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Multiple Cayley-Klein metric learning.

PloS one
As a specific kind of non-Euclidean metric lies in projective space, Cayley-Klein metric has been recently introduced in metric learning to deal with the complex data distributions in computer vision tasks. In this paper, we extend the original Cayle...

Development of a highly sensitive and specific ELISA method for the determination of l-corydalmine in SD rats with monoclonal antibody.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
l-Corydalmine (l-CDL) is a potent analgesic constituent of the traditional Chinese medicine, Rhizoma Corydalis. However, the pharmacokinetic process and tissue distribution of l-CDL in vivo are still unknown. Therefore, it is necessary to establish a...

Mittag-Leffler synchronization of fractional neural networks with time-varying delays and reaction-diffusion terms using impulsive and linear controllers.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a fractional-order neural network system with time-varying delays and reaction-diffusion terms. We first develop a new Mittag-Leffler synchronization strategy for the controlled nodes via impulsive controllers. Using the fra...

Gene2DisCo: Gene to disease using disease commonalities.

Artificial intelligence in medicine
OBJECTIVE: Finding the human genes co-causing complex diseases, also known as "disease-genes", is one of the emerging and challenging tasks in biomedicine. This process, termed gene prioritization (GP), is characterized by a scarcity of known disease...

Construction accident narrative classification: An evaluation of text mining techniques.

Accident; analysis and prevention
Learning from past accidents is fundamental to accident prevention. Thus, accident and near miss reporting are encouraged by organizations and regulators. However, for organizations managing large safety databases, the time taken to accurately classi...

Using machine learning to identify air pollution exposure profiles associated with early cognitive skills among U.S. children.

Environmental pollution (Barking, Essex : 1987)
Data-driven machine learning methods present an opportunity to simultaneously assess the impact of multiple air pollutants on health outcomes. The goal of this study was to apply a two-stage, data-driven approach to identify associations between air ...

Improving dense conditional random field for retinal vessel segmentation by discriminative feature learning and thin-vessel enhancement.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: As retinal vessels in color fundus images are thin and elongated structures, standard pairwise based random fields, which always suffer the "shrinking bias" problem, are not competent for such segmentation task. Recently, a...

Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.

Environmental science and pollution research international
In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme lear...