Scale-invariant vote-based 3D recognition and registration from point clouds

This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a (real and) challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2013 Springer-Verlag Berlin Heidelberg.

Computational engineering design for micro-scale combustors

At present, optimisation is an enabling technology in innovation. Multi-objective and multi-disciplinary design tools are essential in the engineering design process, and have been applied successfully in aerospace and turbomachinery applications extensively. These approaches give insight into the design space and identify the trade-offs between the competing performance measures satisfying a number of constraints at the same time. It is anticipated here that the same benefits can be obtained for the design of micro-scale combustors. In this paper, a multi-disciplinary automated design optimisation system was developed for this purpose, which comprises a commercial computational fluid dynamics package and a multi-objective variant of the Tabu Search optimisation algorithm. The main objectives that are considered in this study are to optimise the main micro-scale combustor design characteristics and to satisfy manufacturability considerations from the very beginning of the whole design operation. Hydrogen-air combustion as well as 14 geometrical and 2 operational parameters are used to describe and model the design problem. Two illustrative test cases will be presented, in which the most important device operational requirements are optimised, and the efficiency of the developed optimisation system is demonstrated. The identification, assessment and suitability of the optimum design configurations are discussed in detail. Copyright © 2012 by ASME.

Computational engineering design for micro-scale combustion devices: A thermally improved configuration

A multi-objective design optimisation study has been carried out with the objectives to improve the overall efficiency of the device and to reduce the fuel consumption for the proposed micro-scale combustor design configuration. In a previous study we identified the topology of the combustion chamber that produced improved behaviour of the device in terms of the above design criteria. We now extend our design approach, and we propose a new configuration by the addition of a micro-cooling channel that will improve the thermal behaviour of the design as previously suggested in literature. Our initial numerical results revealed an improvement of 2.6% in the combustion efficiency when we applied the micro-cooling channel to an optimum design configuration we identified from our earlier multi-objective optimisation study, and under the same operating conditions. The computational modelling of the combustion process is implemented in the commercial computational fluid dynamics package ANSYS-CFX using Finite Rate Chemistry and a single step hydrogen-air reaction. With this model we try to balance good accuracy of the combustion solution and at the same time practicality within the context of an optimisation process. The whole design system comprises also the ANSYS-ICEM CFD package for the automatic geometry and mesh generation and the Multi-Objective Tabu Search algorithm for the design space exploration. We model the design problem with 5 geometrical parameters and 3 operational parameters subject to 5 design constraints that secure practicality and feasibility of the new optimum design configurations. The final results demonstrate the reliability and efficiency of the developed computational design system and most importantly we assess the practicality and manufacturability of the revealed optimum design configurations of micro-combustor devices. Copyright © 2013 by ASME.

Space-charge-limited currents in GaN Schottky diodes

Unusual dark current voltage (I-V) characteristics were observed in GaN Schottky diodes. I-V characteristics of the GaN Schottky diodes were measured down to the magnitude of 10(-14) A. Although these Schottky diodes were clearly rectifying, their I-V characteristics were non-ideal which can be judged from the non-linearity in the semi-logarithmic plots. Careful analysis of the forward bias I-V characteristics on log-log scale indicates space-charge-limited current (SCLC) conduction dominates the current transport in these GaN Schottky diodes. The concentration of the deep trapping centers was estimated to be higher than 10(15) cm(-3). In the deep level transient spectra (DLTS) measurements for the GaN Schottky diodes, deep defect levels around 0.20 eV below the bottom of the conduction band were identified, which may act as the trapping centers. The concentration of the deep centers obtained from the DLTS data is about 5 x 10(15) cm(-3). SCLC measurements may be used to probe the properties of deep levels in wide bandgap GaN-AlGaN compound semiconductors, as is the case with insulators in the presence of trapping centers. (c) 2005 Elsevier Ltd. All rights reserved.

