Université Toulouse-I-Capitole

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Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras. Imaging spectrometers are therefore often referred to as hyperspectral cameras (HSCs). Higher spectral resolution enables material identification via spectroscopic analysis, which facilitates countless applications that require identifying materials in scenarios unsuitable for classical spectroscopic analysis. Due to low spatial resolution of HSCs, microscopic material mixing, and multiple scattering, spectra measured by HSCs are mixtures of spectra of materials in a scene. Thus, accurate estimation requires unmixing. Pixels are assumed to be mixtures of a few materials, called endmembers. Unmixing involves estimating all or some of: the number of endmembers, their spectral signatures, and their abundances at each pixel. Unmixing is a challenging, ill-posed inverse problem because of model inaccuracies, observation noise, environmental conditions, endmember variability, and data set size. Researchers have devised and investigated many models searching for robust, stable, tractable, and accurate unmixing algorithms. This paper presents an overview of unmixing methods from the time of Keshava and Mustard's unmixing tutorial to the present. Mixing models are first discussed. Signal-subspace, geometrical, statistical, sparsity-based, and spatial-contextual unmixing algorithms are described. Mathematical problems and potential solutions are described. Algorithm characteristics are illustrated experimentally.

A fuzzy number is a fuzzy subset of the real line whose highest membership values are clustered around a given real number called the mean value ; the membership function is monotonia on both sides of this mean value. In this paper, the usual algebraic operations on real numbers are extended to fuzzy numbers by the use of a fuzzification principle. The practical use of fuzzified operations is shown to be easy, requiring no more computation than when dealing with error intervals in classic tolerance analysis. The field of applications of this approach seems to be large, since it allows many known algorithms to be fitted to fuzzy data.

BACKGROUND: Public health recommendations and governmental measures during the COVID-19 pandemic have resulted in numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on health behaviours and lifestyles at home is undefined. Therefore, an international online survey was launched in April 2020, in seven languages, to elucidate the behavioural and lifestyle consequences of COVID-19 restrictions. This report presents the results from the first thousand responders on physical activity (PA) and nutrition behaviours. METHODS: Following a structured review of the literature, the "Effects of home Confinement on multiple Lifestyle Behaviours during the COVID-19 outbreak (ECLB-COVID19)" Electronic survey was designed by a steering group of multidisciplinary scientists and academics. The survey was uploaded and shared on the Google online survey platform. Thirty-five research organisations from Europe, North-Africa, Western Asia and the Americas promoted the survey in English, German, French, Arabic, Spanish, Portuguese and Slovenian languages. Questions were presented in a differential format, with questions related to responses "before" and "during" confinement conditions. RESULTS: 1047 replies (54% women) from Asia (36%), Africa (40%), Europe (21%) and other (3%) were included in the analysis. The COVID-19 home confinement had a negative effect on all PA intensity levels (vigorous, moderate, walking and overall). Additionally, daily sitting time increased from 5 to 8 h per day. Food consumption and meal patterns (the type of food, eating out of control, snacks between meals, number of main meals) were more unhealthy during confinement, with only alcohol binge drinking decreasing significantly. CONCLUSION: While isolation is a necessary measure to protect public health, results indicate that it alters physical activity and eating behaviours in a health compromising direction. A more detailed analysis of survey data will allow for a segregation of these responses in different age groups, countries and other subgroups, which will help develop interventions to mitigate the negative lifestyle behaviours that have manifested during the COVID-19 confinement.

We introduce DropConnect, a generalization of Dropout (Hinton et al., 2012), for regular-izing large fully-connected layers within neu-ral networks. When training with Dropout, a randomly selected subset of activations are set to zero within each layer. DropCon-nect instead sets a randomly selected sub-set of weights within the network to zero. Each unit thus receives input from a ran-dom subset of units in the previous layer. We derive a bound on the generalization per-formance of both Dropout and DropCon-nect. We then evaluate DropConnect on a range of datasets, comparing to Dropout, and show state-of-the-art results on several image recognition benchmarks by aggregating mul-tiple DropConnect-trained models. 1.

The paper takes stock of the advances and directions for research on the incomplete contracting front. It first illustrates some of the main ideas of the incomplete contract literature through an example. It then offers methodological insights on the standard approach to modeling incomplete contracts; in particular it discusses a tension between two assumptions made in the literature, namely rationality and the existence of transaction costs. Last, it argues that, contrary to what is commonly argued, the complete contract methodology need not be unable to account for standard institutions such as authority and ownership; and it concludes with a discussion of the research agenda.

