Experimental data and images from the paper “Computation Offloading in Space-Air-Ground Integrated Networks for Diverse Task Requirements with Integrated Reliability Mechanisms.Data on the optimization effect of different algorithms on the SAGIN environment, this data is a csv file. Comparison graph of each data of different algorithms as a jpg file.
This dataset contains 535 recordings of heart and lung sounds captured using a digital stethoscope from a clinical manikin, including both individual and mixed recordings of heart and lung sounds; 50 heart sounds, 50 lung sounds, and 145 mixed sounds. For each mixed sound, the corresponding source heart sound (145 recordings) and source lung sound (145 recordings) were also recorded. It includes recordings from different anatomical chest locations, with normal and abnormal sounds.
PPE Usage Dataset
This repository provides the Personal Protective Equipment (PPE) Usage Dataset, designed for training deep neural networks (DNNs). The dataset was collected using the EFR32MG24 microcontroller and the ICM-20689 inertial measurement unit, which features a 3-axis gyroscope and a 3-axis accelerometer.
The dataset includes data for four types of PPE: helmet, shirt, pants, and boots, categorized into three activity classes: carrying, still, and wearing.
The paucity of data has long hindered the accurate modeling of CO2 concentrations within peatland regions, despite their significance as carbon reservoirs. Peatlands naturally sequester substantial carbon underground, yet disturbances, whether due to climate change or land use shifts, can trigger the release of significant amounts of carbon and other greenhouse gases, thereby disrupting the atmosphere and impacting human lives. The lack of comprehensive data has rendered it challenging to thoroughly assess the peatland regions' contribution to the net ecosystem carbon budget (NECB).
