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Predicting Usefulness of Measuring Structures during Load Tests

Publications associées (167)

Revisiting Multivariate Ring Learning with Errors and Its Applications on Lattice-Based Cryptography

The “Multivariate Ring Learning with Errors” problem was presented as a generalization of Ring Learning with Errors (RLWE), introducing efficiency improvements with respect to the RLWE counterpart thanks to its multivariate structure. Nevertheless, the rec ...

2021

Grammar-based generation of bar networks in static equilibrium with bounded bar lengths

Corentin Jean Dominique Fivet, Ioannis Mirtsopoulos

This paper presents a generative approach for the conceptual design of structures, which aims at exploring alternative bar networks in static equilibrium by means of a grammar rule. Operating on incomplete networks of bars in interim static equilibrium, th ...

2021

The Cost of Scaling a Reliable Interconnection Topology

Rachid Guerraoui, Alexandre David Olivier Maurer

In distributed computing, many papers try to evaluate the message complexity of a distributed system as a function of the number of nodes n. But what about the cost of building the distributed system itself? Assuming that we want to reliably connect n node ...

2020

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Volkan Cevher, Ali Kavis, Shaul Nadav Hallak

This paper analyzes the trajectories of stochastic gradient descent (SGD) to help understand the algorithm’s convergence properties in non-convex problems. We first show that the sequence of iterates generated by SGD remains bounded and converges with prob ...

2020

Multi-View Shape Estimation of Transparent Containers

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions. In this paper, we propose a method for jointly localising container-like obj ...

2020

Estimating The Degree of Sleepiness by Integrating Articulatory Feature Knowledge In Raw Waveform Based CNNs

Julian David Fritsch, Subrahmanya Pavankumar Dubagunta

Speech-based degree of sleepiness estimation is an emerging research problem. This paper investigates an end-to-end approach, where given raw waveform as input, a convolutional neural network (CNN) estimates at its output the degree of sleepiness. Within t ...

2020

Gamma Knife radiosurgery for acromegaly: Evaluating the role of the biological effective dose associated with endocrine remission in a series of 42 consecutive cases

Constantin Tuleasca

Introduction Stereotactic radiosurgery (SRS) is a valuable treatment option for persistent and/or recurrent acromegaly secondary to growth hormone (GH) secreting pituitary adenoma (PA). Here, we assess the role of biological effective dose (BED) received b ...

2020

A Type-and-Effect System for Object Initialization

Martin Odersky, Fengyun Liu, Paolo Giosuè Giarrusso, Ondrej Lhoták

Every newly created object goes through several initialization states: starting from a state where all fields are uninitialized until all of them are assigned. Any operation on the object during its initialization process, which usually happens in the cons ...

2020

Least-Squares Padé approximation of parametric and stochastic Helmholtz maps

Fabio Nobile, Francesca Bonizzoni, Davide Pradovera

The present work deals with rational model order reduction methods based on the single-point Least-Square (LS) Padé approximation techniques introduced in Bonizzoni et al. (ESAIM Math. Model. Numer. Anal., 52(4), 1261–1284 2018, Math. Comput. 89, 1229–1257 ...

2020

White matter hyperintensities at critical crossroads for executive function and verbal abilities in small vessel disease

The presence of white matter lesions in patients with cerebral small vessel disease (SVD) is among the main causes of cognitive decline. We investigated the relation between white matter hyperintensity (WMH) locations and executive and language abilities i ...

2020

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