Purpose The purpose of this paper is to discuss the advantage of a combinatory methodology presented in this study. The paper suggests that the comparison with results of previously developed methods is in high agreement. Design/methodology/approach This paper introduces a combined compromise decision-making algorithm with the aid of some aggregation strategies. The authors have considered a distance measure, which originates from grey relational coefficient and targets to enhance the flexibility of the results. Hence, the weight of the alternatives is placed in the decision-making process with three equations. In the final stage, an aggregated multiplication rule is employed to release the ranking of the alternatives and end the decision process. Findings The authors described a real case of choosing logistics and transportation companies in France from a supply chain project. Some comparisons such as sensitivity analysis approach and comparing to other studies and methods provided to validate the performance of the proposed algorithm. Originality/value The algorithm has a unique structure among MCDM methods which is presented for the first time in this paper.

Laffont and Tirole (LT hereinafter) have written a much-needed book that brings together the theory and practice of telecommunications regulation, especially interconnection pricing, in an era of increasing competition. It is almost a clich6 to observe that the work of these authors, who have produced so much prominent research in this area, is insightful, comprehensive, and elegant; yet such descriptions are needed to aptly characterize this book. The main design feature of the book is a separation of the text from technical boxes that present formal models. This is a laudable plan and it succeeds in making much of the book accessible to those who are familiar with the issues but are not professional economists. It is still fairly technical reading and in places cannot be well understood without venturing into the technical boxes. Certainly only professional economists with some prior understanding of the models can fully digest the material. But for professionals and nonprofessionals alike the effort of reading is rewarded as the text lays bare basic economic lessons that are often misunderstood or lost in the contentiousness and complex details of regulatory practice. Even to those who are very familiar with the material, the book is worth reading simply for the enjoyment of witnessing the depth and breadth of LT's mastery of the material, and their customary eloquence in putting it all together. This book should be read by every consultant, industry participant, and academician with an interest in telecommunications regulation; by any economist who wants to become acquainted with the revolution occurring in the industry; and by the technical staffs of national regulatory agencies. It may be too technical for generalists and state-level regulatory commissions, but it should at least be skimmed by everyone involved in regulating the industry.

There has been some uncertainty concerning the conditions under which a manufacturing system may be termed 'flexible'. To clarify this confusion eight types of flexibilities are defined and described.

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The theory of evidence proposed by G. Shafer is gaining more and more acceptance in the field of artificial intelligence, for the purpose of managing uncertainty in knowledge bases. One of the crucial problems is combining uncertain pieces of evidence stemming from several sources, whether rules or physical sensors. This paper examines the framework of belief functions in terms of expressive power for knowledge representation. It is recalled that probability theory and Zadeh's theory of possibility are mathematically encompassed by the theory of evidence, as far as the evaluation of belief is concerned. Empirical and axiomatic foundations of belief functions and possibility measures are investigated. Then the general problem of combining uncertain evidence is addressed, with focus on Dempster rule of combination. It is pointed out that this rule is not very well adapted to the pooling of conflicting information. Alternative rules are proposed to cope with this problem and deal with specific cases such as nonreliable sources, nonexhaustive sources, inconsistent sources, and dependent sources. It is also indicated that combination rules issued from fuzzy set and possibility theory look more flexible than Dempster rule because many variants exist, and their numerical stability seems to be better.

International audience

Journal Article THE INTERNAL ORGANIZATION OF GOVERNMENT Get access JEAN TIROLE JEAN TIROLE IDEI, Université des Sciences Sociales de Toulouse, Place Anatole FranceF-31042 Toulouse cedex, France; MIT; and CERAS Search for other works by this author on: Oxford Academic Google Scholar Oxford Economic Papers, Volume 46, Issue 1, January 1994, Pages 1–29, https://doi.org/10.1093/oxfordjournals.oep.a042114 Published: 01 January 1994

