35,351 research outputs found
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
. 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
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
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