576 research outputs found
Electronic transport through ballistic chaotic cavities: reflection symmetry, direct processes, and symmetry breaking
We extend previous studies on transport through ballistic chaotic cavities
with spatial left-right (LR) reflection symmetry to include the presence of
direct processes. We first analyze fully LR-symmetric systems in the presence
of direct processes and compare the distribution w(T) of the transmission
coefficient T with that for an asymmetric cavity with the same "optical" S
matrix. We then study the problem of "external mixing" of the symmetry caused
by an asymmetric coupling of the cavity to the outside. We first consider the
case where symmetry breaking arises because two symmetrically positioned
waveguides are coupled to the cavity by means of asymmetric tunnel barriers.
Although this system is asymmetric with respect to the LR operation, it has a
striking memory of the symmetry of the cavity it was constructed from.
Secondly, we break LR symmetry in the absence of direct proceses by
asymmetrically positioning the two waveguides and compare the results with
those for the completely asymmetric case.Comment: 15 pages, 8 Postscript figures, submitted to Phys. Rev.
Memetic Pareto Evolutionary Artificial Neural Networks for the determination of growth limits of Listeria Monocytogenes
The main objective of this work is to automatically
design neural network models with sigmoidal basis
units for classification tasks, so that classifiers are
obtained in the most balanced way possible in terms of
CCR and Sensitivity (given by the lowest percentage of
examples correctly predicted to belong to each class).
We present a Memetic Pareto Evolutionary NSGA2
(MPENSGA2) approach based on the Pareto-NSGAII
evolution (PNSGAII) algorithm. We propose to
augmente it with a local search using the improved
Rprop—IRprop algorithm for the prediction of
growth/no growth of L. monocytogenes as a function of
the storage temperature, pH, citric (CA) and ascorbic
acid (AA). The results obtained show that the
generalization ability can be more efficiently improved
within a framework that is multi-objective instead of a
within a single-objective one
Salmonella in free-ranging quokkas (Setonix brachyurus) from Rottnest Island and the mainland of Western Australia
Salmonella is a genus of Gram-negative, motile, and facultative anaerobic bacteria with a worldwide distribution that contaminates multiple substrates (vegetation, food, soil, and water) and inhabits the gastrointestinal tract of birds, reptiles, and mammals, including humans. Rottnest Island is a popular tourist destination and is abundantly inhabited by quokkas (Setonix brachyurus), a charismatic small wallaby. Current data on the association between Salmonella and quokkas on Rottnest Island are outdated by approximately 30 years. Additionally, previous studies on quokkas on this island and mainland Western Australia did not perform physical examinations or any diagnostic tests. The aim of the project was to assess the prevalence of Salmonella spp. in quokkas from Rottnest Island and mainland Western Australia and correlate the presence of the bacterium with the health of the animal. Ninety-two quokkas from Rottnest Island (n = 71) and populations on the mainland (n = 21) were screened for Salmonella, and a prevalence of 47.9% and 4.8%, respectively, was determined. A total of 16 serovars were identified from 37 isolates; five of these serovars had previously not been described in the quokka. Salmonella appeared to have an effect on the haematology and blood chemistry of quokkas on Rottnest Island consistent with subclinical salmonellosis. The health of Rottnest Island quokkas, and their potential impact on the health of the visitors to the island, should continue to be monitored carefully
A guided data projection technique for classi cation of sovereign ratings: the case of European Union 27
Sovereign rating has had an increasing importance since the beginning of the
nancial crisis. However, credit rating agencies opacity has been criticised by
several authors highlighting the suitability of designing more objective alternative
methods. This paper tackles the sovereign credit rating classi cation
problem within an ordinal classi cation perspective by employing a pairwise
class distances projection to build a classi cation model based on standard regression
techniques. In this work the -SVR is selected as the regressor tool.
The quality of the projection is validated through the classi cation results obtained
for four performance metrics when applied to Standard & Poors, Moody's
and Fitch sovereign rating data of U27 countries during the period 2007-2010.
