Incremental Linear Discriminant Analysis Using Sufficient Spanning Sets and Its Applications

This paper presents an incremental learning solution for Linear Discriminant Analysis (LDA) and its applications to object recognition problems. We apply the sufficient spanning set approximation in three steps i.e. update for the total scatter matrix, between-class scatter matrix and the projected data matrix, which leads an online solution which closely agrees with the batch solution in accuracy while significantly reducing the computational complexity. The algorithm yields an efficient solution to incremental LDA even when the number of classes as well as the set size is large. The incremental LDA method has been also shown useful for semi-supervised online learning. Label propagation is done by integrating the incremental LDA into an EM framework. The method has been demonstrated in the task of merging large datasets which were collected during MPEG standardization for face image retrieval, face authentication using the BANCA dataset, and object categorisation using the Caltech101 dataset. © 2010 Springer Science+Business Media, LLC.

Using Level Sets as the basis for a scalable, parallel geometry engine and mesh generation system

The background to this review paper is research we have performed over recent years aimed at developing a simulation system capable of handling large scale, real world applications implemented in an end-to-end parallel, scalable manner. The particular focus of this paper is the use of a Level Set solid modeling geometry kernel within this parallel framework to enable automated design optimization without topological restrictions and on geometries of arbitrary complexity. Also described is another interesting application of Level Sets: their use in guiding the export of a body-conformal mesh from our basic cut-Cartesian background octree - mesh - this permits third party flow solvers to be deployed. As a practical demonstrations meshes of guaranteed quality are generated and flow-solved for a B747 in full landing configuration and an automated optimization is performed on a cooled turbine tip geometry. Copyright © 2009 by W.N.Dawes.

Water quality of two semi-closed areas in the United Arab Emirates Coast along the Arabian Gulf:a comparative study

A comparative study was carried out between the two biggest creeks along the Arabian Gulf coast of the United Arab Emirates to evaluate impacts of sewage and industrial effluents on their hydrochemical characteristics. Surface and bottom water samples were collected from Abu Dhabi and Dubai creeks during the period from October 1994 to September 1995. The hydrochemical parameters studied were: temperature (21.10-34.00°C), salinity (37.37-47.09%), transparency (0.50-10.0 m), pH (7.97-8.83), dissolved oxygen (1.78-13.93 mg/l) and nutrients ammonia (ND- 13.12,ug-at N/1), nitrite (ND-6.66 ,ug-at N/1), nitrate (ND- 41.18 ,ug-at N/1), phosphate (ND- 13.06 ,ug-at P/1), silicate (0.68-32.50 ,ug-at Si/1), total phosphorus (0.26- 21.48 ,ug-at P/1), and total silicon (0.95- 40.32 ,ug-at Si/1). The present study indicates clearly that seawater of Abu-Dhabi Creek was warmer (28.l2°C) than Dubai (27.56°C) resulting in a higher rate of evaporation. Owing to more evaporation, salinity levels showed higher levels at Abu Dhabi (43.33%) compared to Dubai (39.03%) seawater. The study also revealed higher secchi disc readings at Abu Dhabi Creek (4.68 m) as compared to Dubai Creek (2.60 m) suggesting more transparency at Abu Dhabi Creek. Whereas, seawater of Dubai exhibited higher levels of pH (1.03 times), and dissolved oxygen (1.05 times) than Abu Dhabi seawater due to an increase in productivity. Meantime, seawater of Dubai showed higher tendency to accumulate ammonia (8.22 times), nitrite (10.93 times), nitrate (5.85 times), phosphate (10.64 times), silicate (1.60 times), total phosphorus (3.19 times), and total silicon (1.54 times) compared to Abu Dhabi seawater due to the enrichment of seawater at Dubai with domestic sewage waters which has distinctly elevated the levels of the nutrient salts particularly in inner-most parts of the creek leading to eutrophication signs. The changes occurred in the receiving creek water of Dubai as a result of waste-water disposal that have also reflected on the atomic ratios of nit: Effect of pollution rogen: phosphorus: silicon.

