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Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

Computational intelligence and neuroscience
Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training bas...

Memristor-Based Neural Network Circuit of Full-Function Pavlov Associative Memory With Time Delay and Variable Learning Rate.

IEEE transactions on cybernetics
Most memristor-based Pavlov associative memory neural networks strictly require that only simultaneous food and ring appear to generate associative memory. In this article, the time delay is considered, in order to form associative memory when the fo...

Combining convolutional neural networks and in-line near-infrared spectroscopy for real-time monitoring of the chromatographic elution process in commercial production of notoginseng total saponins.

Journal of separation science
The chromatographic elution process is a key step in the production of notoginseng total saponins. Due to quality variability of loading samples and resin capacity decreasing over cycle time, saponins, especially the five main saponins of notoginseng...

A fast and scalable method for quality assurance of deformable image registration on lung CT scans using convolutional neural networks.

Medical physics
PURPOSE: To develop and evaluate a method to automatically identify and quantify deformable image registration (DIR) errors between lung computed tomography (CT) scans for quality assurance (QA) purposes.

Global Mittag-Leffler stability and synchronization of discrete-time fractional-order complex-valued neural networks with time delay.

Neural networks : the official journal of the International Neural Network Society
Without decomposing complex-valued systems into real-valued systems, this paper investigates existence, uniqueness, global Mittag-Leffler stability and global Mittag-Leffler synchronization of discrete-time fractional-order complex-valued neural netw...

Detecting liver fibrosis using a machine learning-based approach to the quantification of the heart-induced deformation in tagged MR images.

NMR in biomedicine
Liver disease causes millions of deaths per year worldwide, and approximately half of these cases are due to cirrhosis, which is an advanced stage of liver fibrosis that can be accompanied by liver failure and portal hypertension. Early detection of ...

Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools.

Systematic reviews
BACKGROUND: We explored the performance of three machine learning tools designed to facilitate title and abstract screening in systematic reviews (SRs) when used to (a) eliminate irrelevant records (automated simulation) and (b) complement the work o...

Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach.

Computational and mathematical methods in medicine
Emergency departments (EDs) play a vital role in the whole healthcare system as they are the first point of care in hospitals for urgent and critically ill patients. Therefore, effective management of hospital's ED is crucial in improving the quality...

A Multibranch Object Detection Method for Traffic Scenes.

Computational intelligence and neuroscience
The performance of convolutional neural network- (CNN-) based object detection has achieved incredible success. Howbeit, existing CNN-based algorithms suffer from a problem that small-scale objects are difficult to detect because it may have lost its...

An artificial neural network ensemble approach to generate air pollution maps.

Environmental monitoring and assessment
The objective of this research is to propose an artificial neural network (ANN) ensemble in order to estimate the hourly NO concentration at unsampled locations. Spatial interpolation methods and linear regression models with regularization have been...