Fast, scalable master equation solution algorithms. IV. Lanczos iteration with diffusion approximation preconditioned iterative inversion

In this paper we propose a second linearly scalable method for solving large master equations arising in the context of gas-phase reactive systems. The new method is based on the well-known shift-invert Lanczos iteration using the GMRES iteration preconditioned using the diffusion approximation to the master equation to provide the inverse of the master equation matrix. In this way we avoid the cubic scaling of traditional master equation solution methods while maintaining the speed of a partial spectral decomposition. The method is tested using a master equation modeling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long-lived isomerizing intermediates. (C) 2003 American Institute of Physics.

Fast, scalable master equation solution algorithms. III. Direct time propagation accelerated by a diffusion approximation preconditioned iterative solver

In this paper we propose a novel fast and linearly scalable method for solving master equations arising in the context of gas-phase reactive systems, based on an existent stiff ordinary differential equation integrator. The required solution of a linear system involving the Jacobian matrix is achieved using the GMRES iteration preconditioned using the diffusion approximation to the master equation. In this way we avoid the cubic scaling of traditional master equation solution methods and maintain the low temperature robustness of numerical integration. The method is tested using a master equation modelling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long lived isomerizing intermediates. (C) 2003 American Institute of Physics.

A genetic algorithm/method of moments approach to the optimization of an RF coil for MRI applications - Theoretical considerations - Abstract

A Combined Genetic Algorithm and Method of Moments design methods is presented for the design of unusual near-field antennas for use in Magnetic Resonance Imaging systems. The method is successfully applied to the design of an asymmetric coil structure for use at 190MHz and demonstrates excellent radiofrequency field homogeneity.

Identification of slow and fast-acting toxins in a highly ciguatoxic barracuda (Sphyraena barracuda) by HPLC/MS and radiolabelled ligand binding

A barracuda implicated in ciguatera fish poisoning in Guadeloupe was estimated to have an overall flesh toxicity of 15 MUg/g using mouse bioassay. A lipid soluble extract was separated into two toxic fractions, FrA and FrB, on a LH20 Sephadex column eluted with dichloromethane/methanol (1:1). When intraperitoneal injected into mice, FrA provoked symptoms characteristic of slow-acting ciguatoxins, whereas FrB produced symptoms indicative of fast-acting toxins (FAT). High performance liquid chromatography/mass spectrometry/radio-ligand binding (HPLC/MS/RLB) analysis confirmed the two fractions were distinct, because only a weak overlap of some compounds was observed. HPLC/MS/RLB analysis revealed C-CTX-1 as the potent toxin present in FrA, and two coeluting active compounds at m/z 809.43 and 857.42 in FrB, all displaying the characteristic pattern of ion formation for hydroxy-polyethers. Other C-CTX congeners and putative hydroxy-polyether-like compounds were detected in both fractions, however, the RLB found them inactive. C-CTX-1 accounted for >90% of total toxicity in this barracuda and was confirmed to be a competitive inhibitor of brevetoxin binding to voltage-sensitive sodium channels (VSSCs) with a potency two-times lower than P-CTX-1. However, FAT active on VSSCs and

Mapping the royal road and other hierarchical functions

In this paper we present a technique for visualising hierarchical and symmetric, multimodal fitness functions that have been investigated in the evolutionary computation literature. The focus of this technique is on landscapes in moderate-dimensional, binary spaces (i.e., fitness functions defined over {0, 1}(n), for n less than or equal to 16). The visualisation approach involves an unfolding of the hyperspace into a two-dimensional graph, whose layout represents the topology of the space using a recursive relationship, and whose shading defines the shape of the cost surface defined on the space. Using this technique we present case-study explorations of three fitness functions: royal road, hierarchical-if-and-only-if (H-IFF), and hierarchically decomposable functions (HDF). The visualisation approach provides an insight into the properties of these functions, particularly with respect to the size and shape of the basins of attraction around each of the local optima.

Automated traffic route identification through the shared nearest neighbour algorithm

Many organisations need to extract useful information from huge amounts of movement data. One example is found in maritime transportation, where the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes, and accelerating ship traffic. This paper addresses, in a first stage, the research challenge of developing an approach for the automated identification of traffic routes based on clustering motion vectors rather than reconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories in terms of their geometric shape of the path, their position in space, their life span, and changes of speed, direction and other attributes over time. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promising for the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.

