We present new spectroscopic and photometric time series observations of the δ Scuti star FG Vir. We detect the oscillations via changes in the equivalent widths of hydrogen and metal absorption lines. From the ratios between spectroscopic and photometric amplitudes, we assign l values to the eight strongest oscillation modes. In particular, we identify two radial modes (l = 0) and find that th...

This Research presents the effects of interaction between various Kernel functions and different Feature Selection Techniques for improving the learning capability of Support Vector Machine (SVM) in detecting email spams. The interaction of four Kernel functions of SVM i. e. "Normalised Polynomial Kernel (NP)", "Polynomial Kernel (PK)", "Radial Basis Function Kernel (RB...

The GMM (generalized min-max) kernel was recently proposed [5] as a measure of data similarity and was demonstrated effective in machine learning tasks. In order to use the GMM kernel for large-scale datasets, the prior work resorted to the (generalized) consistent weighted sampling (GCWS) to convert the GMM kernel to linear kernel. We call this approach as “GMM-GCWS”. In the machine learning l...

We study the problem of selecting the best parameter values to use for a support vector machine (SVM) with RBF kernel. Our methods extend the well-known formulas for AIC and BIC, and we present two alternative approaches for calculating the necessary likelihood functions for these formulas. Our first approach is based on using the distances of support vectors from the separating hyperplane. Our...

Machine based human action recognition has become very popular in the last decade. Automatic unattended surveillance systems, interactive video games, machine learning and robotics are only few of the areas that involve human action recognition. This paper examines the capability of a known transform, the so-called Trace, for human action recognition and proposes two new feature extraction meth...

Early diagnosis of Parkinson’s Disease (PD) is crucial for effective neuroprotection and early management. Recent neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with 123 I-Ioflupane (DaTSCAN) have shown to detect even early stages of the disease. In this paper, we use the Striatal Binding Ratio (SBR) values that are calculated from ...

Kernel density estimation (KDE) is a popular statistical technique for estimating the underlying density distribution with minimal assumptions. Although they can be shown to achieve asymptotic estimation optimality for any input distribution, cross-validating for an optimal parameter requires significant computation dominated by kernel summations. In this paper we present an improvement to the ...

Recently, the open-set recognition problem has received more attention by the machine learning community given that most classification problems in practice require an open-set treatment. Thus far, many classifiers were mostly developed for the closed-set scenario, i.e., the scenario of classification in which it is assumed that all test samples belong to one of the classes the classifier was t...

This letter focuses on solving the challenging problem of detecting natural image boundaries. A boundary usually refers to the border between two regions with different semantic meanings. Therefore, a measurement of dissimilarity between image regions plays a pivotal role in boundary detection of natural images. To improve the performance of boundary detection, a Learning-based Boundary Metric ...