On-Line Instruction-checking in Pipelined Microprocessors

Microprocessors performances have increased by more than five orders of magnitude in the last three decades. As technology scales down, these components become inherently unreliable posing major design and test challenges. This paper proposes an instruction-checking architecture to detect erroneous instruction executions caused by both permanent and transient errors in the internal logic of a microprocessor. Monitoring the correct activation sequence of a set of predefined microprocessor control/status signals allow distinguishing between correctly and not correctly executed instruction

Statistical Reliability Estimation of Microprocessor-Based Systems

What is the probability that the execution state of a given microprocessor running a given application is correct, in a certain working environment with a given soft-error rate? Trying to answer this question using fault injection can be very expensive and time consuming. This paper proposes the baseline for a new methodology, based on microprocessor error probability profiling, that aims at estimating fault injection results without the need of a typical fault injection setup. The proposed methodology is based on two main ideas: a one-time fault-injection analysis of the microprocessor architecture to characterize the probability of successful execution of each of its instructions in presence of a soft-error, and a static and very fast analysis of the control and data flow of the target software application to compute its probability of success. The presented work goes beyond the dependability evaluation problem; it also has the potential to become the backbone for new tools able to help engineers to choose the best hardware and software architecture to structurally maximize the probability of a correct execution of the target softwar

An Ensemble of Adaptive Classifiers for Improving Faulty and Drifting Sensor Performance

n/

ATPG for Dynamic Burn-In Test in Full-Scan Circuits

Yield and reliability are two key factors affecting costs and profits in the semiconductor industry. Stress testing is a technique based on the application of higher than usual levels of stress to speed up the deterioration of electronic devices and increase yield and reliability. One of the standard industrial approaches for stress testing is high temperature burn-in. This work proposes a full-scan circuit ATPG for dynamic burn-in. The goal of the proposed ATPG approach is to generate test patterns able to force transitions into each node of a full scan circuit to guarantee a uniform distribution of the stress during the dynamic burn-in tes

Sensor-embedded face masks for detection of volatiles in breath: a proof of concept study

The correlation between breath volatilome and health is prompting a growing interest in the development of sensors optimized for breath analysis. On the other hand, the outbreak of COVID-19 evidenced that breath is a vehicle of infection; thus, the introduction of low-cost and disposable devices is becoming urgent for a clinical implementation of breath analysis. In this paper, a proof of concept about the functionalization of face masks is provided. Porphyrin-based sensors are among the most performant devices for breath analysis, but since porphyrins are scarcely conductive, they make use of costly and bulky mass or optical transducers. To overcome this drawback, we introduce here a hybrid material made of conducting polymer and porphyrins. The resulting material can be easily deposited on the internal surface of standard FFP face masks producing resistive sensors that retain the chemical sensitivity of porphyrins implementing their combinatorial selectivity for the identification of volatile compounds and the classification of complex samples. The sensitivity of sensors has been tested with respect to a set of seven volatile compounds representative of diverse chemical families. Sensors react to all compounds but with a different sensitivity pattern. Functionalized face masks have been tested in a proof-of-concept test aimed at identifying changes of breath due to the ingestion of beverages (coffee and wine) and solid food (banana- and mint-flavored candies). Results indicate that sensors can detect volatile compounds against the background of normal breath VOCs, suggesting the possibility to embed sensors in face masks for extensive breath analysis

Automatic March Tests Generations for Static Linked Faults in SRAMs

Static linked faults are considered an interesting class of memory faults. Their capability of influencing the behavior of other faults causes the hiding of the fault effect and makes test algorithm design a very complex task. A large number of March tests with different fault coverage have been published and some methodologies have been presented to automatically generate March tests. In this paper we present an approach to automatically generate March tests for static linked faults. The proposed approach generates better test algorithms then previous, by reducing the test lengt

Cross-Layer Early Reliability Evaluation for the Computing cOntinuum

Advanced multifunctional computing systems realized in forthcoming technologies hold the promise of a significant increase of the computational capability that will offer end-users ever improving services and functionalities (e.g., next generation mobile devices, cloud services, etc.). However, the same path that is leading technologies toward these remarkable achievements is also making electronic devices increasingly unreliable, posing a threat to our society that is depending on the ICT in every aspect of human activities. Reliability of electronic systems is therefore a key challenge for the whole ICT technology and must be guaranteed without penalizing or slowing down the characteristics of the final products. CLERECO EU FP7 (GA No. 611404) research project addresses early accurate reliability evaluation and efficient exploitation of reliability at different design phases, since these aspects are two of the most important and challenging tasks toward this goal

The FDA “black box” warning on antidepressant suicide risk in young adults: More harm than benefits?

The decision made in the year 2004 by the U.S. Food and Drug Administration (FDA) to require a boxed warning on antidepressants regarding the risk of suicidality in young adults still represents a matter of controversy. The FDA warning was grounded on industry-sponsored trials carried one decade ago or earlier. However, within the past decade, an increasing number of reports have questioned the actual validity of the FDA warning, especially considering a decline in the prescription of the antidepressant drugs associated with an increase in the rate of suicidal events among people with severe depression. The present report provides an overview of the FDA black box warning, also documenting two Major Depressive Disorder patients whose refusal to undergo a pharmacological antidepressant treatment possibly led to an increased risk for suicidal behaviors. The concerns raised by the FDA black box warning need to be considered in real-world clinical practice, stating the associated clinical and public health implications

Room Temperature CO Detection by Hybrid Porphyrin-ZnO Nanoparticles

AbstractPorphyrins are the natural candidates to the detection of carbon monoxide however the physical properties of solid-state layers of porphyrins limit their use as gas sensors mainly with mass and optical transducers. Recently we shown that the photonic properties of porphyrins, brilliantly exploited in organic solar cells, can lead to a new class of photo-activated sensors made by porphyrins coated metal oxides. Here we investigate the sensitivity to carbon monoxide of resistive sensors made by zinc oxide nanoparticles coated by a porphyrin layer. Sensors were prepared following two different routes and tested, at room temperature and in various light conditions, to CO and few volatile compounds. Results show a significant sensitivity and selectivity to CO