Yaşar University

About: Yaşar University is a education organization based out in Izmir, Turkey. It is known for research contribution in the topics: Exergy & Job shop scheduling. The organization has 760 authors who have published 1436 publications receiving 20813 citations. The organization is also known as: Yaşar Üniversitesi.

An indicator of monetary conditions for turkey

Abstract: In this study, a Monetary Conditions Index (MCI) for Turkey is constructed for the 2003-2008 period, using a VAR methodology. The MCI weights are estimated on the basis of generalized accumulated responses of the inflation rate to one standard deviation shock to the real short term interest rate and the real rate of appreciation. The responses of output and inflation to interest rate and exchange rate shocks exhibit patterns which point to the structural peculiarities of the Turkish economy. The monetary conditions reflected by the resulting index are consistent with the path of inflation and CBT remarks on the issue.

LGBTQIs in Turkey: the Challenges and Resilience of This Marginalized Group

Abstract: Lesbian, gay, bisexual, transgender, intersex, and queer (LGBTIQ) individuals constitute a large group of minority groups in Turkey. Because of the scarcity of non-existent systematic reviews on the sexual orientation discrimination of LGBTIQ individuals in Turkey, the present study aims to outline the major discriminatory practices against these individuals and fills the gap through a systematic literature review based on rigorous criteria. The present paper examines 21 selected papers, explores key emerging themes and recent developments to identify research gaps, and provides areas for future research. Therefore, “discrimination in employment and at the workplace,” “discrimination in health,” “discrimination in public service,” and “discrimination by the government” were identified as the major themes of the current review. Through these themes, it was further revealed that the key pillars of LGBT discrimination in Turkey rest on the legal frameworks, social institutions, and norms. The best ways to eradicate LGBT discrimination in Turkey rest on modifying, changing, or creating LGBT inclusive/supportive policies within these pillars.

Redesigning the assignment of internal auditors based on auditor utility

Abstract: This study presents a novel model for assignment of internal auditors to branches of businesses. Previous studies have concerned with minimizing the cost but in this model, aim is maximizing auditor’s utility. For this purpose an integer programming model introduced. The objective is maximizing the auditors’ total utility. Each branch has different impact values for auditors, which indicate auditors’ utility level in terms of location, size and type of branches. Also to keep the balance of auditor’s working days and total gained impact values particular constraints are defined for the integer programming model. This implementation has 3 particular steps; first is quantification of the branches’ effects on the auditors. AHP method is used to define branches’ impact values. The second is simulating the durations of auditing process. To minimize the effect of abnormal situations, durations are simulated. Last step is to reach the rotation of auditors, total working days and the total utility of the auditor; the integer programming model is solved by Python-Gurobi Optimizer.

A Preliminary Investigation on the Identification of Peer to Peer Network Applications

Abstract: Identification of P2P (peer to peer) applications inside network traffic plays an important role for route provisioning, traffic policing, flow prioritization, network service pricing, network capacity planning and network resource management. Inspecting and identifying the P2P applications is one of the most important tasks to have a network that runs efficiently. In this paper, we focus on identification of different P2P applications. To this end, we explore four commonly used supervised machine learning algorithms as C4.5, Ripper, SVM(Support Vector Machines), Naive Bayesian and well known unsupervised machine learning algorithm K-Means on four different datasets. We evaluate their performances to identify the P2P applications that each traffic flow belongs to. Evaluations show that, Ripper algorithm gives better results than the others.