Mechanical Behavior of Nanostructured and Microstructured Explosives

Nanostructured hexolites (40/60), (60/40), (80/20) and microstructured hexolite (60/40) powders are pressed by uniaxial compression to obtain explosive charges. This kind of composition is often used for the synthesis of detonation nanodiamonds. The morphology, density and cohesion of the resulting pellets are analyzed in the light of the different used compression parameters. This study allows optimizing the compression parameters to obtain well suited explosive charges from nanostructured explosive components. A good cohesion of the nanostructured explosive pellets could be obtained with increasing the temperature used for the compression. Another very important point is that the nanostructuring of the composites is maintained for every compression.     

Interdisciplinary safety analysis of complex socio-technological systems based on the functional resonance accident model: An application to railway trafficsupervision

This paper presents an application of functional resonance accident models (FRAM) for the safety analysis of complex socio-technological systems, i.e. systems which include not only technological, but also human and organizational components. The supervision of certain industrial domains provides a good example of such systems, because although more and more actions for piloting installations are now automatized, there always remains a decision level (at least in the management of degraded modes) involving human behavior and organizations. The field of application of the study presented here is railway traffic supervision, using modern automatic train supervision (ATS) systems. Examples taken from railway traffic supervision illustrate the principal advantage of FRAM in comparison to classical safety analysis models, i.e. their ability to take into account technical as well as human and organizational aspects within a single model, thus allowing a true multidisciplinary cooperation between specialists from the different domains involved.A FRAM analysis is used to interpret experimental results obtained from a real ATS system linked to a railway simulator that places operators (experimental subjects) in simulated situations involving incidents. The first results show a significant dispersion in performances among different operators when detecting incidents. Some subsequent work in progress aims to make these “performance conditions” more homogeneous, mainly by ergonomic modifications. It is clear that the current human-machine interface (HMI) in ATS systems (a legacy of past technologies that used LED displays) has reached its limits and needs to be improved, for example, by highlighting the most pertinent information for a given situation (and, conversely, by removing irrelevant information likely to distract operators).     

Collaborative software infrastructure for adaptive multiple model simulation

This paper presents a software infrastructure being developed to support the implementation of adaptive multiple model simulations. The paper first describes an abstraction of single and multiple model simulations into the individual operational components with a focus on the relationships and transformations that relate them. Building on that abstraction, consideration is then given to how adaptively controlled multiple model simulations can be constructed using existing simulation components interacting through functional interfaces. This includes addressing how experts would provide the infrastructure with the needed components and define the relations and transformations needed to interact with other components, and for users to define the simulations they wish to be executed. Next, a discussion of the software environment used to implement the multiple model simulation infrastructure is given. Finally, there is discussion of the implementation, using this infrastructure, of two multiscale and one multiple fidelity model simulation applications.     

Building blocks for a two-frequency laser lidar-radar: a preliminary study

A new principle of lidar-radar is theoretically and experimentally investigated. The proposed architecture is based on the use of an rf modulation of the emitted light beam and a direct detection of the backscattered intensity. Use of a radar-processing chain allows one to obtain range and Doppler measurements with the advantages of lidar spatial resolution. We calculate the maximum range of this device, taking into account different possible improvements. In particular, we show that use of a pulsed two-frequency laser and a spatially multimode optical preamplification of the backscattered light leads to calculated ranges larger than 20 km, including the possibility of both range and Doppler measurements. The building blocks of this lidar-radar are tested experimentally: The radar processing of an rf-modulated backscattered cw laser beam is demonstrated at 532 nm, illustrating the Doppler and identification capabilities of the system. In addition, signal-to-noise ratio improvement by optical pre-amplification is demonstrated at 1.06 microm. Finally, a two-frequency passively Q-switched Nd:YAG laser is developed. This laser then permits two-frequency pulses with tunable pulse duration (from 18 to 240 ns) and beat frequency (from 0 to 2.65 GHz) to be obtained.     

Toward tunable thin-film filters for wavelength division multiplexing applications

We provide a detailed analysis of the various problems connected with the development of tunable thin-film filters for wavelength-division multiplexing applications. We examine the relation between the change in layer thickness and the central wavelength shift for various configurations and point out the significance of the structure of the reflectors, the spacer thickness, and the location of the active layers. We describe and compare practical arrangements using either temperature or an electric field as the driving parameter.     

A shape analysis framework for neuromorphometry

This paper addresses in an integrated and systematic fashion the relatively overlooked but increasingly important issue of measuring and characterizing the geometrical properties of nerve cells and structures, an area often called neuromorphology. After discussing the main motivation for such an endeavour, a comprehensive mathematical framework for characterizing neural shapes, capable of expressing variations over time, is presented and used to underline the main issues in neuromorphology. Three particularly powerful and versatile families of neuromorphological approaches, including differential measures, symmetry axes/skeletons, and complexity, are presented and their respective potentials for applications in neuroscience are identified. Examples of applications of such measures are provided based on experimental investigations related to automated dendrogram extraction, mental retardation characterization, and axon growth analysis.     

Design and performance of a product code turbo encoding-decoding prototype

This paper presents the latest results on a block turbo decoder design. We propose a block turbo decoder circuit for the error protection of small data blocks such asAtm cells on anAwgn (additive white Gaussian noise) channel with a code rate close to 0.5. A prototype was developed atEnst Bretagne. It allowsBer (bit error rate) measurements down to 10^?9 and uses programmable gate arrays (Fpga Xilinx circuits). The elementary extendedBch code and the data block size can be modified to fit specifications of different applications.     

Utilisation de la corrélation pondérée dans un processus de détection d’intrusions

Generally, an intruder must perform several actions, organized in an intrusion scenario, to achieve his or her malicious objectives. Actions are modeled by their pre and post conditions, which are a set of logical predicates or negations of predicates. Pre conditions of an action correspond to conditions the system’s state must satisfy to perform the action. Post conditions correspond to the effects of executing the action on the system’s state. When an intruder begins his intrusion, we can deduce, from the alerts generated byidss (Intrusion Detection Systems), several possible scenarios, by correlating attacks, that lead to multiple intrusion objectives. However, with no further analysis, we are not able to decide which are the most plausible ones among the possible scenarios. We propose in this paper to define an order over the possible scenarios by weighting the correlation relations between successive attacks composing the scenarios. These weights reflect to what level executing some actions are necessary to execute some action B. We will see that to be satisfactory, the comparison operator between two scenarios must satisfy some properties.     

Convex Digital Polygons,Maximal Digital Straight Segments and Convergence of Discrete Geometric Estimators

Discrete geometric estimators approach geometric quantities on digitized shapes without any knowledge of the continuous shape. A classical yet difficult problem is to show that an estimator asymptotically converges toward the true geometric quantity as the resolution increases. For estimators of local geometric quantities based on Digital Straight Segment (DSS) recognition this problem is closely linked to the asymptotic growth of maximal DSS for which we show bounds both about their number and sizes on Convex Digital Polygons. These results not only give better insights about digitized curves but indicate that curvature estimators based on local DSS recognition are not likely to converge. We indeed invalidate a conjecture which was essential in the only known convergence theorem of a discrete curvature estimator. The proof involves results from arithmetic properties of digital lines, digital convexity, combinatorics and continued fractions.