Search results for "Crete"

Tomographical aspects of L-convex polyominoes

2007

Modelling mode choice for freight transport using advanced choice experiments

2015

Abstract In this paper we use advanced choice modelling techniques to analyse demand for freight transport in a context of modal choice. To this end, a stated preference (SP) survey was conducted in order to estimate freight shipper preferences for the main attributes that define the service offered by the different transport modes. From a methodological point of view, we focus on two critical issues in the construction of efficient choice experiments. Firstly, in obtaining good quality prior information about the parameters; and secondly, in the improved quality of the experimental data by tailoring a specific efficient design for every respondent in the sample. With these data, different …

Location theories and business location decision: A micro-spatial investigation of a nonmetropolitan area in Canada

2016

This paper draws on location theories to statistically identify the relationship between the location of individual business establishments and the characterization of their local economic environment. Taking a micro-spatial perspective, the paper develops indicators from distance-based measures (DBM) to serve as independent variables in a discrete choice model (DCM). Using a 2006 database of individual business establishments in the Lower-St-Lawrence region—a coherent, nonmetropolitan subsystem of cities in the province of Québec, Canada—we provide an empirical analysis of the determinants of individual establishments’ location decisions in relation to their main economic activity within a…

Using Wave Propagation Simulations and Convolutional Neural Networks to Retrieve Thin Film Thickness from Hyperspectral Images

2021

Ill-posed inversion problems are one of the major challenges when there is a need to combine measurements with the theory and numerical model. In this study, we demonstrate the use of wave propagation simulations to train a convolutional neural network (CNN) for retrieving sub-wavelength thickness profiles of thin film coatings from hyperspectral images. The simulations are produced by solving numerically one-dimensional wave equation with a method based on Discrete Exterior Calculus (DEC). This approach provides a powerful tool to produce large sets of training data for the neural network. CNN was verified by simulated verification sets and measured reflectance spectra, both of which showe…

Fully representable and*-semisimple topological partial*-algebras

2012

We continue our study of topological partial *-algebras, focusing our attention to *-semisimple partial *-algebras, that is, those that possess a {multiplication core} and sufficiently many *-representations. We discuss the respective roles of invariant positive sesquilinear (ips) forms and representable continuous linear functionals and focus on the case where the two notions are completely interchangeable (fully representable partial *-algebras) with the scope of characterizing a *-semisimple partial *-algebra. Finally we describe various notions of bounded elements in such a partial *-algebra, in particular, those defined in terms of a positive cone (order bounded elements). The outcome …

On the Ball-Marsden-Slemrod obstruction for bilinear control systems

2019

International audience; In this paper we present an extension to the case of $L^1$-controls of a famous result by Ball--Marsden--Slemrod on the obstruction to the controllability of bilinear control systems in infinite dimensional spaces.

On Strong Convergence of Halpern’s Method for Quasi-Nonexpansive Mappings in Hilbert Spaces

2016

In this paper, we introduce a Halpern’s type method to approximate common fixed points of a nonexpansive mapping T and a strongly quasi-nonexpansive mappings S, defined in a Hilbert space, such that I − S is demiclosed at 0. The result shows as the same algorithm converges to different points, depending on the assumptions of the coefficients. Moreover, a numerical example of our iterative scheme is given.

Anti-concentration property for random digraphs and invertibility of their adjacency matrices

2016

Let Dn,dDn,d be the set of all directed d-regular graphs on n vertices. Let G be a graph chosen uniformly at random from Dn,dDn,d and M be its adjacency matrix. We show that M is invertible with probability at least View the MathML source1−Cln3⁡d/d for C≤d≤cn/ln2⁡nC≤d≤cn/ln2⁡n, where c,Cc,C are positive absolute constants. To this end, we establish a few properties of directed d-regular graphs. One of them, a Littlewood–Offord-type anti-concentration property, is of independent interest: let J be a subset of vertices of G with |J|≤cn/d|J|≤cn/d. Let δiδi be the indicator of the event that the vertex i is connected to J and δ=(δ1,δ2,…,δn)∈{0,1}nδ=(δ1,δ2,…,δn)∈{0,1}n. Then δ is not concentrate…

118 and Counting … The Periodic Table on its 150th Anniversary.

2019

"Is there still room for more elements in the modern periodic table with its currently 118 elements? Will we need another extra series in the periodic table besides the classical s-, p-, and d-block, and the lanthanides/actinides? Will the periodic table in this region still feature periodicity? …" Read more in the Guest Editorial by C. E. Dullmann.

Hierarchies of probabilistic and team FIN-learning

2001

AbstractA FIN-learning machine M receives successive values of the function f it is learning and at some moment outputs a conjecture which should be a correct index of f. FIN learning has two extensions: (1) If M flips fair coins and learns a function with certain probability p, we have FIN〈p〉-learning. (2) When n machines simultaneously try to learn the same function f and at least k of these machines output correct indices of f, we have learning by a [k,n]FIN team. Sometimes a team or a probabilistic learner can simulate another one, if their probabilities p1,p2 (or team success ratios k1/n1,k2/n2) are close enough (Daley et al., in: Valiant, Waranth (Eds.), Proc. 5th Annual Workshop on C…