Publication

Effects of service loading on the behaviour of a suspension bridge

Related publications (72)

Expression of Prox1 in Medullary Thyroid Carcinoma Is Associated with Chromogranin A and Calcitonin Expression and with Ki67 Proliferative Index, but Not with Prognosis

Medullary thyroid carcinoma (MTC) has been shown to express Prospero homeobox protein 1 (Prox1), a transcription factor whose expression is altered in a variety of human cancers. We conducted a retrospective study on a series of 32 patients with MTC to tes ...
2019

Predicting Modafinil-Treatment Response in Poststroke Fatigue Using Brain Morphometry and Functional Connectivity

Bénédicte Marie Maréchal

Background and Purpose- Poststroke fatigue affects a large proportion of stroke survivors and is associated with a poor quality of life. In a recent trial, modafinil was shown to be an effective agent in reducing poststroke fatigue; however, not all patien ...
LIPPINCOTT WILLIAMS & WILKINS2019

Methodology And Convergence Rates For Functional Time Series Regression

Victor Panaretos, Tung Huy Pham

The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite-dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose inverse is by defi ...
STATISTICA SINICA2018

Data-driven reduced order modeling for time-dependent problems

Jan Sickmann Hesthaven, Mengwu Guo

A data-driven reduced basis (RB) method for parametrized time-dependent problems is proposed. This method requires the offline preparation of a database comprising the time history of the full-order solutions at parameter locations. Based on the full-order ...
2018

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms

Volkan Cevher, Junhong Lin

We study generalization properties of distributed algorithms in the setting of nonparametric regression over a reproducing kernel Hilbert space (RKHS). We first investigate distributed stochastic gradient methods (SGM), with mini-batches and multi-passes o ...
2018

Sensorless Position Detection Framework for a Multi-state Switched Reluctance Actuator of a Textile Machine

Yves Perriard, Yoan René Cyrille Civet, Paolo Germano, Xinchang Liu

Sensorless needle position detection for the actuator of a textile machine is challenging because of its multi current levels used and the transient state when the current changes. A local regression method can be used to represent the variation of inducta ...
IEEE2018

Implementing Fusion Techniques for the Classification of Paralinguistic Information

Jilt Sebastian

This work tests several classification techniques and acoustic features and further combines them using late fusion to classify paralinguistic information for the ComParE 2018 challenge. We use Multiple Linear Regression (MLR) with Ordinary Least Squares ( ...
ISCA-INT SPEECH COMMUNICATION ASSOC2018

Public smoking ban and socioeconomic inequalities in smoking prevalence and cessation: a cross-sectional population-based study in Geneva, Switzerland (1995–2014)

Stéphane Joost, Idris Guessous

Introduction Smoking bans were suggested to reduce smoking prevalence and increase quit ratio but their equity impact remains unclear. We aimed to characterise the socioeconomic status (SES)-related inequalities in smoking prevalence and quit ratio before ...
2018

Predictive models for assessing the passive solar and daylight potential of neighborhood designs: A comparative proof-of-concept study

Marilyne Andersen, Émilie Nault

Despite recent developments, neighborhood-scale performance assessment at the early-design phase is seldom carried out in practice, notably due to high computational complexity, time requirement, and perceived need for expert knowledge, ultimately limiting ...
2017

Modeling, Regression and Optimization

Julien Léo Billeter

This lecture describes the following topics: • Preamble on Linear Algebra • Dynamic and Static Models • Solving Dynamic and Static Models • Solving Regression Problems • Solving Static and Dynamic Optimization Probl ...
2016

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