Flexible manufacturing systems evaluation: An alternative approach

The purpose of this article is to integrate the von Neumann-Morgenstern theory of utility functions and the mean-variance approach of portfolio analysis within the computational framework of selecting a production technology to replace an existing one. A stochastic, static one-period problem is formulated, and a measure that takes into account both the capital costs of implementing the new technology and the random monetary value of its output is identified to solve the problem. The properties of this measure are discussed particularly with reference to the optimal selection decision. An example is described to illustrate the methodology.     

NODAR: mining globally distributed substructures from a single labeled graph

Data mining in structured and semi-structured data focuses on frequent data values. However, in graph data mining, the focus is on common specific topologies. Graph mining, although its ubiquity, is a difficult task since it requires subgraph isomorphism which is known to be NP-complete. In order to effectively prune the search space and thereby save computational time, a graph mining algorithm requires that the support measure of a pattern to be no greater than that of its subpatterns. This property of the support measure is referred to in the literature as the down-closure, anti-monotonicity or admissibility. Unfortunately, when mining a single labeled graph, simply counting the occurrences of a graph pattern may not have the down-closure property. For this, most existing approaches mine frequent substructures in a set of labeled graphs (called also the transactional setting) and few efforts have been devoted to mining frequent globally distributed substructures in a single labeled graph. In this paper, we propose a graph mining algorithm, called NODAR(Non-Overlapping embeDding based grAph mineR), for computing common and globally distributed substructures in a single labeled graph. NODAR adopts the Depth-First Search (DFS) strategy and is based on the SMNOES (Size of Maximum Non Overlapping Embedding Set) as support measure. The core idea of NODAR is to automatically extract frequent subpatterns; and thus without frequency computation thanks to the down-closure property of SMNOES. By adopting this strategy in the computation of frequent substructures, NODAR reduces the number of subgraph isomorphism tests needed to compute pattern frequencies. Experimental results on monograph and transactional graph databases; and comparison with well-known probabilistic and exact algorithms; prove the efficacy of NODAR.     

Discrete second‐order sliding mode control based on optimal sliding function vector for multivariable systems with input–output representation

The technique of linear matrix inequalities is a powerful method for solving optimization problems. In this paper, a sliding function vector was calculated using linear matrix inequalities approach. This technique provided optimal values of the coefficients of the sliding function vector, which led to the reduction of the reachability phase. Then, a discrete second‐order sliding mode control for multivariable systems was developed using this optimal sliding function vector. Two examples were used in order to illustrate the effectiveness of the proposed strategy. Simulation results prove good performances in terms of reduction of the reachability phase. Copyright © 2016 John Wiley & Sons, Ltd.     

A new model to implement Six Sigma in small- and medium-sized enterprises

The Six Sigma approach improves the quality of products in order to ensure customers’ satisfaction. This approach has yielded to interesting results for large enterprises. However, its implementation remains difficult for small- and medium-sized enterprises (SME). In fact, the use of the same tools is insufficient to achieve the objectives when considering financial constraints and the lack of data. The regular tools are complex for SMEs which require an adapted model to implement the approach successfully. In this paper, we propose a new model having the objective to facilitate the integration of Six Sigma in SMEs by avoiding the use of Black Belts, optimising the implementation costs and period, simplifying the Six Sigma structure and enhancing the communication between staff and managers. The model includes two imbricated loops: the first offers immediate improvement actions by estimating the capability and the stability of the process, while the second provides profound improvement actions using the fuzzy logic system and the analytic hierarchical process (AHP) method. An example illustrates the application of the proposed model in an SME.     

Automatic hand motion analysis for the sign language space management

Pattern Analysis and Applications - In this paper, we present a new approach for the sign language (SL) space management based on hand motion analysis from RGB-D data. The aim of this work is to...     

