AIMC Topic:
Computer Simulation

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Evaluating sociotechnical dynamics in a simulated remotely-piloted aircraft system: a layered dynamics approach.

Ergonomics
As coordination mechanisms change and technology failures occur, a sociotechnical system must reorganise itself across human and technological layers to maintain effectiveness. We present a study examining reorganisation across communication, control...

Models and Machines: How Deep Learning Will Take Clinical Pharmacology to the Next Level.

CPT: pharmacometrics & systems pharmacology
Recent advances in machine learning (ML) have led to enthusiasm about its use throughout the biopharmaceutical industry. The ML methods can be applied to a wide range of problems and have the potential to revolutionize aspects of drug development. Th...

Adaptive Neural Control of a Class of Stochastic Nonlinear Uncertain Systems With Guaranteed Transient Performance.

IEEE transactions on cybernetics
In this paper, an adaptive neural network control for stochastic nonlinear systems with uncertain disturbances is proposed. The neural network is considered to approximate an uncertain function in a nonlinear system. And computational burden in opera...

Robust Single-Shot T Mapping via Multiple Overlapping-Echo Acquisition and Deep Neural Network.

IEEE transactions on medical imaging
Quantitative magnetic resonance imaging (MRI) is of great value to both clinical diagnosis and scientific research. However, most MRI experiments remain qualitative, especially dynamic MRI, because repeated sampling with variable weighting parameter ...

Elasticity Versus Hyperelasticity Considerations in Quasistatic Modeling of a Soft Finger-Like Robotic Appendage for Real-Time Position and Force Estimation.

Soft robotics
Various methods based on hyperelastic assumptions have been developed to address the mathematical complexities of modeling motion and deformation of continuum manipulators. In this study, we propose a quasistatic approach for 3D modeling and real-tim...

Craniobot: A computer numerical controlled robot for cranial microsurgeries.

Scientific reports
Over the last few decades, a plethora of tools has been developed for neuroscientists to interface with the brain. Implementing these tools requires precisely removing sections of the skull to access the brain. These delicate cranial microsurgical pr...

Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data.

Medical image analysis
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the earl...

In silico prediction of chemical reproductive toxicity using machine learning.

Journal of applied toxicology : JAT
Reproductive toxicity is an important regulatory endpoint in health hazard assessment. Because the in vivo tests are expensive, time consuming and require a large number of animals, which must be killed, in silico approaches as the alternative strate...

Control of a Humanoid NAO Robot by an Adaptive Bioinspired Cerebellar Module in 3D Motion Tasks.

Computational intelligence and neuroscience
A bioinspired adaptive model, developed by means of a spiking neural network made of thousands of artificial neurons, has been leveraged to control a humanoid NAO robot in real time. The learning properties of the system have been challenged in a cla...

Network structure and input integration in competing firing rate models for decision-making.

Journal of computational neuroscience
Making a decision among numerous alternatives is a pervasive and central undertaking encountered by mammals in natural settings. While decision making for two-option tasks has been studied extensively both experimentally and theoretically, characteri...