Although considered as not safety critical (safety function being performed by other sub-systems), railway supervision systems can contribute to hazardous scenarios. It is of primary importance to identify this type of scenarios and evaluate the behaviour of human operators. A state of the art in human reliability is presented. This article presents an experimental protocol based on an automati...

In this paper two machine learning algorithms, Decision Trees (DT) and Hamming Clustering (HC), are compared in building approximated Reliability Expression (RE). The main idea is to employ a classification technique, trained on a restricted subset of data, to produce an estimate of the RE, which provides reasonably accurate values of the reliability. The experiments show that although both met...

Classification and regression models, either automatically generated from data by machine learning algorithms, or manually encoded with the help of domain experts, are daily used to predict the labels of new instances. Each such individual prediction, in order to be accepted/trusted by users, should be accompanied by an explanation of the prediction as well as by an estimate of its reliability....

⎯Due to the lack of a structure way in determining the free parameters of support vector machines (SVMs), this study uses genetic algorithms (GAs) to select parameters of SVMs. In addition, the developed SVMG (support vector machine with genetic algorithms) model is applied to reliability prediction. Two numerical examples in the literature are employed to illustrate the performances of various...

Long-term reliability of processors is experiencing growing attention since decreasing feature sizes and increasing power consumption have a negative influence on the lifespan. The reliability can also be influenced by Dynamic Power Management (DPM), since it affects the processor’s temperature. In this paper, it is examined how different DPM-strategies for MultiCore processors alter their life...

Random Access Channel (RACH) has been identified as one of the major bottlenecks for accommodating massive number of machine-to-machine (M2M) users in LTE networks, especially for the case of burst arrival of connection requests. As a consequence, the burst resolution problem has sparked a large number of works in the area, analyzing and optimizing the average performance of RACH. However, the ...

Ensuring reliability as the electrical grid morphs into the “smart grid” will require innovations in how we assess the state of the grid, for the purpose of proactive maintenance, rather than reactive maintenance – in the future, we will not only react to failures, but also try to anticipate and avoid them using predictive modeling (machine learning) techniques. To help in meeting this challeng...

CERN is working on a new particle accelerators that will require a very large number of power converters. In that view, the reliability of the whole powering will be a major issue. The use of a redundancy and modularity may help increasing the overall machine availability. However, the reliability of the redundancy system must be high enough to add a significant improvement when compared to sim...

The reliability of communication networks is assessed by employing two machine learning algorithms, Support Vector Machines (SVM) and Hamming Clustering (HC), acting on a subset of possible system configurations, generated by a Monte Carlo simulation and an appropriate Evaluation Function. The experiments performed with two different reliability measures show that both methods yield excellent p...

In this paper we demonstrate the first real-world cloning attack on a commercial PUF-based RFID tag. The examined commercial PUFs can be attacked by measuring only 4 protocol executions, which takes less than 200 ms. Using a RFID smartcard emulator, it is then possible to impersonate, i.e., “clone” the PUF. While attacking the 4-way PUF used by these tags can be done using traditional machine l...