Infrared target-flare discrimination using a ZISC hardware neural network

The last generation of infrared imaging aircraft seekers and trackers uses pattern recognition algorithms to find and keep a lock on an aircraft in the presence of decoy flares. These algorithms identify targets, based on the features of the various objects in the missile’s field of view. Because modern both aircrafts and missiles fly faster than sound, speed of operation of the target identifier is critical. In this article, we propose a target recognition system that respects this time constraint. It is based on an artificial neural network implemented in hardware, as a set of parallel processors on a commercially available silicon chip called a ZISC, for zero instruction set computer. This chip would be integrated in the infrared missile seeker and tracker. We describe the characteristics of the images that the image processing module of this seeker and tracker extracts from the infrared video frames and show how to construct from these translation and rotation invariant features that can be used as input to the neural network. We determine the individual discriminating power of these features by constructing their histograms, which allows us to eliminate some as not being useful for our purpose. Finally, by testing our system on real data, we show that it has a 90% success rate in aircraft-flare identification, and a processing time that during this time, the aircrafts and missiles will have traveled only a few millimeters. Most of the images on which the neural network makes its mistakes are seen to be hard to recognize even by a human expert.     

Uniqueness of the Perfect Fusion Grid on ℤ d

Region merging methods consist of improving an initial segmentation by merging some pairs of neighboring regions. In a graph, merging two regions, separated by a set of vertices, is not straightforward. The perfect fusion graphs defined in J. Cousty et al. (J. Math. Imaging Vis. 30:(1):87–104, 2008) verify all the basic properties required by region merging algorithms as used in image segmentation. Unfortunately, the graphs which are the most frequently used in image analysis (namely, those induced by the direct and the indirect adjacency relations) are not perfect fusion graphs. The perfect fusion grid, introduced in the above mentioned reference, is an adjacency relation on ℤ ^d which can be used in image analysis, which indeed induces perfect fusion graphs and which is “between” the graphs induced by the direct and the indirect adjacencies. One of the main results of this paper is that the perfect fusion grid is the only such graph whatever the dimension d.

Ahead of time static analysis for automatic generation of debugging interfaces to the Linux kernel

The Linux kernel does not export a stable, well-defined kernel interface, complicating the development of kernel-level services, such as device drivers and file systems. While there does exist a set of functions that are exported to external modules, this set of functions frequently changes, and the functions have implicit, ill-documented preconditions. No specific debugging support is provided. We present Diagnosys, an approach to automatically constructing a debugging interface for the Linux kernel. First, a designated kernel maintainer uses Diagnosys to identify constraints on the use of the exported functions. Based on this information, developers of kernel services can then use Diagnosys to generate a debugging interface specialized to their code. When a service including this interface is tested, it records information about potential problems. This information is preserved following a kernel crash or hang. Our experiments show that the generated debugging interface provides useful log information and incurs a low performance penalty.     

Transfer of learning in virtual environments: a new challenge?

The aim of all education is to apply what we learn in different contexts and to recognise and extend this learning to new situations. Virtual learning environments can be used to build skills. Recent research in cognitive psychology and education has shown that acquisitions are linked to the initial context. This provides a challenge for virtual reality in education or training. A brief overview of transfer issues highlights five main ideas: (1) the type of transfer enables the virtual environment (VE) to be classified according to what is learned; (2) the transfer process can create conditions within the VE to facilitate transfer of learning; (3) specific features of VR must match and comply with transfer of learning; (4) transfer can be used to assess a VE’s effectiveness; and (5) future research on transfer of learning must examine the singular context of learning. This paper discusses how new perspectives in cognitive psychology influence and promote transfer of learning through the use of VEs.     

Multi-data source fusion

This paper describes a new approach of heterogeneous data source fusion. Data sources are either static or active: static data sources can be structured or semi-structured, whereas active sources are services. In order to develop data sources fusion systems in dynamic contexts, we need to study all issues raised by the matching paradigms. This challenging problem becomes crucial with the dominating role of the internet. Classical approaches of data integration, based on schemas mediation, are not suitable to the World Wide Web (WWW) environment where data is frequently modified or deleted. Therefore, we develop a loosely integrated approach that takes into consideration both conflict management and semantic rules which must be enriched in order to integrate new data sources. Moreover, we introduce an XML-based Multi-data source Fusion Language (MFL) that aims to define and retrieve conflicting data from multiple data sources. The system, which is developed according to this approach, is called MDSManager (Multi-Data Source Manager). The benefit of the proposed framework is shown through a real world application based on web data sources fusion which is dedicated to online markets indices tracking. Finally, we give an evaluation of our MFL language. The results show that our language improves significantly the XQuery language especially considering its expressiveness power and its performances.     

