Intractability of min- and max-cut in streaming graphs

We show that the exact computation of a minimum or a maximum cut of a given graph G is out of reach for any one-pass streaming algorithm, that is, for any algorithm that runs over the input stream of G's edges only once and has a working memory of o(n²) bits. This holds even if randomization is allowed.     

On the focusing of thermal images

In this paper we present a new thermographic image database, suitable for the analysis of automatic focusing measures. This database contains the images of 10 scenes, each of which is represented once for each of 96 different focus positions. Using this database, we evaluate the usefulness of five focus measures with the goal of determining the optimal focus position. Experimental results reveal that the accurate automatic detection of optimal focus position can be achieved with a low computational burden. We also present an acquisition tool for obtaining thermal images. To the best of our knowledge, this is the first study on the automatic focusing of thermal images.     

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.     

Simple multichannel system for the measurement of the net water flux across biological tissues

This paper describes the development of a simple system for measurement of net water movement through biological membrane barriers. The system is based on the detection of a water meniscus inside a polyethylene tube, which reflects the water movement inside one hemichamber of a modified Ussing chamber containing a membrane barrier. The detection device consists of a commercial computer-controlled flat bed scanner and specifically developed software. This system allows one to perform a relatively high number of individual experiments per physical unit. It is a flexible and affordable device, which allows comparatively more information per unit to be obtained than previously described methods.     

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.     

Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum-matching technique

The concept of imaging spectrometry, or hyperspectral imaging, is becoming increasingly popular in scientific communities in recent years. Hyperspectral imaging data covering the spectral region between 0.4 and 2.5 μm and collected from aircraft and satellite platforms have been used in the study of the earth's atmosphere, land surface, and ocean color properties, as well as on planetary missions. In order to make such quantitative studies, accurate radiometric and spectral calibrations of hyperspectral imaging data are necessary. Calibration coefficients for all detectors in an imaging spectrometer obtained in a laboratory may need to be adjusted when applied to data obtained from an aircraft or a satellite platform. Shifts in channel center wavelengths and changes in spectral resolution may occur when an instrument is airborne or spaceborne due to vibrations, and to changes in instrument temperature and pressure. In this paper, we describe an algorithm for refining spectral calibrations of imaging spectrometer data using observed features in the data itself. The algorithm is based on spectrum-matching of atmospheric water vapor, oxygen, and carbon dioxide bands, and solar Fraunhofer lines. It has been applied to real data sets acquired with airborne and spaceborne imaging spectrometers.