Quantum Chromodynamics (QCD) is believed to be the theory of strong interactions. At high energies, it has been successfully applied to explain the interactions in accelerators. At these energies, the method used to do the calculations is perturbation theory. But at low energies, since the strong coupling constant becomes large, perturbation theory is no longer applicable. Hence, one needs non-perturbative approaches. Some of these approaches are based on the fundamental QCD Lagrangian, such as the QCD sum rules or lattice calculations. Some others use an effective theory approach to relate experimental observables one to the other. Chiral Perturbation Theory (ChPT) is one of these approaches. In this thesis, we make a review of chiral perturbation theory and its applications to study the mixing phenomenon between the neutral pseudoscalar mesons eta and eta-prime.

In this study, Turkey&rsquo / s Internet visibility will be analyzed based on data to be collected from multiple different resources (such as / Google, Yahoo, Altavista, Bing and AOL). Analysis work will involve inspection of DNS queries, Web crawling and some other similar techniques. Our goal is to investigate global Internet and find webs that has common pattern of representing Internet visibility of Turkey and compare their characteristics with other webs&#039 / on the world and discover their similarities and differences.

The aim of this study is to solve Fault Detection and Diagnosis (FDD) problems occurring in nonlinear dynamical systems by using model and knowledge-based FDD methods and to give a priority and a degree about faults. For this purpose, three model-based FDD approaches, called FDD by utilizing principal component analysis (PCA), system identification based FDD and inverse model based FDD are introduced. Performances of these approaches are tested on different nonlinear dynamical systems starting from simple to more complex. New fuzzy discrete event system (FDES) and fuzzy discrete event dynamical system (FDEDS) concepts are introduced and their applicability to an FDD problem is investigated. Two knowledge-based FDD methods based on FDES and FDEDS structures using a fuzzy rule-base are introduced and they are tested on nonlinear dynamical systems. New properties related to FDES and FDEDS such as fuzzy observability and diagnosibility concepts and a relation between them are illustrated. A dynamical rule-base extraction method with classification techniques and a dynamical and a static diagnoser design methods are also introduced. A nonlinear and event based extension of the Luenberger observer and its application as a diagnoser to isolate faults are illustrated. Finally, comparisons between the proposed model and knowledge-based FDD methods are made.