857 resultados para optimisation algorithms


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"November 1982."

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Mode of access: Internet.

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Mode of access: Internet.

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We sought to improve the feasibility of strain rate imaging (SRI) during dobutamine stress echocardiography (DSE) in 56 subjects at low risk of coronary disease. The impact of several SRI changes during acquisition were studied, including: (1) changing from fundamental to harmonic imaging; (2) parallel beam-forming; (3) alteration of spatial resolution and (4) narrow sector acquisition. We assessed SR signal quality, a quantitative measure of signal noise and measurements of SRI. Of 1462 segments evaluated, 6% were uninterpretable at rest and 8% at peak stress. Signal quality was optimised by increasing temporal (p = 0.01) and spatial resolution (p<0.0001 vs. baseline imaging) at rest and peak. Increasing spatial resolution also minimised signal noise (p<0.0001). Inter-observer variability of time to peak SR and peak SR were less with high temporal and spatial resolution. SRI quality can be improved with harmonic imaging and higher temporal resolution but optimisation of spatial resolution is critical. (C) 2004 World Federation for Ultrasound in Medicine Biology.

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Genetic algorithms (GAs) are known to locate the global optimal solution provided sufficient population and/or generation is used. Practically, a near-optimal satisfactory result can be found by Gas with a limited number of generations. In wireless communications, the exhaustive searching approach is widely applied to many techniques, such as maximum likelihood decoding (MLD) and distance spectrum (DS) techniques. The complexity of the exhaustive searching approach in the MLD or the DS technique is exponential in the number of transmit antennas and the size of the signal constellation for the multiple-input multiple-output (MIMO) communication systems. If a large number of antennas and a large size of signal constellations, e.g. PSK and QAM, are employed in the MIMO systems, the exhaustive searching approach becomes impractical and time consuming. In this paper, the GAs are applied to the MLD and DS techniques to provide a near-optimal performance with a reduced computational complexity for the MIMO systems. Two different GA-based efficient searching approaches are proposed for the MLD and DS techniques, respectively. The first proposed approach is based on a GA with sharing function method, which is employed to locate the multiple solutions of the distance spectrum for the Space-time Trellis Coded Orthogonal Frequency Division Multiplexing (STTC-OFDM) systems. The second approach is the GA-based MLD that attempts to find the closest point to the transmitted signal. The proposed approach can return a satisfactory result with a good initial signal vector provided to the GA. Through simulation results, it is shown that the proposed GA-based efficient searching approaches can achieve near-optimal performance, but with a lower searching complexity comparing with the original MLD and DS techniques for the MIMO systems.

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Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

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A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market. (C) 2003 Elsevier B.V. All rights reserved.

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To maximise data output from single-shot astronomical images, the rejection of cosmic rays is important. We present the results of a benchmark trial comparing various cosmic ray rejection algorithms. The procedures assess relative performances and characteristics of the processes in cosmic ray detection, rates of false detections of true objects, and the quality of image cleaning and reconstruction. The cosmic ray rejection algorithms developed by Rhoads (2000, PASP, 112, 703), van Dokkum (2001, PASP, 113, 1420), Pych (2004, PASP, 116, 148), and the IRAF task xzap by Dickinson are tested using both simulated and real data. It is found that detection efficiency is independent of the density of cosmic rays in an image, being more strongly affected by the density of real objects in the field. As expected, spurious detections and alterations to real data in the cleaning process are also significantly increased by high object densities. We find the Rhoads' linear filtering method to produce the best performance in the detection of cosmic ray events; however, the popular van Dokkum algorithm exhibits the highest overall performance in terms of detection and cleaning.

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Beyond the inherent technical challenges, current research into the three dimensional surface correspondence problem is hampered by a lack of uniform terminology, an abundance of application specific algorithms, and the absence of a consistent model for comparing existing approaches and developing new ones. This paper addresses these challenges by presenting a framework for analysing, comparing, developing, and implementing surface correspondence algorithms. The framework uses five distinct stages to establish correspondence between surfaces. It is general, encompassing a wide variety of existing techniques, and flexible, facilitating the synthesis of new correspondence algorithms. This paper presents a review of existing surface correspondence algorithms, and shows how they fit into the correspondence framework. It also shows how the framework can be used to analyse and compare existing algorithms and develop new algorithms using the framework's modular structure. Six algorithms, four existing and two new, are implemented using the framework. Each implemented algorithm is used to match a number of surface pairs. Results demonstrate that the correspondence framework implementations are faithful implementations of existing algorithms, and that powerful new surface correspondence algorithms can be created. (C) 2004 Elsevier Inc. All rights reserved.

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Poly-beta-hydroxyalkanoate (PHA) is a polymer commonly used in carbon and energy storage for many different bacterial cells. Polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), store PHA anaerobically through metabolism of carbon substrates such as acetate and propionate. Although poly-beta-hydroxybutyrate (PHB)and poly-beta-hydroxyvalerate (PHV) are commonly quantified using a previously developed gas chromatography (GC) method, poly-beta-hydroxy-2-methyl valerate (PH2MV) is seldom quantified despite the fact that it has been shown to be a key PHA fraction produced when PAOs or GAOs metabolise propionate. This paper presents two GC-based methods modified for extraction and quantification of PHB, PHV and PH2MV from enhanced biological phosphorus removal (EBPR) systems. For the extraction Of PHB and PHV from acetate fed PAO and GAO cultures, a 3% sulfuric acid concentration and a 2-20 h digestion time is recommended, while a 10% sulfuric acid solution digested for 20 h is recommended for PHV and PH2MV analysis from propionate fed EBPR systems. (c) 2005 Elsevier B.V. All rights reserved.