01. Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed

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Citation - Scopus: 2
Turcoins: Turkish Republic Coin Dataset
(IEEE, 2021) Gökberk, Berk; Akarun, Lale; Temiz, Hüseyin
In this paper, we present a novel and comprehensive dataset which contains Turkish Republic coins minted since 1924 and present a deep learning based system that can automatically classify coins. The proposed dataset consists of 11080 coin images from 138 different classes. To classify coins, we utilize a pre-trained neural network (ResNet50) which is pre-trained on ImageNet. We train the pre-trained neural networks on our dataset by transfer learning. The imbalanced nature of the dataset causes the classifier to show lower performance in classes with fewer samples. To alleviate the imbalance problem, we propose a StyleGAN2-based augmentation method providing realisticfake coins for rare classes. The dataset will be published in http://turcoins.
Citation - WoS: 22
Citation - Scopus: 25
Perceptions of Dating Violence: Assessment and Antecedents
(SAGE Publications, 2020) Toplu-Demirtaş, Ezgi; Fincham, Frank D.; Öztemür, Gizem
Challenging perceptions of violence is crucial to prevent dating violence (DV), because such perceptions intervene in the organization and interpretation of violent events. However, these perceptions have received limited attention. This likely reflects the lack of a psychometric tool to do so. The current study had two purposes: to develop a measure of perceptions of psychological, sexual, and physical DV, and to explore how vertical collectivism, through hostile sexism and violence myth acceptance, shapes perceptions of DV. A total of 491 college students (55.3% women; M = 20.76 years, SD = 1.77 years) completed measures of the vertical collectivism, hostile sexism, domestic violence myth acceptance, and perceptions of DV. The results of exploratory factor analyses revealed a 15-item single-factor measure of perceptions of DV as initial construct validity, which had satisfactory internal consistency. A gender difference emerged in perceptions of DV; college women perceived psychological, sexual, and physical DV as more serious compared with college men. Moreover, the association between vertical collectivism and perceptions of DV was serially mediated via hostile sexism and violence myth acceptance. The findings are discussed in terms of previous research and the need to address the role of vertical collectivism in sexism, myth acceptance, and perceptions of violence in prevention/intervention efforts to reduce vulnerability to DV perpetration and victimization. Several recommendations are outlined to facilitate future research.
Determination of Alzheimer's Disease Stages by Artificial Learning Algorithms
(Lifescience Global, 2025) Bulut, Nurgül; Çakar, Tuna; Arslan, İlker; Akıncı, Zeynep Karaoğlu; Oner, Kevser Setenay
Introduction: This study aims to determine the stages of Alzheimer's disease (AD) using different machine learning algorithms, and compares the performance of these models. Methods: Demographic, genetic, and neurocognitive inventory data from the National Alzheimer's Coordinating Center (NACC) database as well as brain volume/thickness data from magnetic resonance imaging (MRI) scans were used. Deep Neural Networks, Ordinal Logistic Regression, Random Forest, Gaussian Naive Bayes, XGBoost, and LightGBM models were used to identify four different ordinal stages of AD. Results: Although the performance measures of the developed models were similar, the highest classification rate of AD stages was achieved by the Random Forest model (accuracy: 0.86; F1 score: 0.86; AUC: 0.95). The outputs of the model with the best performance were explained by the SHapley Addictive exPlanations (SHAP) method. Conclusions: This indicates that non-invasive markers and machine learning models can be used effectively in early diagnosis and decision support systems to predict stages of AD. © 2025 Elsevier B.V., All rights reserved.
