Understanding Algorithm Performance on an Oversubscribed Scheduling Application

The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithms performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm

Improved sampling of the pareto-front in multiobjective genetic optimizations by steady-state evolution: a Pareto converging genetic algorithm

Previous work on multiobjective genetic algorithms has been focused on preventing genetic drift and the issue of convergence has been given little attention. In this paper, we present a simple steady-state strategy, Pareto Converging Genetic Algorithm (PCGA), which naturally samples the solution space and ensures population advancement towards the Pareto-front. PCGA eliminates the need for sharing/niching and thus minimizes heuristically chosen parameters and procedures. A systematic approach based on histograms of rank is introduced for assessing convergence to the Pareto-front, which, by definition, is unknown in most real search problems. We argue that there is always a certain inheritance of genetic material belonging to a population, and there is unlikely to be any significant gain beyond some point; a stopping criterion where terminating the computation is suggested. For further encouraging diversity and competition, a nonmigrating island model may optionally be used; this approach is particularly suited to many difficult (real-world) problems, which have a tendency to get stuck at (unknown) local minima. Results on three benchmark problems are presented and compared with those of earlier approaches. PCGA is found to produce diverse sampling of the Pareto-front without niching and with significantly less computational effort

Large-scale atomistic density functional theory calculations of phosphorus-doped silicon quantum bits

We present density functional theory calculations of phosphorus dopants in bulk silicon and of several properties relating to their use as spin qubits for quantum computation. Rather than a mixed pseudopotential or a Heitler-London approach, we have used an explicit treatment for the phosphorus donor and examined the detailed electronic structure of the system as a function of the isotropic doping fraction, including lattice relaxation due to the presence of the impurity. Doping electron densities and spin densities are examined in order to study the properties of the dopant electron as a function of the isotropic doping fraction. Doping potentials are also calculated for use in calculations of the scattering cross-sections of the phosphorus dopants, which are important in the understanding of electrically detected magnetic resonance experiments. We find that the electron density around the dopant leads to non-spherical features in the doping potentials, such as trigonal lobes in the (001) plane at energy scales of +12 eV near the nucleus and of -700 meV extending away from the dopants. These features are generally neglected in effective mass theory and will affect the coupling between the donor electron and the phosphorus nucleus. Our density functional calculations reveal detail in the densities and potentials of the dopants which are not evident in calculations that do not include explicit treatment of the phosphorus donor atom and relaxation of the crystal lattice. These details can also be used to parameterize tight-binding models for simulation of large-scale devices.Comment: 22 pages, 8 figure

Structure and energetics of helium adsorption on nanosurfaces

The ground and excited state properties of small helium clusters, 4He_N, containing nanoscale (~3-10 Angstroms) planar aromatic molecules have been studied with quantum Monte Carlo methods. Ground state structures and energies are obtained from importance-sampled, rigid-body diffusion Monte Carlo. Excited state energies due to helium vibrational motion are evaluated using the projection operator, imaginary time spectral evolution technique. We examine the adsorption of N helium atoms (N less than or equal to 24) on a series of planar aromatic molecules (benzene, naphthalene, anthracene, tetracene, phthalocyanine). The first layer of helium atoms is well-localized on the molecule surface, and we find well-defined localized excitations due to in-plane vibrational motion of helium on the molecule surface. We discuss the implications of these confined excitations for the molecule spectroscopy.Comment: 6 pages, 2 figures, QFS 2003 Symposium, submitted to J. Low Temp. Phy

Associations of height, leg length, and lung function with cardiovascular risk factors in the Midspan Family Study

<b>Background</b>: Taller people and those with better lung function are at reduced risk of coronary heart disease (CHD). Biological mechanisms for these associations are not well understood, but both measures may be markers for early life exposures. Some studies have shown that leg length, an indicator of pre-pubertal nutritional status, is the component of height most strongly associated with CHD risk. Other studies show that height-CHD associations are greatly attenuated when lung function is controlled for. This study examines (1) the association of height and the components of height (leg length and trunk length) with CHD risk factors and (2) the relative strength of the association of height and forced expiratory volume in one second (FEV1) with risk factors for CHD. <b>Subjects and methods</b>: Cross sectional analysis of data collected at detailed cardiovascular screening examinations of 1040 men and 1298 women aged 30–59 whose parents were screened in 1972–76. Subjects come from 1477 families and are members of the Midspan Family Study. <b>Setting</b>: The towns of Renfrew and Paisley in the West of Scotland. <b>Results</b>: Taller subjects and those with better lung function had more favourable cardiovascular risk factor profiles, associations were strongest in relation to FEV1. Higher FEV1 was associated with lower blood pressure, cholesterol, glucose, fibrinogen, white blood cell count, and body mass index. Similar, but generally weaker, associations were seen with height. These associations were not attenuated in models controlling for parental height. Longer leg length, but not trunk length, was associated with lower systolic and diastolic blood pressure. Longer leg length was also associated with more favourable levels of cholesterol and body mass index than trunk length. <b>Conclusions</b>:These findings provide indirect evidence that measures of lung development and pre-pubertal growth act as biomarkers for childhood exposures that may modify an individual's risk of developing CHD. Genetic influences do not seem to underlie height-CHD associations

Coping and Management Techniques Used by Chronic Low Back Pain Patients Receiving Treatment From Chiropractors.

