685 research outputs found
Absence of a True Vortex-Glass Phase above the Bragg Glass Transition Line in Bi-2212
In magnetic measurements on BiSrCaCuO (Bi-2212)
single crystals, a general peak with a dynamical feature on both and
curves was found with S the magnetic relaxation rate. At higher fields,
the characteristic exponent becomes negative, together with the positive
curvature of vs. and the scaling based on the 2D vortex glass
theory or plastic creep theory, we conclude that the vortex motion above the
second peak is plastic when and there is no vortex glass phase at
finite temperatures in Bi-2212. The peak of S is then explained as the
crossover between different meta-stable vortex states.Comment: 10 pages, 5 figures, To appear in Physica
Dimensional Crossover of Vortex Dynamics Induced by Gd Substitution on Bi2212 Single Crystals
The vortex dynamics of BiSrCaGdCuO
single crystals is investigated by magnetic relaxation and hysteresis
measurements. By substituting with , it is found that the interlayer
Josephson coupling is weakened and the anisotropy is increased, which leads to
the change of vortex dynamics from 3D elastic to 2D plastic vortex creep.
Moreover, the second magnetization peak, which can be observed in samples near
the optimal doping, is absent in the strongly underdoped (with 2D vortex)
region.Comment: 16 Pages, 6 Figures, To appear in Physica
AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden
The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, their deployment is hindered by the high cost of labelling the crop images to provide data for model training. This study examines the capabilities of semi-supervised and active learning to minimise effort when labelling cotton lint samples while maintaining high classification accuracy. Random forest classification models were developed using supervised learning, semi-supervised learning, and active learning to determine Egyptian cotton grade. Compared to supervised learning (80.20-82.66%) and semi-supervised learning (81.39-85.26%), active learning models were able to achieve higher accuracy (82.85-85.33%) with up to 46.4% reduction in the volume of labelled data required. The primary obstacle when using machine learning for Egyptian cotton grading is the time required for labelling cotton lint samples. However, by applying active learning, this study successfully decreased the time needed from 422.5 to 177.5 min. The findings of this study demonstrate that active learning is a promising approach for developing accurate and efficient machine learning models for grading food and industrial crops
An image processing and machine learning solution to automate Egyptian cotton lint grading
Egyptian cotton is one of the most important commodities for the Egyptian economy and is renowned globally for its quality, which is largely assessed and graded by manual inspection. This grading has several drawbacks, including significant labor requirements, low inspection efficiency, and influence from inspection conditions such as light and human subjectivity. This work proposes a low-cost solution to replace manual inspection with classification models to grade Egyptian cotton lint using images captured by a charge-coupled device camera. While this method has been evaluated for classifying US and Chinese upland cotton staples, it has not been tested on Egyptian cotton, which has unique characteristics and grading requirements. Furthermore, the methodology to develop these classification models has been expanded to include image processing techniques that remove the influence of trash on color measurements and extract features that capture the intra-sample variance of the cotton samples. Three different supervised machine learning algorithms were evaluated: artificial neural networks; random forest; and support vector machines. The highest accuracy models (82.13–90.21%) used a random forest algorithm. The models’ accuracy was limited by the human error associated with labeling the cotton samples used to develop the classification models. Unsupervised machine learning methods, including k-means clustering, hierarchical clustering, and Gaussian mixture models, were used to indicate where labeling errors occurred
Flux-lattice melting in two-dimensional disordered superconductors
The flux line lattice melting transition in two-dimensional pure and
disordered superconductors is studied by a Monte Carlo simulation using the
lowest Landau level approximation and quasi-periodic boundary condition on a
plane. The position of the melting line was determined from the diffraction
pattern of the superconducting order parameter. In the clean case we confirmed
the results from earlier studies which show the existence of a quasi-long range
ordered vortex lattice at low temperatures. Adding frozen disorder to the
system the melting transition line is shifted to slightly lower fields. The
correlations of the order parameter for translational long range order of the
vortex positions seem to decay slightly faster than a power law (in agreement
with the theory of Carpentier and Le Doussal) although a simple power law decay
cannot be excluded. The corresponding positional glass correlation function
decays as a power law establishing the existence of a quasi-long range ordered
positional glass formed by the vortices. The correlation function
characterizing a phase coherent vortex glass decays however exponentially
ruling out the possible existence of a phase coherent vortex glass phase.Comment: 12 pages, 21 figures, final version to appear in Phys. Rev.
Existence of the Abrikosov vortex state in two-dimensional type-II superconductors without pinning
Theory alternative to the vortex lattice melting theories is advertised. The
vortex lattice melting theories are science fiction cond-mat/9811051 because
the Abrikosov state is not the vortex lattice with crystalline long-range
order. Since the fluctuation correction to the Abrikosov solution is infinite
in the thermodynamic limit (K.Maki and H.Takayama, 1972) any fluctuation theory
of the mixed state should consider a superconductor with finite sizes. Such
nonperturbative theory for the easiest case of two-dimensional superconductor
in the lowest Landau level approximation is presented in this work. The
thermodynamic averages of the spatial average order parameter and of the
Abrikosov parameter are calculated. It is shown that the position
H_{c4} of the transition into the Abrikosov state (i.e. in the mixed state with
long-range phase coherence) depends strongly on sizes of two-dimensional
superconductor. Fluctuations eliminate the Abrikosov vortex state in a wide
region of the mixed state of thin films with real sizes and without pinning
disorders, i.e. H_{c4} << H_{c2}. The latter has experimental corroboration in
Phys.Rev.Lett. 75, 2586 (1995).Comment: 4 pages, 0 figure
A new approach for the limit to tree height using a liquid nanolayer model
Liquids in contact with solids are submitted to intermolecular forces
inferring density gradients at the walls. The van der Waals forces make liquid
heterogeneous, the stress tensor is not any more spherical as in homogeneous
bulks and it is possible to obtain stable thin liquid films wetting vertical
walls up to altitudes that incompressible fluid models are not forecasting.
Application to micro tubes of xylem enables to understand why the ascent of sap
is possible for very high trees like sequoias or giant eucalyptus.Comment: In the conclusion is a complementary comment to the Continuum
Mechanics and Thermodynamics paper. 21 pages, 4 figures. Continuum Mechanics
and Thermodynamics 20, 5 (2008) to appea
Critical Behavior of the Supersolid transition in Bose-Hubbard Models
We study the phase transitions of interacting bosons at zero temperature
between superfluid (SF) and supersolid (SS) states. The latter are
characterized by simultaneous off-diagonal long-range order and broken
translational symmetry. The critical phenomena is described by a
long-wavelength effective action, derived on symmetry grounds and verified by
explicit calculation. We consider two types of supersolid ordering:
checkerboard (X) and collinear (C), which are the simplest cases arising in two
dimensions on a square lattice. We find that the SF--CSS transition is in the
three-dimensional XY universality class. The SF--XSS transition exhibits
non-trivial new critical behavior, and appears, within a
expansion to be driven generically first order by fluctuations. However, within
a one--loop calculation directly in a strong coupling fixed point with
striking ``non-Bose liquid'' behavior is found. At special isolated
multi-critical points of particle-hole symmetry, the system falls into the 3d
Ising universality class.Comment: RevTeX, 24 pages, 16 figures. Also available at
http://www.cip.physik.tu-muenchen.de/tumphy/d/T34/Mitarbeiter/frey.htm
- …