This design is a Pulse Shrinking TDC with 2ps resolution, which is reduced to 7 CLBs.

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This paper reports on optical time-of-flight as a detection mode for soft optical deformation sensors. In this work, low-cost miniature light detection and ranging (LiDAR) chips recently developed for consumer mobile device applications perform real-time optical reflectometry at cm scales in soft optical waveguide networks. Our methodscomplement existing work by capturing spatial information that is lost with amplitude-only measurements.

Instructions: 

'''

# This program is to show the histo data from VL53L3CX run on Nucleo.

# Run the ST VL53L3CX Gui first. Select the right sensor ( you can calibrate or not) 

# that connects the optical fibers.( This can also be done with the Realterm) 

# Close the ST VL53L3CX Gui.The Gui will leave either the gui or range channel open.

 

# Open the Realterm (set up wight with all the good parameters )to check the channels.

# Realterm: Check "Display As" and select Ascii (fifth from the bottom), check "New Line mode" and check "Scrollback" at 200.

# Realterm: Change Baud to 460800, and select serial port Necleo is plug in and highligth "open"

# Realterm: Check +CR in the "Send" menu. Use command "ch_list" and hit "Send ASCII" to see channels openings.

# This program is to show the histo data from VL53L3CX run on Nucleo.

# Run the ST VL53L3CX Gui first. Select the right sensor ( you can calibrate or not) 

# that connects the optical fibers.( This can also be done with the Realterm) 

# Close the ST VL53L3CX Gui.The Gui will leave either the gui or range channel open.

 

# Open the Realterm (set up wight with all the good parameters )to check the channels.

# Realterm: Check "Display As" and select Ascii (fifth from the bottom), check "New Line mode" and check "Scrollback" at 200.

# Realterm: Change Baud to 460800, and select serial port Necleo is plug in and highligthed "open"

# Realterm: Check +CR in the "Send" menu. Use command "ch_list" and hit "Send ASCII" to see channels openings.

# Realterm: Use the commands such as "ch_close gui" to close the gui channel and "ch_open histo" to open the histo channel. 

# Realterm: Use "ch_list" to check the channel opening again.

# Realterm: Use "enable" to stream data, and use ^C button to stop streaming data. 

# Realterm: Hit "open" under port to un-highlight and close the port so Python can have access to

# Realterm:the port that you have your Nucleo plugged in, normally shown 1 to 4.

'''

'''

Now this Python program is getting to run and see the Nucleo histo data. Instructions are below.

1. Open a Terminal window on your PC, assuming Python has been installed.

2. Change directory to the program saved in my Documents folder. In this case I enter "cd Documents"

3. Enter "Python First.py" in the terminal to run this program.

4. When the prompt "y" shows up, hit "Enter" a few times until you see the raw histo data showing on the terminal

5. Enter "bar300" to test the histogram graph. The number after bar is the time in seconds

6. Due to some data mis-transmission reasons, it tends to run shorter time than it is set up.

7. You can continue to run "bar3000" for another longer run after your assigned time is up and "y" prompt shows up.

8. Enter "stop" to stop the program when prompted of "y"

9. You can also close the terminal if want to stop the program.

'''

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Pulse Shrinking TDC utilizing the FPGA cell block Architecture. Ultra Compact Design.

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The data provided corresponds to the open-source codes and reference images from a computer interface for real-time gait biofeedback using a Wearable Integrated Sensor System for Data Acquisition.This data is the supplmementary material of the publication I. Sanz-Pena, J. Blanco and J. H. Kim, "Computer Interface for Real-Time Gait Biofeedback Using a Wearable Integrated Sensor System for Data Acquisition," in IEEE Transactions on Human-Machine Systems, https://doi.org/10.1109/THMS.2021.3090738

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This dataset contains multimodal sensor data collected from side-channels while printing several types of objects on an Ultimaker 3 3D printer. Our related research paper titled "Sabotage Attack Detection for Additive Manufacturing Systems" can be found here: https://doi.org/10.1109/ACCESS.2020.2971947. In our work, we demonstrate that this sensor data can be used with machine learning algorithms to detect sabotage attacks on the 3D printer.

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328 Views

The Jackal UGV, from Clearpath Robotics, was used as the data collecting platform. This skid-steer four-wheel-drive vehicle comes with an onboard IMU, two DC motors with encoders that measure wheel angular speeds, and current sensors that measure motor current outputs. On each side of the robot, the front wheel and back wheel are jointed with a gearbox and so spin together at the same rate and direction. The IMU provided vehicle attitude measurements in terms of Euler angles, as well as linear acceleration and angular rate of the vehicle body in three Euclidean axes.

Instructions: 

Each HDF5 file contains four types of data entries: timestamps, signals, images, and labels. A .ipynb code example is included to demonstrate how to retrieve and format data appropriately. 

The .ipynb script requires h5py, numpy, and matplotlib libraries.

** If you plan to load the entire dataset into your memory, make sure your PC has >16 Gb RAM

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125 Views

 

Normal
0

false
false
false

EN-GB
X-NONE
X-NONE

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64 Views

The dataset contains 4600 samples of 12 different hand-movement gestures. Data were collected from four different people using the FMCW AWR1642 radar. Each sample is saved as a CSV file associated with its gesture type.

Instructions: 

Dataset is divided into 12 separate folders associated to different gesture types. Each folder contains gesture samples saved as a CSV file. First line of the CSV file is a headline describing the columns of data: FrameNumber, ObjectNumber, Range, Velocity, PeakValue, x coordinate, y coordinate. In order to read the gestures into matrix representation copy all 12 folders into single folder called “data”. Copy the “read_gesture.py” script to the same folder as “data” and run it. Script will convert CSV files of given gesture type into the numpy matrix.

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This dataset consists of temporal and temperature drift characteristics of Si3N4-gate iSFET andsupplementary files

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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.

Related Paper:

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