TR-Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1927

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Citation - WoS: 2
Citation - Scopus: 2
Between a Rock and a Hard Place: How To Make Sense of Turkey’s S-400 Choice
(SETA Foundation, 2020) Kibaroğlu, Mustafa
With the wrap-up of the S-400 deal with Russia in December 2017, critics argue that Turkey is caught between a rock and a hard place due to the adamant opposition of its NATO allies, the United States in particular, which has threatened Ankara with imposing severe sanctions. Would this be the correct representation of the situation at hand? Does it make any sense for Turkey to engage Russia, an archrival nation, to enhance the security of the country? Is the S-400 deal worth the risk of alienating the allied nations whose projected sanctions may have wide-ranging political, economic and military repercussions? With these questions in mind, this paper will try to shed light on the specifics of the S-400 deal that make one think that it may indeed make sense for Turkey to bear the brunt of engaging Russia. In the same vein, the paper will assess the impact of the S-400 deal on Turkey’s defense industries. The paper will also present the author’s conception of the current “international political non-order” as an underlying factor behind the deal. Finally, the paper will suggest that the S-400 deal must be approached from a wider perspective so as to grasp the extent of the service it has done in bolstering Turkey’s military-industrial complex. © 2020, SETA Foundation. All rights reserved.
Calling for a Reset in Turkish-American Relations in the Post-COVID International Order
(SETA Foundation, 2020) Kibaroğlu, Mustafa
Analysts emphasize that nothing will be the same after the pandemic and refer to the ‘new normal’ that is likely to prevail everywhere in the world. It would be a legitimate question to ask if this would provide a conducive environment for Turkey and the United States to reset their relations that have much deteriorated lately. This article will, first, highlight the contours of the ‘new normal’ narrative by referring to the views expressed by politicians, academics, analysts, journalists and intellectuals from around the world. Second, the article will assess the implications of the parameters of the ‘new normal’ for key actors in world politics, such as the United States, China, the European Union and Russia, as well as Turkey’s Middle Eastern neighbors, with respect to the issues that will be at stake in the international security environment. Finally, the article will make a call for a reset in Turkish-American relations in order for the two long-standing allies to adapt themselves better to post-COVID international politics. © 2020, SETA Foundation. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 5
Consumer Loans' First Payment Default Detection: a Predictive Model
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL, 2020) Sevgili, Türkan; Koç, Utku
A default loan (also called nonperforming loan) occurs when there is a failure to meet bank conditions and repayment cannot be made in accordance with the terms of the loan which has reached its maturity. In this study, we provide a predictive analysis of the consumer behavior concerning a loan’s first payment default (FPD) using a real dataset of consumer loans with approximately 600,000 records from a bank. We use logistic regression, naive Bayes, support vector machine, and random forest on oversampled and undersampled data to build eight different models to predict FPD loans. A two-class random forest using undersampling yielded more than 86% on all performance measures: accuracy, precision, recall, and F1-score. The corresponding scores are even as high as 96% for oversampling. However, when tested on the real and balanced dataset, the performance of oversampling deteriorates as generating synthetic data for an extremely imbalanced dataset harms the training procedure of the algorithms. The study also provides an understanding of the reasons for nonperforming loans and helps to manage credit risks more consciously.
Citation - WoS: 1
Facial Emotion Recognition Using Residual Neural Networks
(2024) Kırbız, Serap
Facial emotion recognition (FER) has been an emerging research topic in recent years. Recent automatic FER systems generally apply deep learning methods and focus on two important issues: lack of sufficient labeled training data and variations in images such as illumination, pose, or expression-related variations among different cultures. Although Convolutional Neural Networks (CNNs) are widely used in automatic FER, they cannot be used when the number of layers is large. Therefore, a residual technique is applied to CNNs and this architecture is named residual neural network. In this paper, an automatic facial emotion recognition method using residual networks with random data augmentation is proposed on a merged FER dataset consisting of 41,598 facial images of size 48 × 48 pixels from seven basic emotion classes. Experimental results show that ResNet34 with data augmentation performs better than CNN with a classification accuracy of 81%.