Fast left ventricle tracking in CMR images using localized anatomical affine optical flow

In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.

Entradas e Bandeiras: estratégia de interiorização das cadeias de fast-food

O presente trabalho analisa a estratégia de entrada de firmas da indústria de fast-food brasileira em novos mercados. Investigamos quais os atributos de uma cidade que atrai firmas dessa indústria e como firmas de diferentes cadeias interagem nas suas decisões de entrada. Os resultados indicam que as firmas adotam uma estratégia do tipo me-too: uma vez que uma firma entra em um mercado inexplorado, as demais tendem a também entrar nesse mercado. A hipótese do artigo é que há uma incerteza quanto ao potencial de um mercado, e a entrada de uma firma sinaliza para as demais que esse potencial é elevado Os ganhos da descoberta e da entrada em um novo mercado com alto potencial dissipam-se rapidamente com a entrada das firmas seguidoras, concedendo uma vantagem temporária para a firma pioneira.

Surgical correction of scoliosis: Numerical analysis and optimization of the procedure

A previously developed model is used to numerically simulate real clinical cases of the surgical correction of scoliosis. This model consists of one-dimensional finite elements with spatial deformation in which (i) the column is represented by its axis; (ii) the vertebrae are assumed to be rigid; and (iii) the deformability of the column is concentrated in springs that connect the successive rigid elements. The metallic rods used for the surgical correction are modeled by beam elements with linear elastic behavior. To obtain the forces at the connections between the metallic rods and the vertebrae geometrically, non-linear finite element analyses are performed. The tightening sequence determines the magnitude of the forces applied to the patient column, and it is desirable to keep those forces as small as possible. In this study, a Genetic Algorithm optimization is applied to this model in order to determine the sequence that minimizes the corrective forces applied during the surgery. This amounts to find the optimal permutation of integers 1, ... , n, n being the number of vertebrae involved. As such, we are faced with a combinatorial optimization problem isomorph to the Traveling Salesman Problem. The fitness evaluation requires one computing intensive Finite Element Analysis per candidate solution and, thus, a parallel implementation of the Genetic Algorithm is developed.

Guitar solo tracker

A motivação para este trabalho vem da necessidade que o autor tem em poder registar as notas tocadas na guitarra durante o processo de improviso. Quando o músico está a improvisar na guitarra, muitas vezes não se recorda das notas tocadas no momento, este trabalho trata o desenvolvimento de uma aplicação para guitarristas, que permita registar as notas tocadas na guitarra eléctrica ou clássica. O sinal é adquirido a partir da guitarra e processado com requisitos de tempo real na captura do sinal. As notas produzidas pela guitarra eléctrica, ligada ao computador, são representadas no formato de tablatura e/ou partitura. Para este efeito a aplicação capta o sinal proveniente da guitarra eléctrica a partir da placa de som do computador e utiliza algoritmos de detecção de frequência e algoritmos de estimação de duração de cada sinal para construir o registo das notas tocadas. A aplicação é desenvolvida numa perspectiva multi-plataforma, podendo ser executada em diferentes sistemas operativos Windows e Linux, usando ferramentas e bibliotecas de domínio público. Os resultados obtidos mostram a possibilidade de afinar a guitarra com valores de erro na ordem de 2 Hz em relação às frequências de afinação standard. A escrita da tablatura apresenta resultados satisfatórios, mas que podem ser melhorados. Para tal será necessário melhorar a implementação de técnicas de processamento do sinal bem como a comunicação entre processos para resolver os problemas encontrados nos testes efectuados.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Lanczos algorithm on the grassmann manifold

5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

A Flexible Architecture for the Computation of Direct and Inverse Transforms in H.264/AVC Video Codecs

A new high throughput and scalable architecture for unified transform coding in H.264/AVC is proposed in this paper. Such flexible structure is capable of computing all the 4x4 and 2x2 transforms for Ultra High Definition Video (UHDV) applications (4320x7680@ 30fps) in real-time and with low hardware cost. These significantly high performance levels were proven with the implementation of several different configurations of the proposed structure using both FPGA and ASIC 90 nm technologies. In addition, such experimental evaluation also demonstrated the high area efficiency of theproposed architecture, which in terms of Data Throughput per Unit of Area (DTUA) is at least 1.5 times more efficient than its more prominent related designs(1).