This study concerns with fault diagnosis of low speed bearing using multi-class relevance
vector machine (RVM) and support vector machine (SVM). A low speed test rig was …

In this study, a novel fault diagnosis system for rotating machinery using thermal imaging is
proposed. This system consists of bi-dimensional empirical mode decomposition (BEMD) for …

Kernel-based machine learning algorithms are based on map** data from the original
input feature space to a kernel feature space of higher dimensionality to solve a linear …

The relevance vector machine (RVM), a Bayesian extension of the support vector machine
(SVM), has considerable potential for the analysis of remotely sensed data. Here, the RVM is …

Multiclass Mahalanobis-Taguchi system (MMTS), the extension of MTS, is developed for
simultaneous multiclass classification and feature selection. In MMTS, the multiclass …

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing
using multi-class relevance vector machine (RVM). A low speed test rig was developed to …

Résumé Les Interfaces Homme-Machine actuelles manquent «d'intelligence émotionnelle»:
elles ne sont pas capables d'identifier les émotions humaines et de prendre cette …

A new methodology is developed to analyze existing monitoring networks. This
methodology incorporates different aspects of monitoring, including vulnerability/probability …

Facial Recognition (FR) has been an active area of research and has diverse applicable
environment, it continues to be a challenging research topic. With the development of image …

This paper describes a method for localizing wireless mobile clients in a multistory building
using a public wireless Local Area Network (LAN) system. Physical location data on …