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Alarm Signal

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Tongwen Chen – 1st expert on this subject based on the ideXlab platform

  • optimal Alarm Signal processing filter design and performance analysis
    IEEE Transactions on Automation Science and Engineering, 2013
    Co-Authors: Yue Cheng, Iman Izadi, Tongwen Chen


    Accuracy and efficiency of Alarm systems are of paramount importance in safe operations of industrial processes. Accuracy is measured by false and missed Alarm rates (probabilities); while efficiency relates to the detection delay and complexity of the technique used. Moving average filters are often employed in industry for improved Alarm accuracy. Can one do better than moving average filters? The following two problems are studied in this paper: First, given both normal and abnormal statistic distributions, how to design an optimal Alarm filter (of fixed complexity) for best Alarm accuracy, minimizing a weighted sum of false and missed Alarm rates? Second, in what cases are moving average filters optimal? For the first problem, design of optimal linear FIR Alarm filters is studied, and a numerical optimization based procedure is proposed. For the second problem, a sufficient condition is given under which the moving average filters are optimal.

Jun Yang – 2nd expert on this subject based on the ideXlab platform

  • A Low-Overhead Timing Monitoring Technique for Variation-Tolerant Near-Threshold Digital Integrated Circuits
    IEEE Access, 2018
    Co-Authors: Weiwei Shan, Xinning Liu, Minyi Lu, Liang Wan, Jun Yang


    Near-threshold computing brings several times of magnitude improvement in energy efficiency of digital circuits. However, it also introduces several times of deteriorated delay variations caused by process, voltage and temperature (PVT) variations. In-situ timing monitoring based adaptive techniques can mitigate excessive timing margins caused by PVT variations, but current frequency and/or voltage tuning methods cause large performance loss. In this paper, we propose a low overhead timing error prediction monitor and a super-fast clock stretching circuit to solve this problem. They are both optimized for near-threshold voltage of 0.5V. When there are timing margins, the frequency will be increased. Until when the timing is intense due to variations, timing monitors will generate a predicted Alarm Signal. Accordingly, the system clock will be stretched immediately to avoid real timing errors. Applied on a 40nm CMOS Bitcoin Miner chip, simulation results show that the whole system operating at near-threshold voltage can increase the frequency to up to 2.1×compared to the original non-monitored circuit. Our method can increase the energy efficiency to mitigate near-threshold variations effectively.

Tarunraj Singh – 3rd expert on this subject based on the ideXlab platform

  • the effects of adverse condition warning system characteristics on driver performance an investigation of Alarm Signal type and threshold level
    Behaviour & Information Technology, 2002
    Co-Authors: Nitin Gupta, Ann M Bisantz, Tarunraj Singh


    This study addresses the issues concerning the design of adverse condition warning systems (ACWS). ACWS are designed to sense adverse road and weather conditions as well as system states that can negatively impact driving performance leading to skids or accidents, and alert drivers to these conditions. In this case, an ACWS was designed to sense when a car was likely to skid. A virtual-driving environment was used to test two levels of Alarm sensitivity (low and high) and two types of auditory Alarm Signal (Binary ON/OFF and Graded) along with a no-Alarm control group. Dependent measures reflected driver performance, response to the Alarm Signal and trust in the alerting system. Results indicated that participants had fewer skids in the low sensitivity and graded Alarm Signal condition compared to some other alerting system configurations. Participants in the graded Alarm Signal condition also had a greater degree of lateral control over the vehicle. Additionally, trust was found to be lower for the high …