Analysis of TerraSAR-X data and their sensitivity to soil surface parameters over bare agricultural fields

The sensitivity of TerraSAR-X radar signals to surface soil parameters has been examined over agricultural fields, using HH polarization and various incidence angles (26°, 28°, 50°, 52°). The results show that the radar signal is slightly more sensitive to surface roughness at high incidence (50°–52°) than at low incidence (26°–28°). The difference observed in the X-band, between radar signals reflected by the roughest and smoothest areas, reaches a maximum of the order of 5.5 dB at 50°–52°, and 4 dB at 26°–28°. This sensitivity increases in the L-band with PALSAR/ALOS data, for which the dynamics of the return radar signal as a function of soil roughness reach 8 dB at HH38°. In the C-band, ASAR/ENVISAT data (HH and VV polarizations at an incidence angle of 23°) are characterised by a difference of about 4 dB between the signals backscattered by smooth and rough areas.Our results also show that the sensitivity of TerraSAR-X signal to surface roughness decreases in very wet and frozen soil conditions. Moreover, the difference in backscattered signal between smooth and rough fields is greater at high incidence angles. The low-to-high incidence signal ratio (Δσ° = σ_26°–28°/σ_50°–52°) decreases with surface roughness, and has a dynamic range, as a function of surface roughness, smaller than that of the backscattering coefficients at low and high incidences alone. Under very wet soil conditions (for soil moistures between 32% and 41%), the radar signal decreases by about 4 dB. This decrease appears to be independent of incidence angle, and the ratio Δσ° is found to be independent of soil moisture.     

Preparation of nanocomposite by adding of Tunisian nanoclay in unsaturated polyester matrix: mechanical and thermal study

Unsaturated Polyester (UP) resin is widely used for many applications such as reinforced plastic (FRP) and polymer composites. However, these materials suffer from their low mechanical and thermal properties. For enhancing their performance, researchers have used Tunisian montmorillonite (MMT) for manufacturing of unsaturated polyester-montmorillonite (UP-MMT) nanocomposite synthesized by dispersing the UP resin into the silicate layers of MMT. The MMT has been modified ammonium quaternary as organic cation (OMMT). Test results, supported by mechanical testing, X-ray diffraction, thermal analysis (DSC and TGA) and transmission electron microscopy, indicated that the mechanical properties and the thermal stability of unsaturated polyester with OMMT nanocomposite (UP/OMMT) are better than those of pure UP. The degradation temperature increased by 78 °C with the addition of organic modification, and SEM micrographs show good dispersion of modified montmorillonite in the polymer matrix. Tensile strength is increased by 81 % for the UP/OMMT nanocomposite.     

Theoretical study of dynamic triplet–triplet annihilation in sexithiophene crystal

We present a theoretical treatment of the triplet-pair exciton annihilation under microwave excitation in a sexithiophene crystal. This treatment gives a satisfactory fit of the observed effects and leads to the determination of the singlet annihilation rate constant λ and the effective decay rate β. The ZFS parameters D and E are also determined.     

Copolyethersulfones of 1,4:3,6-dianhydrohexitols and bisphenol A

The synthesis of biosourced copolyethersulfones by polycondensation of 1,4:3,6-dianhydrohexitol monomers and bisphenol A is reported. Structures and properties of these copolymers were investigated in each case. In the first part, the impact of the position of the two hydroxyl groups of isosorbide, isomannide, and isoidide is discussed. In the second part, we focused on improving the cost/thermal properties balance by introducing controlled proportions of bisphenol A as comonomer. The addition of bisphenol A serves two purposes. The first one is to maintain good thermal and mechanical properties of resulting copolymers. The second reason is to insure low-cost route to copolyethersulfones for a potential use in industrial applications. All the products have been fully characterized by NMR spectroscopy, MALDI-TOF spectrometry, and viscosimetry. The thermal properties were studied by differential scanning calorimetry (DSC).     

A robust ant colony optimization-based algorithm for community mining in large scale oriented social graphs

Community detection plays a key role in such important fields as biology, sociology and computer science. For example, detecting the communities in protein–protein interactions networks helps in understanding their functionalities. Most existing approaches were devoted to community mining in undirected social networks (either weighted or not). In fact, despite their ubiquity, few proposals were interested in community detection in oriented social networks. For example, in a friendship network, the influence between individuals could be asymmetric; in a networked environment, the flow of information could be unidirectional. In this paper, we propose an algorithm, called ACODIG, for community detection in oriented social networks. ACODIG uses an objective function based on measures of density and purity and incorporates the information about edge orientations in the social graph. ACODIG uses ant colony for its optimization. Simulation results on real-world as well as power law artificial benchmark networks reveal a good robustness of ACODIG and an efficiency in computing the real structure of the network.