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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Diplomacy within the security framework in Turkey and Romania during the Interwar Period(Brill Academic Publishers, 2024) Department of History; Emek, Berk; Barlas, Dilek; Department of History; College of Social Sciences and Humanities; Graduate School of Social Sciences and HumanitiesThis article aims to highlight shifting diplomatic positions in Turkey and Romania and their stances towards the League of Nations collective security network during the interwar period. It takes a comparative approach to demonstrate the diplomatic activity and strategic decision-making mechanism employed by two strategically important Balkan and Black Sea countries vis-à-vis the fragile international system from the 1920s onwards. The rising threat of revisionism and declining belief in the League’s sanctioning power gradually led these countries to set their differences in foreign policy aside and strengthened the idea of joint regional action in the 1930s. Supported by primary sources from different archives, this comparative study proposes a new outlook, by demonstrating the contribution made by the notions of external threat and common aggressor to changing foreign policy perspectives in both countries. © 2024 Brill Academic Publishers. All rights reserved.Publication Metadata only Turkification policies of republican Turkey(Cambridge Univ Press, 2004) N/A; Department of History; Palaz, Cenk; Teaching Faculty; Department of History; College of Social Sciences and Humanities; 236358N/APublication Metadata only Automatic detection of road types from the third military mapping survey of Austria-Hungary historical map series with deep convolutional neural networks(IEEE-inst Electrical Electronics Engineers inc, 2021) N/A; N/A; Department of History; Can, Yekta Said; Gerrits, Petrus Johannes; Kabadayı, Mustafa Erdem; Resercher; Master Student; Faculty Member; Department of History; College of Social Sciences and Humanities; Graduate School of Social Sciences and Humanities; College of Social Sciences and Humanities; N/A; N/A; 33267With the increased amount of digitized historical documents, information extraction from them gains pace. Historical maps contain valuable information about historical, geographical and economic aspects of an era. Retrieving information from historical maps is more challenging than processing modern maps due to lower image quality, degradation of documents and the massive amount of non-annotated digital map archives. Convolutional Neural Networks (CNN) solved many image processing challenges with great success, but they require a vast amount of annotated data. for historical maps, this means an unprecedented scale of manual data entry and annotation. in this study, we first manually annotated the Third Military Mapping Survey of austria-Hungary historical map series conducted between 1884 and 1918 and made them publicly accessible. We recognized different road types and their pixel-wise positions automatically by using a CNN architecture and achieved promising results.Publication Metadata only Cyprus under British colonial rule: culture, politics, and the movement toward union with Greece, 1878-1954(Cambridge Univ Press, 2021) N/A; Department of History; Rappas, Alexis; Faculty Memer; Department of History; College of Social Sciences and Humanities; 50773N/APublication Metadata only Byzantium and Venice, 1204-1453: collected studies(Oxford University Press (OUP), 2013) Department of History; Magdalino, Paul; Faculty Member; Department of History; College of Social Sciences and Humanities; N/APublication Metadata only The Armenian genocide and its denial: a review of recent scholarship(Cambridge Univ Press, 2015) Department of History; Baker, Mark R.; Faculty Member; Department of History; College of Social Sciences and Humanities; N/AN/APublication Metadata only Friends or foes? Diplomatic relations between Italy and Turkey, 1923-36(Cambridge Univ Press, 2004) Department of History; Barlas, Dilek; Faculty Member; Department of History; College of Social Sciences and Humanities; 4172Publication Metadata only Superior photodynamic therapy of colon cancer cells by selenophene-bodipy-loaded superparamagnetic iron oxide nanoparticles(2022) Karaman, Osman; Günbaş, Görkem; N/A; Department of History; Department of Chemistry; Department of Chemistry; N/A; Sertçelik, Kübra Nur Özvural; Almammadov, Toghrul; Kölemen, Safacan; Acar, Havva Funda Yağcı; Onbaşlı, Kübra; Master Student; Researcher; Faculty Member; Faculty Member; Researcher; Department of History; Department