Search results for "ensemble"
showing 10 items of 162 documents
Improving the prediction of air pollution peak episodes generated by urban transport networks
2016
Abstract This paper illustrates the early results of ongoing research developing novel methods to analyse and simulate the relationship between trasport-related air pollutant concentrations and easily accessible explanatory variables. The final scope is to integrate the new models in traditional traffic management support systems for a sustainable mobility of road vehicles in urban areas. This first stage concerns the relationship between the hourly mean concentration of nitrogen dioxide (NO2) and explanatory factors reflecting the NO2 mean level one hour back, along with traffic and weather conditions. Particular attention is given to the prediction of pollution peaks, defined as exceedanc…
A New Monte Carlo Method for the Titration of Molecules and Minerals
2007
The charge state of molecules and solid/liquid interfaces is of paramount importance in the understanding of the reactivity and the physico-chemical properties of many systems. In this work, we porpose a new Monte Carlo method in the grand canonical ensemble using the primitive model, which allows us to simulate the titration behavior of macromolecules or solids at constant pH. The method is applied to the charging process of colloidal silica particles dispersed in a sodium salt solution for various concentrations and calcium silicate hydrate nano-particles in a calcium hydroxide solution. An excellent agreement is found between the experimental and simulated results.
Phase transitions and quantum effects in adsorbed monolayers
1996
Phase transitions in absorbed (two-dimensional) fluids and in absorbed layers of linear molecules are studied with a combination of path integral Monte Carlo (PIMC), Gibbs ensemble Monte Carlo (GEMC), and finite size scaling techniques. For a classical (nonadditive) hard-disk fluid the “critical” nonadditivities, where the entropy-driven phase separations set in, are presented. For a fluid with internal quantum states the gas-liquid coexistence region, tricritical, and triple points can be determined, and a comparison with density functional (DFT) results shows good agreement for the freezing densities. LinearN 2 molecules adsorbed on graphite (in the √3 × √3 structure) show a transition fr…
Coadsorption of NRR and HER Intermediates Determines the Performance of Ru-N4 toward Electrocatalytic N2 Reduction
2021
Efficiency of the electrochemical N2 reduction reaction (NRR) to ammonia is seriously limited by the competing hydrogen evolution reaction (HER) but our current atomic-scale insight on the factors controlling HER/NRR competition are unknown. Herein we unveil the elementary mechanism, thermodynamics, and kinetics determining the HER/NRR selectivity on the state-of-the-art NRR electrocatalyst, Ru-N4 using constant potential density functional theory calculations (DFT). The calculations show that NRR and HER intermediates coadsorb on the catalyst where HER is greatly suppressed by the NRR intermediates. The first reaction step leading to either *NNH or *H determines the selectivity towards NRR…
A Behavior-Based Intrusion Detection System Using Ensemble Learning Techniques
2022
Intrusion Detection Systems (IDSs) play a key role in modern ICT security. Attacks detected and reported by IDSs are often analyzed by administrators who are tasked with countering the attack and minimizing its damage. Consequently, it is important that the alerts generated by the IDS are as detailed as possible. In this paper, we present a multi-layered behavior-based IDS using ensemble learning techniques for the classification of network attacks. Three widely adopted and appreciated models, i.e., Decision Trees, Random Forests, and Artificial Neural Networks, have been chosen to build the ensemble. To reduce the system response time, our solution is designed to immediately filter out tra…
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…
Multi-speckle autocorrelation spectroscopy — a new strategy to monitor ultraslow dynamics in dense and nonergodic media
2007
We present a modification of the conventional dynamic light scattering set-up which allows to monitor the intensity fluctuations of many independent spatial Fourier components of the density fluctuations, i.e. “speckles”, simultaneously by using a charge-coupled device (CCD) camera as area detector. By averaging over the intensity autocorrelation function the final 10–20% decay of the intermediate scattering function in very dense colloidal dispersions is obtained with much higher accuracy. At the same time this multi-speckle autocorrelation spectroscopy provides an alternative route for constructing ensemble-averaged intermediate scattering functions in nonergodic media by replacing the av…
Classical Statistical Mechanics
2003
Some aspects of statistical mechanics that are particularly important for computer simulation approaches are recalled. Using Ising and classical Heisenberg models as examples, various statistical ensembles and appropriate thermodynamic potentials are introduced, and concepts such as Legendre transformations between ensembles and the thermodynamic integration method to obtain the entropy are mentioned. Probability distributions characterizing statistical fluctuations are discussed, fluctuation relations for response functions are derived, and the behavior of these quantities at first and second order phase transitions are described qualitatively. Also the general consequences of phase coexis…
Transitions between imperfectly ordered crystalline structures: A phase switch Monte Carlo study
2012
A model for two-dimensional colloids confined laterally by ``structured boundaries'' (i.e., ones that impose a periodicity along the slit) is studied by Monte Carlo simulations. When the distance $D$ between the confining walls is reduced at constant particle number from an initial value ${D}_{0}$, for which a crystalline structure commensurate with the imposed periodicity fits, to smaller values, a succession of phase transitions to imperfectly ordered structures occur. These structures have a reduced number of rows parallel to the boundaries (from $n$ to $n\ensuremath{-}1$ to $n\ensuremath{-}2$, etc.) and are accompanied by an almost periodic strain pattern, due to ``soliton staircases'' …