AIMC Topic: Computer Simulation

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Dynamic event-based state estimation for delayed artificial neural networks with multiplicative noises: A gain-scheduled approach.

Neural networks : the official journal of the International Neural Network Society
This study is concerned with the state estimation issue for a kind of delayed artificial neural networks with multiplicative noises. The occurrence of the time delay is in a random way that is modeled by a Bernoulli distributed stochastic variable wh...

Transcranial MR Imaging-Guided Focused Ultrasound Interventions Using Deep Learning Synthesized CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Transcranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull densit...

A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory.

Sensors (Basel, Switzerland)
In order to analyze the complex interactive behaviors between the robot and two humans, this paper presents an adaptive optimal control framework for human-robot-human physical interaction. N-player linear quadratic differential game theory is used t...

Whole-body voxel-based internal dosimetry using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: In the era of precision medicine, patient-specific dose calculation using Monte Carlo (MC) simulations is deemed the gold standard technique for risk-benefit analysis of radiation hazards and correlation with patient outcome. Hence, we propo...

Random Forests Approach for Causal Inference with Clustered Observational Data.

Multivariate behavioral research
There is a growing interest in using machine learning (ML) methods for causal inference due to their (nearly) automatic and flexible ability to model key quantities such as the propensity score or the outcome model. Unfortunately, most ML methods for...

SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems.

Neural networks : the official journal of the International Neural Network Society
We propose new symplectic networks (SympNets) for identifying Hamiltonian systems from data based on a composition of linear, activation and gradient modules. In particular, we define two classes of SympNets: the LA-SympNets composed of linear and ac...

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.

Genes
The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most of our understanding of this association comes from the study of long range chromatin interaction ma...

Detachment of the remora suckerfish disc: kinematics and a bio-inspired robotic model.

Bioinspiration & biomimetics
Remora suckerfish can attach to a wide diversity of marine hosts, however, their detachment mechanism remains poorly understood. Through analyzing high-speed videos, we found that the detachment of the live remora (Echeneis naucrates) is a rapid beha...

A soft pneumatic bistable reinforced actuator bioinspired by Venus Flytrap with enhanced grasping capability.

Bioinspiration & biomimetics
Soft actuators, as an important part of soft robotics, have attracted significant attention due to their inherent compliance, flexibility and safety. However, low capacity in force and load limits their applications. Prestored elastic energy can impr...

CWLy-pred: A novel cell wall lytic enzyme identifier based on an improved MRMD feature selection method.

Genomics
Cell wall lytic enzymes play key roles in biochemical, morphological, genetic research and industry fields. To save time and labor costs, bioinformatic methods are usually adopted to narrow the scope of in vitro experimentation. In this paper, we est...