Optimal Capacity of the Blume-Emery-Griffiths perceptron

A Blume-Emery-Griffiths perceptron model is introduced and its optimal capacity is calculated within the replica-symmetric Gardner approach, as a function of the pattern activity and the imbedding stability parameter. The stability of the replica-symmetric approximation is studied via the analogue of the Almeida-Thouless line. A comparison is made with other three-state perceptrons.Comment: 10 pages, 8 figure

A spherical Hopfield model

We introduce a spherical Hopfield-type neural network involving neurons and patterns that are continuous variables. We study both the thermodynamics and dynamics of this model. In order to have a retrieval phase a quartic term is added to the Hamiltonian. The thermodynamics of the model is exactly solvable and the results are replica symmetric. A Langevin dynamics leads to a closed set of equations for the order parameters and effective correlation and response function typical for neural networks. The stationary limit corresponds to the thermodynamic results. Numerical calculations illustrate our findings.Comment: 9 pages Latex including 3 eps figures, Addition of an author in the HTML-abstract unintentionally forgotten, no changes to the manuscrip

Measurement of mesoscopic High-TcT_c superconductors using Si mechanical micro-oscillators

In a superconducting mesoscopic sample, with dimensions comparable to the London penetration depth, some properties are qualitatively different to those found in the bulk material. These properties include magnetization, vortex dynamics and ordering of the vortex lattice. In order to detect the small signals produced by this kind of samples, new instruments designed for the microscale are needed. In this work we use micromechanical oscillators to study the magnetic properties of a Bi$_2$Sr$_2$CaCu$_2$O$_{8 + \delta}$ disk with a diameter of 13.5 microns and a thickness of 2.5 microns. The discussion of our results is based on the existence and contribution of inter and intra layer currents.Comment: 4 pages, 6 figure

How the Belgian wind farm business made us discover the challenging environment of marine sand dunes

During the last decade, it has become clear that sand dunes are important features in the Belgian wind farm concession area. Because they influence not only the design seabed levels, but also the hydrodynamic forcings and installation methods for both cable and foundations, the study of the seabed morphodynamics is essential for all wind farm projects. This paper starts with an overview of the geographic and morphological setting of the Belgian wind farm concession areas and presents an overview of the key features of the bedforms in the different concessions. Next the importance and impact of the sand dunes during the design and development of these wind farms is illustrated by exploring the different types of studies and investigations which have been performed in relation to seabed & morphology, the hydrodynamic loadings, the installation methods and the environmental impact assessments

Vortex liquid correlations induced by in-plane field in underdoped Bi2Sr2CaCu2O8+d

By measuring the Josephson Plasma Resonance, we have probed the influence of an in-plane magnetic field on the pancake vortex correlations along the c-axis in heavily underdoped Bi2Sr2CaCu2O8+d (Tc = 72.4 +/- 0.6 K) single crystals both in the vortex liquid and in the vortex solid phase. Whereas the in-plane field enhances the interlayer phase coherence in the liquid state close to the melting line, it slightly depresses it in the solid state. This is interpreted as the result of an attractive force between pancake vortices and Josephson vortices, apparently also present in the vortex liquid state. The results unveil a boundary between a correlated vortex liquid in which pancakes adapt to Josephson vortices, and the usual homogeneous liquid.Comment: 2 pages, submitted to the Proceedings of M2S HTSC VIII Dresde

Minimalist AdaBoost for blemish identification in potatoes

We present a multi-class solution based on minimalist Ad- aBoost for identifying blemishes present in visual images of potatoes. Using training examples we use Real AdaBoost to rst reduce the fea- ture set by selecting ve features for each class, then train binary clas- siers for each class, classifying each testing example according to the binary classier with the highest certainty. Against hand-drawn ground truth data we achieve a pixel match of 83% accuracy in white potatoes and 82% in red potatoes. For the task of identifying which blemishes are present in each potato within typical industry dened criteria (10% coverage) we achieve accuracy rates of 93% and 94%, respectively