Mg和V2O5共溅射制备+4价钒的氧化物薄膜

在常温、高真空条件下,采用高纯金属镁靶和V₂O₅靶进行共溅射,利用镁原子的还原性,将+5价的钒还原为+4价,在硅衬底上制备钒的氧化物薄膜。当Mg和V的原子比为1:2时,XPS测试表明薄膜中有V4+和V2+存在。X射线衍射结果显示,制备的薄膜主要成分是MgV₂O₅,且结晶状况良好。温度-电阻率测试结果显示,薄膜在20℃附近有相变行为,电阻温度系数高达－8.6%/K,回线弛豫温度约为0.3℃,负温度系数热敏电阻材料常数高达6700。这一发现为制备非制冷焦平面探测用的热敏薄膜材料提供了新的思路。     

Characterization of Liquid Resin Infusion (LRI) filling by fringe pattern projection and in situ thermocouples

Prepregs are not alone suited to the manufacturing of new types of aircraft structural parts that tend to be thicker and have more complex shapes. Direct processes called Liquid Composites Moulding (LCM), like Resin Transfer Moulding (RTM) or Resin Infusion Process (LRI: Liquid Resin Infusion, RFI: Resin Film Infusion) are now available. Particular attention is paid here to LRI process that looks very promising. In order to optimize both the design and manufacturing parameters in LRI processes, a general model to analyze the isothermal fluid flow through highly compressible porous media such as fibrous preforms has been recently proposed [1], [2], [3]. To validate the model and to improve the knowledge of the LRI process, an experimental approach is proposed. Two different measurement techniques, micro-thermocouple sensors and fringe projection technique, have been used to characterize the process. It appears that results derived from both techniques are in agreement and support the assumption that the resin flow occurs mainly transversely to the preform plane.     

Polynomial algorithms for subisomorphism of nD open combinatorial maps

Combinatorial maps describe the subdivision of objects in cells, and incidence and adjacency relations between cells, and they are widely used to model 2D and 3D images. However, there is no algorithm for comparing combinatorial maps, which is an important issue for image processing and analysis. In this paper, we address two basic comparison problems, i.e., map isomorphism, which involves deciding if two maps are equivalent, and submap isomorphism, which involves deciding if a copy of a pattern map may be found in a target map. We formally define these two problems for nD open combinatorial maps, we give polynomial time algorithms for solving them, and we illustrate their interest and feasibility for searching patterns in 2D and 3D images, as any child would aim to do when he searches Wally in Martin Handford’s books.     

Sensor fault detection and isolation filter for polytopic LPV systems: A winding machine application

In this paper, a fault diagnosis method is developed for a particular class of nonlinear systems described by a polytopic linear parameter varying (LPV) formulation. The main contribution consists in the synthesis of an accurate fault detection and isolation (FDI) filter and also a sensor fault magnitude estimation with a quality factor. This quality factor of the filter underlines if the fault estimation can be used or not. Stability conditions of the polytopic LPV filter are studied by ensuring poly-quadratic stability with Linear Matrix Inequality (LMI) representation. The effectiveness of this global FDI scheme through LPV modelization, filter design and stability analysis, is illustrated on a real winding machine under multiple sensor faults.     

Fair multi-agent task allocation for large datasets analysis

MapReduce is a design pattern for processing large datasets distributed on a cluster. Its performances are linked to the data structure and the runtime environment. Indeed, data skew can yield an unfair task allocation, but even when the initial allocation produced by the partition function is well balanced, an unfair allocation can occur during the reduce phase due to the heterogeneous performance of nodes. For these reasons, we propose an adaptive multi-agent system. In our approach, the reducer agents interact during the job and the task reallocation is based on negotiation in order to decrease the workload of the most loaded reducer and so the runtime. In this paper, we propose and evaluate two negotiation strategies. Finally, we experiment our multi-agent system with real-world datasets over heterogeneous runtime environment.     

Multivariate analysis of human behavior data using fuzzy windowing: Example with driver–car–environment system

In most human component system studies performed in simulators, several factors (or independent variables) (at least two, i.e., individual and time) and many variables (or dependent variables) are present. Large and complex databases have to be analyzed. Instead of using rather automatic procedures, this article suggest that, for a very first analysis at least, the human being must be present and he/she must choose a method being adapted to the data, which is different to run a method supposing that the data fit such or such model. This article suggests starting the analysis while keeping both the multifactorial (MF) and multivariate (MV) aspects. To achieve this aim, with the possibility to show nonlinear relationships, a MFMV exploration of the experimental database is performed using the pair (fuzzy space windowing, Multiple Correspondence Analysis). Then may come an inference analysis. This long (due to multiple large graphical views) but rich procedure is illustrated and discussed using a car driving study example.     

EDGly: detection of influential nodes using game theory

Identifying those nodes that play a critical role within a network is of great importance. Many applications such as gossip spreading, disease spreading, news dispersion, identifying prominent individuals in a social network, etc. may take advantage of this knowledge in a complex network. The basic concept is generally to identify the nodes with the highest criticality in a network. As a result, the centrality principle has been studied extensively and in great detail, focusing on creating a consistent and accurate location of nodes within a network in terms of their importance. Both single centrality measures and group centrality measures, although, have their certain drawbacks. Other solutions to this problem include the game-theoretic Shapley Value (SV) calculations measuring the effect of a collection of nodes in complex networks via dynamic network data propagation process. Our novel proposed algorithm aims to find the most significant communities in a graph with community structure and then employs the SV-based games to find the most influential node from each community. A Susceptible-Infected-Recovered (SIR) model has been employed to distinctly determine each powerful node's capacity to spread. The results of the SIR simulation have also been used to show the contrast between the spreading capacity of nodes found through our proposed algorithm and that of nodes found using SV-algorithm and centrality measures alone.

     

Quantum transport in graphene nanonetworks

The quantum transport properties of graphene nanoribbon networks are investigated using first-principles calculations based on density functional theory. Focusing on systems that can be experimentally realized with existing techniques, both in-plane conductance in interconnected graphene nanoribbons and tunneling conductance in out-of-plane nanoribbon intersections were studied. The characteristics of the ab initio electronic transport through in-plane nanoribbon cross-points is found to be in agreement with results obtained with semiempirical approaches. Both simulations confirm the possibility of designing graphene nanoribbon-based networks capable of guiding electrons along desired and predetermined paths. In addition, some of these intersections exhibit different transmission probability for spin up and spin down electrons, suggesting the possible applications of such networks as spin filters. Furthermore, the electron transport properties of out-of-plane nanoribbon cross-points of realistic sizes are described using a combination of first-principles and tight-binding approaches. The stacking angle between individual sheets is found to play a central role in dictating the electronic transmission probability within the networks.     

First lessons of the Toulouse ammonium nitrate disaster, 21st September 2001, AZF plant, France

A terrible explosion of ammonium nitrate, killing 30 people, occurred on 21st September 2001, in Toulouse, in AZF plant belonging to Grande Paroisse Company, TotalFinaElf Group. The manufactured chemicals in the plant were mainly ammonium nitrate, ammonium nitrate-based fertilisers and other chemicals including chlorinated compounds. The origins of the accident haven't found yet an agreement among investigators (company, justice). The aim of this paper is to provide abroad an overview of some lessons learnt on that accident, from many perspectives, following the national debates and parliamentary enquiry as well as the various technical accident investigations.