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The Potts Neural Network approach to non-binary discrete optimizationproblems is described. It applies to problems that can be described asa set of elementary 'multiple choice' options. Instead of the conventionalbinary (Ising) neurons, mean field Potts neurons, having several availablestates, are used to describe the elementary degrees of freedom of suchproblems. The dynamics consists of iteratin
A general introduction to the use of feed-back artificial neural networks (ANN) for obtaining good approximate solutions to combinatorial optimization problems is given, assuming no previous knowledge in the field. In particular we emphasize a novel neural mapping technique which efficiently reduces the solution space. This approach maps the problems onto Potts glass rather than spin glass models.
We devise a feed-forward Artificial Neural Network (ANN) procedure for predicting utility loads and present the resulting predictions for two test problems given by ``The Great Energy Predictor Shootout - The First Building Data Analysis and Prediction Competition''. Key ingredients in our approach are a method ($\delta$ -test) for determiningrelevant inputs and the Multilayer Perceptron. These me
The generic relation between continuous polymers and zero-componentEuclidean field-theories is reviewed, and exemplified by polymers withcontact and Coulomb interactions. An analogous relation on thelattice is also discussed, relating the statistics of self-avoidingwalks to a zero-component spin-model.
The recurrent neural network approach to combinatorial optimization has during the last decade evolved into a competitive and versatile heuristic method, that can be used on a wide range of problem types. In the state-of-the-art neural approach the discrete elementary decisions (not necessarily binary) are represented by continuous Potts mean-field neurons, interpolating between the available disc
For combinatorial optimization problems that can be formulated as Ising or Potts spin systems, the Mean Field (MF) approximation yields a versatile and simple ANN heuristic, Deterministic Annealing. For problems involving assignments (or permutations), the situation is more complex -- the natural analog of the MF approximation lacks the simplicity present in the Potts and Ising cases. In this arti
The stress response is governed by automatic neurological and hormonal processes that occur before we become consciously aware of a dangerous situation. If stress ensues for 15-30 seconds, the hormonal processes may have progressed so far that recovery takes an hour or longer instead of minutes. Stress can affect our behavior and in certain professions, such as the police force and emergency servi
The LUCID-2 detector is the main online and oine luminosity monitor of the ATLASexperiment. It provides 104 dierent luminosity measurements from different algorithms for each of the thousands of LHC bunches. The new detector is using the quartz windows of 10 mm diameter photomultipliers and optical quartz bers as the Cherenkov medium. A main challenge for a luminometer is to keep the eciency const
Purpose: Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual
The current study aims to computationally evaluate the hemodynamic impact of a novel sealing mechanism employed by a recently developed endograft (Ovation TriVascular Stent-Graft System) for endovascular aneurysm repair. The exploitation of two inflatable O-rings to achieve sealing may be advantageous in terms of accommodating challenging anatomies, but comes at a price of a marked inflow stenosis
Segmented cross sectional MRI images were used to construct 3D virtual models of the carotid bifurcation in 5 healthy volunteers. Geometric features such as bifurcation angle, planarity angle, asymmetry angle tortuosity and curvature were calculated for the normal head posture and were compared to the equivalent values acquired with the head rotated clockwise by up to 80 degrees. The results obtai
Posture changes may influence the geometry and hemodynamics of the carotid bifurcation [1]. As a result, head rotation may cause geometric changes that alter the hemodynamic variables previously cited to correlate with the development of atherosclerosis. Such variables include oscillating wall shear stress (WSS) and particle residence times. Glor et al. [1] had reported changes in the right caroti
The use of realistic anatomic human carotid artery bifurcation (CB) models with a realistic blood waveform leads to physiologically relevant numerical simulations. To study the effects of head posture on the geometry and hemodynamics of the CB, Magnetic resonance imaging (MRI) was used on six healthy volunteers in two different head postures: 1) the supine neutral (N) and 2) the prone with rightwa
This review examines four imaging modalities; ultrasound (US), digital subtraction angiography (DSA), magnetic resonance imaging (MRI) and computed tomography (CT), that have common or potential applications in vascular access (VA). The four modalities are reviewed under their primary uses, techniques, advantages and disadvantages, and future directions that are specific to VA. Currently, US is th
