Search results for "Modeling"

CLUSTER MONTE CARLO ALGORITHMS IN STATISTICAL MECHANICS

1992

The cluster Monte Carlo method, where variables are updated in groups, is very efficient at second order phase transitions. Much better results can be obtained with less computer time. This article reviews the method of Swendsen and Wang and some of its applications.

Group Metropolis Sampling

2017

Monte Carlo (MC) methods are widely used for Bayesian inference and optimization in statistics, signal processing and machine learning. Two well-known class of MC methods are the Importance Sampling (IS) techniques and the Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce the Group Importance Sampling (GIS) framework where different sets of weighted samples are properly summarized with one summary particle and one summary weight. GIS facilitates the design of novel efficient MC techniques. For instance, we present the Group Metropolis Sampling (GMS) algorithm which produces a Markov chain of sets of weighted samples. GMS in general outperforms other multiple try schemes…

Theoretical Foundations of the Monte Carlo Method and Its Applications in Statistical Physics

2002

In this chapter we first introduce the basic concepts of Monte Carlo sampling, give some details on how Monte Carlo programs need to be organized, and then proceed to the interpretation and analysis of Monte Carlo results.

Semantic and Logic Modeling of Disaster Simulation for Multi-agent Systems

2019

Structured Output SVM for Remote Sensing Image Classification

2011

Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees,…

Status of the EU DEMO HCLL breeding blanket design development

2018

International audience; In the framework of the European “HORIZON 2020” innovation and research programme, the EUROfusion Consortium develops a design of a fusion power demonstrator (DEMO). One of the key components in the fusion reactor is the Breeding Blanket (BB) surrounding the plasma, ensuring tritium self-sufficiency, heat removal for conversion into electricity, and neutron shielding. CEA-Saclay, with the support of Wigner-RCP and Centrum výzkumu Řež, is in charge of the development of one of the four BB concepts investigated in Europe for DEMO: the Helium Cooled Lithium Lead (HCLL) BB. The rationales of the HCLL are the use of Eurofer as structural material, eutectic liquid lithium-…

Computational Homogenization of Heterogeneous Materials by a Novel Hybrid Numerical Scheme

2020

The Virtual Element Method (VEM) is a recent numerical technique capable of dealing with very general polygonal and polyhedral mesh elements, including irregular or non-convex ones. Because of this feature, the VEM ensures noticeable simplification in the data preparation stage of the analysis, especially for problems whose analysis domain features complex geometries, as in the case of computational micro-mechanics problems. The Boundary Element Method (BEM) is a well known, extensively used and effective numerical technique for the solution of several classes of problems in science and engineering. Due to its underlying formulation, the BEM allows reducing the dimensionality of the proble…

Energy Conscious Building Design

1987

Since the beginning of energy crisis many design tools have been developed in order to enable the designer to cope with energy consumption in buildings. These tools are of different kind: from very sophisticated simulation models to simplified (often too much) methods. Each of them offers various advantages and disadvantages, and it is up to the designer to choose among them.

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise-Basics and Options for Wearable Devices.

2018

The use of wearable devices or "wearables" in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the p…

Generation of User Interfaces from Business Process Model Notation (BPMN)

2019

Business Process Model Notation focuses on functional processes; so, the design of the interface generally depends on the subjective experience of the analyst. This thesis proposes a new method to generate interfaces from BPMN models. The idea is to identify rules from BPMN to interfaces in existing real projects. We have analyzed 7 Bizagi projects to generalize a list of rules. It has been done considering five BPMN patterns. Apart from BPMN primitives, there are rules that depend on elements of Class Diagrams to know how to generate the interfaces. When the rules have several alternatives to generate the interfaces, we need an unambiguous semantics to specify which alternative we are goin…