31 research outputs found
Symbolic QED Pre-silicon Verification for Automotive Microcontroller Cores: Industrial Case Study
We present an industrial case study that demonstrates the practicality and
effectiveness of Symbolic Quick Error Detection (Symbolic QED) in detecting
logic design flaws (logic bugs) during pre-silicon verification. Our study
focuses on several microcontroller core designs (~1,800 flip-flops, ~70,000
logic gates) that have been extensively verified using an industrial
verification flow and used for various commercial automotive products. The
results of our study are as follows: 1. Symbolic QED detected all logic bugs in
the designs that were detected by the industrial verification flow (which
includes various flavors of simulation-based verification and formal
verification). 2. Symbolic QED detected additional logic bugs that were not
recorded as detected by the industrial verification flow. (These additional
bugs were also perhaps detected by the industrial verification flow.) 3.
Symbolic QED enables significant design productivity improvements: (a) 8X
improved (i.e., reduced) verification effort for a new design (8 person-weeks
for Symbolic QED vs. 17 person-months using the industrial verification flow).
(b) 60X improved verification effort for subsequent designs (2 person-days for
Symbolic QED vs. 4-7 person-months using the industrial verification flow). (c)
Quick bug detection (runtime of 20 seconds or less), together with short
counterexamples (10 or fewer instructions) for quick debug, using Symbolic QED
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Sustainable Reduction of Sleepiness through Salutogenic Self-Care Procedure in Lunch Breaks: A Pilot Study
The aim of the study was to elucidate the immediate, intermediate, and anticipatory sleepiness reducing effects of a salutogenic self-care procedure called progressive muscle relaxation (PMR), during lunch breaks. The second exploratory aim deals with determining the onset and long-term time course of sleepiness changes. In order to evaluate the intraday range and interday change of the proposed relaxation effects, 14 call center agents were assigned to either a daily 20-minute self-administered PMR or a small talk (ST) group during a period of seven months. Participants' levels of sleepiness were analyzed in a controlled trial using anticipatory, postlunchtime, and afternoon changes of sleepiness as indicated by continuously determined objective reaction time measures (16,464 measurements) and self-reports administered five times per day, once per month (490 measurements). Results indicate that, in comparison to ST, the PMR break (a) induces immediate, intermediate, and anticipatory reductions in sleepiness; (b) these significant effects remarkably show up after one month, and sleepiness continues to decrease for at least another five months. Although further research is required referring to the specific responsible mediating variables, our results suggest that relaxation based lunch breaks are both accepted by employees and provide a sustainable impact on sleepiness
Erfassung von Schläfrigkeit in Funkverkehr-gestützter Kommunikation: sprachsignal-basierte Mustererkennungsanalyse phonetisch-linguistischer Merkmale
An evaluation of the effect of anxiety on speech - computational prediction of anxiety from sustained vowels
EOG feature relevance determination for microsleep detection
Automatic relevance determination (ARD) was applied to two-channel EOG recordings for microsleep event (MSE) recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC) and logarithmic power spectral densities (PSD) averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ) was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM), in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 - 4.9 % and 1.9 - 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 - 0.006 % and 0.002 - 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respec-tively. GRLVQ permits objective feature reduction by inclu-sion of all processing stages, but is not as accurate as SVM
Applying multiple classifiers and non-linear dynamics features for detecting sleepiness from speech
Evaluation of the pain level from speech: introducing a novel pain database and benchmarks
A paper in Speech Communication: 13. ITG-Fachtagung Sprachkommunikation 201
Are men more sleepy than women or does it only look like: automatic analysis of sleepy speech
Minimale Belastung elektrischer Netze durch Ladevorgänge von Elektrobussen
Im städtischen Verkehr ist die klassische als Umweltverbund bezeichnete Förderung umwelt-freundlicher Verkehrsarten seit langem in der Verkehrsplanung etabliert. Durch die qualitätsgerechte Gestaltung der Angebotspalette öffentlicher Verkehrssysteme ist es der Bevölkerung hierbei möglich, auch ohne ein eigenes Automobil ihre Mobilitätsbedürfnisse weitestgehend flexibel zu befriedigen. Der ÖPNV kann durch den Einsatz alternativer Antriebskonzepte einen weiteren Beitrag zu einer verringerten Emission von Schall und Luftschadstoffen (PM10, CO2 und NOx) leisten. In diesem Zusammenhang stellt insbesondere die Ablösung von Diesel- durch Elektrobusse ein großes Potenzial dar. Allerdings stellt dieser Paradigmenwechsel die ÖPNV-Unternehmen bereits in der Planung ihres Verkehrssystems vor neuartige Herausforderungen. Aktuell im ÖPNV eingesetzte Elektrobusse bewältigen ihre tägliche Fahrleistung nur mit Zwischenladevorgängen. Erfolgt das Zwischenladen auf eine örtlich und zeitlich ungünstige Weise, übersteigt der Leistungsbedarf die durch die Nieder-spannungsverteilnetze bereitgestellte Leistung. Das Projekt MENDEL (Minimale Belastung elektrischer Netze durch Ladevorgänge von Elektrobussen) verfolgt die Ziele einer Minimierung der Investitionskosten für die Ladeinfrastruktur durch die optimale Ausnutzung vorhandener Niederspannungsverteilnetze zur Versorgung der Ladestellen. Dadurch wird weitgehend die Errichtung zusätzlicher Trafostationen zum Anschluss an das Mittelspannungsnetz vermieden. Zum anderen wird eine Minimierung der Betriebskosten für die Ladeinfrastruktur durch eine Minimierung des verbrauchsunabhängigen Leistungspreises sowie des Energieverbrauchs der Busse im operativen Betrieb angestrebt