How the Cephei E-Course Syllabus Design Was Developed and Implemented
(Springer International Publishing, 2022) Kurban, Fell Caroline
While the digitalization of education has been around since the 1990s, it is only since the Covid-19 pandemic that it has really taken hold in education, when universities were forced to rapidly move online and traditional patterns of teaching were no longer viable. This pushed universities to provide a blended learning environment drawing on technologies that our students, as digital natives, had already been using on a daily basis for some time. However, blended learning is only effective if underpinned by tried and tested learning frameworks—something that many universities were not prepared for when the shift to online learning took place. The Cooperative e-learning Platform for Industrial Innovation (CEPHEI) however, was already prepared and ready for this shift, as from 2017 it had been working on the development of an e-learning platform with the aim of digitizing education while also integrating the reality of professional innovation activities into the context of education according to the demands of industry. To achieve this aim, one of the first phases of the project was to identify key learning frameworks for e-course syllabus design, based on existing research, that could be used to provide recommendations for instructors in the development of their CEPHEI courses. This chapter presents the culmination of this process and provides a framework that can be used by instructors or institutions wishing to design e-learning courses. To make these frameworks tangible for the reader, examples are given throughout the chapter from an undergraduate environmental engineering course in a civil engineering department. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
Citation - WoS: 2
Citation - Scopus: 5
Increasing Procurement Efficiency Through Optimal E-Commerce Enablement Scheduling
(Emerald Group Publishing Ltd., 2019) Özlük, Özgür; Cholette, Susan; Clark, Andrew G
Purpose: This study aims to show how cost savings can be achieved through optimizing the scheduling of e-commerce enablements. The University of California is one of the largest, most prestigious public education and research systems in the world, yet diminished state support is driving the search for system-wide cost savings. Design/methodology/approach: This study documents the preparation for and rollout of an e-procurement system across a subset of campuses. A math programing tool was developed for prioritizing the gradual rollout to generate the greatest expected savings subject to resource constraints. Findings: The authors conclude by summarizing the results of the rollout, discussing lessons learned and their benefit to decision-makers at other public institutions. Originality/value: The pilot program comprising three campuses has been predicted to yield $1.2m in savings over a one-year period; additional sensitivity analysis with respect to savings, project timelines and other rollout decisions illustrate the robustness of these findings.
Citation - Scopus: 1
The Evolution of Water Diplomacy Frameworks: The Euphrates-Tigris Basin as a Case Study
(Springer, 2024) Kibaroğlu, Ayşegül
Water diplomacy encompasses the processes and institutions through which the national interests and identities of sovereign states are represented to one another. It is enshrined in international law, which states use to explain and justify their policies to concerned actors in the international system. States mostly prefer traditional tools of water diplomacy such as negotiation and mediation to resolve disputes in transboundary river basins. This chapter explores water diplomacy along with its main principles and actors. On the one hand, the state has been the main actor in shaping transboundary water policies and conducting water diplomacy throughout the last few decades of water disputes. On the other hand, international organizations, international financial agencies, non-governmental organizations, and science-policy (Track II) initiatives also participate in water diplomacy. A brief discussion of emerging water diplomacy approaches is followed by a case study on the evolution of water diplomacy frameworks in the Euphrates-Tigris river basin.
Citation - WoS: 3
Citation - Scopus: 4
A Novel Graph Transformation Strategy for Optimizing Sptrsv on Cpus
(Wiley, 2023) Yılmaz, Buse
Sparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present a novel graph transformation strategy to increase the parallelism degree of a sparse matrix and compare it to our previous strategy. It is seen that our transformation strategy can provide a speedup as high as 1.42x$$ 1.42x $$.
Citation - WoS: 16
Citation - Scopus: 20
Selecting Suicide Ideation Assessment Instruments: a Meta-Analytic Review
(SAGE Publications, 2017) Duncan, Kelly; Atalay, Zümra; Erford, Bradley T.; Jackson, Jessica; Bardhoshi, Gerta
Psychometric meta-analyses and reviews were provided for four commonly used suicidal ideation instruments: the Beck Scale for Suicide Ideation, the Suicide Ideation Questionnaire, the Suicide Probability Scale, and Columbia–Suicide Severity Rating Scale. Practical and technical issues and best use recommendations for screening and outcome research are offered.
Optimizing Collective Building Management Through a Machine Learning-Based Decision Support System
(IEEE, 2023) Güvençli, Mert; Dağ, Hasan; Doğan, Erkan; Çakar, Tuna; Özyürüyen, Burcu; Kiran, Halil
This study presents the design, implementation, and evaluation of a Decision Support System (DSS) developed for Collective Building Management. Given the potential advantages of machine learning techniques in this domain, the research explores how these techniques can be used to improve collective building management. The dataset consists of 824,932 records and 15 attributes, after preprocessing the data to fill in missing values with the median. The random forest algorithm was chosen for model training and achieved a performance rate of 71.2%. This model can be used to optimize decision processes in collective building management. The proposed prototype is notable for its ability to automatically generate operational plans. In conclusion, machine learning-based DSSs are effective tools for collective building management.
