Search results for "Ensemble"
showing 10 items of 162 documents
Structure of longitudinal chromomagnetic fields in high energy collisions
2014
We compute expectation values of spatial Wilson loops in the forward light cone of high-energy collisions. We consider ensembles of gauge field configurations generated from a classical Gaussian effective action as well as solutions of high-energy renormalization group evolution with fixed and running coupling. The initial fields correspond to a color field condensate exhibiting domain-like structure over distance scales of order the saturation scale. At later times universal scaling emerges at large distances for all ensembles, with a nontrivial critical exponent. Finally, we compare the results for the Wilson loop to the two-point correlator of magnetic fields.
Classical and Quantum Two-Dimensional Fluids in the Gibbs Ensemble
1994
We study the properties of model fluids in two spatial dimensions with Gibbs ensemble Monte Carlo (GEMC) techniques. In particular in the first part of the paper we study the entropy driven phase separation in case of a nonadditive symmetric hard disc fluid and locate by a combination of GEMC with finite size scaling techniques the critical line of nonadditivities as a function of the system density, which separates the mixing/demixing regions, we compare with a simple approximation. In the second part we successfully combine path integral Monte Carlo (PIMC) and GEMC techniques in order to locate the gas-liquid coexistence densities for a fluid with classical degrees of freedom and internal…
Assembly Assistance System with Decision Trees and Ensemble Learning
2021
This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …
Replica-exchange molecular dynamics simulation for supercooled liquids
2000
We investigate to what extend the replica-exchange Monte Carlo method is able to equilibrate a simple liquid in its supercooled state. We find that this method does indeed allow to generate accurately the canonical distribution function even at low temperatures and that its efficiency is about 10-100 times higher than the usual canonical molecular dynamics simulation.
T100: A modern classic ensemble to profile irony and stereotype spreaders
2022
In this work we propose a novel ensemble model based on deep learning and non-deep learning classifiers. The proposed model was developed by our team for participating at the Profiling Irony and Stereotype Spreaders (ISSs) task hosted at PAN@CLEF2022. Our ensemble (named T100), include a Logistic Regressor (LR) that classifies an author as ISS or not (nISS) considering the predictions provided by a first stage of classifiers. All these classifiers are able to reach state-of-the-art results on several text classification tasks. These classifiers (namely, the voters) are a Convolutional Neural Network (CNN), a Support Vector Machine (SVM), a Decision Tree (DT) and a Naive Bayes (NB) classifie…
Computing the Arrangement of Circles on a Sphere, with Applications in Structural Biology
2009
International audience; Balls and spheres are the simplest modeling primitives after affine ones, which accounts for their ubiquitousness in Computer Science and Applied Mathematics. Amongst the many applications, we may cite their prevalence when it comes to modeling our ambient 3D space, or to handle molecular shapes using Van der Waals models. If most of the applications developed so far are based upon simple geometric tests between balls, in particular the intersection test, a number of applications would obviously benefit from finer pieces of information. Consider a sphere $S_0$ and a list of circles on it, each such circle stemming from the intersection between $S_0$ and another spher…
Variety and volatility in financial markets
2000
We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the $n$ stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days subsequent to these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments are fluctua…
GPU accelerated Monte Carlo simulations of lattice spin models
2011
We consider Monte Carlo simulations of classical spin models of statistical mechanics using the massively parallel architecture provided by graphics processing units (GPUs). We discuss simulations of models with discrete and continuous variables, and using an array of algorithms ranging from single-spin flip Metropolis updates over cluster algorithms to multicanonical and Wang-Landau techniques to judge the scope and limitations of GPU accelerated computation in this field. For most simulations discussed, we find significant speed-ups by two to three orders of magnitude as compared to single-threaded CPU implementations.
Prototype-based learning on concept-drifting data streams
2014
Data stream mining has gained growing attentions due to its wide emerging applications such as target marketing, email filtering and network intrusion detection. In this paper, we propose a prototype-based classification model for evolving data streams, called SyncStream, which dynamically models time-changing concepts and makes predictions in a local fashion. Instead of learning a single model on a sliding window or ensemble learning, SyncStream captures evolving concepts by dynamically maintaining a set of prototypes in a new data structure called the P-tree. The prototypes are obtained by error-driven representativeness learning and synchronization-inspired constrained clustering. To ide…
State and parameter update in a coupled energy/hydrologic balance model using ensemble Kalman filtering
2012
Summary The capability to accurately monitor and describe daily evapotranspiration (ET) in a cost effective manner is generally attributed to hydrological models. However, continuous solution of energy and water balance provides precise estimations only when a detailed knowledge of sub-surface characteristics is available. On the other hand, residual surface energy balance models, based on remote observation of land surface temperature, are characterised by sufficient accuracy, but their applicability is limited by the lack of high frequency and high resolution thermal data. A compromise between these two methodologies is represented by the use of data assimilation scheme to include sparse …