OF THE DISSERTATION Composition of Image Analysis Processes through Object-Centered Hierarchical Planning by Leiguang Gong, Ph.D. Dissertation Director: Professor Casimir A. Kulikowski The present thesis describes a new approach to biomedical image interpretation | the knowledge-based composition of image analysis processes through object-centered hierarchical planning. Its computer implementat...

In this paper a new method for defining a transformation between a source color space and a more perceptual uniform color space will be presented. The main idea is to use a three dimensional FreeForm Deformation to deform a source color space in such a way, that the new distances between chosen color samples match psychophysically estimated data as close as possible. This deformation of space i...

When we encounter a malicious rumor or an infectious disease outbreak, immunizing k nodes of the relevant network with limited resources is always treated as an extremely effective method. The key challenge is how we can insulate limited nodes to minimize the propagation of those contagious things. In previous works, the best k immunised nodes are selected by learning the initial status of node...

Comparable to other optimization techniques, the performance of Evolution Strategies (ESs) depends on a suitable choice of internal strategy control parameters. Apart from a xed setting, ESs facilitate an adjustment of such parameters within a selfadaptation process. For step-size control in particular, various adaptation concepts have been evolved early in the development of ESs. These algorit...

Mutagenesis is a process which forces the coverage of certain zones of the search space during the generations of an evolution strategy, by keeping track of the covered ranges for the different variables in the so called gene matrix. Originally introduced as an artifact to control the automated stopping criterion in a memetic algorithm, ESLAT, it also improved the exploration capabilities of th...

Case-based problem-solving systems reason and learn from experiences, building up case libraries of problems and solutions to guide future reasoning. The expected bene ts of this learning process depend on two types of regularity: (1) problem-solution regularity, the relationship between problem-to-problem and solution-to-solution similarity measures that assures that solutions to similar prior...

A framework for knowledge-based scienti c discovery in geological databases has been developed. The discovery process consists of two main steps: context de nition and equation derivation. Context de nition properly de nes and formulates homogeneous regions, each of which is likely to produce a unique and meaningful analytic formula for the goal variable. Clustering techniques and a suite of vi...

Several evolutionary approaches have been applied to global optimization problems with significant success. Evolution strategies proved to be efficient global optimizers. However, these algorithms have several parameters which the setting is not simple. Thus, it is crucial to investigate how to set dynamically these parameters during the search. In this paper, a new parameter-less evolution str...

Due to the exibility in adapting to diierent tness landscapes, self-adaptive evolutionary algorithms (SA-EAs) have been gaining popularity in the recent past. In this paper, we postulate the properties that SA-EA operators should have for successful applications in real-valued search spaces. Speciically, population mean and variance of a number of SA-EA operators, such as various real-parameter...

Although techniques for using formal speci cations have been progressing, methods for developing formal speci cations themselves have improved little. To alleviate this problem, we propose a parallel re nement approach to speci cation acquisition where the designer uses an object-oriented speci cation representation while an underlying speci cation composition system manipulates an equivalent t...