AIMC Topic: Humans

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Advances in Biodegradable Electronic Skin: Material Progress and Recent Applications in Sensing, Robotics, and Human-Machine Interfaces.

Advanced materials (Deerfield Beach, Fla.)
The rapid growth of the electronics industry and proliferation of electronic materials and telecommunications technologies has led to the release of a massive amount of untreated electronic waste (e-waste) into the environment. Consequently, catastro...

Protocol for the operation of a breathing and vaping biomimetic robot to delineate real-time inhaled particle profile of electronic cigarettes.

STAR protocols
We recently developed a robotic human vaping mimetic real-time particle analyzer (HUMITIPAA) to evaluate the impact of change in chemical constituents and breathing profiles of electronic cigarettes (ECs) on potential pulmonary toxicity. Here, we des...

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity.

Journal of chemical information and modeling
Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always requ...

Toward Region-Aware Attention Learning for Scene Graph Generation.

IEEE transactions on neural networks and learning systems
Scene graph generation (SGGen) is a challenging task due to a complex visual context of an image. Intuitively, the human visual system can volitionally focus on attended regions by salient stimuli associated with visual cues. For example, to infer th...

Position-Aware Participation-Contributed Temporal Dynamic Model for Group Activity Recognition.

IEEE transactions on neural networks and learning systems
Group activity recognition (GAR) aiming at understanding the behavior of a group of people in a video clip has received increasing attention recently. Nevertheless, most of the existing solutions ignore that not all the persons contribute to the grou...

Inverse-Based Approach to Explaining and Visualizing Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
This article presents a new method for understanding and visualizing convolutional neural networks (CNNs). Most existing approaches to this problem focus on a global score and evaluate the pixelwise contribution of inputs to the score. The analysis o...

Vision-Based Topological Mapping and Navigation With Self-Organizing Neural Networks.

IEEE transactions on neural networks and learning systems
Spatial mapping and navigation are critical cognitive functions of autonomous agents, enabling one to learn an internal representation of an environment and move through space with real-time sensory inputs, such as visual observations. Existing model...

Usability Evaluation of Augmented Reality: A Neuro-Information-Systems Study.

Journal of visualized experiments : JoVE
This study introduces an experimental paradigm for a usability test of emerging technologies in a management information system (MIS). The usability test included both subjective and objective evaluations. For the subjective evaluation, a usability q...

Deep Learning in the Detection of Disinformation about COVID-19 in Online Space.

Sensors (Basel, Switzerland)
This article focuses on the problem of detecting disinformation about COVID-19 in online discussions. As the Internet expands, so does the amount of content on it. In addition to content based on facts, a large amount of content is being manipulated,...

Spatial statistical machine learning models to assess the relationship between development vulnerabilities and educational factors in children in Queensland, Australia.

BMC public health
BACKGROUND: The health and development of children during their first year of full time school is known to impact their social, emotional, and academic capabilities throughout and beyond early education. Physical health, motor development, social and...