Design and operation of integrated pilot-scale dimethyl ether synthesis system via pyrolysis/gasification of corncob

The integrated pilot-scale dimethyl ether (DME) synthesis system from corncob was demonstrated for modernizing utilization of biomass residues. The raw bio-syngas was obtained by the pyrolyzer/gasifier at the yield rate of 40-45 Nm(3)/h. The content of tar in the raw bio-syngas was decreased to less than 20 mg/Nm(3) by high temperature gasification of the pyrolysates under O-2-rich air. More than 70% CO2 in the raw bio-syngas was removed by pressure-swing adsorption unit (PSA). The bio-syngas (H-2/CO approximate to 1) was catalytically converted to DME in the fixed-bed tubular reactor directly over Cu/Zn/Al/HZSM-5 catalysts. CO conversion and space-time yield of DME were in the range of 82.0-73.6% and 124.3-203.8 kg/m(cat)(3)/h, respectively, with a similar DME selectivity when gas hourly space velocity (GHSV, volumetric flow rate of syngas at STP divided by the volume of catalyst) increased from 650 h(-1) to 1500 h(-1) at 260 degrees C and 4.3 MPa. And the selectivity to methanol and C-2(+) products was less than 0.65% under typical synthesis condition. The thermal energy conversion efficiency was ca. 32.0% and about 16.4% carbon in dried corncob was essentially converted to DME with the production cost of ca. (sic) 3737/ton DME. Cu (111) was assumed to be the active phase for DME synthesis, confirmed by X-ray diffraction (XRD) characterization.

Scale study of direct synthesis of dimethyl ether from biomass synthesis gas

We investigated the synthesis of dimethyl ether (DME) from biomass synthesis gas using a kind of hybrid catalyst consisting of methanol and HZSM-5 zeolite in a fixed-bed reactor in a 100 ton/year pilot plant. The biomass synthesis gas was produced by oxygen-rich gasification of corn core in a two-stage fixed bed. The results showed that CO conversions reached 82.00% and 73.55%, the selectivities for DME were 73.95% and 69.73%, and the space-time yields were 124.28 kg m- 3 h- 1 and 203.80 kg m- 3 h- 1 when gas hourly space velocities were 650 h- 1 and 1200 h- 1, respectively. Deoxidation and tar removal from biomass synthesis gas was critical to the stable operation of the DME synthesis system. Using single-pass synthesis, the H2/CO ratio improved from 0.98-1.17 to 2.12-2.22. The yield of DME would be increased greatly if the exhaust was reused after removal of the CO2.

Small-scale turbulent fluctuations beyond Taylor's frozen-flow hypothesis

The space-time cross-correlation function C-T(r, tau) of local temperature fluctuations in turbulent Rayleigh-Benard convection is obtained from simultaneous two-point time series measurements. The obtained C-T(r, tau) is found to have the scaling form C-T(r(E), 0) with r(E)=[(r-U tau)(2)+ V-2 tau(2)](1/2), where U and V are two characteristic velocities associated with the mean and rms velocities of the flow. The experiment verifies the theory and demonstrates its applications to a class of turbulent flows in which the requirement of Taylor's frozen flow hypothesis is not met.

Large-scale structure of the fast solar wind

Breen, Andrew; Bisi, M.M.; Fallows, R.A.; Habbal, S.R., (2007) 'Large-scale structure of the fast solar wind', Journal of Geophysical Research 112(A6) pp.A06101 RAE2008

Orientational Harmonic Model for Rotation, Translation, and Scale Invariant Pattern Representation in Biological Vision

The proposed model, called the combinatorial and competitive spatio-temporal memory or CCSTM, provides an elegant solution to the general problem of having to store and recall spatio-temporal patterns in which states or sequences of states can recur in various contexts. For example, fig. 1 shows two state sequences that have a common subsequence, C and D. The CCSTM assumes that any state has a distributed representation as a collection of features. Each feature has an associated competitive module (CM) containing K cells. On any given occurrence of a particular feature, A, exactly one of the cells in CMA will be chosen to represent it. It is the particular set of cells active on the previous time step that determines which cells are chosen to represent instances of their associated features on the current time step. If we assume that typically S features are active in any state then any state has K^S different neural representations. This huge space of possible neural representations of any state is what underlies the model's ability to store and recall numerous context-sensitive state sequences. The purpose of this paper is simply to describe this mechanism.

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

An Exploration into Fern Genome Space.

Ferns are one of the few remaining major clades of land plants for which a complete genome sequence is lacking. Knowledge of genome space in ferns will enable broad-scale comparative analyses of land plant genes and genomes, provide insights into genome evolution across green plants, and shed light on genetic and genomic features that characterize ferns, such as their high chromosome numbers and large genome sizes. As part of an initial exploration into fern genome space, we used a whole genome shotgun sequencing approach to obtain low-density coverage (∼0.4X to 2X) for six fern species from the Polypodiales (Ceratopteris, Pteridium, Polypodium, Cystopteris), Cyatheales (Plagiogyria), and Gleicheniales (Dipteris). We explore these data to characterize the proportion of the nuclear genome represented by repetitive sequences (including DNA transposons, retrotransposons, ribosomal DNA, and simple repeats) and protein-coding genes, and to extract chloroplast and mitochondrial genome sequences. Such initial sweeps of fern genomes can provide information useful for selecting a promising candidate fern species for whole genome sequencing. We also describe variation of genomic traits across our sample and highlight some differences and similarities in repeat structure between ferns and seed plants.

