This dataset achieves compressed representation of video data primarily by annotating the relationships between objects, object attributes, and objects in the video. This representation method effectively removes redundant information while preserving the core semantic information of the video.
This series of raw data contains two types of data:
a) synthetically generated data: each file comprises 10^8 bytes, while each byte represents a single symbol drawn from an alphabet with K different symbols. The distribution of theses symbols is either uniform or geometrically (truncated). For K > 256, the files contain 2 bytes per symbol.
b) real-life data (3 files): one screen shot 1785 x 1225 px and two prediction-error images of same size.
This dataset contains EEG recordings collected from 103 Iranian children aged 6–10 years. According to DSM-5 diagnostic criteria, 49 participants were diagnosed with ADHD (22 females, 27 males), while 54 were healthy controls (24 females, 30 males). ADHD participants were recruited from clinical centers, and controls were selected from summer leisure centers in Mashhad, Iran. Only participants with IQ > 75 and without epilepsy or comorbid psychiatric disorders were included. No participant was taking medication at the time of EEG recording.
This dataset was collected using the AWR1843BOOST mmWave radar and the DCA1000 raw data acquisition board. It contains 11,161 samples, including 12 gesture classes and 7 human action classes. Data were recorded with multiple participants, repeated approximately 10 times, and captured across eight diverse environments—laboratories, corridors, and outdoor locations. The dataset includes both static and dynamic secondary targets to reflect realistic conditions and support robust gesture-recognition research under data-loss scenarios.
This dataset provides the resources associated with the paper “A Collaborative Microphone Clustering Framework for Multi-Task Distributed Microphone Arrays”, submitted to IEEE/ACM Transactions on Audio, Speech, and Language Processing.
It includes the simulated distributed microphone array (DMA) data used to evaluate the proposed end–cloud collaborative clustering framework.
All simulation data are generated using the pyroomacoustics toolkit and speech samples from the PTDB-TUG corpus.
TUS at 12 W/cm² significantly increased MEP amplitudes (p = 0.036), indicating enhanced corticospinal excitability.
Electromagnetic behavior of modern radio-frequency front-end printed circuit boards is increasingly shaped by unintentional radiation sources that urgently needed localization and identification in early design stage. The scanned data is for source localization and identification of the radio-frequency front-end printed circuit board.
A continuous multi-terrain lower-limb motion dataset (CMLMD), comprising three scenarios (level ground, stairs, and ramps), five basic motion modes, and eight transitional modes, has been publicly released. The dataset includes 35 participants and a total of 7000 gait cycles.
Listening to 5 Japanese vowels and imagine the sound they have heard.
With white noise as control condition.
Each participant was recorded at same time of two days.
The data acquisition system developed using LabVIEW, captures the hydraulic status of the road machinery through eight pressure sensors, four temperature sensors, and four flow sensors.
