Evaluation of VICAR software capability for land information support system needs

A preliminary evaluation of the processing capability of the VICAR software for land information support system needs is presented. The geometric and radiometric properties of four sets of LANDSAT data taken over the Elk River, Idaho quadrangle were compared. Storage of data sets, the means of location, pixel resolution, and radiometric and geometric characteristics are described. Recommended modifications of VICAR programs are presented

Experimental study on population-based incremental learning algorithms for dynamic optimization problems

Copyright @ Springer-Verlag 2005.Evolutionary algorithms have been widely used for stationary optimization problems. However, the environments of real world problems are often dynamic. This seriously challenges traditional evolutionary algorithms. In this paper, the application of population-based incremental learning (PBIL) algorithms, a class of evolutionary algorithms, for dynamic problems is investigated. Inspired by the complementarity mechanism in nature a Dual PBIL is proposed, which operates on two probability vectors that are dual to each other with respect to the central point in the genotype space. A diversity maintaining technique of combining the central probability vector into PBIL is also proposed to improve PBILs adaptability in dynamic environments. In this paper, a new dynamic problem generator that can create required dynamics from any binary-encoded stationary problem is also formalized. Using this generator, a series of dynamic problems were systematically constructed from several benchmark stationary problems and an experimental study was carried out to compare the performance of several PBIL algorithms and two variants of standard genetic algorithm. Based on the experimental results, we carried out algorithm performance analysis regarding the weakness and strength of studied PBIL algorithms and identified several potential improvements to PBIL for dynamic optimization problems.This work was was supported by UK EPSRC under Grant GR/S79718/01

Population-based incremental learning with associative memory for dynamic environments

Copyright © 2007 IEEE. Reprinted from IEEE Transactions on Evolutionary Computation. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In recent years there has been a growing interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) due to its importance in real world applications. Several approaches, such as the memory and multiple population schemes, have been developed for EAs to address dynamic problems. This paper investigates the application of the memory scheme for population-based incremental learning (PBIL) algorithms, a class of EAs, for DOPss. A PBIL-specific associative memory scheme, which stores best solutions as well as corresponding environmental information in the memory, is investigated to improve its adaptability in dynamic environments. In this paper, the interactions between the memory scheme and random immigrants, multi-population, and restart schemes for PBILs in dynamic environments are investigated. In order to better test the performance of memory schemes for PBILs and other EAs in dynamic environments, this paper also proposes a dynamic environment generator that can systematically generate dynamic environments of different difficulty with respect to memory schemes. Using this generator a series of dynamic environments are generated and experiments are carried out to compare the performance of investigated algorithms. The experimental results show that the proposed memory scheme is efficient for PBILs in dynamic environments and also indicate that different interactions exist between the memory scheme and random immigrants, multi-population schemes for PBILs in different dynamic environments

Performance limitations of observer-based feedback for transient energy growth suppression

Transient energy growth suppression is a common control objective for feedback flow control aimed at delaying transition to turbulence. A prevailing control approach in this context is observer-based feedback, in which a full-state feedback controller is applied to state estimates from an observer. The present study identifies a fundamental performance limitation of observer-based feedback control: whenever the uncontrolled system exhibits transient energy growth in response to optimal disturbances, control by observer-based feedback will necessarily lead to transient energy growth in response to optimal disturbances for the closed-loop system as well. Indeed, this result establishes that observer-based feedback can be a poor candidate for controller synthesis in the context of transient energy growth suppression and transition delay: the performance objective of transient energy growth suppression can never be achieved by means of observer-based feedback. Further, an illustrative example is used to show that alternative forms of output feedback are not necessarily subject to these same performance limitations, and should also be considered in the context of transient energy growth suppression and transition control.Comment: 7 pages; 1 figur

AgRISTARS: Renewable resources inventory. Land information support system implementation plan and schedule

The planning and scheduling of the use of remote sensing and computer technology to support the land management planning effort at the national forests level are outlined. The task planning and system capability development were reviewed. A user evaluation is presented along with technological transfer methodology. A land management planning pilot test of the San Juan National Forest is discussed

Controlled cavity-QED using a photonic crystal waveguide-cavity system

We introduce a photonic crystal waveguide-cavity system for controlling single photon cavity-QED processes. Exploiting Bloch mode analysis, and medium-dependent Green function techniques, we demonstrate that the propagation of single photons can be accurately described analytically, for integrated periodic waveguides with little more than four unit cells, including an output coupler. We verify our analytical approach by comparing to rigorous numerical calculations for a range of photonic crystal waveguide lengths. This allows one to nano-engineer various regimes of cavity-QED with unprecedented control. We demonstrate Purcell factors of greater than 1000 and on-chip single photon beta factors of about 80% efficiency. Both weak and strong coupling regimes are investigated, and the important role of waveguide length on the output emission spectra is shown, for vertically emitted emission and output waveguide emission