A multi-scale atomistic-continuum modelling of crack propagation in a two-dimensional macroscopic plate

A novel multi-scale seamless model of brittle-crack propagation is proposed and applied to the simulation of fracture growth in a two-dimensional Ag plate with macroscopic dimensions. The model represents the crack propagation at the macroscopic scale as the drift-diffusion motion of the crack tip alone. The diffusive motion is associated with the crack-tip coordinates in the position space, and reflects the oscillations observed in the crack velocity following its critical value. The model couples the crack dynamics at the macroscales and nanoscales via an intermediate mesoscale continuum. The finite-element method is employed to make the transition from the macroscale to the nanoscale by computing the continuum-based displacements of the atoms at the boundary of an atomic lattice embedded within the plate and surrounding the tip. Molecular dynamics (MD) simulation then drives the crack tip forward, producing the tip critical velocity and its diffusion constant. These are then used in the Ito stochastic calculus to make the reverse transition from the nanoscale back to the macroscale. The MD-level modelling is based on the use of a many-body potential. The model successfully reproduces the crack-velocity oscillations, roughening transitions of the crack surfaces, as well as the macroscopic crack trajectory. The implications for a 3-D modelling are discussed.

Computational modelling of multi-physics and multi-scale processes in parallel

This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.

Decadal basin-scale changes in diatoms, dinoflagellates, and phytoplankton color across the North Atlantic

The Continuous Plankton Recorder (CPR) survey has been used to characterize phytoplankton and zooplankton space-time dynamics in the North Sea since 1931 and in the North Atlantic since 1939. Phytoplankton biomass is assessed from these samples by visual assessment of the green color of the silk mesh, the Phytoplankton Color Index (PCI), and the total count of diatoms and dinoflagellates. Species with a frequency of occurrence greater than 1% in the samples are used as indicator species of the community. We investigated (1) long-term fluctuations of phytoplankton biomass, total diatoms, and total dinoflagellates; (2) geographical variation of patterns; (3) the relationship between phytoplankton and climate forcing in the North Atlantic CPR samples; (4) the relative contribution of diatoms and dinoflagellates to the PCI; and (5) the fluctuations of the dominant species over the period of survey to provide more information on the processes linking climate to changes in the phytoplankton community. As a result of the differences in microscopic analysis methods prior to 1958, our analyses were conducted for the period ranging from 1958 to 2002. The North Atlantic was divided into six regions identified through bathymetric criteria and separated along a North-South axis. Based on 12 monthly time series, we demonstrate increasing trends in PCI and total dinoflagellates and a decrease in total diatoms.

Can the subtropical North Atlantic permanent thermocline be observed from space?

The analysis of remotely sensed altimeter data and in situ measurements shows that ERS 2 radar can monitor the ocean permanent thermocline from space. The remotely sensed sea level anomaly data account for similar to 2/3 of the temperature variance or vertical displacement of isotherms at a depth of similar to 550 m in the Subtropical North Atlantic Ocean near 32.5 degree N. This depth corresponds closely to the region of maximum temperature gradient in the permanent thermocline where near semi-annual internal vertical displacements reach 200 to 300 m. The gradient of the altimeter sea level anomaly data correlates well with measured ocean currents to a depth of 750 m. It is shown that observations from space can account for similar to 3/4 of the variance of ocean currents measured in situ in the permanent thermocline over a 2-y period. The magnification of the permanent thermocline displacement with respect to the displacement of the sea surface was determined as - x650 and gives a measure of the ratio of barotropic to baroclinic decay scale of geostrophic current with depth. The overall results are used to interpret an eight year altimeter data tie series in the Subtropical North Atlantic at 32.5 degree N which shows a dominant wave or eddy period near 200 days, rather than semi-annual and increases in energy propagating westward in 1995 (west of 25 degree W). The effects of rapid North Atlantic Oscillation climate change on ocean circulation are discussed. The altimeter data for the Atlantic were Fourier analysed. It is shown how the annual and semi-annual components relate to the seasonal maximum cholorophyll-a SeaWiFS signal in tropical and equatorial regions due to the lifting of the thermocline caused by seasonally varying ocean currents forced by wind stress.