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
Assessment of the Disaster Recovery Progress Through Mathematical Modelling
(TMMOB İnşaat Mühendisleri Odası, 2020) Dikmen, Seyyit Ümit; Sönmez, Murat; Akbıyıklı, Rıfat
Natural disasters, especially major earthquakes, cause widespread devastation in the built environment. Hence, the major component of the recovery in its aftermath constitutes a chain of projects starting at different times, having different costs and durations. In this study, the post disaster recovery curve modelled through a mathematical approach taking into account these properties of the projects. The approach followed is based on the project S-curve concept that provides the opportunity to simulate the progress by outlining the project spending. Well-known mathematical functions are adapted to model the project spending and the handover processes. Monte Carlo simulation is performed to evaluate the general behavior of the recovery curve using the model developed. Weibull distribution is used to generate the model’s parameters. Results of the Monte Carlo simulation demonstrate that the recovery process exhibits an S-shape, the duration of initial portion and the slope of the bulk portion being significantly governed by the level of preparedness of the community.
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.
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.
Citation - WoS: 3
Citation - Scopus: 4
Time - Cost Relationships for Superstructure Projects in Turkey
(TMMOB İnşaat Mühendisleri Odası, 2020) Dikmen, Seyyit Ümit; Akbıyıklı, Rıfat; Sönmez, Murat
The concept of time-cost relationship in construction projects was first introduced by Bromilow. Bromilow used the data of the superstructure projects completed in Australia in the creation of the proposed time-cost model (BTC model). The aim of this study is to determine the time-cost relationship of superstructure projects in Turkey. Time and cost data of superstructure projects completed between the years of 1999-2018 was used in the study. Data was grouped primarily on the basis of the intended use of buildings (individual buildings, educational buildings, hospitals, industrial buildings and social housing), and then time-cost relationships were separately determined for each group. In addition, the effects of the parameters such as exchange rates and the number of non-working days on the time-cost relationship were investigated statistically.
Citation - WoS: 4
Citation - Scopus: 6
Turkey's Green Imagination: the Spatiality of the Low-Carbon Energy Transition Within the Eu Green Deal
(Uluslararasi Iliskiler Konseyi Dernegi, 2023) Akçalı, Emel; Özel, Soli; Görmüş, Evrim
This article asks the extent to which the EU Green Deal influences the EU periphery today and builds on the spatial conditions of multiple, co-existing decarbonization pathways within the EU Green Deal while problematizing the 'green imagination' of Turkey as an immediate neighbour and a candidate country for membership in the EU. As such, it uncovers that the current low-carbon transition process in Turkey is prone to be shaped by the highly politicized energy market in an authoritarian neoliberal structure on the one hand, and Turkey's priorities in energy issues and hard security on the other. The findings further reveal that Turkey's efforts to use more domestic energy resources to meet its consumption needs might also interfere with its efforts and obligations to decarbonize its energy sector. The scrutiny into the low-carbon energy transition in Turkey accordingl contributes further insight into the consequences of the spatiality of such transitions in an authoritarian neoliberal context, and what other alternative policies can be imagined and put in practice. Thus, more empirical research is warranted to reveal the spatiality of the low-carbon energy transition across various geographical settings. At the same time, the article argues that both the EU and its partners such as Turkey should be weary of creating green utopias when redesigning their green-energy space since utopias tout court may not always stimulate large-scale change in a revolutionary way in terms of sustainability, feasibility, good practice, and inclusiveness in decision-making processes.
Citation - WoS: 1
Citation - Scopus: 1
Us Policies Adrift in a Levant in Turmoil
(Stradigma, 2018) Özel, Soli; Görmüş, Evrim
The Levant has constituted one of the core areas of interest for US foreign policy since the Second World War. The aim of this article is to shed light on the US policies towards the Levant, mostly during the last two American administrations, to understand how the vicissitudes of the region and of American politics made Washington’s policy towards the Levant look biased, at times incompetent, and most importantly inconsistent. This article examines the changes in approach to the region as a whole from one administration to the next on issues such as the protection of Israel’s sovereignty, supporting friendly regimes, fighting terrorism, and containing Iran. The hesitations and shifts in policy towards Syria are given a longer treatment as they speak both to the yet not finalized American policy towards the Levant but also to show how the US has shifted track and moved away from unseating President Assad to focus more on containing and if possible rolling over Iran.
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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