Efficient diagnosis of multiprocessor systems under probabilistic models

The problem of fault diagnosis in multiprocessor systems is considered under a probabilistic fault model. The focus is on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. Lower and upper bounds on the number of tests required for regular systems are also presented. A class of regular systems which includes hypercubes is shown to be correctly diagnosable with high probability. In all cases, the number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis techniques

Transient fluctuation of the prosperity of firms in a network economy

The transient fluctuation of the prosperity of firms in a network economy is investigated with an abstract stochastic model. The model describes the profit which firms make when they sell materials to a firm which produces a product and the fixed cost expense to the firms to produce those materials and product. The formulae for this model are parallel to those for population dynamics. The swinging changes in the fluctuation in the transient state from the initial growth to the final steady state are the consequence of a topology-dependent time trial competition between the profitable interactions and expense. The firm in a sparse random network economy is more likely to go bankrupt than expected from the value of the limit of the fluctuation in the steady state, and there is a risk of failing to reach by far the less fluctuating steady state

Learning to Read Bilingually Modulates the Manifestations of Dyslexia in Adults

Published online: 28 Mar 2018According to the Grain Size Accommodation hypothesis (Lallier & Carreiras, 2017), learning to read in two languages differing in orthographic consistency leads to a cross-linguistic modulation of reading and spelling processes. Here, we test the prediction that bilingualism may influence the manifestations of dyslexia. We compared the deficits of English monolingual and early Welsh–English bilingual dyslexic adults on reading and spelling irregular English words and English-like pseudowords. As predicted, monolinguals were relatively more impaired in reading pseudowords than irregular words, whereas the opposite was true for bilinguals. Moreover, monolinguals showed stronger sublexical processing deficits than bilinguals and were poorer spellers overall. This study shows that early bilingual reading experience has long-lasting effects on the manifestations of dyslexia in adulthood. It demonstrates that learning to read in a consistent language like Welsh in addition to English gives bilingual dyslexic adults an advantage in English literacy tasks strongly relying on phonological processing.This research was funded by the Fyssen Foundation, the European Commission (FP7-PEOPLE-2010-IEF, Proposal N°274352, BIRD, to M.L) the European Research Council (ERC advanced grant, BILITERACY, to M.C., and ERC- 209704 to G.T.), the Spanish government (PSI2015-65338-P to M.L, and PSI2015-67353-R to M.C.), and the Economic and Social Research Council UK (RES-E024556-1 to G.T.). BCBL acknowledges funding from Ayuda Centro de Excelencia Severo Ochoa SEV-2015-0490

Hamilton cycles in graphs and hypergraphs: an extremal perspective

As one of the most fundamental and well-known NP-complete problems, the Hamilton cycle problem has been the subject of intensive research. Recent developments in the area have highlighted the crucial role played by the notions of expansion and quasi-randomness. These concepts and other recent techniques have led to the solution of several long-standing problems in the area. New aspects have also emerged, such as resilience, robustness and the study of Hamilton cycles in hypergraphs. We survey these developments and highlight open problems, with an emphasis on extremal and probabilistic approaches.Comment: to appear in the Proceedings of the ICM 2014; due to given page limits, this final version is slightly shorter than the previous arxiv versio