Data analysis is a very challenging task in LC-MS metabolomic studies. The use of powerful
analytical techniques (eg, high-resolution mass spectrometry) provides high-dimensional …

Feature-based molecular networking (FBMN) is a popular analysis approach for liquid
chromatography–tandem mass spectrometry-based non-targeted metabolomics data. While …

In this study, multi-objective optimum energy management strategies are developed for pre-
and post-transmission parallel hybrid electric vehicles. The first strategy aims to improve fuel …

With the rapid development of mobile networks and the proliferation of mobile devices,
spatial crowdsourcing, which refers to recruiting mobile workers to perform location-based …

Because of the widespread use of nondestructive measurement techniques, such as
spectroscopy, spectral imaging, which allow scientists to swiftly obtain a complete spectrum …

Balancing competing objectives to select an optimal design of experiments involves flexibly
combining measures to select a winner. The Pareto front approach for simultaneously …

Low noise constructions receive more and more attention in highly industrialized countries.
Consequently, decrease of noise radiation challenges a growing community of engineers …

Nonlinear grey Bernoulli multivariate model NGBMC (1, n) is known as a novel forecasting
model for nonlinear time series with small samples. However, ill-posed problem would make …

Clustering is one of the important methods for prolonging the network lifetime in wireless
sensor networks (WSNs). It involves grou** of sensor nodes into clusters and electing …

Clustering is a significant data mining task which partitions datasets based on similarities
among data. This technique plays a very important role in the rapidly growing field known as …