Finding and Counting Vertex-Colored Subtrees

The problems studied in this article originate from the Graph Motif problem introduced by Lacroix et al. (IEEE/ACM Trans. Comput. Biol. Bioinform. 3(4):360–368, 2006) in the context of biological networks. The problem is to decide if a vertex-colored graph has a connected subgraph whose colors equal a given multiset of colors M. It is a graph pattern-matching problem variant, where the structure of the occurrence of the pattern is not of interest but the only requirement is the connectedness. Using an algebraic framework recently introduced by Koutis (Proceedings of the 35th International Colloquium on Automata, Languages and Programming (ICALP), Lecture Notes in Computer Science, vol. 5125, pp. 575–586, 2008) and Koutis and Williams (Proceedings of the 36th International Colloquium on Automata, Languages and Programming (ICALP), Lecture Notes in Computer Science, vol. 5555, pp. 653–664, 2009), we obtain new FPT algorithms for Graph Motif and variants, with improved running times. We also obtain results on the counting versions of this problem, proving that the counting problem is FPT if M is a set, but becomes #W[1]-hard if M is a multiset with two colors. Finally, we present an experimental evaluation of this approach on real datasets, showing that its performance compares favorably with existing software.     

Energy-aware feedback control for a H.264 video decoder

Embedded devices using highly integrated chips must cope with conflicting constraints, while executing computationally demanding applications under limited energy storage. Automatic control and feedback loops appear to be an effective solution to simultaneously accommodate for performance uncertainties due to the tiny scale gates variability, varying and poorly predictable computing demands and limited energy storage constraints. This paper presents the example of an embedded video decoder controlled by several feedback loops to carry out the trade-off between decoding quality and energy consumption, exploiting the frequency and voltage scaling capabilities of the chip. The inner loop controls the dynamic voltage and frequency scaling through a fast predictive control strategy. The outer loop computes the scheduling set-points needed by the inner loop to process frames decoding. The feedback loops have been implemented on a stock PC and experimental results are provided.     

Leaf area index mapping in northern Canada

Leaf area index (LAI) is an important structural vegetation parameter that is commonly derived from remotely sensed data. It has been used as a reliable indicator for vegetation's cover, status, health and productivity. In the past two decades, various Canada-wide LAI maps have been generated by the Canada Centre for Remote Sensing (CCRS). These products have been produced using a variety of very coarse satellite data such as those from SPOT VGT and NOAA AVHRR satellite data. However, in these LAI products, the mapping of the Canadian northern vegetation has not been performed with field LAI measurements due in large part to scarce in situ measurements over northern biomes. The coarse resolution maps have been extensively used in Canada, but finer resolution LAI maps are needed over the northern Canadian ecozones, in particular for studying caribou habitats and feeding grounds.

In this study, a new LAI algorithm was developed with particular emphasis over northern Canada using a much finer resolution of remotely sensed data and in situ measurements collected over a wide range of northern arctic vegetation. A statistical relationship was developed between the in situ LAI measurements collected over vegetation plots in northern Canada and their corresponding pixel spectral information from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. Furthermore, all Landsat TM and ETM+ data have been pre-normalized to NOAA AVHRR and SPOT VGT data from the growing season of 2005 to reduce any seasonal or temporal variations. Various spectral vegetation indices developed from the Landsat TM and ETM?+?data were analysed in this study. The reduced simple ratio index (RSR) was found to be the most robust and an accurate estimator of LAI for northern arctic vegetation. An exponential relationship developed using the Theil–Sen regression technique showed an R ² of 0.51 between field LAI measurement and the RSR. The developed statistical relationship was applied to a pre-existing Landsat TM 250 m resolution mosaic for northern Canada to produce the final LAI map for northern Canada ecological zones. Furthermore, the 250 m resolution LAI estimates, per ecological zone, were almost generally lower than those of the CCRS Canada-wide VGT LAI maps for the same ecozones. Validation of the map with LAI field data from the 2008 season, not used in the derivation of the algorithm, shows strong agreement between the in situ LAI measurement values and the map-estimated LAI values.     

Near-optimal parameterization of the intersection of quadrics: III. Parameterizing singular intersections

We conclude, in this third part, the presentation of an algorithm for computing an exact and proper parameterization of the intersection of two quadrics. The coordinate functions of the parameterizations in projective space are polynomial, whenever it is possible. They are also near-optimal in the sense that the number of distinct square roots appearing in the coefficients of these functions is minimal except in a small number of cases (characterized by the real type of the intersection) where there may be an extra square root.     

