In this paper, we present and discuss a new interval-based method of reliability estimation using fault trees for the case of uncertain and time-varying input reliability data. The approach is based on the generation of output distributions (probability estimates with appropriate ranges of uncertainty) which preserve the effects of uncertainty in the input (component or subsystem-level) data. T...

Uncertainties in structural parameters and in the excitation, and consequently in the response, obviously affect the structural reliability considerably. In this work, recent developments in the reliability analysis for the treatment of uncertain linear structures subjected to dynamic loading are presented. Although any reliability problem could be solved in principle by Direct Monte Carlo simu...

In this paper, we present and compare some exact methods to resolve the network reliability problems. These problems concern all kinds of networks, such as computer, communication or power networks. When components of the network are subject to random failures, the network may or may not continue functioning after the failures of some components. The probability that the network will function i...

Providing protection against the hazards of space radiation is a major challenge to the exploration and development of space. The great cost of added radiation shielding is a potential limiting factor in deep space operations. In this enabling technology, we have developed methods for optimized shield design over multi-segmented missions involving multiple work and living areas in the transport...

There are many probabilistic and statistical approaches to modelling software reliability. Software reliability estimates are used for various purposes: during development, to make the release decision; and after the software has been taken into use, as part of system reliability estimation, as a basis of maintenance recommendations, and further improvement, or a basis of the recommendation to ...

Current iterative methods for solving linear equations assume reliability of data (no “bit flips”) and arithmetic (correct up to rounding error). If faults occur, the solver usually either aborts, or computes the wrong answer without indication. System reliability guarantees consume energy or reduces performance. As processor counts continue to grow, these costs will become unbearable. Instead,...

Saliency methods aim to explain the predictions of deep neural networks. These methods lack reliability when the explanation is sensitive to factors that do not contribute to the model prediction. We use a simple and common pre-processing step —adding a constant shift to the input data— to show that a transformation with no effect on the model can cause numerous methods to incorrectly attribute...

This volume focuses on stochastic methods developed for reliability modeling and risk analysis. Reliability theory and risk analysis have been closely related, and stochastic methods that are commonly used in both fields serve as a natural conduit through which useful concepts and best practices can migrate from one field to the other. This special volume highlights this convergence of reliabil...

This paper deals with digital VLSI design aspects related to reliability. The focus is on the problem of reliability evaluation in combinational logic circuits. We present some methods for this evaluation that can be easily integrated in a tradidional design flow. Also we describe suitable metrics for performance estimation of concurrent error detection schemes.

No matter the area of science, fundamental concepts are inexorably linked with instrumentation used to obtain measurements of them. In nursing science (Ventura, Hinshaw, & Atwood, 1981) as in all sciences, measurements should be faithful representations of characteristics of interest that gauge quantity with minimal error and enable examination of relationships and testing of hypotheses arising...