31,655 research outputs found
Product 45
No full textContribution to a curated book of Australian 45rpm single covers. This contribution is a discussion about the possibilities afforded by available technologies in the late 70s in the production of music-related artwork: record covers, posters, handbills etc
Famished, a performance with poetry, vocals and musical score, in collaboration with vocalist Lauren Kinsella and composer Ed Bennett
No full textFamished, the performance, based on the book of the same name, is an 80-minute live performance with poetry, vocalisation and an electronic score. It is touring 13 venues in the UK and Ireland, including at the Dublin Literary Festival on May 25 and the Belfast Book Festival on June 16, 2019
Benefits of a population: five mechanisms that advantage population-based algorithms
No full textThis paper identifies five distinct mechanisms by which a population-based algorithm might have an advantage over a solo-search algorithm in classical optimization. These mechanisms are illustrated through a number of toy problems. Simulations are presented comparing different search algorithms on these problems. The plausibility of these mechanisms occurring in classical optimization problems is discussed. The first mechanism we consider relies on putting together building blocks from different solutions. This is extended to include problems containing critical variables. The second mechanism is the result of focusing of the search caused by crossover. Also discussed in this context is strong focusing produced by averaging many solutions. The next mechanism to be examined is the ability of a population to act as a low-pass filter of the landscape, ignoring local distractions. The fourth mechanism is a population's ability to search different parts of the fitness landscape, thus hedging against bad luck in the initial position or the decisions it makes. The final mechanism is the opportunity of learning useful parameter values to balance exploration against exploitation
Introduction
No full textThis volume draws together essays from leading scholars on the challenges that arise for health, law, policy and ethics at the intersections of health, rights and globalization. The papers in this volume address global issues in public health, globalization and bioethics, and globalization and biotechnology. This volume will be invaluable to all those interested in global issues in health
Farrell, Ed. Song - Couple of Fellows.
No full textAn audio clip of Ed Farrell and another person singing Couple of Fellows with accordion accompaniment. It is sung in English with commentary at the end by Ed Farrell: "Mom used to sing it; she’d make us say our prayers and then she’d sing to us.
UA68/8/2 Ed Stansbury Oral History
No full textAn interview on November 5, 1976 with Ed Stansbury, WKU physical education faculty member 1934-1947 conducted by James Bennett
Genetic Drift in Genetic Algorithm Selection Schemes
No full textA method for calculating genetic drift in terms of changing population fitness variance is presented. The method allows for an easy comparison of different selection schemes and exact analytical results are derived for traditional generational selection, steady-state selection with varying generation gap, a simple model of Eshelman's CHC algorithm, and evolution strategies. The effects of changing genetic drift on the convergence of a GA are demonstrated empirically
Togetherness
No full textTogetherness is an immersive work which explores contradictory notions of independence, pluralism and unity in music.
Togetherness was commissioned with support from the Leverhulme Trust and Moving On Music. The premiere was given by Decibel at the Moving On Music ‘Tempered’ Festival in the Crescent Arts Centre, Belfast in November 2015
Learning the large-scale structure of the max-sat landscape using populations
No full textA new algorithm for solving MAX-SAT problems is introduced which clusters good solutions, and restarts the search from the closest feasible solution to the centroid of each cluster. This is shown to be highly efficient for finding good solutions of large MAX-SAT problems. We argue that this success is due to the population learning the large-scale structure of the fitness landscape. Systematic studies of the landscape are presented to support this hypothesis. In addition, a number of other strategies are tested to rule out other possible explanations of the success. Preliminary results are shown indicating that extensions of the proposed algorithm can give similar improvements on other hard optimisation problems
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