Dose calculations using artificial neural networks: A feasibility study for photon beams

Direct dose calculations are a crucial requirement for Treatment Planning Systems. Some methods, such as Monte Carlo, explicitly model particle transport, others depend upon tabulated data or analytic formulae. However, their computation time is too lengthy for clinical use, or accuracy is insufficient, especially for recent techniques such as Intensity-Modulated Radiotherapy. Based on artificial neural networks (ANNs), a new solution is proposed and this work extends the properties of such an algorithm and is called NeuRad.Prior to any calculations, a first phase known as the learning process is necessary. Monte Carlo dose distributions in homogeneous media are used, and the ANN is then acquired. According to the training base, it can be used as a dose engine for either heterogeneous media or for an unknown material. In this report, two networks were created in order to compute dose distribution within a homogeneous phantom made of an unknown material and within an inhomogeneous phantom made of water and TA6V4 (titanium alloy corresponding to hip prosthesis).All NeuRad results were compared to Monte Carlo distributions. The latter required about 7 h on a dedicated cluster (10 nodes). NeuRad learning requires between 8 and 18 h (depending upon the size of the training base) on a single low-end computer. However, the results of dose computation with the ANN are available in less than 2 s, again using a low-end computer, for a 150×1×150 voxels phantom. In the case of homogeneous medium, the mean deviation in the high dose region was less than 1.7%. With a TA6V4 hip prosthesis bathed in water, the mean deviation in the high dose region was less than 4.1%.Further improvements in NeuRad will have to include full 3D calculations, inhomogeneity management and input definitions.     

In Situ X-Ray Radiography and Tomography Observations of the Solidification of Aqueous Alumina Particle Suspensions—Part I: Initial Instants

This paper investigates by in situ high-resolution X-ray radiography and tomography the behavior of colloidal suspensions of alumina partic les during directional solidification by freezing. The combination of these techniques provided both qualitative and quantitative information about the propagation kinetic of the solid/liquid interface, the particle redistribution between the crystals and a particle-enriched phase, and the three-dimensional organization of the ice crystals. In this first part of two companion papers, the precursor phenomena leading to directional crystallization during the first instants of solidification are studied. Mullins–Sekerka instabilities are not necessary to explain the dynamic evolution of the interface pattern. Particle redistribution during these first instants is dependent on the type of crystals growing into the suspension. The insights gained into the mechanisms of solidification of colloidal suspensions may be valuable for the materials processing routes derived for this type of directional solidification (freeze-casting), and of general interest for those interested in the interactions between solidification fronts and inert particles.     

Low sintering temperature of (Zn0.65Mg0.35)TiO3–xCaTiO3-based dielectric with controlled temperature coefficient

(Zn_0.65Mg_0.35)TiO₃–xCaTiO₃-based dielectric ceramics sintered at low temperature thanks to ZnO–B₂O₃ glass phase addition are investigated. The effects of such additions on the dilatometric curves, the microstructure, the phase composition and the dielectric properties have been carefully examined. It is shown that the sintering temperature is significantly lowered to 930 °C by the addition of 2 wt.% of ZnO–B₂O₃ glass phase. The temperature coefficient of permittivity (τ_?) could be controlled by varying the CaTiO₃ content and lead to near zero τ_? value. As an optimal composition, (Zn_0.65Mg_0.35)TiO₃ + 7%CaTiO₃, co-sinterable with silver electrodes at 930 °C, exhibits at 1 MHz, a relative permittivity of ?_r = 21, a temperature coefficient of the permittivity τ_? of ?4 ppm/°C and low dielectric losses (tan(δ) < 10^?3). These interesting properties make this system promising to manufacture Ag-based electrodes multilayer dielectric devices.     

Characterisation of carbon blacks produced by solar thermal dissociation of methane

Solar methane dissociation appears as a possible route toward a hydrogen-based economy. The competitiveness of the process strongly depends on the carbon black properties and economic value. At CNRS-PROMES, a 50 kW tubular solar reactor was developed to produce carbon black and hydrogen from methane. The reaction was carried out in a graphite receiver crossed by seven graphite tubes heated up by concentrated solar radiations at the 1 MW CNRS solar furnace. The temperatures ranged between 1608 K and 1928 K and the methane flow-rates varied from 10.5 to 21 NL/min. Total methane dissociation was reached with hydrogen yield higher than 80% and the carbon yield was drastically affected by the acetylene by-product. The carbon samples were analysed in detail and their properties were compared to a commercial conductive grade carbon black. Transmission electron microscopy showed primary particles of 10–70 nm diameter. The crystallinity of the samples was characterised by Raman spectroscopy. It was also possible to correlate the specific surface area with the reaction temperature and with the concentrations of residual methane and of the acetylene by-product. The resistivity and the structure of the agglomerates were determined by simultaneous measurements of the conductivity and the density under compression.