Sensors
Thermocouples are widely used in industrial applications due to their robustness, low cost, reliability and ability to survive in harsh environments. However, these thermocouples are prone to failure in a highly acidic medium such as nuclear fuel reprocessing plants. This paper investigates the degradation phenomenon and its effect on measurement accuracy when a thermocouple with mechanical damage to the protective sheath is placed in a corrosive media.
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This dataset contains measured data from five sensor modules designed for monitoring the oxygen concentration in the air in a hospital environment, especially in rooms where oxygen therapy can potentially occurs. This data is crucial from a safety point of view, as a higher oxygen concentration can increase the risk of fire development.
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This dataset protocol details the acquisition of a surface electromyography (sEMG) dataset from the Tibialis Anterior (TA) and Gastrocnemius Lateralis (GL) muscles of 20 healthy adults, with an equal distribution of 10 male and 10 female participants. The data was collected using the Delsys Trigno wireless EMG system during a 30-second walking session. Proper electrode placement on the specified muscles was ensured for accurate signal capture. Ethical considerations were addressed, with approval from the Institutional Review Board and informed consent from participants.
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This paper presents a bi-directional Long ShortTerm Memory (LSTM) model for the detection of landslides. Previous uses of machine learning in this setting have demonstrated its general potential, which necessitates the implementation of a suitable algorithm. Landslides are natural disasters that can cause significant destruction and disruption in the affected areas. Early detection is the key to minimizing the impact of landslides, so it is important to develop accurate and efficient models.
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The dataset consists of measurements of four different stages of degradation in low-voltage contactors used for industrial purposes. The measurements were obtained with fiber Bragg grating (FBG) sensors that detect the dynamic deformation generated in switching under different internal components. The measurements were processed and features from PSD, FFT and TSFEL python library were extracted. The features of PSD and FFT were acquired in 40 sliding windows of 50Hz from the signal.
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This dataset comprises gunshot audio and supporting data released as part of ShotSpotter Tech Note 098, "Precision and accuracy of acoustic gunshot location in an urban environment".
The data derive from a series of live fire tests of the ShotSpotter Respond gunshot location system conducted in Pittsburgh, PA on December 18th, 2018 by the Pittsburgh Bureau of Police. ShotSpotter uses live fire tests to validate that the deployed sensor density is appropriate for the community in question, and to ensure the system is ready for production use.
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In this brief, the distributed cubature information filtering method is proposed to solve the state estimation problem of target in passive sensor network. Firstly, the observation system model of bearing-only sensor network is established and analysised. The sensor node pairs only measure the relative angle information, and then the state estimation of the target is realized based on the DCIF algorithm.
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Dataset for validation of a new magnetic field-based wearable breathing sensor (MAG), which uses the movement of the chest wall as a surrogate measure of respiratory activity. Based on the principle of variation in magnetic field strength with the distance from the source, this system explores Hall effect sensing, paired with a permanent magnet, embedded in a chest strap.
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