Hyperparameter estimation for satellite image restoration using a MCMC maximum-likelihood method

The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ? function, involving two hyperparameters. Our goal is to estimate the optimal parameters in order to automatically reconstruct images. We propose to use the maximum-likelihood estimator (MLE), applied to the observed image. We need sampling from prior and posterior distributions. Since the convolution prevents use of standard samplers, we have developed a modified Geman-Yang algorithm, using an auxiliary variable and a cosine transform. We present a Markov chain Monte Carlo maximum-likelihood (MCMCML) technique which is able to simultaneously achieve the estimation and the reconstruction.     

A framework for dynamic implicit curve approximation by an irregular discrete approach

The approximation of implicit planar curves by line segments is a very classical problem. Many algorithms use interval analysis to approximate this curve, and to handle the topology of the final reconstruction. In this article, we use discrete geometry tools to build an original geometrical and topological representation of the implicit curve. The polygonal approximation contains few segments, and the Reeb graph permits to sum up efficiently the shape and the topology of the curve. Furthermore, we propose two algorithms to process local cells refinement and local cells grouping schemes. We illustrate these schemes with a global system that efficiently handles manual or automatic fast updates on the global reconstruction, by considering topological or geometrical constraints. We also compare the speed and the quality of our approach with two classical methods.     

Enacting language games: the development of a sense of ‘we‐ness’ in online forums

A sense of ‘we‐ness’– enacted through collective identity and culture – is both crucial in online, remote contexts, and particularly difficult to develop in such settings. Using Wittgenstein's concept of language games, we examine how participants of two online forums construct collective identity and culture through their discursive practices. We suggest a strong performative interpretation of the notion of language games, i.e. members of a community produce a sense of we‐ness through their participation in the language game while also defining their expected behaviours and actions. We illustrate how the notion of language games offers an approach for researching and analysing the emergence of collective identity and culture in online forums.     

Automatic computation of pebble roundness using digital imagery and discrete geometry

The shape of sedimentary particles is an important property, from which geographical hypotheses related to abrasion, distance of transport, river behavior, etc. can be formulated. In this paper, we use digital image analysis, especially discrete geometry, to automatically compute some shape parameters such as roundness, i.e. a measure of how much the corners and edges of a particle have been worn away.In contrast to previous work in which traditional digital images analysis techniques, such as Fourier transform, are used, we opted for a discrete geometry approach that allowed us to implement Wadell's original index, which is known to be more accurate, but more time consuming to implement in the field.Our implementation of Wadell's original index is highly correlated (92%) with the roundness classes of Krumbein's chart, used as a ground-truth. In addition, we show that other geometrical parameters, which are easier to compute, can be used to provide good approximations of roundness.We also used our shape parameters to study a set of pebbles digital images taken from the Progo basin river network (Indonesia). The results we obtained are in agreement with previous work and open new possibilities for geomorphologists thanks to automatic computation.     

The other side of ranking schemes: generating weights for specified outcomes

This paper treats the problem of how to determine weights in a ranking, which will cause a selected entity to attain the highest possible position. We establish that there are two types of entities in a ranking scheme: those which can be ranked as number one and those which cannot. These two types of entities can be identified using the “ranking hull” of the data; a polyhedral set that envelops the data. Only entities with data points on the boundary of this hull can attain the number one position. There are no weights that will make an entity whose data point is in the interior of the hull to ever attain the number one position. We deal with these two types of entities separately. In the first case, we propose an approach for finding a set of weights that, under special conditions, will result in a selected entity achieving the top of the ranking without ties and without ignoring any of the attributes. For the second category of entities, we devise a procedure to guarantee that these entities will attain their highest possible position in the ranking. The first case will require using interior point methods to solve a linear program (LP). The second case involves a binary mixed integer formulation. These two mathematical programs were tested on data from a well‐known university ranking.     

FAST: acceleration from theory to practice

Fast acceleration of symbolic transition systems (Fast) is a tool for the analysis of systems manipulating unbounded integer variables. We check safety properties by computing the reachability set of the system under study. Even if this reachability set is not necessarily recursive, we use innovative techniques, namely symbolic representation, acceleration and circuit selection, to increase convergence. Fast has proved to perform very well on case studies. This paper describes the tool, from the underlying theory to the architecture choices. Finally, Fast capabilities are compared with those of other tools. A range of case studies from the literature is investigated. This paper is mainly based on results presented at CAV 2003, TACAS 2004 and ATVA 2005.     

Improving security and performance of an Ad Hoc network through a multipath routing strategy

Privacy and security solutions require today the protection of personal information so that it may not be disclosed to unauthorized participant for illegal purposes. It is a challenge to address these issues in networks with strong constraints such as Ad Hoc network. The security increase is often obtained with a quality of service (QoS) decrease. We propose in this paper a solution that provides at the anonymity, security to Ad Hoc network with a limited impact on QoS. This method could be efficient against some viral attacks. We also give some security proofs of our solution for Ad Hoc networks. The work of Hervé Aiache and Cédric Tavernier was supported by DISCREET, IST project no. 027679, funded in part by the European Commission’s Information Society Technology 6th Framework Programme.     

Measuring Affective Clarity Indirectly: Individual Differences in Response Latencies of State.

This research investigated a new method to measure momentary affective clarity indirectly, which is based on latencies of responses to state affect items. Three studies revealed that this indirect measure of momentary clarity demonstrated high reliability and stability as well as convergent and predictive validity. The indirect measure was associated with dispositional clarity when the concept of clarity was activated before measuring response latencies (Studies 1 and 2) and was related to self-reports of momentary clarity (Study 3). Furthermore, Study 3 demonstrated that indirectly measured clarity decreased after an affectively complex film. Indirectly, but not directly, measured momentary clarity predicted a more positive affective state at the end of the study. This effect was mediated by affect regulation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)