Modeling evaporation effects in conditional moment closure for spray autoignition

Simulations of an n-heptane spray autoigniting under conditions relevant to a diesel engine are performed using two-dimensional, first-order conditional moment closure (CMC) with full treatment of spray terms in the mixture fraction variance and CMC equations. The conditional evaporation term in the CMC equations is closed assuming interphase exchange to occur at the droplet saturation mixture fraction values only. Modeling of the unclosed terms in themixture fraction variance equation is done accordingly. Comparison with experimental data for a range of ambient oxygen concentrations shows that the ignition delay is overpredicted. The trend of increasing ignition delay with decreasing oxygen concentration, however, is correctly captured. Good agreement is found between the computed and measured flame lift-off height for all conditions investigated. Analysis of source terms in the CMC temperature equation reveals that a convective-reactive balance sets in at the flame base, with spatial diffusion terms being important, but not as important as in lifted jet flames in cold air. Inclusion of droplet terms in the governing equations is found to affect the mixture fraction variance field in the region where evaporation is the strongest, and to slightly increase the ignition delay time due to the cooling associated with the evaporation. Both flame propagation and stabilization mechanisms, however, remain unaffected. © 2011 Taylor & Francis.

Convex approaches to model wavelet sparsity patterns

Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing of the simple Markovian dependency structure. This leads to reconstruction problems that are non-convex optimizations. Past work has dealt with this issue by resorting to greedy or suboptimal iterative reconstruction methods. In this paper, we propose new modeling approaches based on group-sparsity penalties that leads to convex optimizations that can be solved exactly and efficiently. We show that the methods we develop perform significantly better in de-convolution and compressed sensing applications, while being as computationally efficient as standard coefficient-wise approaches such as lasso. © 2011 IEEE.

The performance of closed reactor grade plutonium-thorium fuel cycles in reduced-moderation pressurised water reactors

The production of long-lived transuranic (TRU) waste is a major disadvantage of fission-based nuclear power. Previous work has indicated that TRU waste can be virtually eliminated in a pressurised water reactor (PWR) fuelled with a mixture of thorium and TRU waste, when all actinides are returned to the reactor after reprocessing. However, the optimal configuration for a fuel assembly operating this fuel cycle is likely to differ from the current configuration. In this paper, the differences in performance obtained in a reduced-moderation PWR operating this fuel cycle were investigated using WIMS. The chosen configuration allowed an increase of at least 20% in attainable burn-up for a given TRU enrichment. This will be especially important if the practical limit on TRU enrichment is low. The moderator reactivity coefficients limit the enrichment possible in the reactor, and this limit is particularly severe if a negative void coefficient is required for a fully voided core. Several strategies have been identified to mitigate this. Specifically, the control system should be designed to avoid a detrimental effect on moderator reactivity coefficients. The economic viability of this concept is likely to be dependent on the achievable thermal-hydraulic operating conditions. © 2012 Elsevier Ltd. All rights reserved.

Polarisation diversity of conformal arrays based on geometric algebra via convex optimisation

A simple and general design procedure is presented for the polarisation diversity of arbitrary conformal arrays; this procedure is based on the mathematical framework of geometric algebra and can be solved optimally using convex optimisation. Aside from being simpler and more direct than other derivations in the literature, this derivation is also entirely general in that it expresses the transformations in terms of rotors in geometric algebra which can easily be formulated for any arbitrary conformal array geometry. Convex optimisation has a number of advantages; solvers are widespread and freely available, the process generally requires a small number of iterations and a wide variety of constraints can be readily incorporated. The study outlines a two-step approach for addressing polarisation diversity in arbitrary conformal arrays: first, the authors obtain the array polarisation patterns using geometric algebra and secondly use a convex optimisation approach to find the optimal weights for the polarisation diversity problem. The versatility of this approach is illustrated via simulations of a 7×10 cylindrical conformal array. © 2012 The Institution of Engineering and Technology.