Recursive decomposition tree of a Moore co-family and closure algorithm

A collection of sets on a ground set U _n (U _n ?=?{1,2,...,n}) closed under intersection and containing U _n is known as a Moore family. The set of Moore families for a fixed n is in bijection with the set of Moore co-families (union-closed families containing the empty set) denoted ${\mathbb{M}}_n$ . This paper follows the work initiated in Colomb et al. (Ann Math Artif Intell 67(2):109–122, 2013) in which we have given an inductive definition of the lattice of Moore co-families. In the present paper we use this definition to define a recursive decomposition tree of any Moore co-family and we design an original algorithm to compute the closure under union of any family. Then we compare performance of this algorithm to performance of Ganter’s algorithm and Norris’ algorithm.     

Wearable cognitive assistants in a factory setting: a critical review of a promising way of enhancing cognitive performance and well-being

Cognition, Technology & Work - Rapid technological innovations are constantly influencing the complexification and automatization of the work lines pushing human operators to use diverse...     

Comparing the Performance of Organic Solvent Nanofiltration Membranes in Non-Polar Solvents

Organic solvent nanofiltration (OSN) is gradually expanding from academic research to industrial implementation. The need for membranes with low and sharp molecular weight cutoffs that are able to operate under aggressive OSN conditions is increasing. However, the lack of comparable and uniform performance data frustrates the screening and membrane selection for processes. Here, a collaboration is presented between several academic and industrial partners analyzing the separation performance of 10 different membranes using three model process mixtures. Membrane materials range from classic polymeric and thin film composites (TFCs) to hybrid ceramic types. The model solutions were chosen to mimic cases relevant to today's industrial use: relatively low molar mass solutes (330–550 Da) in n-heptane, toluene, and anisole.     

A memetic algorithm to solve an unrelated parallel machine scheduling problem with auxiliary resources in semiconductor manufacturing

In this paper, we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant. The photolithography workshop is often a bottleneck, and improving scheduling decisions in this workshop can help to improve indicators of the whole plant. Two optimization criteria are separately considered: the weighted flow time (to minimize) and the number of products that are processed (to maximize). After stating the problem and giving some properties on the solution space, we show how these properties help us to efficiently solve the problem with the proposed memetic algorithm, which has been implemented and tested on large generated instances. Numerical experiments show that good solutions are obtained within a reasonable computational time.     

Invariant representation of facial expressions for blended expression recognition on unknown subjects

Facial expressions analysis plays an important part in emotion detection. However, having an automatic and non-intrusive system to detect blended facial expression is still a challenging problem, especially when the subject is unknown to the system. Here, we propose a method that adapts to the morphology of the subject and that is based on a new invariant representation of facial expressions. In our system, one expression is defined by its relative position to 8 other expressions. As the mode of representation is relative, we show that the resulting expression space is person-independent. The 8 expressions are synthesized for each unknown subject from plausible distortions. Recognition tasks are performed in this space with a basic algorithm. The experiments have been performed on 22 different blended expressions and on either known or unknown subjects. The recognition results on known subjects demonstrate that the representation is robust to the type of data (shape and/or texture information) and to the dimensionality of the expression space. The recognition results on 22 expressions of unknown subjects show that a dimensionality of the expression space of 4 is enough to outperform traditional methods based on active appearance models and accurately describe an expression.     

Inter-MAC Green Path Selection for Heterogeneous Networks

Gigabit home networks represent a key technology to make the Future Internet success a reality. Consumers will require networks to be simple to install, without the need of any new wire and with green consideration. To make this network ubiquitous, seamless and robust, a technology independent MAC layer will ensure its global control and provide connectivities to any number of devices the user wishes to connect to it in any room. In order to make this vision comes true, substantial progress is required in the fields of protocol design and in systems architectures. For this goal, we introduce a new convergence layer denoted inter-MAC, which provides a common infrastructure to the home network, Among the inter-MAC functionalities, we focused the interest on the path selection mechanism including the green aspect. To improve quality of service, reduce energy consumption and radiofrequency devices number, we define a new path selection protocol based on several metrics. We present some preliminary results obtained on an experimental test bed.     

Finding a dominating set on bipartite graphs

Finding a dominating set of minimum cardinality is an NP-hard graph problem, even when the graph is bipartite. In this paper we are interested in solving the problem on graphs having a large independent set. Given a graph G with an independent set of size z, we show that the problem can be solved in time O^∗(²n−z), where n is the number of vertices of G. As a consequence, our algorithm is able to solve the dominating set problem on bipartite graphs in time O^∗(²n/2). Another implication is an algorithm for general graphs whose running time is O(n^1.7088).     

Synthesis methods of array antenna excitation laws

Standard numerical optimization methods become very computational time consuming when dealing with synthesis of array antenna excitation laws, especially when number of elements exceeds a few tenths. Array antenna designer needs a fast and efficient synthesis tool, since the design phase implies several reoptimizations within the definition phase, in order to satisfy tradeoffs on antagonistic requirements : performances, size, cost,… We propose the use of an efficient, from the computational time point of view, and secured, from the convergence point of view, synthesis method illustrated by two examples. The optimized solution satisfies a sta-tionarity condition, which leads to steady solutions in frequency but also with regard to errors (manufacturing, …). Based on analytical calculus performed before any numerical resolution and together with the use of fast Fourier transform algorithms, this method leads to reduced optimization times (in the order of a minute) for arrays of some tenths up to some hundred feeds, computations being performed on a pc. Two theoretical applications are presented and for each of them a computed example is also shown; moreover possible extensions are considered.