A general-purpose tunable landscape generator

The research literature on metalieuristic and evolutionary computation has proposed a large number of algorithms for the solution of challenging real-world optimization problems. It is often not possible to study theoretically the performance of these algorithms unless significant assumptions are made on either the algorithm itself or the problems to which it is applied, or both. As a consequence, metalieuristics are typically evaluated empirically using a set of test problems. Unfortunately, relatively little attention has been given to the development of methodologies and tools for the large-scale empirical evaluation and/or comparison of metaheuristics. In this paper, we propose a landscape (test-problem) generator that can be used to generate optimization problem instances for continuous, bound-constrained optimization problems. The landscape generator is parameterized by a small number of parameters, and the values of these parameters have a direct and intuitive interpretation in terms of the geometric features of the landscapes that they produce. An experimental space is defined over algorithms and problems, via a tuple of parameters for any specified algorithm and problem class (here determined by the landscape generator). An experiment is then clearly specified as a point in this space, in a way that is analogous to other areas of experimental algorithmics, and more generally in experimental design. Experimental results are presented, demonstrating the use of the landscape generator. In particular, we analyze some simple, continuous estimation of distribution algorithms, and gain new insights into the behavior of these algorithms using the landscape generator.

Interpretation of the temperature dependence of rate constants in biosensor studies

A comparison is made between Arrhenius and transition-state analyses of the temperature dependence of rate constants reported in four published biosensor studies. Although the Eyring transition-state theory seemingly affords a more definitive solution to the problem of characterizing the activation energetics, the analysis is equivocal because of inherent assumptions about reaction mechanism and the magnitude of the transmission coefficient. In view of those uncertainties it is suggested that a preferable course of action entails reversion to the empirical Arrhenius analysis with regard to the energy of activation and a preexponential factor. The former is essentially equivalent to the enthalpy of activation, whereas the magnitude of the latter indicates directly the extent of disparity between the frequency of product formation and the universal frequency factor (temperature multiplied by the ratio of the Boltzmann and Planck constants) and hence the likelihood of a more complicated kinetic mechanism than that encompassed by the Eyring transition-state theory. (C) 2004 Elsevier Inc. All rights reserved.

Comparison of virulence gene profiles of Escherichia coli strains isolated from healthy and diarrheic swine

A combination of uni- and multiplex PCR assays targeting 58 virulence genes (VGs) associated with Escherichia coli strains causing intestinal and extraintestinal disease in humans and other mammals was used to analyze the VG repertoire of 23 commensal E. coli isolates from healthy pigs and 52 clinical isolates associated with porcine neonatal diarrhea (ND) and postweaning diarrhea (PWD). The relationship between the presence and absence of VGs was interrogated using three statistical methods. According to the generalized linear model, 17 of 58 VGs were found to be significant (P < 0.05) in distinguishing between commensal and clinical isolates. Nine of the 17 genes represented by iha, hlyA, aidA, east1, aah, fimH, iroN(E).(coli), traT, and saa have not been previously identified as important VGs in clinical porcine isolates in Australia. The remaining eight VGs code for fimbriae (F4, F5, F18, and F41) and toxins (STa, STh, LT, and Stx2), normally associated with porcine enterotoxigenic E. coli. Agglomerative hierarchical algorithm analysis grouped E. coli strains into subclusters based primarily on their serogroup. Multivariate analyses of clonal relationships based on the 17 VGs were collapsed into two-dimensional space by principal coordinate analysis. PWD clones were distributed in two quadrants, separated from ND and commensal clones, which tended to cluster within one quadrant. Clonal subclusters within quadrants were highly correlated with serogroups. These methods of analysis provide different perspectives in our attempts to understand how commensal and clinical porcine enterotoxigenic E. coli strains have evolved and are engaged in the dynamic process of losing or acquiring VGs within the pig population.

