Representing location choice within activity-based models

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Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

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A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

The collimation system of the Future Circular Collider, operating with leptons (FCC-ee), must protect not only the experiments against backgrounds, but also the machine itself from beam losses. With a 17.8 MJ stored energy of the electron and positron beam ...

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We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

The ITER Electron Cyclotron Resonance Heating and Current Drive (ECRH&CD) system relies on 1 MW 170 GHz Gyrotrons to provide the mm-wave power needed for plasma heating, current drive, and magneto-hydrodynamic control. The design and modeling of the contro ...

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

Anthropogenic modification of natural landscapes to urban environments impacts land-atmosphere interactions in the boundary layer. Ample research has demonstrated the effect of such landscape transitions on development of the urban heat island (UHI), but c ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

In this paper we propose a Monte Carlo maximum likelihood estimation strategy for discretely observed Wright–Fisher diffusions. Our approach provides an unbiased estimator of the likelihood function and is based on exact simulation techniques that are of s ...

Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

The objective of this study is to address the difficulty of simplifying the geometric model in which a differential problem is formulated, also called defeaturing, while simultaneously ensuring that the accuracy of the solution is maintained under control. ...

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

We present a validation of a three-dimensional, two-fluid simulation of plasma turbulence in the TJ-K stellarator, a low temperature plasma experiment ideally suited for turbulence measurements. The simulation is carried out by the GBS code, recently adapt ...

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

Representing location choice within activity-based models

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On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience

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Spectral Estimators for High-Dimensional Matrix Inference

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Collimation simulations for the FCC-ee

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

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Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

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Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Unbiased Likelihood Estimation of Wright–Fisher Diffusion Processes

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

A Shape Derivative Approach to Domain Simplification

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Validation of GBS plasma turbulence simulation of the TJ-K stellarator

An equilibrated flux a posteriori error estimator for defeaturing problems

Stochastic adaptive resampling for the estimation of discrete choice models

Functional data analysis with rough sample paths?