10,726 research outputs found
Revisiting the Majorana Relativistic Theory of Particles with Arbitrary Spin
In 1932 Ettore Majorana published an article proving that relativity allows
any value for the spin of a quantum particle and that there is no privilege for
the half integer spin. The Majorana idea was so innovative for the time that
the scientific community understood its importance only towards the end of the
thirties. This paper aims to highlight the depth of the scientific thought of
Majorana that, well in advance of its time, opened the way for modern particle
physics and introduced for the first time the idea of a universal quantum
equation, able to explain the behavior of particles with arbitrary spin and of
any nature, regardless the value of their speed. It will be analyzed in detail
and made explicit all the steps that lead to the physical mathematical
formulation of the Majorana theory. A part of these steps require basic
knowledge of quantum physics but not for this should be regarded as trivial
since they show the physical meaning hidden into the structure of the equation.
Moreover, the explicit method for the construction of the infinite matrices
will be given, by which the infinite components of the wave functions
representing the fundamental and excited states of the particle are calculated.Comment: Paper revised after publication on "Advances in Physics Theories and
Applications", Vol. 48 (2015) - ISSN (Paper)2224-719X ISSN (Online)2225-063
Superluminal Tunneling of a Relativistic Half-Integer Spin Particle Through a Potential Barrier
This paper investigates the problem of a relativistic Dirac half integer spin
free particle tunneling through a rectangular quantum-mechanical barrier. If
the energy difference between the barrier and the particle is positive, and the
barrier width is large enough, there is proof that the tunneling may be
superluminal. For first spinor components of particle and antiparticle states,
the tunneling is always superluminal regardless the barrier width. Conversely,
the second spinor components of particle and antiparticle states may be either
subluminal or superluminal depending on the barrier width. These results derive
from studying the tunneling time in terms of phase time. For the first spinor
components of particle and antiparticle states, it is always negative while for
the second spinor components of particle and antiparticle states, it is always
positive, whatever the height and width of the barrier. In total, the tunneling
time always remains positive for particle states while it becomes negative for
antiparticle ones. Furthermore, the phase time tends to zero, increasing the
potential barrier both for particle and antiparticle states. This agrees with
the interpretation of quantum tunneling that the Heisenberg uncertainty
principle provides. This study results are innovative with respect to those
available in the literature. Moreover, they show that the superluminal
behaviour of particles occurs in those processes with high-energy confinement.Comment: 13 pages, 8 figure
Fair comparison of skin detection approaches on publicly available datasets
Skin detection is the process of discriminating skin and non-skin regions in
a digital image and it is widely used in several applications ranging from hand
gesture analysis to track body parts and face detection. Skin detection is a
challenging problem which has drawn extensive attention from the research
community, nevertheless a fair comparison among approaches is very difficult
due to the lack of a common benchmark and a unified testing protocol. In this
work, we investigate the most recent researches in this field and we propose a
fair comparison among approaches using several different datasets. The major
contributions of this work are an exhaustive literature review of skin color
detection approaches, a framework to evaluate and combine different skin
detector approaches, whose source code is made freely available for future
research, and an extensive experimental comparison among several recent methods
which have also been used to define an ensemble that works well in many
different problems. Experiments are carried out in 10 different datasets
including more than 10000 labelled images: experimental results confirm that
the best method here proposed obtains a very good performance with respect to
other stand-alone approaches, without requiring ad hoc parameter tuning. A
MATLAB version of the framework for testing and of the methods proposed in this
paper will be freely available from https://github.com/LorisNann
A Critic Evaluation of Methods for COVID-19 Automatic Detection from X-Ray Images
In this paper, we compare and evaluate different testing protocols used for
automatic COVID-19 diagnosis from X-Ray images in the recent literature. We
show that similar results can be obtained using X-Ray images that do not
contain most of the lungs. We are able to remove the lungs from the images by
turning to black the center of the X-Ray scan and training our classifiers only
on the outer part of the images. Hence, we deduce that several testing
protocols for the recognition are not fair and that the neural networks are
learning patterns in the dataset that are not correlated to the presence of
COVID-19. Finally, we show that creating a fair testing protocol is a
challenging task, and we provide a method to measure how fair a specific
testing protocol is. In the future research we suggest to check the fairness of
a testing protocol using our tools and we encourage researchers to look for
better techniques than the ones that we propose
- …