abstract background: nursing process is a scientific approach in the provision of qualified nursing cares. however, in practice, the implementation of this process is faced with numerous challenges. with the knowledge of the challenges associated with the implementation of the nursing process, the nursing processes can be developed appropriately. due to the lack of comprehensive information on ...

The paper discusses three major issues First it discusses why it makes sense to approach problems in a hierarchical fashion It de nes the class of hierarchically decomposable functions that can be used to test the algorithms that approach problems in this fashion Finally the Bayesian optimization algorithm BOA is extended in order to solve the proposed class of problems

Abstract. A method is presented for constructing effective stochastic models for the timeevolution of spatial averages in finite-difference discretizations of partial differential equations. This method relies on the existence of a time-scale separation in the dynamics of the spatial averages and fine-grid variables. The spatial averages, thus, are treated as the slow variables in the system an...

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...