Summary This article aims to consolidate the psychological microfoundations of corporate social responsibility (CSR) by taking stock and evaluating the recent surge of person‐focused CSR research. With a systematic review, the authors identify, synthesize, and organize three streams of micro‐CSR studies—focused on (i) individual drivers of CSR engagement, (ii) individual processes of CSR evaluations, and (iii) individual reactions to CSR initiatives—into a coherent behavioral framework. This review highlights significant gaps, methodological issues, and imbalances in the treatment of the three components in prior micro‐CSR research. It uncovers the need to conceptualize how multiple drivers of CSR interact and how the plurality of mechanisms and boundary conditions that can explain individual reactions to CSR might be integrated theoretically. By organizing micro‐CSR studies into a coherent framework, this review also reveals the lack of connections within and between substreams of micro‐CSR research; to tackle them, this article proposes an agenda for further research, focused on six key challenges. Copyright © 2017 John Wiley & Sons, Ltd.

This paper presents a variational-based approach for fusing hyperspectral and multispectral images. The fusion problem is formulated as an inverse problem whose solution is the target image assumed to live in a lower dimensional subspace. A sparse regularization term is carefully designed, relying on a decomposition of the scene on a set of dictionaries. The dictionary atoms and the supports of the corresponding active coding coefficients are learned from the observed images. Then, conditionally on these dictionaries and supports, the fusion problem is solved via alternating optimization with respect to the target image (using the alternating direction method of multipliers) and the coding coefficients. Simulation results demonstrate the efficiency of the proposed algorithm when compared with state-of-the-art fusion methods.

International audience

Recent research on the microfoundations of corporate social responsibility (CSR) has highlighted the need for improved measures to evaluate how stakeholders perceive and subsequently react to CSR initiatives. Drawing on stakeholder theory and data from five samples of employees (N = 3,772), the authors develop and validate a new measure of corporate stakeholder responsibility (CStR), which refers to an organization’s context-specific actions and policies designed to enhance the welfare of various stakeholder groups by accounting for the triple bottom line of economic, social, and environmental performance; it is conceptualized as a superordinate, multidimensional construct. Results from exploratory factor analyses, first- and second-order confirmatory factor analyses, and structural equation modeling provide strong evidence of the convergent, discriminant, incremental, and criterion-related validities of the proposed CStR scale. Two-wave longitudinal studies further extend prior theory by demonstrating that the higher-order CStR construct relates positively and directly to organizational pride and perceived organizational support, as well as positively and indirectly to organizational identification, job satisfaction, and affective commitment, beyond the contribution of overall organizational justice, ethical climate, and prior measures of perceived CSR.

= 1,635 Mechanical Turkers) were presented with a series of headlines. For each, they were first asked to give an initial, intuitive response under time pressure and concurrent working memory load. They were then given an opportunity to rethink their response with no constraints, thereby permitting more deliberation. We also compared these responses to a (deliberative) 1-response baseline condition where participants made a single choice with no constraints. Consistent with the classical account, we found that deliberation corrected intuitive mistakes: Participants believed false headlines (but not true headlines) more in initial responses than in either final responses or the unconstrained 1-response baseline. In contrast-and inconsistent with the Motivated System 2 Reasoning account-we found that political polarization was equivalent across responses. Our data suggest that, in the context of fake news, deliberation facilitates accurate belief formation and not partisan bias. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A discrete-event system is a system whose behavior can be described by means of a set of time-consuming activities, performed according to a prescribed ordering. Events correspond to starting or ending some activity. An analogy between linear systems and a class of discrete-event systems is developed. Following this analogy, such discrete-event systems can be viewed as linear, in the sense of an appropriate algebra. The periodical behavior of closed discrete-event systems, i.e., involving a set of repeatedly performed activities, can be totally characterized by solving an eigenvalue and eigenvector equation in this algebra. This problem is numerically solved by an efficient algorithm which basically consists of finding the shortest paths from one node to all other nodes in a graph. The potentiality of this approach for the performance evaluation of flexible manufacturing systems is emphasized; the case of a flowshop-like production process is analyzed in detail.

In this paper we study the evolution of the labor share in the OECD. We show it is essentially related to the capital-output ratio; that this relationship is shifted by factors like the price of imported materials or capital-augmenting technological progress; and that discrepancies between the marginal product of labor and the real wage ---due to, e.g., labor adjustment costs or union wage bargaining--- cause departures from it. We also provide empirical evidence on the determinants of the labor share with panel data on 13 industries and 12 countries for 1972-93.