Abstract Public health responses to the COVID-19 pandemic since March 2020 have led lockdowns and social distancing in most countries around world, with a shift from traditional work environment virtual one. Employees been encouraged home where possible slow down viral infection. The massive increase volume of professional activities executed online has posed new context for cybercrime, number ...

PHAISANGITTISAGUL, EKACHAI. Signal Processing using Wavelets for Enhancing Electronic Nose Performance. (Under the direction of Dr. H. Troy Nagle.) In recent years, many new technologies of electronic devices that mimic the mammalian olfactory system, electronic noses (e-noses), have been developed in many research institutions and commercial organizations around the world. These devices have b...

Sensor drift is the most challenging problem in gas sensing at present. We propose a novel two-dimensional classifier ensemble strategy to solve the gas discrimination problem, regardless of the gas concentration, with high accuracy over extended periods of time. This strategy is appropriate for multi-class classifiers that consist of combinations of pairwise classifiers, such as support vector...

This paper presents a radar target recognition method using kernel locally linear embedding (KLLE) and a kernel-based nonlinear representative and discriminative (KNRD) classifier. Locally linear embedding (LLE) is one of the representative manifold learning algorithms for dimensionality reduction. In this paper, LLE is extended by using kernel technique, which gives rises to the KLLE algorithm...

the extended homogeneous balance method is used to construct exacttraveling wave solutions of the maccari system, in which thehomogeneous balance method is applied to solve the riccati equationand the reduced nonlinear ordinary differential equation. many exacttraveling wave solutions of the maccari system equation aresuccessfully obtained.

The analysis of functional data, is a common task in bioinformatics. Spectral data as obtained from mass spectrometric measurements in clinical proteomics are such functional data leading to new challenges for an appropriate analysis. Here we focus on the determination of classification models for such data. In general the available approaches for this task initially transform the spectra into ...

Recently, Learning Classifier Systems (LCS) and particularly XCS have arisen as promising methods for classification tasks and data mining. This paper investigates two models of accuracy-based learning classifier systems on different types of classification problems. Departing from XCS, we analyze the evolution of a complete action map as a knowledge representation. We propose an alternative, U...

When a multiple classifier system is employed, one of the most popular methods to accomplish the classifier fusion is the simple majority voting. However, when the performance of the ensemble members is not uniform, the efficiency of this type of voting generally results affected negatively. In the present paper, new functions for dynamic weighting in classifier fusion are introduced. Experimen...

In this paper we present a new approach to classifying radiographs, which is the first important task of the IRMA system. Given an image, we compute posterior probabilities for each image class, as this information is needed for further IRMA processing. Classification is done by using an extended version of Simard’s tangent distance within a kernel density based classifier. We propose a new dis...