Failure detection and consensus in the crash-recovery model

Summary. We study the problems of failure detection and consensus in asynchronous systems in which processes may crash and recover, and links may lose messages. We first propose new failure detectors that are particularly suitable to the crash-recovery model. We next determine under what conditions stable storage is necessary to solve consensus in this model. Using the new failure detectors, we give two consensus algorithms that match these conditions: one requires stable storage and the other does not. Both algorithms tolerate link failures and are particularly efficient in the runs that are most likely in practice – those with no failures or failure detector mistakes. In such runs, consensus is achieved within time and with 4 n messages, where is the maximum message delay and n is the number of processes in the system. Received: May 1998 / Accepted: November 1999     

An adaptive learning approach for 3-D surface reconstruction from point clouds.

In this paper, we propose a multiresolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3-D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen's self-organizing map (SOM). Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multiresolution, iterative scheme. Reconstruction was experimented on with several point sets, including different shapes and sizes. Results show generated meshes very close to object final shapes. We include measures of performance and discuss robustness.     

Efficient matching and indexing of graph models in content-basedretrieval

In retrieval from image databases, evaluation of similarity, based both on the appearance of spatial entities and on their mutual relationships, depends on content representation based on attributed relational graphs. This kind of modeling entails complex matching and indexing, which presently prevents its usage within comprehensive applications. In this paper, we provide a graph-theoretical formulation for the problem of retrieval based on the joint similarity of individual entities and of their mutual relationships and we expound its implications on indexing and matching. In particular, we propose the usage of metric indexing to organize large archives of graph models, and we propose an original look-ahead method which represents an efficient solution for the (sub)graph error correcting isomorphism problem needed to compute object distances. Analytic comparison and experimental results show that the proposed lookahead improves the state-of-the-art in state-space search methods and that the combined use of the proposed matching and indexing scheme permits for the management of the complexity of a typical application of retrieval by spatial arrangement     

Définition théorique des paramètres en fort niveau d’un multipôle actif non linéaire

In this paper, large signal non linear P parameters are rigorously defined, allowing the characterization of non linear active n-port circuits in the frequency domain with the aim of computer aided design of power microwave devices. No a priori conditions bind the parameters to the variables describing the input signal. However the following rules apply to the parameters: they may be function of any input variables of the n-port circuit; the expression of the large-signal parameters should become identical to the expression of the linear parameters characterizing the n-port circuit under linear operating conditions when the values of the input variables tend to zero. An application of the definition to afet is demonstrated.     

Medical Positron Imaging with a Dense Drift Space MultiWire Proportional Chamber

A multiplanar positron camera is proposed, made of six MWPC modules, arranged to form the lateral surface of a hexagonal prism. Each 50 x 50 cm(2) module has a single MWPC sandwiched by two 2-cm thick lead glass tube converters. The experimental results for a 15 x 15 cm(2) test module are reported. For 511 keV gamma-rays incident almost perpendicular onto a 1.0-cm thick converter, a detection efficiency of 4.3%, a time resolution of 130 ns (FWHM) and a spatial resolution of 2.8 mm (FWHM) have been measured with a standard Argon-Methane (70-30) mixture at 1.2 atm. The chamber may also be operated in high resolution mode: 1.2-mm (FWHM) spatial resolution has been measured at a 50% lower efficiency. The use of fast delay lines (specific delay 8 ns/cm) for the position read-out ensures a high rate capability. The expected performance of the six-module MWPC camera is discussed and compared with that of a BGO crystal ring camera. The MWPC solution seems very attractive not only for its low cost and simplicity of construction, but also for its fully three-dimensional imaging capability.     

Multiaxial fatigue and failure analysis of helical compression springs

Multiaxial fatigue criteria are applied to the analysis of helical compression springs. The critical plane approaches, Fatemi–Socie and Wang–Brown, and the Coffin–Manson method based on shear deformation, were used to predict fatigue lives of the springs under constant amplitude loading. Experimental fatigue lives are compared with the multiaxial fatigue criteria predictions. The stress analysis was carried out in the finite element code ANSYS, and the multiaxial fatigue study was performed using the fatigue software nCode. A failure analysis was conducted in order to determine the fatigue crack initiation point and a comparison of that location with the most damaged zone predicted by the numerical analysis is made. The Fatemi–Socie critical plane approach gives a good prediction of fatigue life. While the Wang–Brown criterion overestimates spring fatigue life, the Coffin–Mason model gives conservative results.     

ESA-based in-fiber nanocavity for hydrogen-peroxide detection

A fiber-optic sensor sensitive to hydrogen peroxide has been designed based on the electrostatic layer-by-layer self-assembly method. Prussian blue has been deposited in a polymeric structure formed by Poly(allylamine hydrochloride) and poly(acrylic acid). The concentration that can be detected range between 10/sup -6/-10/sup -3/ M, and recovery of the sensor after immersion into a reductive agent was demonstrated. The response of the sensor is independent of the pH for values that range between 4-7.4. Some rules for estimation of the refractive index of the material deposited and the thickness of the bilayers are also presented.     

A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory.

Electronic neuromorphic devices with on-chip, on-line learning should be able to modify quickly the synaptic couplings to acquire information about new patterns to be stored (synaptic plasticity) and, at the same time, preserve this information on very long time scales (synaptic stability). Here, we illustrate the electronic implementation of a simple solution to this stability-plasticity problem, recently proposed and studied in various contexts. It is based on the observation that reducing the analog depth of the synapses to the extreme (bistable synapses) does not necessarily disrupt the performance of the device as an associative memory, provided that 1) the number of neurons is large enough; 2) the transitions between stable synaptic states are stochastic; and 3) learning is slow. The drastic reduction of the analog depth of the synaptic variable also makes this solution appealing from the point of view of electronic implementation and offers a simple methodological alternative to the technological solution based on floating gates. We describe the full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning. In the absence of stimuli, the memory is preserved indefinitely. During the stimulation the synapse undergoes quick temporary changes through the activities of the pre- and postsynaptic neurons; those changes stochastically result in a long-term modification of the synaptic efficacy. The intentionally disordered pattern of connectivity allows the system to generate a randomness suited to drive the stochastic selection mechanism. We check by a suitable stimulation protocol that the stochastic synaptic plasticity produces the expected pattern of potentiation and depression in the electronic network.     

Weighted walkthroughs between extended entities for retrieval by spatial arrangement

In the access to image databases, queries based on the appearing visual features of searched data reduce the gap between the user and the engineering representation. To support this access modality, image content can be modeled in terms of different types of features such as shape, texture, color, and spatial arrangement. An original framework is presented which supports quantitative nonsymbolic representation and comparison of the mutual positioning of extended nonrectangular spatial entities. Properties of the model are expounded to develop an efficient computation technique and to motivate and assess a metric of similarity for quantitative comparison of spatial relationships. Representation and comparison of binary relationships between entities is then embedded into a graph-theoretical framework supporting representation and comparison of the spatial arrangements of a picture. Two prototype applications are described.