Sensors
Manual palpation of organs played a vital role in detecting abnormalities in open surgeries. However, surgeons
have lost this ability with the development of minimally invasive surgeries. This challenge led to the development of artificial sensors for palpating the patient's organs and tissue. The majority of research done is related to improving the measurement of tissue compliance by the development of versatile force sensors for surgical
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826 Views
In situations when the precise position of a machine is unknown, localization becomes crucial. It is crucial to identify and ascertain the machine's position. This research focuses on improving the position prediction accuracy over long-range networks using a unique machine learning-based technique. In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting approach using LoRa technology, this study suggested an ML-based algorithm.
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637 Views
This dataset captures the results of a simulation experiment on underwater collaborative navigation and formation control techniques for DSUA-IVV using DSUA sensors. The data includes the following: 1) the leader and follower's position, velocity amplitude, and motion direction in a fixed formation. 2) The leader and follower's location and amplitude of velocity during the formation transition process. 3) DSUA sensor sensitivity analysis data. Code files for processing and visualizing this data are also included in the dataset.
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129 Views
Automated and autonomous industrial inspection is a longstanding research field, driven by the necessity to enhance safety and efficiency within industrial settings. In addressing this need, we introduce an autonomously navigating robotic system designed for comprehensive plant inspection. This innovative system comprises a robotic platform equipped with a diverse array of sensors integrated to facilitate the detection of various process and infrastructure parameters.
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291 Views
RRN-ATR-Net is a radar echo data set containing the micro-Doppler signatures (m-Ds) of different aerial targets, with a total sample size of 1200. It is available for researchers interested in this field but having difficulty collecting data. The data set is acquired using Texas Instruments' AWR1642BOOST radar sensor and the DCA1000EVM high-speed data acquisition card. The target types subject to acquisition include quadrotor (Phantom3s), fixed-wing (Cessna182), helicopter (T-REX450), and bionic bird (Gogo Bird1020).
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340 Views
This data repository comprises three distinct datasets tailored for different predictive modeling tasks. The first dataset is a synthetic dataset designed to simulate multivariate time series patterns, incorporating both linear and non-linear dependencies among input and target features. The second dataset, the Beijing Air Quality PM2.5 dataset, consists of PM2.5 measurements alongside meteorological data like temperature, humidity, and wind speed, with the objective of predicting PM2.5 concentrations.
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363 Views
We utilized Digital Ocean's cloud service, setting up three Linux virtual machines, each with 1vCPU, 1GB of memory, and a 10GB disk. The architecture included an API gateway for routing requests to a stateless application service backed by a database for storing application data. The application operates the service under a fluctuating workload generated by a load-testing script to simulate real-world usage scenarios. The target source or the application service is integrated with Prometheus, a monitoring tool for gathering system metrics.
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463 Views
This paper proposes and experimentally validates a distributed temperature alarm system based on carbon dioxide (CO2)-filled side air-holes fiber (SAHF), interrogated through a conventional (incoherent) optical time-domain reflectometer (OTDR). Customizable alarm threshold temperatures can be designed and set by adjusting the pressure of the CO2 filling the air-hole region, which in turn determines a threshold temperature under which CO2 liquefies.
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19 Views
This dataset presents a comprehensive collection of measurements from a Thermoelectric Generator (TEG) energy harvesting prototype, equipped with nine PT100 temperature sensors and detailed recordings of voltage and current outputs. Collected over a 12-month period starting in October 2022, the data provide insights into the performance of the TEG under varying environmental conditions.
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358 Views
This paper presents a deep learning model for fast and accurate radar detection and pixel-level localization of large concealed metallic weapons on pedestrians walking along a sidewalk. The considered radar is stationary, with a multi-beam antenna operating at 30 GHz with 6 GHz bandwidth. A large modeled data set has been generated by running 2155 2D-FDFD simulations of torso cross sections of persons walking toward the radar in various scenarios.
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8 Views