Search results for "value"
showing 10 items of 5321 documents
Borrowing and appropriation of works of art: an exploratory approach
2017
Borrowing of works of art is a consumption experience cannot be limited to its aesthetic dimension. Based on 18 semi-structured interviews with individuals and 28 «memories of works of art» published on the artothèque l’inventaire, this research aims to describe and understand experience with artwork to understand the various hybrid forms of possession of the object and the modalities of the process of appropriation. Given the results, trois figures of consumption seem to appear when it comes to borrow a work of art: the voluntary simplicity, the radical materialism and the ordinary materialism.
Improving the thermal performance of the transparent building envelope: finite element analysis of possible techniques to reduce the U-value of the g…
2012
U-value of glazed elements is often a critical issue because these components, due to their small thickness and to the poor resistance of the glass and frame materials, cause very relevant heat fluxes. This paper presents an investigation on the thermal properties of a particular glazed component: the glassblock. Generally standard glassblocks have high U- values in comparison to the maximum values allowed by energy efficiency standards for glazed surfaces. This paper reports a summary of possible solutions that could improve the performances of the glassblock. A set of new configurations of the glassblock has been defined by schematic models and their overall thermal resistance has been as…
Combination of CDF and D0 measurements of the W boson helicity in top quark decays
2012
Aaltonen, T. et al.
Governance, board diversity and firm value
2010
This paper investigates the relations between firm on board diversity and firm value on a sample of Italian Publicly listed firm. Specifically, we look at the composition of boards (as defined board size, Majority of independent directors, leadership structure) and at his diversity (defined as the percentage of women and directors of other, average age of the board, other board’s member appointment). We provide evidence that board diversity positively affect performance.
Fast Graph Filters for Decentralized Subspace Projection
2020
A number of inference problems with sensor networks involve projecting a measured signal onto a given subspace. In existing decentralized approaches, sensors communicate with their local neighbors to obtain a sequence of iterates that asymptotically converges to the desired projection. In contrast, the present paper develops methods that produce these projections in a finite and approximately minimal number of iterations. Building upon tools from graph signal processing, the problem is cast as the design of a graph filter which, in turn, is reduced to the design of a suitable graph shift operator. Exploiting the eigenstructure of the projection and shift matrices leads to an objective whose…
Bayesian inference for the extremal dependence
2016
A simple approach for modeling multivariate extremes is to consider the vector of component-wise maxima and their max-stable distributions. The extremal dependence can be inferred by estimating the angular measure or, alternatively, the Pickands dependence function. We propose a nonparametric Bayesian model that allows, in the bivariate case, the simultaneous estimation of both functional representations through the use of polynomials in the Bernstein form. The constraints required to provide a valid extremal dependence are addressed in a straightforward manner, by placing a prior on the coefficients of the Bernstein polynomials which gives probability one to the set of valid functions. The…
Bayesian Checking of the Second Levels of Hierarchical Models
2007
Hierarchical models are increasingly used in many applications. Along with this increased use comes a desire to investigate whether the model is compatible with the observed data. Bayesian methods are well suited to eliminate the many (nuisance) parameters in these complicated models; in this paper we investigate Bayesian methods for model checking. Since we contemplate model checking as a preliminary, exploratory analysis, we concentrate on objective Bayesian methods in which careful specification of an informative prior distribution is avoided. Numerous examples are given and different proposals are investigated and critically compared.
Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially o…
2014
In the near future, millions of load curves measuring the electricity consumption of French households in small time grids (probably half hours) will be available. All these collected load curves represent a huge amount of information which could be exploited using survey sampling techniques. In particular, the total consumption of a specific cus- tomer group (for example all the customers of an electricity supplier) could be estimated using unequal probability random sampling methods. Unfortunately, data collection may undergo technical problems resulting in missing values. In this paper we study a new estimation method for the mean curve in the presence of missing values which consists in…
Asymptotic and bootstrap tests for subspace dimension
2022
Most linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices, see e.g. Ye and Weiss (2003), Tyler et al. (2009), Bura and Yang (2011), Liski et al. (2014) and Luo and Li (2016). The eigen-decomposition of one scatter matrix with respect to another is then often used to determine the dimension of the signal subspace and to separate signal and noise parts of the data. Three popular dimension reduction methods, namely principal component analysis (PCA), fourth order blind identification (FOBI) and sliced inverse regression (SIR) are considered in detail and the first two moments of subsets of the eigenvalues are used to test…
A Deployment Model to Extend Ethically Aligned AI Implementation Method ECCOLA
2021
There is a struggle in Artificial intelligence (AI) ethics to gain ground in actionable methods and models to be utilized by practitioners while developing and implementing ethically sound AI systems. AI ethics is a vague concept without a consensus of definition or theoretical grounding and bearing little connection to practice. Practice involving primarily technical tasks like software development is not aptly equipped to process and decide upon ethical considerations. Efforts to create tools and guidelines to help people working with AI development have been concentrating almost solely on the technical aspects of AI. A few exceptions do apply, such as the ECCOIA method for creating ethic…