This validated projection is later used for ranking visualization which might be
suitable to build a decision support syste
A CMOS self-contained quadrature signal generator for soc impedance spectroscopy
This paper presents a low-power fully integrated quadrature signal generator for system-on-chip (SoC) impedance spectroscopy applications. It has been designed in a 0.18 µm-1.8 V CMOS technology as a self-contained oscillator, without the need for an external reference clock. The frequency can be digitally tuned from 10 to 345 kHz with 12-bit accuracy and a relative mean error below 1.7%, thus supporting a wide range of impedance sensing applications. The proposal is experimentally validated in two impedance spectrometry examples, achieving good magnitude and phase recovery results compared to the results obtained using a commercial LCR-meter. Besides the wide frequency tuning range, the proposed programmable oscillator features a total power consumption lower than 0.77 mW and an active area of 0.129 mm2, thus constituting a highly suitable choice as stimulation module for instrument-on-a-chip devices
A weed monitoring system using UAV-imagery and the Hough transform
Usually, crops require the use of herbicides as a useful manner of controlling the
quality and quantity of crop production. Although there are weed-free areas, the most
common approach is to broadcast herbicides entirely over crop fields, resulting in a
reduction of profits and increase in environmental risks. Recently, patch spraying has
allowed the use of site-specific weed management, allowing precise and timely weed maps at
very early phenological stage, either by ground sampling or remote analysis. Remote imagery
from piloted planes and satellites are not suitable for this purpose given their low spatial and
temporal resolutions, however, unmanned aerial vehicles (UAV) represent an excellent
alternative. This paper presents a new classification framework for weed monitoring via UAV
showing promising results and accurate generalisation in different scenariosLos cultivos precisan del uso de herbicidas para controlar la calidad y cantidad
de producción. A pesar de que las malas hierbas se distribuyen en rodales, la práctica más
extendida es la fumigación de herbicidas en todo el cultivo, resultando en un aumento del
coste y de riesgos mediambientales. La pulvericación por parches ha dado lugar al auge de
otras técnicas de manejo de malas hierbas, permitiendo su tratamiento en un estado
fenológico temprano. Las imágenes remotas de aviones pilotados o satélites no son útiles en
este caso debido a su baja resolución espacial y temporal. Sin embargo, este no es el caso de
los vehículos aéreos no tripulados. Este artículo presenta un nuevo método para
monitorización de malas hierbas usando este tipo de vehículos, mostrando resultados
prometedore
Ordinal and nominal classication of wind speed from synoptic pressure patterns
Wind speed reconstruction is a challenging problem in areas (mainly wind
farms) where there are not direct wind measures available. Di erent approaches
have been applied to this reconstruction, such as measure-correlatepredict
algorithms, approaches based on physical models such as reanalysis
methods, or more recently, indirect measures such as pressure, and its relation
to wind speed. This paper adopts the latter method, and deals with wind
speed estimation in wind farms from pressure measures, but including different
novelties in the problem treatment. Existing synoptic pressure-based
indirect approaches for wind speed estimation are based on considering the
wind speed as a continuous target variable, estimating then the corresponding
wind series of continuous values. However, the exact wind speed is not
always needed by wind farms managers, and a general idea of the level of
speed is, in the majority of cases, enough to set functional operations for the
farm (such as wind turbines stop, for example). Moreover, the accuracy of the models obtained is usually improved for the classi cation task, given that
the problem is simpli ed. Thus, this paper tackles the problem of wind speed
prediction from synoptic pressure patterns by considering wind speed as a
discrete variable and, consequently, wind speed prediction as a classi cation
problem, with four wind level categories: low, moderate, high or very high.
Moreover, taking into account that these four di erent classes are associated
to four values in an ordinal scale, the problem can be considered as an ordinal
regression problem. The performance of several ordinal and nominal classi-
ers and the improvement achieved by considering the ordering information
are evaluated. The results obtained in this paper present the Support Vector
Machine as the best tested classi er for this task. In addition, the use of
the intrinsic ordering information of the problem is shown to signi cantly
improve ranks with respect to nominal classi cation, although di erences in
accuracy are smal
Spectral functions and pseudogap in the t-J model
We calculate spectral functions within the t-J model as relevant to cuprates
in the regime from low to optimum doping. On the basis of equations of motion
for projected operators an effective spin-fermion coupling is derived. The self
energy due to short-wavelength transverse spin fluctuations is shown to lead to
a modified selfconsistent Born approximation, which can explain strong
asymmetry between hole and electron quasiparticles. The coupling to
long-wavelength longitudinal spin fluctuations governs the low-frequency
behavior and results in a pseudogap behavior, which at low doping effectively
truncates the Fermi surface.Comment: Minor corrections; to appear in Phys. Rev. B (RC
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