AIMC Topic: Computer Simulation

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Design and analysis of coiled fiber reinforced soft pneumatic actuator.

Bioinspiration & biomimetics
Fiber reinforced elastomeric enclosures (FREEs) are soft pneumatic actuators that can contract and generate forces upon pressurization. Typical engineering applications utilize FREEs in their straight cylindrical configuration and derive actuation di...

A Reinforcement Learning Neural Network for Robotic Manipulator Control.

Neural computation
We propose a neural network model for reinforcement learning to control a robotic manipulator with unknown parameters and dead zones. The model is composed of three networks. The state of the robotic manipulator is predicted by the state network of t...

A Theory of Sequence Indexing and Working Memory in Recurrent Neural Networks.

Neural computation
To accommodate structured approaches of neural computation, we propose a class of recurrent neural networks for indexing and storing sequences of symbols or analog data vectors. These networks with randomized input weights and orthogonal recurrent we...

Practical Time-Varying Formation Tracking for Second-Order Nonlinear Multiagent Systems With Multiple Leaders Using Adaptive Neural Networks.

IEEE transactions on neural networks and learning systems
Practical time-varying formation tracking problems for second-order nonlinear multiagent systems with multiple leaders are investigated using adaptive neural networks (NNs), where the time-varying formation tracking error caused by time-varying exter...

Spatial extreme learning machines: An application on prediction of disease counts.

Statistical methods in medical research
Extreme learning machines have gained a lot of attention by the machine learning community because of its interesting properties and computational advantages. With the increase in collection of information nowadays, many sources of data have missing ...

Runtime Programmable and Memory Bandwidth Optimized FPGA-Based Coprocessor for Deep Convolutional Neural Network.

IEEE transactions on neural networks and learning systems
The deep convolutional neural network (DCNN) is a class of machine learning algorithms based on feed-forward artificial neural network and is widely used for image processing applications. Implementation of DCNN in real-world problems needs high comp...

Psychosocial factors associated with intended use of automated vehicles: A simulated driving study.

Accident; analysis and prevention
This study applied the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to assess drivers' intended use of automated vehicles (AVs) after undertaking a simulated driving task. In addition, this study explored the potential f...

Too Much of a Good Thing: How Novelty Biases and Vocabulary Influence Known and Novel Referent Selection in 18-Month-Old Children and Associative Learning Models.

Cognitive science
Identifying the referent of novel words is a complex process that young children do with relative ease. When given multiple objects along with a novel word, children select the most novel item, sometimes retaining the word-referent link. Prior work i...

Emotion computing using Word Mover's Distance features based on Ren_CECps.

PloS one
In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chi...