Engineering Commons^™

Investigation Of Image Feature Extraction By A Genetic Algorithm, Steven P. Brumby, James P. Theiler, Simon J. Perkins, Neal R. Harvey, John J. Szymanski, Jeffrey J. Bloch, Melanie Mitchell

Computer Science Faculty Publications and Presentations

We describe the implementation and performance of a genetic algorithm which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photography data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.

Two Approaches To Critical Path Scheduling For A Heterogeneous Environment, Guangxia Liu

Computer Science Theses & Dissertations

Advances in computing and networking technologies are making large scale distributed heterogeneous computing a reality. Multi-Disciplinary Optimization (MDO) is a class of applications that is being addressed under this paradigm. It consists of multiple heterogeneous modules interacting with each other to solve an overall design problem. An efficient implementation of such an application requires scheduling heterogeneous modules (with different computing and disk 1/0 requirements) on a heterogeneous set of resources (with different CPU, memory, disk IO specifications).

Given a set of tasks and a set of resources, an optimal schedule of the tasks on the resources is very hard to …