Sensors
A synthetic dataset designed to evaluate transfer learning performance for RF domain adaptation in the publication Assessing the Value of Transfer Learning Metrics for RF Domain Adaptation. The dataset contains a total of 13.8 million examples, with 600k examples each of 22 modulation schemes (given below) and AWGN noise (200k each for training, validation, and testing); 512 raw IQ samples per example.
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Minimally-Invasive Surgeries can benefit from having miniaturized sensors on surgical graspers to provide additional information to the surgeons. One such potential sensor is an ultrasound transducer. At long travel distances, the ultrasound transducer can accurately measure its ultrasound wave's time of flight, and from it, classify the grasped tissue. However, the ultrasound transducer has a ringing artifact arising from the decaying oscillation of its piezo element, and at short travel distances, the artifact blends with the acoustic echo.
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Context awareness is an emerging field in pervasive computing with applications that have started to emerge in medical systems. The present work seeks to determine which contexts are important for medical applications and what various domains of context aware applications exist in healthcare. Methods: A systematic scoping review of context aware medical systems currently being used in healthcare settings was conducted.
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The ANDON tower uses the low-cost NRF24L01 transceiver to send the experimental data from the sensor node to the coordinator node, with a computer connected to the coordinator node to store the data in a CSV file. The transceiver uses the SPI protocol for communication with the ANDON tower microcontroller. Its maximum range is 30 meters, however the maximum distance in the experimental scenario is 16 m. The transceiver works in the 2.4GHz free band and allows setting the transmission power in -18dBm, -12dBm, -6dBm and 0dBm.
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In-house raw audio data is collected from road traffic areas in Durgapur, a sub-urban city in India. We have developed a customized android application for collecting the data from the environment. Approximately 124km road traffic area is covered to do the same. The android application helps us to monitor the noise data in different sampling rates and bit rates. The sampling rate can be set to one of 8000 Hz, 16 000 Hz, 32 000 Hz, 44 100 Hz, 48 000 Hz. On the other hand, the bit rate can be set to one of 24 kbps, 48 kbps, 96 kbps, 128 kbps, 192 kbps.
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This repository shares the dataset of our publication "NR-LOM: LiDAR Odometry and Mapping Integrating 5G New Radio Technology". The raw data contains LiDAR, IMU, GNSS, encoder measurements in rosbag. Besides we also provide raw 5G measurements and real-time 5G positions from a 5G PRS beacon.
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creating a 3D reconstruction of an object using multiple inward depth sensors that can be imported into any augmented/virtual reality application.
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With the rapid deployment of indoor Wi-Fi networks, Channel State Information (CSI) has been used for device-free occupant activity recognition. However, various environmental factors interfere with the stable propagation of Wi-Fi signals indoors, which causes temporal variation of CSI data. In this study, we investigated temporal CSI variation in a real-world housing environment and its impact on learning-based occupant activity recognition.
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Two dataset collected by USkin tactile sensors for detecting grasping stability and slip detection during lifting objects.
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