161 research outputs found

    A machine learning-based approach to optimize repair and increase yield of embedded flash memories in automotive systems-on-chip

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    Nowadays, Embedded Flash Memory cores occupy a significant portion of Automotive Systems-on-Chip area, therefore strongly contributing to the final yield of the devices. Redundancy strategies play a key role in this context; in case of memory failures, a set of spare word- and bit-lines are allocated by a replacement algorithm that complements the memory testing procedure. In this work, we show that replacement algorithms, which are heavily constrained in terms of execution time, may be slightly inaccurate and lead to classify a repairable memory core as unrepairable. We denote this situation as Flash memory false fail. The proposed approach aims at identifying false fails by using a Machine Learning approach that exploits a feature extraction strategy based on shape recognition. Experimental results carried out on the manufacturing data show a high capability of predicting false fails

    Recent Trends and Perspectives on Defect-Oriented Testing

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    Electronics employed in modern safety-critical systems require severe qualification during the manufacturing process and in the field, to prevent fault effects from manifesting themselves as critical failures during mission operations. Traditional fault models are not sufficient anymore to guarantee the required quality levels for chips utilized in mission-critical applications. The research community and industry have been investigating new test approaches such as device-aware test, cell-aware test, path-delay test, and even test methodologies based on the analysis of manufacturing data to move the scope from OPPM to OPPB. This special session presents four contributions, from academic researchers and industry professionals, to enable better chip quality. We present results on various activities towards this objective, including device-aware test, software-based self-test, and memory test

    Test, Reliability and Functional Safety Trends for Automotive System-on-Chip

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    This paper encompasses three contributions by industry professionals and university researchers. The contributions describe different trends in automotive products, including both manufacturing test and run-time reliability strategies. The subjects considered in this session deal with critical factors, from optimizing the final test before shipment to market to in-field reliability during operative life

    Integrative epigenome-wide analysis demonstrates that DNA methylation may mediate genetic risk in inflammatory bowel disease

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    Epigenetic alterations may provide important insights into gene-environment interaction in inflammatory bowel disease (IBD). Here we observe epigenome-wide DNA methylation differences in 240 newly-diagnosed IBD cases and 190 controls. These include 439 differentially methylated positions (DMPs) and 5 differentially methylated regions (DMRs), which we study in detail using whole genome bisulphite sequencing. We replicate the top DMP (RPS6KA2) and DMRs (VMP1, ITGB2 and TXK) in an independent cohort. Using paired genetic and epigenetic data, we delineate methylation quantitative trait loci; VMP1/microRNA-21 methylation associates with two polymorphisms in linkage disequilibrium with a known IBD susceptibility variant. Separated cell data shows that IBD-associated hypermethylation within the TXK promoter region negatively correlates with gene expression in whole-blood and CD8+ T cells, but not other cell types. Thus, site-specific DNA methylation changes in IBD relate to underlying genotype and associate with cell-specific alteration in gene expression

    Assessment of PV Plant Monitoring System by Means of Unmanned Aerial Vehicles

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    Photovoltaic (PV) plant monitoring is recently representing an important field in the energy market, due to the large diffusion of PV plants, often built with low technical standards in the past decade and lack of accuracy in OM activities after the first 5-year life of the plant. In this paper, the authors proposed an expert system that, based on the image integration obtained by means of Unmanned Aerial Vehicles (UAVs), is able to identify some defects in PV modules and to analyze from an economical point the impact of these defects

    Interfacial Strength and Morphology of New Self-adhesive Resin Cements

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    5nonenoneCantoro A; Goracci C; Mazzoni A; Breschi L; Ferrari MCantoro, A; Goracci, C; Mazzoni, Annalisa; Breschi, Lorenzo; Ferrari, M
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