Analysis and implementation of a new constant acceleration subcycling algorithm

An algorithm for explicit integration of structural dynamics problems with multiple time steps is proposed that averages accelerations to obtain subcycle states at a nodal interface between regions integrated with different time steps. With integer time step ratios, the resulting subcycle updates at the interface sum to give the same effect as a central difference update over a major cycle. The algorithm is shown to have good accuracy, and stability properties in linear elastic analysis similar to those of constant velocity subcycling algorithms. The implementation of a generalised form of the algorithm with non-integer time step ratios is presented. (C) 1997 by John Wiley & Sons, Ltd.

Willingness of Sri Lankan farmers to pay for a scheme to conserve elephants: An empirical analysis

This paper explores the feasibility of adopting an integrated economic approach to raise farmers’ tolerance of the presence of elephants on their farming lands. Responses to this approach were sought from a sample of farmers in the areas affected by human elephant conflict in the northwestern province of Sri Lanka. Results from a contingent valuation survey of their willingness to pay for a scheme to conserve elephants are also reported. Two separate logit regression analyses were undertaken to examine the factors that influence the farmers’ responses for the payment principle question and their opinions on the integrated economic approach. Although found that the majority of the respondents expressed their willingness to pay for the proposed scheme and supported for the implementation of the integrated approach, we have insufficient data yet to determine if their support and financial contribution would be sufficient to set up this programme and also to predict its economic viability. Nevertheless, the overall finding of this study provides an improved economic assessment of the farmers’ attitudes towards the wild elephant in Sri Lanka. At the same time the study shows that, contrary to commonly held assumptions, farmers in this developing country, do support wildlife conservation.

Addressing shortcomings in the Household Responsibility System - Empirical analysis of the Two-Farmland System in Shandong Province

Despite apparent overwhelming benefits, implementation of the Household Responsibility System (HRS) in China contained a number of flaws. The Two-Farmland System (TFS), which originated in Pingdu City in Shandong Province, sought to address the twin problems of land fragmentation and economies of size. A stochastic frontier production function analysis that isolates the impacts of land allocation reforms suggests that the TFS increased efficiency by around 7%. This article highlights the need for empirical analysis to assess objectively the merits or otherwise of particular reforms. (C) 2002 Elsevier Science Inc. All rights reserved.

Testing insect movement theory: empirical analysis of pest data routinely collected from agricultural crops

Observations of an insect's movement lead to theory on the insect's flight behaviour and the role of movement in the species' population dynamics. This theory leads to predictions of the way the population changes in time under different conditions. If a hypothesis on movement predicts a specific change in the population, then the hypothesis can be tested against observations of population change. Routine pest monitoring of agricultural crops provides a convenient source of data for studying movement into a region and among fields within a region. Examples of the use of statistical and computational methods for testing hypotheses with such data are presented. The types of questions that can be addressed with these methods and the limitations of pest monitoring data when used for this purpose are discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulae for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.

Convergence analysis of a discrete-time single-unit gradient ICA algorithm

We revisit the one-unit gradient ICA algorithm derived from the kurtosis function. By carefully studying properties of the stationary points of the discrete-time one-unit gradient ICA algorithm, with suitable condition on the learning rate, convergence can be proved. The condition on the learning rate helps alleviate the guesswork that accompanies the problem of choosing suitable learning rate in practical computation. These results may be useful to extract independent source signals on-line.

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

The status and relevance of Vietnamese journalism education: An empirical analysis

Based primarily on data from indepth interviews with senior journalists and journalism educators as well as a content analysis of journalism curricula, this paper sets out to provide an overview of the demand, overall provision structure, teaching materials and methods of Vietnamese journalism education. It first shows that with a fast expansion in both size and substance, the Vietnamese media system is beginning to feel the urgent need for formal journalism education. However, the country's major journalism programs have been criticised for producing hundreds of unqualified journalism graduates a year. In general, the most deplorable aspects of Vietnamese journalism education include its body of outdated and awkward teaching material, its undue focus on theories and politics at the expense of practical training, its lack of qualified teaching staff and its inadequate teaching resources.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.