10,378 research outputs found
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RGFGA: An efficient representation and crossover for grouping genetic algorithms
There is substantial research into genetic algorithms that are used to group large numbers of
objects into mutually exclusive subsets based upon some fitness function. However, nearly all
methods involve degeneracy to some degree.
We introduce a new representation for grouping genetic algorithms, the restricted growth function
genetic algorithm, that effectively removes all degeneracy, resulting in a more efficient search. A new crossover operator is also described that exploits a measure of similarity between chromosomes in a population. Using several synthetic datasets, we compare the performance of our representation and crossover with another well known state-of-the-art GA method, a strawman
optimisation method and a well-established statistical clustering algorithm, with encouraging results
Discerning the Form of the Dense Core Mass Function
We investigate the ability to discern between lognormal and powerlaw forms
for the observed mass function of dense cores in star forming regions. After
testing our fitting, goodness-of-fit, and model selection procedures on
simulated data, we apply our analysis to 14 datasets from the literature.
Whether the core mass function has a powerlaw tail or whether it follows a pure
lognormal form cannot be distinguished from current data. From our simulations
it is estimated that datasets from uniform surveys containing more than
approximately 500 cores with a completeness limit below the peak of the mass
distribution are needed to definitively discern between these two functional
forms. We also conclude that the width of the core mass function may be more
reliably estimated than the powerlaw index of the high mass tail and that the
width may also be a more useful parameter in comparing with the stellar initial
mass function to deduce the statistical evolution of dense cores into stars.Comment: 6 pages, 2 figures, accepted for publication in PAS
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Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate time series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is important for many decision making activities. One area that has been largely overlooked so far is the particular type of time series where the data set consists of a large number of variables but with a small number of observations. In this paper we describe the development of a novel computational method based on Natural Computation and sparse matrices that bypasses the size restrictions of traditional statistical MTS methods, makes no distribution assumptions, and also locates the associated parameters. Extensive results are presented, where the proposed method is compared with both traditional statistical and heuristic search techniques and evaluated on a number of criteria. The results have implications for a wide range of applications involving the learning of short MTS models
Threat or boost: Social comparison affects older people’s performance differently depending on task domain
Objectives. In this research, we investigate whether social comparison with younger people can result in either a stereotype-based threat or boost in older people’s performance.
Methods. Study 1 used nationally representative data to establish domains of performance in which older people are either stereotypically disadvantaged or advantaged relative to younger people. Study 2 was an experiment to test how a potentially threatening versus control versus enhancing comparison with younger people would affect performance in negatively and positively stereotyped task domains.
Results. As predicted, compared with the control condition, stereotype threat caused performance decrements in both task domains. This effect was partially mediated by anxiety. Moreover, the enhancing social comparison boosted performance, but only on a crossword task, a task on which older people’s abilities are favorably stereotyped.
Discussion. The research demonstrates that a threatening comparison can result in underperformance by older people both in negatively and positively self-stereotyped task domains. It also demonstrates that social comparison with younger people can enhance older people’s performance in a positively stereotyped task domain. The implications for creating circumstances likely to enable older people to achieve their full potential are discussed
A Lattice Boltzmann Model of Binary Fluid Mixture
We introduce a lattice Boltzmann for simulating an immiscible binary fluid
mixture. Our collision rules are derived from a macroscopic thermodynamic
description of the fluid in a way motivated by the Cahn-Hilliard approach to
non-equilibrium dynamics. This ensures that a thermodynamically consistent
state is reached in equilibrium. The non-equilibrium dynamics is investigated
numerically and found to agree with simple analytic predictions in both the
one-phase and the two-phase region of the phase diagram.Comment: 12 pages + 4 eps figure
Magnetic inflation and stellar mass. IV. four low-mass kepler eclipsing binaries consistent with non-magnetic stellar evolutionary models
Low-mass eclipsing binaries (EBs) show systematically larger radii than model predictions for their mass, metallicity, and age. Prominent explanations for the inflation involve enhanced magnetic fields generated by rapid rotation of the star that inhibit convection and/or suppress flux from the star via starspots. However, derived
masses and radii for individual EB systems often disagree in the literature. In this paper, we continue to investigate low-mass EBs observed by NASA’s Kepler spacecraft, deriving stellar masses and radii using high-quality spacebased light curves and radial velocities from high-resolution infrared spectroscopy. We report masses and radii for three Kepler EBs, two of which agree with previously published masses and radii (KIC 11922782 and KIC 9821078). For the third EB (KIC 7605600), we report new masses and show the secondary component is likely fully convective (M2 = 0.17 ± 0.01M☉ and = - ☉ + R2 0.199 0.002R 0.001 ). Combined with KIC 10935310 from Han et al., we find that the masses and radii for four low-mass Kepler EBs are consistent with modern stellar evolutionary
models for M dwarf stars and do not require inhibited convection by magnetic fields to account for the stellar radii.Published versio
A Review and Meta-Analysis of Age-Based Stereotype Threat: Negative Stereotypes, Not Facts, Do the Damage.
Stereotype threat effects arise when an individual feels at risk of confirming a negative stereotype about their group and consequently underperforms on stereotype relevant tasks (Steele, 2010). Among older people, underperformance across cognitive and physical tasks is hypothesized to result from age-based stereotype threat (ABST) because of negative age-stereotypes regarding older adults’ competence. The present review and meta-analyses examine 22 published and 10 unpublished articles, including 82 effect sizes (N = 3882) investigating ABST on older people’s (Mage = 69.5) performance. The analysis revealed a significant small-to-medium effect of ABST (d = .28) and important moderators of the effect size. Specifically, older adults are more vulnerable to ABST when (a) stereotype-based rather than fact-based manipulations are used (d = .52); (b) when performance is tested using cognitive measures (d = .36); and (c) occurs reliably when the dependent variable is measured proximally to the manipulation. The review raises important theoretical and methodological issues, and areas for future research. (PsycINFO Database Record (c) 2015 APA, all rights reserved
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ICARUS: Intelligent coupon allocation for retailers using search
Many retailers run loyalty card schemes for their customers offering incentives in the form of money off coupons. The total value of the coupons depends on how much the customer has spent. This paper deals with the problem of finding the smallest set of coupons such that each possible total can be represented as the sum of a pre-defined number of coupons. A mathematical analysis of the problem leads to the development of a genetic algorithm solution. The algorithm is applied to real world data using several crossover operators and compared to well known straw-person methods. Results are promising showing that considerable time can be saved by using this method, reducing a few days worth of consultancy time to a few minutes of computation
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