Gary E. Price ◽  
Robert D. Michal ◽  
James M. O'Neil
Keyword(s):  

2007 ◽  
Vol 23 (3) ◽  
pp. 157-165 ◽  
Author(s):  
Carmen Hagemeister

Abstract. When concentration tests are completed repeatedly, reaction time and error rate decrease considerably, but the underlying ability does not improve. In order to overcome this validity problem this study aimed to test if the practice effect between tests and within tests can be useful in determining whether persons have already completed this test. The power law of practice postulates that practice effects are greater in unpracticed than in practiced persons. Two experiments were carried out in which the participants completed the same tests at the beginning and at the end of two test sessions set about 3 days apart. In both experiments, the logistic regression could indeed classify persons according to previous practice through the practice effect between the tests at the beginning and at the end of the session, and, less well but still significantly, through the practice effect within the first test of the session. Further analyses showed that the practice effects correlated more highly with the initial performance than was to be expected for mathematical reasons; typically persons with long reaction times have larger practice effects. Thus, small practice effects alone do not allow one to conclude that a person has worked on the test before.


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