The aim of this study was to assess the preference of pregnant women for mode of delivery in an uncomplicated pregnancy and reasons of their choice, also to determine if maternal characteristics were predictors of maternal preference. Pregnant women applying to the antenatal clinic for a routine control visit were recruited. After verbal consents, a questionnaire was administered to 1,588 pregnant women. Of the women questioned, 84.1% opted for vaginal delivery whereas only 15.9% opted for an elective caesarean delivery. The main reasons for vaginal delivery preference were; earlier healing and earlier hospital discharge, being a more physiological way of delivery and previous vaginal delivery history. The most common reasons for choosing caesarean delivery were; fear of vaginal delivery, tubal ligation demand and to avoid labour pain. Educational status, occupation and gestational age were not found to be influencing factors but age, parity and monthly income were found to be influencing factors for maternal preference.

This paper introduces the work on building a machine translation system for Arabic-to-Turkish in the news domain. Our work includes collecting parallel datasets in several ways for a new and low-resource language pair, building baseline systems with state-ofthe-art architectures and developing language specific algorithms for better translation. Parallel datasets are mainly collected three different ways; i) translating Arabic texts into Turkish by professional translators, ii) exploiting the web for open-source Arabic-Turkish parallel texts, iii) using back-translation. We performed preliminary experiments for Arabicto-Turkish machine translation with neural (Marian) machine translation tools with a novel morphologically motivated vocabulary reduction method.

We describe the TÜBİTAK Turkish-English machine translation systems submissions in both directions for the WMT 2016: News Translation Task. We experiment with phrase-based and hierarchical phrase-based systems for both directions using word-level and morpheme-level representations for the Turkish side. Finally we perform system combination which results in 0.5 BLEU increase for Turkishto-English and 0.3 BLEU increase for English-to-Turkish.