A Declarative Approach to Network Device Configuration Correctness

Configuration Logic (CL) is a formal language that allows a network engineer to express constraints in terms of the actual parameters found in the configuration of network devices. We present an efficient algorithm that can automatically check a pool of devices for conformance to a set of CL constraints; moreover, this algorithm can point to the part of the configuration responsible for the error when a constraint is violated. Contrary to other validation approaches that require dumping the configuration of the whole network to a central location in order to be verified, we also present an algorithm that analyzes the correct formulas and greatly helps reduce the amount of data that need to be transferred to that central location, pushing as much of the evaluation of the formula locally on each device. The procedure is also backwards-compatible, in such a way that a device that does not (or only partially) supports a local evaluation may simply return a subset or all of its configuration. These capabilities have been integrated into a network management tool called ValidMaker.     

Inhomogeneous shear flows of linear polymers

Solutions of a system of equations of nonlinear viscoelastic fluid motion describing inhomogeneous shear flows of linear polymers are indicated.Notation _ij stress tensor - p pressure - F_i mass force vector - _ij Kronecker delta - coefficient of shear viscosity - relaxation time - _ij inner parameter - _ij=vi/x_j velocity gradient tensor - ₀ initial value of the shear viscosity coefficient - ₀ initial value of the relaxation time - D dimensionless first invariant of the additional stress tensor - A, B, C constants of integration - f(D) universal function characterizing the material - r, , z cylindrical coordinates - u=v_z axial component of the velocity vector - v=v circumferential component of the velocity vector - ₁, ₂ first and second differences of the normal stress - Q volume mass flow rate - R radius of a circular tube - R₁, R₂ radii of the inner and outer cylinders, respectively - M moment per unit length Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 41, No. 3, pp. 449–456, September, 1981.     

Personality Organizations, Psychiatric Severity, and Self and Object Representations.

This study examined the hypothesis that psychotic, borderline, and neurotic personality organizations (POs) present a progressive differentiation between self and object representations and an increasing integration of their bad and good aspects. Fifty patients participated in the study. Measures included scales of self and object representations (S. J. Blatt, S. A. Bers, & C. E. Schaffer, 1993; S. J. Blatt, H. Wiseman, E. Prince-Gibson, & C. Gatt, 1991), as well as the Personality Organization Diagnostic Form (L. Diguer & L. Normandin, 1997) and estimations of psychiatric severity. Results showed that PO groups differed in terms of the integration of the object and its valence. It was also observed that although object and self representations were closely intertwined, the latter showed more discrimination between POs than the former. Psychiatric severity was shown to correlate more with object representations than self representations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The limitations and potential of AVHRR GAC data for continental scale fire studies

Global Area Coverage (GAC) data from the Advanced Very High Resolution Radiometer (AVHRR) are available on a daily basis, dating back to July 1981. The AVHRR's 3·55–3·93 μm channel is suitable for detection of terrestrial hot spots, such as bushfires. The long-term archives and global cover make the GAC a potentially valuable data source for large scale fire studies. However, these data are sampled spatially through a combination of line skipping and averaging. This study shows that the sampling affects the sensitivity of GAC for fire detection in relation to ecosystem and season. The GAC are found to provide a reasonable measure of fire activity in grassland and open b'ush savannah, but to perform poorly in the forest margins. Overall at least 79 per cent of fires detected with non-sampled AVHRR data are missed by the GAC. This severely limits the use of GAC data for quantitative fire studies. The GAC does appear to provide a reasonable measure of fire calendar (i.e., variations in fire activity with time) and on a continental scale successfully identifies the main regions of fire activity. The potential of these data for continental scale fire studies is illustrated through the preliminary analysis of 277 GAC mosaics of Africa for the period September 1988 to August 1989.     

Technical Note Simulation of MEIS-II data on 5S code to quantify algal concentration in an intertidal area

An atmospheric correction algorithm due to Deschamps et al. (1981) has been applied to MEIS-II data. Some atmospheric conditions such as continental and maritime aerosol models have been used in this work. Simulation on 5S code was made with Thematic Mapper Band 4 and Spot band 3. All these pieces of the puzzle permitted the qualification of algal concentration in an intertidal area, which was the aim of this work. Continental or maritime aerosol models gave a similar result due probably to the specific area, located between land and nearshore. Apparent radiance is smaller than corrected radiance because absorption process takes place in this part of the spectrum (0.8 to 0.9μm). When apparent radiance is higher than 30 Wm^?2 sr^?1 μm^?1 algal concentration is overestimated by up to 60 per cent.     

A first try at identification of sea ice using the three beam scatterometer of ERS-1

Regional-scale behaviour of backscattering at C-band is investigated using data of the ERS-1 three-beam scatterometer, the AMI-WIND, during November 1991, over the Arctic ocean. The normalized radar cross-section appears as a linear function of incidence angle, whose two parameters vary considerably between zones of first-year and multi-year sea ice. Once determined the slope parameter of the AMI-WIND data, measured normalized radar cross-sections are corrected to bring them to a single reference incidence angle. False-colour mapping of this variable displays first-year and multi-year sea ice zones as determined previously from several passive micro-wave sensors (ESMR. SSM,/I)     

Nearest neighbour analysis applied to synthetic aperture radar images for the description of urban land cover and land use

This article presents an analysis method for the creation of an image variable that represents built-up land cover and land use within the urban fabric. The method is inspired by the nearest neighbour analysis and the data are from the synthetic aperture radar systems COSMO-SkyMed (CSK) and Radarsat-2 (RS2). Point features were identified from the extreme high backscattering values for each image and the spatial pattern extracted to represent the proportion of built-up land cover as clustered, random, or dispersed. The coefficient of association between the continuous nearest neighbour ratio image and the land-cover percentage cover in four classes are ?0.9 and ?0.8 with the CSK and the RS2 images, respectively. Considering a two-class land-cover scheme, the coefficient of association between variables approaches ?0.9 for both images. Clustered features highlight individual buildings that are mixed in various neighbouring land-cover and land-use types. Residential land use is particularly well outlined using the CSK image, while large institutional, commercial, and light industry buildings are enhanced through the RS2 cross-polarization nearest neighbour ratio images.