A new approach of data clustering using a flock of agents

This paper presents a new bio-inspired algorithm (FClust) that dynamically creates and visualizes groups of data. This algorithm uses the concepts of a flock of agents that move together in a complex manner with simple local rules. Each agent represents one data. The agents move together in a 2D environment with the aim of creating homogeneous groups of data. These groups are visualized in real time, and help the domain expert to understand the underlying structure of the data set, like for example a realistic number of classes, clusters of similar data, isolated data. We also present several extensions of this algorithm, which reduce its computational cost, and make use of a 3D display. This algorithm is then tested on artificial and real-world data, and a heuristic algorithm is used to evaluate the relevance of the obtained partitioning.     

Détermination du facteur de multiplication M pour un fonctionnement optimal des photodétecteurs à avalanche

The purpose of this paper is relative to the determination of the multiplication factor Mfor an optimum behaviour of the avalanche photodetector. Two types of avalanche photodetector s are compared: a silicon structure n ⁺ πpπp ⁺ Read diode and a GaAlAs heterostructure. Calculating the Noise Equivalent Power (nep)of the whole system, the law S_i(f) =2q I_phoM_x is used, where the parameter x is determined experimentally in both avalanche photodetectors. The exponent x (between 2 and 4) dominates in the nep expression and the ideal nep for the avalanche photodetector system is obtained when x equals 2.     

SUPPRESSION OF PERIOD DOUBLING CHATTER IN HIGH-SPEED MILLING BY SPINDLE SPEED VARIATION

Spindle speed variation is a well known technique to suppress regenerative machine tool vibrations, but it is usually considered to be effective only for low spindle speeds. In the current paper, spindle speed variation is applied to the high speed milling process, at the spindle speeds where the constant speed cutting results in period doubling chatter. The stability analysis of triangular and sinusoidal shape variations is made numerically with the semi-discretization method. It is shown that the milling process can be stabilized by increasing the amplitude of the spindle speed variation, while the frequency of the variation has no significant effect on the dynamic behaviour. The results are validated by experiments. Based on the analysis of the machined workpieces, it is shown that the surface roughness can also be decreased by the spindle speed variation technique.     

Extensions to the repetitive branch and bound algorithm for globally optimal clusterwise regression

A branch and bound strategy is proposed for solving the clusterwise regression problem, extending Brusco's repetitive branch and bound algorithm (RBBA). The resulting strategy relies upon iterative heuristic optimization, new ways of observation sequencing, and branch and bound optimization of a limited number of ending subsets. These three key features lead to significantly faster optimization of the complete set and the strategy has more general applications than only for clusterwise regression. Additionally, an efficient implementation of incremental calculations within the branch and bound search algorithm eliminates most of the redundant ones. Experiments using both real and synthetic data compare the various features of the proposed optimization algorithm and contrasts them against a benchmark mixed logical-quadratic programming formulation optimized by CPLEX. The results indicate that all components of the proposed algorithm provide significant improvements in processing times, and, when combined, generally provide the best performance, significantly outperforming CPLEX.     

Correlation between machining direction,cutter geometry and step-over distance in 3-axis milling: Application to milling by zones

Computer-Aided Manufacturing (CAM) occupies an increasingly important role in engineering with all it has to offer in terms of new possibilities and improving designer/manufacturer productivity. The present study addresses machining of free-form surfaces on a 3-axis NC machine tool. There have recently been a large number of studies devoted to planning tool paths on free-form surfaces with various strategies being adopted. These strategies are intended to increase efficiency by reducing the overall length of machining. Often, the choice of the cutter is arbitrary and the work focuses on planning. In order to boost productivity, the present work offers assistance in choosing the cutting tool, the machining direction and cutting by surface zones, adopting a milling strategy by parallel planes. To do so, a comparison is made between milling using a spherical end milling cutter and a torus end milling cutter with the same outer radius. This comparison relates to the radius of curvature of the trace left by the cutter at the point of contact between the tool and the workpiece in relation to the direction of feed motion.