Algorithms exploiting spare capacity and tasks laxities for fault detection and location in real-time multiprocessor systems

Mahesh, K.; Manimaran, G.; Murthy, C. Siva Ram; Somani, Arun K.

doi:10.1109/ipps.1998.670009

Cited by 2 publications

(1 citation statement)

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“…Spare-capacity scheduling: In [15], an algorithm was proposed with fault-detection and location capabilities for real-time systems based on the myopic algorithm. The objective of the algorithm was to improve the schedulability and to use the spare capacity of idle processors for fault-detection and location.…”

Section: Related Workmentioning

confidence: 99%

Value-based scheduling in real-time systems

Sivasubramanian¹

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Section: Related Workmentioning

confidence: 99%

Value-based scheduling in real-time systems

Sivasubramanian¹

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Improving the Reliability of Peer Review Without a Gold Standard

Äijö,

Elgort,

Becker

et al. 2024

J Digit Imaging. Inform. med.

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Peer review plays a crucial role in accreditation and credentialing processes as it can identify outliers and foster a peer learning approach, facilitating error analysis and knowledge sharing. However, traditional peer review methods may fall short in effectively addressing the interpretive variability among reviewing and primary reading radiologists, hindering scalability and effectiveness. Reducing this variability is key to enhancing the reliability of results and instilling confidence in the review process. In this paper, we propose a novel statistical approach called “Bayesian Inter-Reviewer Agreement Rate” (BIRAR) that integrates radiologist variability. By doing so, BIRAR aims to enhance the accuracy and consistency of peer review assessments, providing physicians involved in quality improvement and peer learning programs with valuable and reliable insights. A computer simulation was designed to assign predefined interpretive error rates to hypothetical interpreting and peer-reviewing radiologists. The Monte Carlo simulation then sampled (100 samples per experiment) the data that would be generated by peer reviews. The performances of BIRAR and four other peer review methods for measuring interpretive error rates were then evaluated, including a method that uses a gold standard diagnosis. Application of the BIRAR method resulted in 93% and 79% higher relative accuracy and 43% and 66% lower relative variability, compared to “Single/Standard” and “Majority Panel” peer review methods, respectively. Accuracy was defined by the median difference of Monte Carlo simulations between measured and pre-defined “actual” interpretive error rates. Variability was defined by the 95% CI around the median difference of Monte Carlo simulations between measured and pre-defined “actual” interpretive error rates. BIRAR is a practical and scalable peer review method that produces more accurate and less variable assessments of interpretive quality by accounting for variability within the group’s radiologists, implicitly applying a standard derived from the level of consensus within the group across various types of interpretive findings.

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Algorithms exploiting spare capacity and tasks laxities for fault detection and location in real-time multiprocessor systems

Cited by 2 publications

References 4 publications

Value-based scheduling in real-time systems

Value-based scheduling in real-time systems

Improving the Reliability of Peer Review Without a Gold Standard

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