Mention Detection in Turkish Coreference Resolution
(Tubitak Scientific & Technological Research Council Turkey, 2024) Demir, Seniz; Akdag, Hanifi Ibrahim
A crucial step in understanding natural language is detecting mentions that refer to real-world entities in a text and correctly identifying their boundaries. Mention detection is commonly considered a preprocessing step in coreference resolution which is shown to be helpful in several language processing applications such as machine translation and text summarization. Despite recent efforts on Turkish coreference resolution, no standalone neural solution to mention detection has been proposed yet. In this article, we present two models designed for detecting Turkish mentions by using feed-forward neural networks. Both models extract all spans up to a fixed length from input text as candidates and classify them as mentions or not mentions. The models differ in terms of how candidate text spans are represented. The first model represents a span by focusing on its first and last words, whereas the representation also covers the preceding and proceeding words of a span in the second model. Mention span representations are formed by using contextual embeddings, part-of-speech embeddings, and named-entity embeddings of words in interest where contextual embeddings are obtained from pretrained Turkish language models. In our evaluation studies, we not only assess the impact of mention representation strategies on system performance but also demonstrate the usability of different pretrained language models in resolution task. We argue that our work provides useful insights to the existing literature and the first step in understanding the effectiveness of neural architectures in Turkish mention detection.
Citation - WoS: 2
Citation - Scopus: 3
Reforming Higher Education Finance in Turkey: the Alumni-Crowdfunded Student Debt Fund "a-Csdf" Model
(TEDMEM, 2016) Son-Turan, Semen
This study presents an innovative and sustainable system formobilizing Turkish university alumni to contribute to acrowdfunded pool repackaged as a student debt instrument withan elaborate performance tracking tool, various payoff structuresand income-contingent repayment schedules. The ultimate aim isto offer a remedy for the conspicuous global shortage ofalternative finance sources and various forms of aid to highereducation students in the short-term, and, through enablingequitable and egalitarian access to quality higher education,transforming society and enhancing economic development in thelonger-term. The model rests upon a six-dimensional frameworkand its infrastructure is facilitated by a newly emerged form ofdigitally enhanced financing, “crowdfunding”. The researchmethod involves content analysis and data triangulation forvalidation purposes to determine the sub-themes surrounding thehigher education problem in Turkey. The theme-driven keywordsare searched for on Turkey’s first original social network, EksiSozluk, to uncover trends and biases towards student loans, debtrepayment and associated concepts. Subsequently, the samekeywords are utilized in a Google Trends search volume analysis,and are finally validated by a focus group discussion. Thetheoretical framework to explain students’ attitudes towardsborrowing and loan repayment and the motivation behind alumniand charitable giving, rests mainly on behavioral economics. TheA-CDSF Model uniquely addresses the higher education financeproblem in Turkey and offers an easily implementable originalsolution for institutions and policy makers.
Sesli Betimleme Araştırmalarında Güncel Yönelimler
(BÜTEK Boğaziçi Eğitim Turizm Teknopark Uygulama ve Dan. Hiz. San. Tic. A.Ş., 2018) Güven, Mine
Bu tanıtım yazısının amacı, dünyada sesli betimleme konusunda yürütülen araştırmalardaki güncel yönelimlerden yola çıkarak Türkiye’de sesli betimleme konusunda dilbilim bağlamında gerçekleştirilebilecek bilimsel araştırma ve etkinlikler için genel bir çerçeve çizmektir. Uluslararası alanyazınındaki araştırmalar, sesli betimlemenin üretim, iletim ve tüketim aşamalarına yoğunlaşmaktadır. Üretim aşamasıyla ilgili görsel-işitsel ürün/ortam, sesli betimleme türevleri, metnin nitelikleri ve dili, betimlemeci yetkinlikleri ve eğitimi, metin üretim zamanı, metin üretim yöntemi ve metnin seslendirilmesi konularına değinilmiştir. İletim aşamasıyla ilgili, analog ve sayısal televizyon bağlamında iletim teknolojileriyle çeşitli ortamlardaki alıcı aygıtı olanakları tartışılmıştır. Tüketim aşamasıyla ilgili olaraksa metnin kullanıcı tarafından alımlanması, deneysel çalışmalar bağlamında algısal ve bilişsel yönleriyle ele alınmıştır. Sesli betimleme araştırmalarındaki bu yönelimlerin dikkate alınması, Türkiye’deki dilbilimsel sesli betimleme çalışmaları açısından yol gösterici olabileceği gibi Türkçeye özgü en iyi uygulamaların oluşmasına da katkıda bulunabilir.
