AIMC Topic: Computer Simulation

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Condition Monitoring of Ball Bearings Based on Machine Learning with Synthetically Generated Data.

Sensors (Basel, Switzerland)
Rolling element bearing faults significantly contribute to overall machine failures, which demand different strategies for condition monitoring and failure detection. Recent advancements in machine learning even further expedite the quest to improve ...

Agreement in Spiking Neural Networks.

Journal of computational biology : a journal of computational molecular cell biology
We study the problem of binary agreement in a spiking neural network (SNN). We show that binary agreement on inputs can be achieved with of auxiliary neurons. Our simulation results suggest that agreement can be achieved in our network in time. We...

Self-consistent determination of long-range electrostatics in neural network potentials.

Nature communications
Machine learning has the potential to revolutionize the field of molecular simulation through the development of efficient and accurate models of interatomic interactions. Neural networks can model interactions with the accuracy of quantum mechanics-...

Rotating neurons for all-analog implementation of cyclic reservoir computing.

Nature communications
Hardware implementation in resource-efficient reservoir computing is of great interest for neuromorphic engineering. Recently, various devices have been explored to implement hardware-based reservoirs. However, most studies were mainly focused on the...

3D-Printed Soft Sensors for Adaptive Sensing with Online and Offline Tunable Stiffness.

Soft robotics
The stiffness of a soft robot with structural cavities can be regulated by controlling the pressure of a fluid to render predictable changes in mechanical properties. When the soft robot interacts with the environment, the mediating fluid can also be...

Object-Based Reliable Visual Navigation for Mobile Robot.

Sensors (Basel, Switzerland)
Visual navigation is of vital importance for autonomous mobile robots. Most existing practical perception-aware based visual navigation methods generally require prior-constructed precise metric maps, and learning-based methods rely on large training...

A New Generation of ResNet Model Based on Artificial Intelligence and Few Data Driven and Its Construction in Image Recognition Model.

Computational intelligence and neuroscience
The paper proposes an A-ResNet model to improve ResNet. The residual attention module with shortcut connection is introduced to enhance the focus on the target object; the dropout layer is introduced to prevent the overfitting phenomenon and improve ...

Power and Area Efficient Cascaded Effectless GDI Approximate Adder for Accelerating Multimedia Applications Using Deep Learning Model.

Computational intelligence and neuroscience
Approximate computing is an upsurging technique to accelerate the process through less computational effort while keeping admissible accuracy of error-tolerant applications such as multimedia and deep learning. Inheritance properties of the deep lear...

Prediction Model of Stress Intensity Factor of Circumferential Through Crack in Elbow Based on Neural Network.

Computational intelligence and neuroscience
Using ANSYS software to establish the finite element model of crack bending tube, the SIF at the tip of the crack is calculated for the difference in the diameter of the pipe, the outer diameter of the elbow, and the bending angle of the bend pipe, a...

Neural Network-Based Decoding Input Stimulus Data Based on Recurrent Neural Network Neural Activity Pattern.

Doklady biological sciences : proceedings of the Academy of Sciences of the USSR, Biological sciences sections
The paper reports the assessment of the possibility to recover information obtained using an artificial neural network via inspecting neural activity patterns. A simple recurrent neural network forms dynamic excitation patterns for storing data on in...