Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration si...

The novel method of deception detecting based on speech signal is proposed in this study. Extracting prosodic and non-linear dynamics (NLD) feature sets from speech signal and applying relevance vector machine (RVM) classification method is the primary target of this paper. Here, the sustained speakerdepended phonation samples of deception and non-deception were applied. In this paper, 30 proso...

This research describes the unsteady two-dimensional reacting flows around a circular cylinder. The numerical solution combines the random vortex method for incompressible two-dimensional viscous fluid flow with a Simple Line Interface Calculation (SLIC) algorithm for the propagation of flame interface. To simplify the governing equations, two fundamental assumptions namely Low Mach Number and ...

Relevance Vector Machine (RVM) is a novel kernel method based on Sparse Bayesian, which has many advantages such as its kernel functions without the restriction of Mercer’s conditions, the relevance vectors automatically determined. In this paper, a new RVM model optimized by Particle Swarm Optimization (PSO) is proposed, and it is applied to groundwater level forecasting. The simulation experi...

This study examines the capability of the Relevance Vector Machine (RVM) and Multivariate Adaptive Regression Spline (MARS) for prediction of ultimate capacity of driven piles and drilled shafts. RVM is a sparse method for training generalized linear models, while MARS technique is basically an adaptive piece-wise regression approach. In this paper, pile capacity prediction models are developed...

The Relevance Vector Machine(RVM) is a widely accepted Bayesian model commonly used for regression and classification tasks. In this paper we propose a multikernel version of the RVM and present an alternative inference algorithm based on Fourier domain computation to solve this model for large scale problems, e.g. images. We then apply the proposed method to the object detection problem with p...