AIMC Topic: Humans

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Remaining Useful Life Prediction from 3D Scan Data with Genetically Optimized Convolutional Neural Networks.

Sensors (Basel, Switzerland)
In the current industrial landscape, increasingly pervaded by technological innovations, the adoption of optimized strategies for asset management is becoming a critical key success factor. Among the various strategies available, the "Prognostics and...

Adaptive Attention Memory Graph Convolutional Networks for Skeleton-Based Action Recognition.

Sensors (Basel, Switzerland)
Graph Convolutional Networks (GCNs) have attracted a lot of attention and shown remarkable performance for action recognition in recent years. For improving the recognition accuracy, how to build graph structure adaptively, select key frames and extr...

Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends.

Sensors (Basel, Switzerland)
Wearable assistive robotics is an emerging technology with the potential to assist humans with sensorimotor impairments to perform daily activities. This assistance enables individuals to be physically and socially active, perform activities independ...

Designing Acceptable Robots for Assisting Older Adults: A Pilot Study on the Willingness to Interact.

International journal of environmental research and public health
The aim of this paper was to explore the psychosocial determinants that lead to acceptability and willingness to interact with a service robot, starting with an analysis of older users' behaviors toward the Robot-Era platform, in order to provide str...

Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients.

International journal of molecular sciences
Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult...

Deep learning-driven scaffold hopping in the discovery of Akt kinase inhibitors.

Chemical communications (Cambridge, England)
Scaffold hopping has been widely used in drug discovery and is a topic of high interest. Here a deep conditional transformer neural network, SyntaLinker, was applied for the scaffold hopping of a phase III clinical Akt inhibitor, AZD5363. A number of...

Modelling dielectric elastomer circuit networks for soft biomimetics.

Bioinspiration & biomimetics
In order to obtain entirely soft bio-inspired robots, fully soft electronic circuits are needed. Dielectric elastomers (DEs) are electroactive polymers that have demonstrated multifunctionality. The same material can achieve different tasks like actu...

Characterising the nationwide burden and predictors of unkept outpatient appointments in the National Health Service in England: A cohort study using a machine learning approach.

PLoS medicine
BACKGROUND: Unkept outpatient hospital appointments cost the National Health Service £1 billion each year. Given the associated costs and morbidity of unkept appointments, this is an issue requiring urgent attention. We aimed to determine rates of un...

A Driving Performance Forecasting System Based on Brain Dynamic State Analysis Using 4-D Convolutional Neural Networks.

IEEE transactions on cybernetics
Vehicle accidents are the primary cause of fatalities worldwide. Most often, experiencing fatigue on the road leads to operator errors and behavioral lapses. Thus, there is a need to predict the cognitive state of drivers, particularly their fatigue ...

A Master-Slave Binary Grey Wolf Optimizer for Optimal Feature Selection in Biomedical Data Classification.

BioMed research international
A new master-slave binary grey wolf optimizer (MSBGWO) is introduced. A master-slave learning scheme is introduced to the grey wolf optimizer (GWO) to improve its ability to explore and get better solutions in a search space. Five high-dimensional bi...