of Chemistry; Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Koç University Boron and Advanced Materials Application and Research Center (KUBAM) / Koç Üniversitesi Bor ve İleri Malzemeler Uygulama ve Araştırma Merkezi (KUBAM); Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); Graduate School of Sciences and Engineering; N/A; College of Sciences; College of Sciences; N/A; N/A; N/A; 272051; 178902; N/ADevelopment of targeted nanoparticles as carriers to deliver photosensitizers to cancer cells is highly beneficial for ensuring the expected therapeutic outcome of photodynamic therapy. Herein, polyacrylic acid (PAA) coated superparamagnetic iron oxide nanoparticles (SPIONs), conjugated with endothelial growth factor receptor (EGFR) targeting Cetuximab (Cet) were loaded with a BODIPY-based (BOD-Se-I) photosensitizer (Cet-PAA@SPION/BOD-Se-I) to achieve enhanced and selective photodynamic therapy on colon cancer cells. In vitro studies showed that Cet-PAA@SPION/BOD-Se-I improved phototoxicity dramatically compared to free BOD-Se-I on the HT29 cell line due to high uptake of the photosensitizer via endothelial growth factor receptor. Most importantly, the developed nano-agent completely eliminated the phototoxicity of BOD-Se-I on the healthy L929 cell line.Publication Metadata only Automatic CNN-based Arabic numeral spotting and handwritten digit recognition by using deep transfer learning in Ottoman population registers(Mdpi, 2020) N/A; Department of History; Can, Yekta Said; Kabadayı, Mustafa Erdem; Researcher; Faculty Member; Department of History; College of Social Sciences and Humanities; College of Social Sciences and Humanities; N/A; 33267Historical manuscripts and archival documentation are handwritten texts which are the backbone sources for historical inquiry. Recent developments in the digital humanities field and the need for extracting information from the historical documents have fastened the digitization processes. Cutting edge machine learning methods are applied to extract meaning from these documents. Page segmentation (layout analysis), keyword, number and symbol spotting, handwritten text recognition algorithms are tested on historical documents. For most of the languages, these techniques are widely studied and high performance techniques are developed. However, the properties of Arabic scripts (i.e., diacritics, varying script styles, diacritics, and ligatures) create additional problems for these algorithms and, therefore, the number of research is limited. In this research, we first automatically spotted the Arabic numerals from the very first series of population registers of the Ottoman Empire conducted in the mid-nineteenth century and recognized these numbers. They are important because they held information about the number of households, registered individuals and ages of individuals. We applied a red color filter to separate numerals from the document by taking advantage of the structure of the studied registers (numerals are written in red). We first used a CNN-based segmentation method for spotting these numerals. In the second part, we annotated a local Arabic handwritten digit dataset from the spotted numerals by selecting uni-digit ones and tested the Deep Transfer Learning method from large open Arabic handwritten digit datasets for digit recognition. We achieved promising results for recognizing digits in these historical documents.Publication Metadata only Working for the state in the urban economies of Ankara, Bursa, and Salonica: from empire to nation state, 1840s-1940s(Cambridge University Press (CUP), 2016) N/A; Department of History; Kabadayı, Mustafa Erdem; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267In most cases, and particularly in the cases of Greece and Turkey, political transformation from multinational empire to nation state has been experienced to a great extent in urban centres. In Ankara, Bursa, and Salonica, the cities selected for this article, the consequences of state-making were drastic for all their inhabitants; Ankara and Bursa had strong Greek communities, while in the 1840s Salonica was the Jewish metropolis of the eastern Mediterranean, with a lively Muslim community. However, by the 1940s, Ankara and Bursa had lost almost all their non-Muslim inhabitants and Salonica had lost almost all its Muslims. This article analyses the occupational structures of those three cities in the mid-nineteenth century and the first half of the twentieth, tracing the role of the state as an employer and the effects of radical political change on the city-level historical dynamics of labour relations.