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Amid global climate change, rising atmospheric methane (CH4) concentrations significantly influence the climate system, contributing to temperature increases and atmospheric chemistry changes. Accurate monitoring of these concentrations is essential to support global methane emission reduction goals, such as those outlined in the Global Methane Pledge targeting a 30% reduction by 2030. Satellite remote sensing, offering high precision and extensive spatial coverage, has become a critical tool for measuring large-scale atmospheric methane concentrations.
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This database, collected at the Neural Engineering Laboratory, Iran University of Science and Technology, comprises iEEG recordings from Wistar rats during healthy and epileptic conditions. Recordings were collected from 5 rats (3 males, 2 females, weighing 260-378 g and aged 4-5 months). iEEG signals were recorded from 3 brain sites: motor cortex (left M1), thalamus (left ANT), and hippocampus (right CA1) of freely moving rats. As a result, for each rat, a matrix with 3 columns (representing the 3 signals) is available in this dataset.
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466 Views
Spread spectrum time domain reflectometry (SSTDR) is proposed to replace the VNA or UWB pulsed systems and switches in a microwave imaging system. These tests evaluate an SSTDR system (Keysight N7081A) from 2-4 GHz. 16 ultrawideband (UWB) antennas were placed in contact with the breast phantom. The McGill breast phantom is a hemispherical carbon-based phantom with the electrical properties of fat. A cylindrical hole allows for the insertion of a plug with fat properties or fat+tumor properties. These were both measured and provided in the attached data set.
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253 Views
This dataset contains electrocardiography (ECG) data recorded under controlled laboratory conditions. The primary objective of the measurement was to evaluate and compare different types of electrodes made from conductive textile materials in terms of their signal quality and performance. The dataset includes recordings from both conventional adhesive electrodes and textile electrodes to assess their suitability for ECG monitoring.
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52 Views
TOWalk: A Multi-Modal Dataset for Real-World Movement Analysis
The TOWalk Dataset has been developed to support research on gait analysis, with a focus on leveraging data from head-worn sensors combined with other wearable devices. This dataset provides an extensive collection of movement data captured in both controlled laboratory settings and natural, unsupervised real-world conditions in Turin (Italy).
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296 Views
Synthetic EEG Dataset for CNN Training: Clean and Artifact-Contaminated Signals
This dataset consists of synthetically generated EEG and EMG signals designed for training Convolutional Neural Networks (CNNs) in artifact detection and removal. The dataset includes both clean EEG signals and EEG signals contaminated with simulated EMG artifacts from various sources.
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203 Views
As an important component of inertial guidance and navigation, micro-electro-mechanical-system (MEMS) gyroscope is widely used in many fields. However, the accumulation of noise errors limits the long-term accuracy and further application of MEMS gyroscope. This paper proposes a novel denoising method for MEMS gyroscope based on interpolated complementary ensemble local mean decomposition with adaptive noise (ICELMDAN) and gated recurrent unit-unscented Kalman filter (GRU-UKF).
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This dataset contains signals collected on 7 different dates from 13 wired Ethernet network cards transmitted using the 100BASE-TX protocol. The signal is collected at the access point (switch side) using an oscilloscope with a sampling rate of 625Mbps and a sampling accuracy of 8 bits.
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1) RPaviaU-DPaviaC Dataset: The RPaviaU-DPaviaC dataset is constructed by amalgamating two publicly accessible HSI datasets: the ROSIS Pavia University (RPaviaU) scene and the DAIS Pavia Center (DPaviaC) scene. The RPaviaU dataset, featuring dimensions of 610 × 340 × 103, was acquired by the ROSIS HSI sensor over the terrain of the University of Pavia, Italy. Conversely, the DPaviaC dataset, with dimensions of 400 × 400 × 72, was collected using the DAIS sensor over the central area of Pavia City, Italy. These two scenes share a common set of seven land cover classes.
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215 Views