AIMC Topic: Principal Component Analysis

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Classification of adult human dentate nucleus border neurons: Artificial neural networks and multidimensional approach.

Journal of theoretical biology
AIMS: Primary aim in this study is to investigate whether external and internal border neurons of adult human dentate nucleus express the same neuromorphological features or belong to a different morphological types i.e. whether can be classified not...

Evaluating the ability of artificial neural network and PCA-M5P models in predicting leachate COD load in landfills.

Waste management (New York, N.Y.)
Waste burial in uncontrolled landfills can cause serious environmental damages and unpleasant consequences. Leachates produced in landfills have the potential to contaminate soil and groundwater resources. Leachate management is one of the major issu...

Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models.

PloS one
The motivation behind this research is to innovatively combine new methods like wavelet, principal component analysis (PCA), and artificial neural network (ANN) approaches to analyze trade in today's increasingly difficult and volatile financial futu...

Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization.

Computational and mathematical methods in medicine
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this st...

Cognitive Test Scores in UK Biobank: Data Reduction in 480,416 Participants and Longitudinal Stability in 20,346 Participants.

PloS one
UK Biobank includes 502,649 middle- and older-aged adults from the general population who have undergone detailed phenotypic assessment. The majority of participants completed tests of cognitive functioning, and on average four years later a sub-grou...

Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent behavioral disorders in childhood and adolescence. Recently, network-based diagnosis of ADHD has attracted great attentions due to the fact that ADHD disease is ...

Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes.

PloS one
The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we a...

Demixed principal component analysis of neural population data.

eLife
Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information...

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine.

Applied spectroscopy
Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we ...

Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor.

Bioresource technology
The performance of a laboratory-scale anaerobic bioreactor was investigated in the present study to determine methane (CH4) content in biogas yield from digestion of organic fraction of municipal solid waste (OFMSW). OFMSW consists of food waste, veg...