Citation - Scopus: 1
Design and Fpga Implementation of Uav Simulator for Fast Prototyping
(IEEE, 2023) Aydın, Yusuf; Ayhan, Tuba; Akyavaş , İrfan
As production and advances in motor and battery cell technology progress, unmanned aerial vehicles (UAVs) are gaining more and more acceptance and popularity. Unfortunately, the design and prototyping of UAVs is an expensive and long process. This paper proposes a fast, component based simulation environment for UAVs so that they can be roughly tested without a damage risk. Moreover, the combined effect of individual component choices can be observed with the simulator to reduce design time. The simulator is flexible in the sense that detailed aerodynamic effects and selected components models can be included. In this work, the simulator is proposed, model parameters are extracted for a particular UAV for testing the simulator and it is implemented on an field programmable gate array (FPGA) to increase simulation speed. The simulator calculates battery state of charge (SOC), position, velocity and acceleration of the UAV with gravity, drag, propeller air inflow velocity. The simulator runs on the FPGA fabric of AMD-XCKU13P with simulation steps of 1 ms.
Citation - WoS: 1
Citation - Scopus: 1
Developmental Differences in Children and Adults' Enforcement of Explore Versus Exploit Search Strategies in the United States and Turkey
(Wiley, 2024) Kiefer, Sarah L.; Aksu, Ece; Şen, Hilal H.; Lucca, Kelsey
Across development, as children acquire a deeper understanding of their environment, they explore less and take advantage, or "exploit," what they already know. Here, we test whether children also enforce exploration-oriented search behaviors onto others. Specifically, we ask whether children are more likely to encourage a search agent to explore versus exploit their environment, and whether this pattern varies across childhood (between 3 and 6 years). We also ask whether this pattern differs between children and adults, and generalizes across two different sociocultural contexts-Turkey and the United States-that differ on dimensions that might relate to children's decisions about exploration (e.g., curiosity-focused educational practices, attitudes toward uncertainty avoidance). Participants (N = 358) watched an agent search for rewards and were asked at various points whether the agent should "stay" (exploit) in their current location, or "go" (explore) to a new location. At all points in the experiment, children enforced exploration significantly more often than adults. Early in the agent's search, children in the US enforced exploration more often than children in Turkey; later in the search, younger children (from both sociocultural contexts) were more likely to continue enforcing exploration compared to older children. These findings highlight that children are not only highly exploratory themselves, but also enforce exploration onto others-underscoring the central role that exploration plays in driving early cognitive development across diverse sociocultural contexts.Research Highlights The current study examined developmental and cross-cultural differences in children and adults' enforcement of explore-exploit search strategies. Children in the US and Turkey enforced exploration more than adults, who enforced exploitation more often; results were generally consistent across cultures with small differences. Mirroring developmental changes in children's own search behavior; the tendency to enforce exploration decreased between 3- to 6-years of age. Findings underscore the central role of an "exploration mindset" in children's early decision-making-even when exploration has no direct benefits to the child themselves.
Citation - WoS: 2
Citation - Scopus: 2
Classification of Altruistic Punishment Decisions by Optical Neuroimaging and Machine Learning Methods
(IEEE, 2023) Erözden, Ozan; Şahin, Türkay; Akyürek, Güçlü; Filiz, Gözde; Çakar, Tuna
Altruistic punishment (third-party punishment) is important in terms of maintaining social norms and promoting prosocial behavior. This study examined data obtained using the near infrared spectroscopy (fNIRS) method to predict altruistic punishment decisions. It was found that specific neural activity patterns were significantly related to decisions regarding the punishment of the perpetrator. This research contributes to the development of social decision-making models and helps advance our understanding of the cognitive and neural processes involved in third-party punishments.
