Publications related to Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data

Painting Taylor vortices with cellulose nanocrystals: Suspension flow supercritical spectral dynamics

We study the flow stability and spatiotemporal spectral dynamics of cellulose nanocrystal (CNC) suspensions in a custom Taylor-Couette flow cell using the intrinsic shear induced birefringence and liquid crystalline properties of CNC suspensions for flow v ...

Aip Publishing2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Claudia Rebeca Binder Signer, Matteo Barsanti, Selin Yilmaz

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Prateek Bansal, Thomas Gasos

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Sampling of alternatives in migration aspiration models

Michel Bierlaire, Evangelos Paschalidis

The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...

2023

An Ordinal Latent Variable Model of Conflict Intensity

Robert West

Measuring the intensity of events is crucial for monitoring and tracking armed conflict. Advances in automated event extraction have yielded massive data sets of '' who did what to whom '' micro-records that enable datadriven approaches to monitoring confl ...

Assoc Computational Linguistics-Acl2023

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Julien Favre, Brigitte Jolles-Haeberli

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

FRONTIERS MEDIA SA2023

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Michel Bierlaire

In this paper, we present a spatial branch and bound algorithm to tackle the continuous pricing problem, where demand is captured by an advanced discrete choice model (DCM). Advanced DCMs, like mixed logit or latent class models, are capable of modeling de ...

2023

Analysis-aware defeaturing of complex geometries with Neumann features

Ondine Gabrielle Chanon, Pablo Antolin Sanchez

Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...

Wiley2023

Preserved Corticospinal Tract Revealed by Acute Perfusion Imaging Relates to Better Outcome After Thrombectomy in Stroke

Friedhelm Christoph Hummel, Philipp Johannes Koch

BACKGROUND:The indication for mechanical thrombectomy (MT) in stroke patients with large vessel occlusion has been constantly expanded over the past years. Despite remarkable treatment effects at the group level in clinical trials, many patients remain sev ...

Lippincott Williams & Wilkins2023

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

Yara Kayyali El Alem

In this thesis we address various factors that contribute both theoretically and practically to mitigating supply demand mismatches. The thesis is composed of three chapters, where each chapter is an independent scientific paper. In the first paper, we dev ...

EPFL2023

Tumor control and radiobiological fingerprint after Gamma Knife radiosurgery for posterior fossa meningiomas: A series of 46 consecutive cases

Constantin Tuleasca

Introduction: Gamma Knife radiosurgery (GKR) can be a valuable treatment option for posterior cranial fossa meningiomas (PCFM). We retrospectively analyzed outcomes of GKR for PCFM.& nbsp;Methods: Were included forty-six patients with 47 PCFM. Primary endp ...

2022

Pixels: An Efficient Column Store for Cloud Data Lakes

Anastasia Ailamaki, Haoqiong Bian

To benefit from the cloud’s higher elasticity and price-efficiency, most modern data-lake engines support S3-like cloud object storage (COS) services as their optional or preferred underlying storage. Meanwhile, the widespread column stores, such as Parque ...

IEEE2022

Mesh d-refinement: a data-based computational framework to account for complex material response

Jean-François Molinari, Sacha Zenon Wattel, Antonio Joaquin Garcia Suarez

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...

2023

Analysis-aware defeaturing of complex geometries

Ondine Gabrielle Chanon, Pablo Antolin Sanchez

Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...

2022

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Urs von Gunten

Ozonation of secondary-treated wastewater for the abatement of micropollutants requires a reliable control of ozone doses. Changes in the UV absorbance of dissolved organic matter (DOM) during ozonation allow to estimate micropollutant abatement on-line an ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Soil-Structure Interaction effects on the seismic behavior of steel moment resisting frames: Preliminary assessment

Dimitrios Lignos

The purpose of this paper is to assess the influence of soil-structure interaction and site effects on the seismic behavior of steel moment-resisting frames, with a view to describing the underlying “physics” behind the damage mechanisms triggered. We exam ...

European Earthquake Engineering Association2022

Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity

Michel Bierlaire, Prateek Bansal

Mixed logit models with unobserved inter-and intra-individual heterogeneity hierarchically extend standard mixed logit models by allowing tastes to vary randomly both across individuals and across choice situations encountered by the same individual. Recen ...

ELSEVIER SCI LTD2021

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Michel Bierlaire, Virginie Janine Camille Lurkin, Stefano Bortolomiol

Oligopolistic competition occurs in various transportation markets. In this paper, we introduce a framework to find approximate equilibrium solutions of oligopolistic markets in which demand is modeled at the disaggregate level using discrete choice models ...

INFORMS2021

Integrating advanced discrete choice models in mixed integer linear optimization

Michel Bierlaire, Meritxell Pacheco Paneque, Bernard Gendron

In many transportation systems, a mismatch between the associated design and planning decisions and the demand is typically encountered. A tailored system is not only appealing to operators, which could have a better knowledge of their operational costs, b ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Francesca Criscuolo

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

2021