OBJECTIVES:The purpose of this study was to describe coping strategies (eg, mechanisms, including self-treatment) that a person uses to reduce pain and its impact on functioning as reported by patients with chronic low back pain who were seen by doctors of chiropractic and how these coping strategies vary by patient characteristics. METHODS:Data were collected from a national sample of US chiropractic patients recruited from chiropractic practices in 6 states from major geographical regions of the United States using a multistage stratified sampling strategy. Reports of coping behaviors used to manage pain during the past 6 months were used to create counts across 6 domains: cognitive, self-care, environmental, medical care, social activities, and work. Exploratory analyses examined counts in domains and frequencies of individual items by levels of patient characteristics. RESULTS:A total of 1677 respondents with chronic low back pain reported using an average of 9 coping behaviors in the prior 6 months. Use of more types of behaviors were reported among those with more severe back pain, who rated their health as fair or poor and who had daily occurrences of pain. Exercise was more frequent among the healthy and those with less pain. Female respondents tended to report using more coping behaviors than men, and Hispanics more than non-Hispanics. CONCLUSION:Persons with chronic back pain were proactive in their coping strategies and frequently used self-care coping strategies like those provided by chiropractors in patient education. In alignment with patients' beliefs that their condition was chronic and lifelong, many patients attempted a wide range of coping strategies to relieve their pain

Comparing the Penman-Monteith equation and a modified Jarvis-Stewart model with an artificial neural network to estimate stand-scale transpiration and canopy conductance

The responses of canopy conductance to variation in solar radiation, vapour pressure deficit and soil moisture have been extensively modelled using a Jarvis-Stewart (JS) model. Modelled canopy conductance has then often been used to predict transpiration using the Penman-Monteith (PM) model. We previously suggested an alternative approach in which the JS model is modified to directly estimate transpiration rather than canopy conductance. In the present study we used this alternative approach to model tree water fluxes from an Australian native forest over an annual cycle. For comparative purposes we also modelled canopy conductance and estimated transpiration via the PM model. Finally we applied an artificial neural network as a statistical benchmark to compare the performance of both models. Both the PM and modified JS models were parameterised using solar radiation, vapour pressure deficit and soil moisture as inputs with results that compare well with previous studies. Both models performed comparably well during the summer period. However, during winter the PM model was found to fail during periods of high rates of transpiration. In contrast, the modified JS model was able to replicate observed sapflow measurements throughout the year although it too tended to underestimate rates of transpiration in winter under conditions of high rates of transpiration. Both approaches to modelling transpiration gave good agreement with hourly, daily and total sums of sapflow measurements with the modified JS and PM models explaining 87% and 86% of the variance, respectively. We conclude that these three approaches have merit at different time-scales. © 2009 Elsevier B.V. All rights reserved

COVNET : A cooperative coevolutionary model for evolving artificial neural networks

This paper presents COVNET, a new cooperative coevolutionary model for evolving artificial neural networks. This model is based on the idea of coevolving subnetworks. that must cooperate to form a solution for a specific problem, instead of evolving complete networks. The combination of this subnetwork is part of a coevolutionary process. The best combinations of subnetworks must be evolved together with the coevolution of the subnetworks. Several subpopulations of subnetworks coevolve cooperatively and genetically isolated. The individual of every subpopulation are combined to form whole networks. This is a different approach from most current models of evolutionary neural networks which try to develop whole networks. COVNET places as few restrictions as possible over the network structure, allowing the model to reach a wide variety of architectures during the evolution and to be easily extensible to other kind of neural networks. The performance of the model in solving three real problems of classification is compared with a modular network, the adaptive mixture of experts and with the results presented in the bibliography. COVNET has shown better generalization and produced smaller networks than the adaptive mixture of experts and has also achieved results, at least, comparable with the results in the bibliography

Long term trends of stand transpiration in a remnant forest during wet and dry years

Daily and annual rates of stand transpiration in a drought year and a non-drought year are compared in order to understand the adaptive responses of a remnant woodland to drought and predict the effect of land use change. Two methods were used to estimate stand transpiration. In the first, the ratio of sap velocity of a few trees measured for several hundred days to the mean sap velocity of many trees measured during brief sampling periods (generally 6-7 trees for 5 or 6 days), called the Esv method is used to scale temporally from the few intensive study periods. The second method used was the Penman-Monteith (P-M) equation (called the EPM method). Weather variables and soil moisture were used to predict canopy conductance, which in turn was used to predict daily and annual stand transpiration. Comparisons of daily transpiration estimated with the two methods showed larger values for the EPM method during a drought year and smaller values for the EPM when the rainfall was above average. Generally, though, annual estimates of stand transpiration were similar using the two methods. The Esv method produced an estimate of 318 mm (61% of rainfall) in the drought year and 443 mm (42%) in the year having above average rainfall. The EPM method estimated stand transpiration as 379 mm (73%) and 398 mm (37%), respectively, for the two years. Both estimates of annual stand transpiration demonstrated that the remnant forest showed resilience to an extreme and long-term drought. More importantly, the annual estimates showed that in dry years a larger proportion of rainfall was used as transpiration, and groundwater recharge was absent but in years with above average rainfall recharge was significantly increased. Changes in leaf area index were minimal between years and changes in stomatal conductance were the dominant mechanism for adapting to the drought. The remnant forest rapidly responded to increased water availability after the drought through a new flush of leaves and increased stomatal conductance. © 2007 Elsevier B.V. All rights reserved