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Standards Research Data

Reconfigurable Intelligent Surface(RIS) benchmarking results and simulation code.

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This code and related data is related to research work on quantified benchmarking of Reconfigurable Intelligent Surface (RIS). Related research article has been submitted to VTM titled "Reconfigurable Intelligent Surfaces: Tradeoff between Unit-Cell- and Surface-Level Design under Quantifiable Benchmarks". 'ReadMe.text' file in 'RIS_restricted_02.zip' explains how to use the code to generate RIS configurations for RIS of arbitrary size and unit cell design, which can accomodate restricting to certain size grouped control.

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Typical charge/discharge of a supercapacitor

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The data set deals with a typicla charge-discharge cycle of a supercapacitor (here a NICHICON UM series, 2.7V, 1F):

  • Very fast charge of the EDLC
  • Discharge at more or less constant power

Data have been sampled at 10 Hz with the biologic VMP3 potentiostat.

 

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Incomplete datasets for UP-FHDI

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Parallel fractional hot-deck imputation (P-FHDI) is a general-purpose, assumption-free tool for handling item nonresponse in big incomplete data by combining the theory of FHDI and parallel computing. FHDI cures multivariate missing data by filling each missing unit with multiple observed values (thus, hot-deck) without resorting to distributional assumptions. P-FHDI can tackle big incomplete data with millions of instances (big-n) or 10, 000 variables (big-p).

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HF RFID Tag Chip Impedance Measurements

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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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Experimental data of sEMG, US imaging, GRF, and markers for walking on treadmill across multiple speeds

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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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Dataset for End-to-end Latency Measurements of Standalone and Concatenated LPWAN Architectures with LoRa and LTE-M Networks

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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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