1546 Tarihli İstanbul Vakıfları Tahrir Defterine Göre XVI. Yüzyıl İstanbul unda Kap Kacak Vakıfları

Informational Efficiency of the İstanbul Securities Exchange and Some Rationale for Public Regulation

The primary objective of this paper is to test informational efficiency of the A random walk test is performed for weak-form efficiency. In addition, day of the week effects are investigated to test semi-strong form efficiency. Empirical results verify that the İSE Composite Index is neither weak-form nor semi-strong form efficient although the nature and degree of inefficiency differ across pe...

İstanbul Technical University Institute of Science and Technology Face Recognition under Varying Illumination

ii PREFACE This study is a result of a successful joint-venture with my adviser Prof. Dr. Muhittin Gökmen. I am thankful to him for his continuous assistance on preparing this project. Special thanks to the assistants of the Computer Vision Laboratory for their steady support and help in many topics related with the project.

Prevalence of latent prostate cancer and prostatic intraepithelial neoplasia in İstanbul, Turkey: an autopsy study

Results: Th e prevalence of PCa was 19.8% and the decade rates (decades 5-8) were 9.5%, 12.5%, 18.8%, and 37%, respectively (P < 0.011). Th e rates of high-grade prostatic intraepithelial neoplasia (HGPIN) were 33.3%, 31.3%, 56.3%, and 25.9% for decades 5-8, respectively (P > 0.05). A total of 68.4% of PCa cases were HGPIN. Th ere was a statistically signifi cant correlation among HGPIN, PCa, a...

1546 Technical

cular disease (3 ). Such high concentrations of circulating adhesion molecules may be of interest for diagnostic and prognostic purposes, as demonstrated for ICAM-1 and P-selectin, which provide useful information in healthy individuals and in patients with cardiovascular diseases (9 ). However, reference values for healthy children and adults have not been defined. In the current study, we mea...

İstanbul Bi̇lgi̇ University Institute of Social Sciences Direction of Change Prediction in the Eur/usd Exchange Rate Volatility Using Neural Network Models