A simple, rapid procedure is required for the routine detection and quantification of haemolysis, one of the main sources of unreliable results in serum analysis. In this study, we compared two different approaches for the rapid determination of haem...
IEEE transactions on neural networks and learning systems
Jul 6, 2022
Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias...
The paper deals with a lead-through method of programming for industrial robots. The goal is to automatically reproduce 6DoF trajectories of a tool wielded by a human operator demonstrating a motion task. We present a novel motion-tracking system bui...
The amount of available biological data has exploded since the emergence of high-throughput technologies, which is not only revolting the way we recognize molecules and diseases but also bringing novel analytical challenges to bioinformatics analysis...
Computational intelligence and neuroscience
May 25, 2022
At present, most of the handling industrial robots working on the production line are operated by teaching or preprogramming, which makes the flexibility of the production line poor and does not meet the flexible production requirements of the materi...
Machine learning models are widely applied to predict molecular properties or the biological activity of small molecules on a specific protein. Models can be integrated in a conformal prediction (CP) framework which adds a calibration step to estimat...
Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional ma...
Traffic conflict techniques represent the state-of-the-art for road safety assessments. However, the lack of research on transferability of conflict-based crash risk models, which refers to applying the developed crash risk estimation models to a set...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Mar 26, 2022
In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was firstly proposed. The 1-D Raman spectral data was converted into images and used for predicting the biochemical value of blood glucose. 106 sets of blood spectru...
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