AIMC Topic:
Computer Simulation

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Protocol-based state estimation for delayed Markovian jumping neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the state estimation problem for a class of Markovian jumping neural networks (MJNNs) with sensor nonlinearities, mode-dependent time delays and stochastic disturbances subject to the Round-Robin (RR) scheduling mechanism...

Perturbation Theory-Machine Learning Study of Zeolite Materials Desilication.

Journal of chemical information and modeling
Zeolites are important materials for research and industrial applications. Mesopores are often introduced by desilication but other properties are also affected, making its optimization difficult. In this work, we demonstrate that Perturbation Theory...

Novel robust control of a 7-DOF exoskeleton robot.

PloS one
This paper proposes a novel robust control method for the control of a 7-DOF exoskeleton robot. The external disturbances and unknown dynamics in the form of friction forces, different upper-limb's mass, backlash, and input saturation make robot unst...

Convolutional Neural Networks with Template-Based Data Augmentation for Functional Lung Image Quantification.

Academic radiology
RATIONALE AND OBJECTIVES: We propose an automated segmentation pipeline based on deep learning for proton lung MRI segmentation and ventilation-based quantification which improves on our previously reported methodologies in terms of computational eff...

UKF-based remote state estimation for discrete artificial neural networks with communication bandwidth constraints.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the remote state estimator design problem for a class of discrete neural networks under communication bandwidth constraints. Due to the limited bandwidth of the transmission channel, only partial components of the measure...

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

Journal of neuroscience methods
BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging.

Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery.

Journal of chemical information and modeling
The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, method comparison is difficult because of various flaws of the currently employed evaluation metrics. We...

Risk Evaluation Model of Highway Tunnel Portal Construction Based on BP Fuzzy Neural Network.

Computational intelligence and neuroscience
Risk assessment for tunnel portals in the construction stage has been widely recognized as one of the most critical phases in tunnel construction as it easily causes accident than the overall length of a tunnel. However, the risk in tunnel portal con...

Controlling Complexity of Cerebral Cortex Simulations-I: CxSystem, a Flexible Cortical Simulation Framework.

Neural computation
Simulation of the cerebral cortex requires a combination of extensive domain-specific knowledge and efficient software. However, when the complexity of the biological system is combined with that of the software, the likelihood of coding errors incre...

In Silico Prediction of Major Clearance Pathways of Drugs among 9 Routes with Two-Step Support Vector Machines.

Pharmaceutical research
PURPOSE: The clearance pathways of drugs are critical elements for understanding the pharmacokinetics of drugs. We previously developed in silico systems to predict the five clearance pathway using a rectangular method and a support vector machine (S...