Differential evolution based total transfer capability assessment with optimal dispatch

In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.

Embedded Voxel Colouring

The reconstruction of a complex scene from multiple images is a fundamental problem in the field of computer vision. Volumetric methods have proven to be a strong alternative to traditional correspondence-based methods due to their flexible visibility models. In this paper we analyse existing methods for volumetric reconstruction and identify three key properties of voxel colouring algorithms: a water-tight surface model, a monotonic carving order, and causality. We present a new Voxel Colouring algorithm which embeds all reconstructions of a scene into a single output. While modelling exact visibility for arbitrary camera locations, Embedded Voxel Colouring removes the need for a priori threshold selection present in previous work. An efficient implementation is given along with results demonstrating the advantages of posteriori threshold selection.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Reproductive dynamics of endeavour prawns, Metapenaeus endeavouri and M-ensis, in Albatross Bay, Gulf of Carpentaria, Australia

The spawning patterns of two penaeid prawns, Metapenaeus endeavouri (Schmitt) and M. ensis (De Haan), were examined from data collected at 45 stations between March 1986 and March 1992. An index of population fecundity based on the abundance, proportion and fecundity of sexually mature females was used as a measure of spawning output of the prawn stock. The population fecundity index for M. ensis was higher than that for M. endeavouri. The monthly population fecundity index for M. endeavouri varied markedly among years, while that for M. ensis was consistent among years. Spawning of M. endeavouri occurred year-round, while that of M. ensis was concentrated mainly in spring (September to November). For M. endeavouri, a minor spawning, derived from a relatively small number of summer spawners, occurred in the 20 to 30 m offshore waters in summer. In early summer (after May), the major spawning group consisted of large females from the winter-spawning cohort, and the spawning area shifted to depths of 30 to 60 m. In winter (July), the major spawning, derived from the winter-spawning cohort, occurred at depths of 20 to 40 m. For M. ensis, the major spawning, derived from the spring-spawning cohort, was observed in depths < 50 m and was concentrated particularly in inshore waters ( 50 m). These results suggest that mature female M. endeavouri and M. ensis move offshore (>40 m) by May and July, respectively, and return to shallow waters (

Finite difference time domain (FDTD) method for modeling the effect of switched gradients on the human body in MRI

Numerical modeling of the eddy currents induced in the human body by the pulsed field gradients in MRI presents a difficult computational problem. It requires an efficient and accurate computational method for high spatial resolution analyses with a relatively low input frequency. In this article, a new technique is described which allows the finite difference time domain (FDTD) method to be efficiently applied over a very large frequency range, including low frequencies. This is not the case in conventional FDTD-based methods. A method of implementing streamline gradients in FDTD is presented, as well as comparative analyses which show that the correct source injection in the FDTD simulation plays a crucial rule in obtaining accurate solutions. In particular, making use of the derivative of the input source waveform is shown to provide distinct benefits in accuracy over direct source injection. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and the source injection method has been verified against examples with analytical solutions. Results are presented showing the spatial distribution of gradient-induced electric fields and eddy currents in a complete body model.

Acquisition and loss of Porphyromonas gingivalis, Actinobacillus actinomycetemcomitans and Prevotella intermedia over a 5-year period: effect of a triclosan/copolymer dentifrice

Objectives: The present study describes the natural history of Porphyromonas gingivalis, Actinobacillus actinomycetemcomitans and Prevotella intermedia over a 5-year period and the effect of a triclosan/copolymer dentifrice on these organisms in a normal adult population. Material and Methods: Subgingival plaque samples were collected from 504 adult volunteers. Probing pocket depths (PPD) and relative attachment levels were measured using an automated probe. Participants were matched for disease status (CPI), plaque index, age and gender, and allocated to receive either a triclosan/copolymer or placebo dentifrice. Re-examination and subgingival plaque sampling was repeated after 1, 2, 3, 4 and 5 years. P. gingivalis, A. actinomycetemcomitans and P. intermedia were detected and quantitated using an enzyme linked immunosorbent assay. Logistic regression and generalised linear modelling were used to analyse the data. Results: This 5-year longitudinal study showed considerable volatility in acquisition and loss (below the level of detection) of all three organisms in this population. Relatively few subjects had these organisms on multiple occasions. While P. gingivalis was related to loss of attachment and to PPD greater than or equal to3.5 mm, there was no relationship between A. actinomycetemcomitans or P. intermedia and disease progression over the 5 years of the study. Smokers with P. gingivalis had more PPD greater than or equal to3.5 mm than smokers without this organism. There was no significant effect of the triclosan dentifrice on P. gingivalis or A. actinomycetemcomitans . Subjects using triclosan were more likely to have P. intermedia than those not using the dentifrice; however this did not translate into these subjects having higher levels of P. intermedia and its presence was uniform showing no signs of increasing over the course of the study. Conclusion: The present 5-year longitudinal study has shown the transient nature of colonisation with P. gingivalis , A. actinomycetemcomitans and P. intermedia in a normal adult population. The use of a triclosan-containing dentifrice did not lead to an overgrowth of these organisms. The clinical effect of the dentifrice would appear to be independent of its antimicrobial properties.

