This article develops a wavelet decomposition of a stochastic process which parallels a time{localized Cram er (Fourier) spectral representation. We provide a time{scale instead of a time{frequency decomposition and, hence, instead of thinking as scale in terms of \inverse frequency" we start from genuine time{scale building blocks or \atoms". Using this class of locally stationary wavelet (LSW...

MOTIVATION There is a growing literature on wavelet theory and wavelet methods showing improvements on more classical techniques, especially in the contexts of smoothing and extraction of fundamental components of signals. G+C patterns occur at different lengths (scales) and, for this reason, G+C plots are usually difficult to interpret. Current methods for genome analysis choose a window size ...

OBJECTIVES This review outlines the methodological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications. METHODS The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST), the continuous Morlet wavelet transform (CMWT), ...

Nowadays, deep learning and convolutional neural networks (CNNs) have become widespread tools in many biomedical engineering studies. CNN is an end-to-end tool which makes processing procedure integrated, but in some situations, this processing tool requires to be fused with machine learning methods to be more accurate. In this paper, a hybrid approach based on deep features extracted from Wave...

With increasing customer demand, industry 4.0 gained a lot of interest, which is based on smart factories. In factories, robotic components are vulnerable to failure due various industrial operations such as assembly, manufacturing, and product handling. Timely fault detection diagnosis (FDD) important keep the operation smooth. Previously, only unloaded-based FDD algorithms were considered for...

Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach avoiding plant disturbances and shutdown. Recently, Motor Current Signature Analysis (MCSA) reported technique in detection identification of individual multiple Induction (IM) faults. However, checking fault classification with deep learning models its comparison among themselves or ...

Sebagai wilayah yang sedang berkembang, Distrik Aimas sebagai Ibukota Kabupaten Sorong memiliki tantangan tentang masalah kesenjangan dan ketidakmerataan pembangunan fasilitas sosial ekonomi, sehingga penentuan tingkat kekotaan sekaligus dengan potensi sebagaia sentral perkembangan ekonomi menjadi penting untuk dilakukan. Tujuan penelitian ini yaitu mengetahui hirarki di Aimas. Adapun metode di...

Abstract Introduction Koopman operator theory and the Hankel alternative view of (HAVOK) model have been widely used to investigate chaotic dynamics in complex systems. Although statistics intermittent evaluated HAVOK model, they are not adequate characterize forcing. We proposed spectral analysis method transition between apeanic non-apneaic episodes predict impending OSA episodes. Methods Apn...

Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with propensity rapid crack propagation, has limited application of γ-TiAl. Any cracks introduced during ma...

Autism spectrum disorder (ASD) is a mental and the main problem in ASD treatment has no definite cure, one possible option to control its symptoms. Conventional assessment using questionnaires may not be accurate required evaluation of trained experts. Several attempts use resting-state functional magnetic resonance imaging (fMRI) as an assisting tool combined with classifier have been reported...