A constraint programming approach to cutset problems

We consider the problem of finding a cutset in a directed graph G=(V,E)$G=(V,E)$, i.e., a set of vertices that cuts all cycles in G  . Finding a cutset of minimum cardinality is NP-hard. There exist several approximate and exact algorithms, most of them using graph reduction techniques. In this paper, we propose a constraint programming approach to cutset problems and design a global constraint for computing cutsets. This cutset constraint is a global constraint over boolean variables associated to the vertices of a given graph and states that the subgraph restricted to the vertices having their boolean variable set to true is acyclic. We propose a filtering algorithm based on graph contraction operations and inference of simple boolean constraints, that has a linear time complexity in O(|E|+|V|)$O(|E|+|V|)$. We discuss search heuristics based on graph properties provided by the cutset constraint, and show the efficiency of the cutset constraint on benchmarks of the literature for pure minimum cutset problems, and on an application to log-based reconciliation problems where the global cutset constraint is mixed with other boolean constraints.     

Combining ergonomics, culture and scenario for the design of a cooperation platform

Analyzing the way computer technologies are used is crucial for their development. Such analyses make it possible to evaluate these technologies and enhance their evolution. The present article presents some ideas drawn from the development of a cooperation platform for elementary school children (10–11 years old). On the basis of an obvious ergonomic requirement, we worked on two other dimensions: cultural aspects and the teaching scenario. The goal was to set up observation situations and analyze the conversations produced during those situations, in order to understand what using the platform meant to both the pupils and their teachers.

On Similarity Measures for Multimedia Database Applications

A multimedia database query consists of a set of fuzzy and boolean (or crisp) predicates, constants, variables, and conjunction, disjunction, and negation operators. The fuzzy predicates are evaluated based on different media criteria, such as color, shape, layout, keyword. Since media-based evaluation yields similarity values, results to such a query is defined as an ordered set. Since many multimedia applications require partial matches, query results also include tuples which do not satisfy all predicates. Hence, any fuzzy semantics which extends the boolean semantics of conjunction in a straight forward manner may not be desirable for multimedia databases. In this paper, we focus on the problem of ‘given a multimedia query which consists of multiple fuzzy and crisp predicates, how to provide the user with a meaningful overall ranking.’ More specifically, we study the problem of merging similarity values in queries with multiple fuzzy predicates. We describe the essential multimedia retrieval semantics, compare these with the known approaches, and propose a semantics which captures the retrieval requirements in multimedia databases. Received 13 August 1999 / Revised 13 May 2000 / Accepted in revised form 26 July 2000     

Software assessment using metrics: A comparison across large C++ and Java systems

This paper presents an assessment method to evaluate the quality of object oriented software systems. The assessment method is based on source code abstraction, object–oriented metrics and graphical representation. The metrics used and the underlying model representing the software are presented. The assessment method experiment is part of an industrial research effort with the Bell Canada Quality Engineering and Research Group. It helps evaluators assess the quality and risks associated with software by identifying code fragments presenting unusual characteristics. The assessment method evaluates object–oriented software systems at three levels of granularity: system level, class level and method level. One large C++ and eight Java software systems, for a total of over one million lines of code, are presented as case studies. A critical analysis of the results is presented comparing the systems and the two languages.     

Tree-decomposition based heuristics for the two-dimensional bin packing problem with conflicts

This paper deals with the two-dimensional bin packing problem with conflicts (BPC-2D). Given a finite set of rectangular items, an unlimited number of rectangular bins and a conflict graph, the goal is to find a conflict-free packing of the items minimizing the number of bins used. In this paper, we propose a new framework based on a tree-decomposition for solving this problem. It proceeds by decomposing a BPC-2D instance into subproblems to be solved independently. Applying this decomposition method is not straightforward, since merging partial solutions is hard. Several heuristic strategies are proposed to make an effective use of the decomposition. Computational experiments show the practical effectiveness of our approach.     

Accelerated multiplicative updates and hierarchical ALS algorithms for nonnegative matrix factorization

Nonnegative matrix factorization (NMF) is a data analysis technique used in a great variety of applications such as text mining, image processing, hyperspectral data analysis, computational biology, and clustering. In this letter, we consider two well-known algorithms designed to solve NMF problems: the multiplicative updates of Lee and Seung and the hierarchical alternating least squares of Cichocki et al. We propose a simple way to significantly accelerate these schemes, based on a careful analysis of the computational cost needed at each iteration, while preserving their convergence properties. This acceleration technique can also be applied to other algorithms, which we illustrate on the projected gradient method of Lin. The efficiency of the accelerated algorithms is empirically demonstrated on image and text data sets and compares favorably with a state-of-the-art alternating nonnegative least squares algorithm.     

Estimating the Natural Illumination Conditions from a Single Outdoor Image

Given a single outdoor image, we present a method for estimating the likely illumination conditions of the scene. In particular, we compute the probability distribution over the sun position and visibility. The method relies on a combination of weak cues that can be extracted from different portions of the image: the sky, the vertical surfaces, the ground, and the convex objects in the image. While no single cue can reliably estimate illumination by itself, each one can reinforce the others to yield a more robust estimate. This is combined with a data-driven prior computed over a dataset of 6 million photos. We present quantitative results on a webcam dataset with annotated sun positions, as well as quantitative and qualitative results on consumer-grade photographs downloaded from Internet. Based on the estimated illumination, we show how to realistically insert synthetic 3-D objects into the scene, and how to transfer appearance across images while keeping the illumination consistent.     

Cognitive conflict in human-automation interactions: a psychophysiological study

The review of literature in sociology and distributed artificial intelligence reveals that the occurrence of conflict is a remarkable precursor to the disruption of multi-agent systems. The study of this concept could be applied to human factors concerns, as man-system conflict appears to provoke perseveration behavior and to degrade attentional abilities with a trend to excessive focus. Once entangled in such conflicts, the human operator will do anything to succeed in his current goal even if it jeopardizes the mission. In order to confirm these findings, an experimental setup, composed of a real unmanned ground vehicle, a ground station is developed. A scenario involving an authority conflict between the participants and the robot is proposed. Analysis of the effects of the conflict on the participants' cognition and arousal is assessed through heart-rate measurement (reflecting stress level) and eye-tracking techniques (index of attentional focus). Our results clearly show that the occurrence of the conflict leads to perseveration behavior and can induce higher heart rate as well as excessive attentional focus. These results are discussed in terms of task commitment issues and increased arousal. Moreover, our results suggest that individual differences may predict susceptibility to perseveration behavior.     

Minimum variance prediction and control for adaptive optics

Adaptive Optics (AO) systems enable to compensate the adverse effects of atmospheric turbulence on ground-based telescopes’ images in real time, using a deformable mirror (DM) inserted in the telescope’s optical path, and measurements provided by a wavefront sensor (WFS). This paper revisits minimum-variance (MV) control design for astronomical AO systems in a state-space framework. It presents a survey of the modeling and control issues arising in this multi-variable disturbance rejection problem. In a linear time-invariant framework, and under some mild assumptions, the optimal solution to MV control for AO systems is shown to be a discrete-time LQG controller. This result holds for a DM with instantaneous response, and for a fairly general class of DM’s dynamics. The state-space approach is extended to Wide-field Adaptive Optics (WfAO) configurations involving several DMs and/or WFSs. Integral-action control used in existing AO systems is compared with the LQG controller. Experimental WfAO results obtained on a laboratory test bench are presented, showing significant improvement in performance. Finally, open issues and perspectives of applicative and/or theoretical interests are discussed.