Estimating physical activity level: The role of domestic activities

Appropriate measures of physical activity are essential for determining the population prevalence of physical activity, for tracking trends over time, and for guiding intervention efforts. Physical activity measurement is characterised by the synthesis of information on the type, frequency, intensity, and duration of activity over a specified period. To date, emphasis in physical activity assessment has been on the measurement of leisure time physical activities. However, some domestic and transport related activities entail energy expenditures equivalent to moderate intensity of 3.0–6.0 METS1 considered to be of sufficient intensity to achieve a health benefit are yet to be included in routine population level physical activity surveillance. This leads to population estimates based only on measures of leisure time physical activities.

Winding patterns for biplanar MRI shim coils with rectangular and circular target-field regions

A method is presented for calculating the winding patterns required to design independent zonal and tesseral biplanar shim coils for magnetic resonance imaging. Streamline, target-field, Fourier integral and Fourier series methods are utilized. For both Fourier-based methods, the desired target field is specified on the surface of the conducting plates. For the Fourier series method it is possible to specify the target field at additional depths interior to the two conducting plates. The conducting plates are confined symmetrically in the xy plane with dimensions 2a x 2b, and are separated by 2d in the z direction. The specification of the target field is symmetric for the Fourier integral method, but can be over some asymmetric portion pa < x < qa and sb < y < tb of the coil dimensions (-1 < p < q < 1 and -1 < s < t < 1) for the Fourier series method. Arbitrary functions are used in the outer sections to ensure continuity of the magnetic field across the entire coil face. For the Fourier series case, the entire field is periodically extended as double half-range sine or cosine series. The resultant Fourier coefficients are substituted into the Fourier series and integral expressions for the internal and external magnetic fields, and stream functions on both the conducting surfaces. A contour plot of the stream function directly gives the required coil winding patterns. Spherical harmonic analysis of field calculations from a ZX shim coil indicates that example designs and theory are well matched.

Bayesian estimation of g-and-k distributions using MCMC

In this paper we investigate a Bayesian procedure for the estimation of a flexible generalised distribution, notably the MacGillivray adaptation of the g-and-κ distribution. This distribution, described through its inverse cdf or quantile function, generalises the standard normal through extra parameters which together describe skewness and kurtosis. The standard quantile-based methods for estimating the parameters of generalised distributions are often arbitrary and do not rely on computation of the likelihood. MCMC, however, provides a simulation-based alternative for obtaining the maximum likelihood estimates of parameters of these distributions or for deriving posterior estimates of the parameters through a Bayesian framework. In this paper we adopt the latter approach, The proposed methodology is illustrated through an application in which the parameter of interest is slightly skewed.

Optimisation of poly-b-hydroxyalkanoate analysis using gas chromatography for enhanced biological phosphorus removal systems

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.

Improved joint control using a genetic algorithm for a humanoid robot

This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Hormonal factors and risk of aneurysmal subarachnoid hemorrhage - An international population-based, case-control study

Background and Purpose-Subarachnoid hemorrhage (SAH) is more common in women than in men, but the role of hormonal factors in its etiology remains uncertain. The aim of this study was to examine the relationship between hormonal factors and risk of SAH in women. Methods-This was a prospective, multicenter, population-based, case-control study performed in 4 major urban centers in Australia and New Zealand. Two hundred sixty-eight female cases of first-ever aneurysmal SAH occurred during 1995-1998. Controls were 286 frequency-matched women from the general population of each center. Outcome measures included risk of SAH associated with use of oral contraceptive pills (OCPs), hormone replacement therapy (HRT), and various endogenous hormonal factors including menstrual patterns, parity, age at birth of first child, and breast-feeding practices. Results-Cases and controls did not differ with regard to menstrual and reproductive history except in age at bir th of first child, where older age was associated with reduced risk of SAH (odds ratio [OR], 0.63; 95% CI, 0.43, 0.91). Relative to never use of HRT, the adjusted OR for over use of HRT was 0.64 (95% CI, 0.41, 0.98), which did not alter significantly after further adjustment for possible confounding factors. Borderline evidence of an inverse association was detected for past use of HRT (adjusted OR, 0.59; 95% CI, 0.30, 1.13) and current use of HRT (adjusted OR, 0.67; 95% CI, 0.40, 1.13), but there was no evidence of an association for use of OCPs (adjusted OR, 0.97; 95% CI, 0.58, 1.60). Conclusions-The risks of SAH are lower in women whose first pregnancy is at an older age and women who have ever used HRT but not OCPs. The findings suggest an independent etiologic role for hormonal factors in the pathogenesis of aneurysmal SAH and provide support for a protective role fur HRT on risk of SAH in postmenopausal women.

Cervical screening: population-based comparisons between self-reported survey and registry-derived Pap test rates

Objective: To compare self-reported cervical screening rates, as recorded in the 1998 NSW Health Survey, with registry-based cervical screening rates for NSW for the same period; and to examine factors associated with over-estimates of cervical screening rates by self-report. Methods: Self-reported cervical screening data was extracted from the 1998 NSW Health Survey, biennial screening rates estimated and compared with biennial cervical screening rates for 1997-98, as recorded on the NSW Pap Test Register (PTR). Rates and differences were related to socio-demographic characteristics of the 17 Area Health Services of NSW. Results: According to the 1998 NSW Health Survey, 74% of women reported having a Pap test during the previous two years. The equivalent rate recorded on the NSW PTR for 1997-98 was 62% (p