It is generally believed that good modularization of software leads to systems which are easier to design, develop, test, maintain and evolve [1]. Software clustering using search–based techniques has been well studied using a hill climbing approach [2,4,5,6]. Hill climbing suffers from the problem of local optima, so some improvement may be expected by by considering more sophisticated search-...

As the size of the Internet increases, the amount of data available to users has dramatically risen, resulting in an information overload for users. This work involved the creation of an intelligent information news filtering system named INFOS (Intelligent News Filtering Organizational System) to reduce the user’s search burden by automatically eliminating Usenet news articles predicted to be ...

As the size of the Internet increases, the amount of data available to users has dramatically risen, resulting in an information overload for users. This work shows that information overload is a problem, and that data is organized poorly by existing browsers. To address these problems, an intelligent information news filtering system named INFOS (Intelligent News Filtering Organizational Syste...

The up-link bandwidth in satellite networks and in advanced traffic wireless information system is very limited. A server broadcasts data files provided by different independent providers and accessed by many clients in a round-robin manner. The clients who access these files may have different patterns of access. Some clients may wish to access several files in any order (AND), some wish to ac...

Title of dissertation: HILL-CLIMBING SMT PROCESSOR RESOURCE DISTRIBUTION Seungryul Choi, Doctor of Philosophy, 2006 Dissertation directed by: Professor Donald Yeung Department of Electrical and Computer Engineering The key to high performance in SMT processors lies in optimizing the shared resources distribution among simultaneously executing threads. Existing resource distribution techniques o...

Learning the structure of a Bayesian Network (BN) with score-based solutions involves exploring search space possible graphs and moving towards graph that maximises given objective function. Some algorithms offer exact guarantee to return highest score, while others approximate in exchange for reduced computational complexity. This paper describes an BN learning algorithm, which we call Model A...