Intrusion Detection Systems Using Adaptive Regression Splines

Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable intrusion detection systems. Due to increasing incidents of cyber attacks, building effective intrusion detection systems (IDS) are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. In this paper, we report a performance analysis between Multivariate Adaptive Regression Splines (MARS), neural networks and support vector machines. The MARS procedure builds flexible regression models by fitting separate splines to distinct intervals of the predictor variables. A brief comparison of different neural network learning algorithms is also given

Radiative production of the Lambda(1405) resonance in K collisions on protons and nuclei

We have carried a theoretical study of the K^- p\to M B \gamma reaction with M B = K^-p, \bar{K}^0 n, \pi^- \Sigma^+, \pi^+ \Sigma^-, \pi^0 \Sigma^0, \pi^0 \Lambda, for K^- lab. momenta between 200 and 500 MeV/c, using a chiral unitary approach for the strong K^-p interaction with its coupled channels. The \Lambda(1405) resonance, which is generated dynamically in this approach, shows up clearly in the d\sigma/dM_I spectrum, providing new tests for chiral symmetry and the unitary approach, as well as information regarding the nature of the resonance. The photon detection alone, summing all channels, is shown to reproduce quite accurately the strength and shape of the \Lambda(1405) resonance. Analogous reactions in nuclei can provide much information on the properties of this resonance in a nuclear medium.Comment: 11 pages, 3 postscripts figure

Uncertainties in the solar photospheric oxygen abundance

The purpose of this work is to better understand the confidence limits of the photospheric solar oxygen abundance derived from three-dimensional models using the forbidden [OI] line at 6300 \AA , including correlations with other parameters involved. We worked with a three-dimensional empirical model and two solar intensity atlases. We employed Bayesian inference as a tool to determine the most probable value for the solar oxygen abundance given the model chosen. We considered a number of error sources, such as uncertainties in the continuum derivation, in the wavelength calibration and in the abundance/strength of Ni. Our results shows correlations between the effects of several parameters employed in the derivation. The Bayesian analysis provides robust confidence limits taking into account all of these factors in a rigorous manner. We obtain that, given the empirical three-dimensional model and the atlas observations employed here, the most probable value for the solar oxygen abundance is $\log(\epsilon_O) = 8.86\pm0.04$. However, we note that this uncertainty does not consider possible sources of systematic errors due to the model choice.Comment: Accepted for publication in Astronomy and Astrophysic