Standards Research Data

Database for a moderation of technological acceptance research

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This is a dataset is an example of a distribution of 20 correlated Bernoulli random variables.

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This work provides the measurement data of sixteen high frequency (HF) radio frequency identification (RFID) transponder (tag) chips. In particular, the chip input impedance was characterized versus chip input voltage at 13.56 MHz. The measurement is based on the radio frequency current-voltage impedance measurement method and achieves, compared to previous work, higher measurement accuracy of lower than 1.5 %. The accompanying publication provides additional details.

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1.Visualization of convolutional neural network layers for one participant at ROI 301 * 301

2.Convolutional neural network structure analysis in Matlab

3.Convolutional neural network Matlab code

4.Videos of brightness mode (B-mode) ultrasound images from two participants during the recorded walking trials at 5 different speeds

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This is the result found by multi-tree-search.</p>

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Extensive experimental measurement campaigns of more than 30,000 data points of end-to-end latency measurements for the following network architecture schemes is available:

  • Unlicensed IoT (standalone LoRa)
  • Cellular IoT (standalone LTE-M)
  • Concatenated IoT (LoRa interfaced with LTE-M)

Download Data.zip to access all relevant files for the open data measurements.

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The data are associated with a submitted journal paper.

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   Dataset angin adalah

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This dataset supports researchers in the validation process of solutions such as Intrusion Detection Systems (IDS) based on artificial intelligence and machine learning techniques for the detection and categorization of threats in Cyber Physical Systems (CPS). To that aim, data have been acquired from a water distribution hardware-in-the-loop testbed which emulates water passage between nine tanks via solenoid-valves, pumps, pressure and flow sensors. The testbed is composed by a real partition which is virtually connected to a simulated one.

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<p><span class="fontstyle0">Software architecture is the most important determinant<br />to systematically achieve quality attributes in a software<br />system, including software performance. However there is no<br />comprehensive understanding of why and how to integrate<br />software architecture and performance analysis to guide research.<br />To fill this gap, this paper presents a systematic review of 83<br />studies.

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