Citation - WoS: 2
Citation - Scopus: 2
Stancetaking in Spoken Elf Discourse in Academic Settings: Interpersonal Functions of I Don’t Know as a Face-Maintaining Strategy
(Hacettepe University, 2021) Çiftçi, Hatime; Akbaş, Erdem
Our study examines interpersonal functions enacted through a stance marker in spoken ELF academic discourse. We specifically focus on investigating the functions of I don’t know in an academic speech event by embracing an interpersonal pragmatics and sociolinguistics perspective to figure out how it contributes to the act of stancetaking as an intersubjective activity. We have examined 14 interactions of doctoral defense discussions from the ELFA corpus. Our detailed discourse analysis of these doctoral defense discussions has revealed five distinctive interpersonal functions of the stance marker I don’t know allowing speakers to construct their stance and adopt a face-maintaining strategy in the ongoing spoken discourse: prefacing a suggestion, seeking acceptance, hedging/mitigating, checking agreement, and expressing uncertainty. Considering the highly-context dependent and context-regenerated functions of I don’t know, our study attempts to delve into the relational and interpersonal aspect of communication, and thus contributes to research in this strand by disclosing the interpersonal functions of stancetaking as an intersubjective activity with a particular focus on ELF academic discourse.
The Future of Türkiye-NATO Relations in Light of the Strained Transatlantic Dialogue
(Seta Foundation, 2025) Kibaroğlu, Mustafa
This commentary aims to assess the impact of the changing approach of the U.S. under Trump's second administration on transatlantic relations, the future of NATO, its engagement in the war in Ukraine, and the prospects for further expansion toward the east. The paper also aims to shed light on how these developments may affect the future of Türkiye-NATO relations. While Türkiye remains a critical NATO member due to its strategic geography and military capabilities, domestic skepticism towards the Alliance has grown in response to unresolved disputes and perceived double standards. The commentary ultimately underscores that Türkiye’s future in NATO will depend on the Alliance’s ability to reconcile internal divisions, recalibrate its strategic vision, and balance Türkiye’s security concerns with broader transatlantic priorities. © 2025, SETA Foundation. All rights reserved.
Citation - WoS: 2
Turkiye's Water Security Policy: Energy, Agriculture, and Transboundary Issues
(2022) Kibaroğlu, Ayşegül
Water security refers to the availability of adequate quantities and qualities of water for societal needs and resilient ecosystems in the context of current conditions and future global change. Achieving water security is directly linked to food and energy security, protecting and preserving eco systems, and addressing key vulnerabilities and risks from climate change. Good water governance –including transboundary cooperation– is a crit ical feature of any effort to achieve water security. Yet the concept of water security remains abstract and broad. In an attempt to make the concept of water security-relevant in practice, this paper delineates Türkiye’s water se curity policy and practices through institutional and cross-sectoral (energy and food) analysis. Specific attention is paid to Türkiye’s transboundary water security policies.
War as the True Adversary and Türkiye’s Pivotal Role in Forging Peace
(SETA Foundation, 2024) Çağlar, Barış
The central thesis of this article depends on deterrence theory and posits that nuclear war, rather than any specific nation or faction, constitutes the true adversary in the Russia-Ukraine conflict and that averting nuclear escalation must be prioritized above all else. After establishing the rationale for this position, the commentary offers a critical analysis of both Western and Russian policies, highlighting their role in intensifying the conflict without sufficiently accounting for the risks of nuclear confrontation. As an alternative peaceful path, the article examines the Turkish approach as a concise applied case study, emphasizing its balanced diplomatic and military engagement with both Ukraine and Russia. Through its promotion of dialogue and facilitation of peace negotiations, Türkiye exemplifies a strategic approach to conflict resolution that aims not only to prevent further escalation —especially the threat of nuclear conflict— but also to pave the way toward sustainable peace. © 2024, SETA Foundation. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 8
Zaman Pencereli ve Değişken Başlama Zamanlı Bir Araç Rotalama Problemi için Sütun Türetme Temelli Matsezgiseller
(DergiPark, 2019) Küçükaydın, Hande
In this study, a vehicle routing problem with time windows is investigated, where the costs depend on the total duration of vehicle routes and the starting time from the depot for each vehicle is determined by a decision maker. In order to solve the problem, two column generation based mat-heuristics are developed, where the first one makes use of the iterated local search and the second one uses the variable neighbourhood search. In order to assess the accuracy of the mat-heuristics, they are first compared with an exact algorithm on small instances taken from the literature. Since their performance are quite satisfactory, they are further tested on 87 large instances by running each algorithm 3 times for each instance. The computational results prove that the mat-heuristic using the variable neighbourhood search outperforms the other one. Hence, this enables to obtain a good feasible solution in a very short time when it is not possible to solve large instances with an exact solution method in a reasonable CPU time.

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