Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal an...
Neural networks : the official journal of the International Neural Network Society
Jul 21, 2017
Two-dimensional principal component analysis (2DPCA) employs squared F-norm as the distance metric for dimensionality reduction. It is commonly known that squared F-norm is sensitive to the presence of outliers. To address this problem, we use F-norm...
Automatic feature extraction and classification are two main tasks in abnormal ECG beat recognition. Feature extraction is an important prerequisite prior to classification since it provides the classifier with input features, and the performance of ...
Fargesia Franchet emend. Yi is closely allied with Thamnocalamus Munro but differs in many major morphological characteristics. Based on traditional morphological characters, it is difficult to differentiate these two genera. The current study measur...
. Error-free diagnosis of Alzheimer's disease (AD) from healthy control (HC) patients at an early stage of the disease is a major concern, because information about the condition's severity and developmental risks present allows AD sufferer to take p...
Alzheimer's disease (AD) is a progressive, neurodegenerative brain disorder that attacks neurotransmitters, brain cells, and nerves, affecting brain functions, memory, and behaviors and then finally causing dementia on elderly people. Despite its sig...
Food research international (Ottawa, Ont.)
May 20, 2017
Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authenticatio...
Neural networks : the official journal of the International Neural Network Society
Apr 24, 2017
Reservoir computing is a recently introduced machine learning paradigm that has been shown to be well-suited for the processing of spatiotemporal data. Rather than training the network node connections and weights via backpropagation in traditional r...
Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid ...
The international journal of cardiovascular imaging
Mar 20, 2017
The aim of this study was to analyze the whole temporal profiles of the segmental deformation curves of the left ventricle (LV) and describe their interrelations to obtain more detailed information concerning global LV function in order to be able to...