Missing the Good Old Days: Investigating Outgroup Attitudes Through Collective Nostalgia and Global Identification
(Taylor and Francis, 2022) Şengül, Denizhan; Doğan, Zeynep; Akkurt, Bengisu; Koç, Yasin; Aksu, Ayça; Anderson, Joel
Collective nostalgia is a group-based emotion that refers to the longing for the “good old days” of one's ingroup. Research shows that collective nostalgia usually benefits relationships with other in-group members, while hampering intergroup relations. However, this depends on the past remembered. Moreover, global identification predicts positive intergroup relations, yet this depends on whether the target group is perceived to be aligned with a global culture. Accordingly, we tested how collective nostalgia and global identification can then be linked to inclusionary vs. exclusionary outgroup attitudes in Turkey in relation to Kurds, Armenians, LGBTQ+ individuals and Syrian refugees. The results showed (N = 1090) that collective nostalgia was related to positive attitudes towards Kurds, Armenians and gay men, whereas it was negatively related to attitudes towards Syrian refugees. Moreover, contrary to expectations, we found that global identification predicted positive attitudes towards all outgroups. These findings are not surprising given the changing political climate and increasing intergroup conflict in Turkey. We speculate that the meaning attributed to the “good old days” of Turkey predicted these positive attitudes except for Syrian refugees who are perceived to be today's problem. Overall, the relationship between nostalgia and outgroup attitudes are more complex than research has so far shown, and the content of the past remembered might be important to understand this relationship.
Citation - WoS: 1
Citation - Scopus: 1
A Novel Tunable Vortex-Induced Vibration Wind Energy Harvester
(Ieee, 2024) Dorantes Gonzalez, Dante Jorge
This study presents a novel approach to enhancing the efficiency and robustness of vortex-induced vibration energy harvesters for wind energy conversion. Through the development and evaluation of alternative tunable stiffness mechanisms, particularly focusing on a discrete-tunable mechanism with three levels of torsional springs, significant improvements in energy capture and construction simplicity have been achieved. By optimizing dynamic models and conducting thorough structural analyses, potential weaknesses in the design have been identified and addressed. The innovative tunable mechanism, currently undergoing patent review, represents a substantial advancement in the field of renewable energy technologies, offering a promising solution for urban energy harvesting applications. This research underscores the importance of continuous innovation and optimization in energy harvesting systems to meet the evolving demands for sustainable energy production.
Özyinelemeli Sinir Ağları ile Türkçe Doğal Dil Üretimi
(TÜBİTAK, 2018) Demir, Şeniz; Gökmen, Muhittin
İnsanlar arasındaki iletişimi sağlayan doğal diller, zaman içinde insanlarla etkin ve kullanıcı dostu etkileşim kurabilmek amacıyla sistemler ve yazılımlar tarafından kullanılmaya başlanmıştır. Tıpkı insanlar gibi sesli veya yazılı doğal dil ifadelerini anlayabilen ve sonrasında kullanıcıların beklentilerini karşılayabilen dil tabanlı teknolojiler (örn. arama motorları, bilgisayar destekli eğitici sistemler ve diyalog sistemleri) bu motivasyonla ortaya çıkmıştır. Bu çalışmalarda, problemin doğası ve hedef dilin yapısındaki zorluklara ek olarak insanların doğal dilleri nasıl öğrendiğini ve kullandığını modellemedeki kısıtlar başarım oranlarını etkilemiştir. Günümüzde, dil tabanlı teknolojiler insanlar tarafından yaygın şekilde kullanılıyor olsalar da (örn. Google Arama Motoru ve Apple Siri), ulaşılan teknolojik seviye hedef dile göre çeşitlilik göstermektedir. Sondan eklemeli ve zengin dil yapısı ile Türkçe geliştirilen teknolojik çözümler ve üretilen veri kaynakları açısından pek çok doğal dilin gerisinde kalmaktadır. Ayrıca, bugüne kadar Türkçe dil teknolojileri konusunda yapılan çalışmaların ağırlıklı olarak dili işleme, anlama ve analiz etmeye dönük (örn. kelimelerin morfolojik analizi, özel isim tespiti, bağlılık çözümlemesi, metin sınıflandırma ve metin özetleme) olduğu gözlemlenmektedir. Türkçe dil üretimi konusunda sınırlı yeteneklere sahip ve akademik seviyede kalarak devamı getirilmemiş birkaç çalışma mevcuttur. Fakat bu çalışmalar karmaşık sayılabilecek dilbilimi teorileri ile ifade edilen içerik ifadelerini cümlelere dönüştürmekten öteye geçmemiştir ve başka uygulamalarla entegre olarak test edilmemiştir. Bu çalışmada, Türkçe dilinin derin öğrenme tabanlı bir sistem (dil aracı) ile otomatik olarak üretimi hedeflenmektedir. Bu sistemin, girdi olarak verilen içerik ifadelerini Türkçe dili kurallarına uygun ve anlaşılır cümlelere dönüştüreceği öngörülmektedir. Literatürdeki en kapsamlı Türkçe dil üretimi sistemi olması planlanan bu çalışmada son yıllarda pek çok dil teknolojisinde başarımı ispat edilmiş diziden diziye öğrenebilen (örn. kelime dizisinden başka bir kelime dizisi) özyinelemeli sinir ağı yapıları kullanılacaktır. Bu ağların sağladığı dinamiklik ile farklı çeşitler (örn. uzun kısa süreli bellek ve girişli özyinelemeli birim) ve genişlemeler (örn. dikkat mekanizması) denenecektir ve başarımı en yüksek sinir ağı mimarisi belirlenecektir. Buna ek olarak, sinir ağlarının kullanımı bazı faktörlerin (örn. bağlam bilgisi ve kullanıcı tercihleri) sisteme entegrasyonuna ve üretim aşamasına olan etkilerinin incelenmesine imkân sağlayacaktır.
