Discrete-time signal processing
This research introduces the Open Seizure Database and Toolkit as a novel, publicly accessible resource designed to advance non-electroencephalogram seizure detection research. This paper highlights the scarcity of resources in the non-electroencephalogram domain and establishes the Open Seizure Database as the first openly accessible database containing multimodal sensor data from 49 participants in real-world, in-home environments.
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A recent study [1] alerts on the limitations of evaluating anomaly detection algorithms on popular time-series datasets such as Yahoo, Numenta, or NASA, among others. In particular, these datasets are noted to suffer from known flaws suchas trivial anomalies, unrealistic anomaly density, mislabeled ground truth, and run-to-failure bias. The TELCO dataset corresponds to twelve different time-series, with a temporal granularity of five minutes per sample, collected and manually labeled for a period of seven months between January 1 and July 31, 2021.
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Radio Frequency (RF) signals transmitted by Global Navigation Satellite Systems (GNSS) are exploited as signals of opportunity in many scientific activities, ranging from sensing waterways and humidity of the terrain to the monitoring of the ionosphere. The latter can be pursued by processing the GNSS signals through dedicated ground-based monitoring equipment, such as the GNSS Ionospheric Scintillation and Total Electron Content Monitoring (GISTM) receivers.
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<p>Two-electrode straight open magnetic source (TSOMS) has been widely used on the magnetic minesweeper and magnetic decoy. Fast-forward modeling and obtaining the high-precision magnetic field in the air are the prerequisites for real-time inversion and positioning of the TSOMS. In this paper, we propose an algorithm to calculate the magnetic field of the two-electrode straight open magnetic source (MFTSOMS) by previous theoretical research. And a classical algorithm of electric dipole magnetic field is used to verify the correctness of our algorithm.
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A clinical trial using three locations of the Dialysis Center of China Medical University Hospital (CMUH) was implemented to conduct unguarded gait monitoring of three independent 1.5 m walkways from 2021/11/12 to 2022/5/18. This clinical trial was approved by the Institutional Review Board (CMUH108-REC2-022) of CMUH Research Ethics Center. In addition, all methods performed in this study were in accordance with current regulations and guidelines.
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Device fingerprinting is a technique for remote indirect identification or classification of a device of interest. This database is designated for device fingerprinting by current consumption; it includes current recordings for 22" computer displays from 40 devices - 20 Dell P2217H and 20 Dell E2214H. Two signals for each device were sampled independently and sequentially to provide independent train and test parts. Each sampled signal includes a 250-second recording at a 50kHz sampling frequency.
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The data involves 15 years of daily data of DJI, S&P, and IXIC, ranging from 01/01/2005 to 12/31/2020.
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