This paper introduces the Chinese Social Media Autism Children Dataset (CSMACD), a novel resource for autism spectrum disorder (ASD) research. CSMACD compiles high-definition, unobstructed frontal facial images of Chinese children (aged 6 months to 15 years) with ASD, sourced from mainstream social media platforms (e.g., Bilibili, Douyin, and Tencent Video). Videos were identified using ASD-related keywords (e.g., "autism," "Star Baby") and recommendation algorithms.
Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder that impairs a person's ability to concentrate, manage impulses, and maintain attention. ADHD can have a wide range of repercussions, including academic and professional difficulties as well as relationship and emotional issues. Individuals with ADHD may also have handwriting impairments, such as poor fine motor coordination, legibility, and writing speed. These writing difficulties may be related to dysgraphia, a specific writing impairment that affects people with ADHD.
As human-robot interaction rapidly spreads in numerous fields, the subject of robot acceptance gains increasing importance. Visual similarity to the human body, as occurs for humanoids, is generally not enough to guarantee acceptance in physical interaction, as acceptance directly links to comfort and ergonomics, which are measured in terms of the quality of the robot movement perceived by the human. This paper discusses the connection between comfort and similarity of the robot movement to the human one.
Microarchitectural attacks have become more threatening the society than before with the increasing diversity of attacks such as Spectre and Meltdown. Vendor patches cannot keep up with the pace of the new threats, which makes the dynamic anomaly detection tools more evident than before. Unfortunately, hardware performance counters (HPCs) utilized in previous works lead to high performance overhead and detection of a few microarchitectural attacks due to the small number of counters that can be profiled concurrently.
The experimental data provide hand motion signals and forearm EMG signals generated during simulated Parkinson's tremor in 10 normal subjects. The sampling frequency of the experimental equipment IMU is 100Hz, and the sampling frequency of the myoelectric armband Myo is 200Hz. The collection process of this experimental data has been approved by the Ethics Review Committee of Harbin Institute of Technology. In order to protect the privacy of the subjects, the author's consent is requested before using this data.
These files are associated with the manuscript "Stability of Power Supply Bootstrapped Unity-Gain Buffers" and help reproduce and explore the figures from the paper, which show the main results. First, the results from simulation are imported and graphed as in Fig. 6. Next, the equations from the manuscript are implemented to show that they output correct predictions reproducing the Nyquist diagram from Fig. 7. Finally, the experimentally recorded step responses are imported and graphed as in Fig. 9.
Dataset haiving the curvature and spline values for the roundabout
These datasets report data of 64 Force Sensing Resistors at multiple voltages. It was foun that the input voltage can be used to trim sensors' sensitivity and ultimately to reduce dispersion. The DMAIC cycle was used to reduce process variability on the basis of the Six Sigma Methodology. The zip folder contains:
1) a Matlab file for loading the data
2) four .txt files with the experimental data of Force Sensing resistors
The Dada dataset is associated with the paper “Debiasing Android Malware Datasets: How can I trust your results if your dataset is biased?”. The goal of this dataset is to provide a new updated dataset of goodware/malware applications that can be used by other researchers for performing experiments, for example, detection or classification algorithms. The dataset contains the applications hashes and some characteristics.