Citation - Scopus: 5
An Antipodal Vivaldi Antenna Design for Torso Imaging in a Coupling Medium
(IEEE, 2021) Çayören, Mehmet; Bilgin, Egemen; Joof, Sulayman; Doğu, Semih
An antipodal Vivaldi antenna designed to operate in a coupling medium with a relative dielectric constant of epsilon(r) = 25 for microwave imaging of torso is presented in this paper. The proposed antenna is similar to the conventional antipodal Vivaldi antenna but with optimized parameters to radiate in the desired coupling medium. The antenna has a size of 120x70 mm(2) and operating over 230-1000 MHz frequency bandwidth with a peak gain of 5.42 dBi and peak front-to-back ratio of 143 dB. The designed antenna shows a better performance compared to other antennas used for microwave torso imaging. To assess the actual performance, a realistic human torso phantom is implemented to detect the water accumulation in the lungs, and as the inversion method linear sampling method is used. The 3-D reconstruction results show that the proposed antenna can be a candidate for microwave torso imaging applications.
Diyalog Geliştirme için Bağlaşımlı Tensör Ayrıştırma Yöntemleri
(TÜBİTAK, 2021) Şimşek, Serap Kırbız; Cemgil, Ali Taylan; Liutkus, Antoine
Ayrıştırma tabanlı ses modelleme yöntemleri, hesaplama gücünün artmasıyla ve istatistiksel modelleme yöntemlerinin gelişmesiyle birlikte yaygın olarak kullanılmaktadır. Bu yöntemler, ses kodlama, müziksel bilgi çıkarımı, müziğin notaya dökülmesi, içerik analizi, kaynak ayrıştırma, ses onarımı ve gürbüz konuşmacı tanımanın da aralarında bulunduğu birçok alanda kullanılmaktadır. Bizim bu projede temel amacımız, birden fazla kaynak içeren ses kayıtlarındaki konuşma işaretlerini güçlendirmek için kaynak ayrıştırma algoritmalarından faydalanarak bir yöntem geliştirmektir. Diyalog ve ortamdaki diğer sesler arasındaki doğru dengeyi bulmak ses mühendisleri için önemli bir problem olup, dinleyici şikayetlerinin de gittikçe artan bir sebebini oluşturmaktadır. Dinleyiciler, kendi kişisel tercihlerine, dinleme ortamlarına ve duymalarına uygun olarak diyalog ve çevresel sesler arasındaki ses dengesini kendileri ayarlamak istemektedirler. Bu projedeki temel amaçlar ve aşamalar aşağıdaki gibidir: i) Durağan olmayan çok boyutlu zaman serilerinde, matris ve tensör ayrıştırma modellerini kullanarak diyalog içeren ses kayıtlarından diyalogların ayrıştırılması ve bunun daha sonra kayıtta bulunan diğer seslerle farklı oranlarda yeniden birleştirilmesiyle, kullanıcının ihtiyaçlarına ya da zevkine dayalı bir kayıt dinlemesini sağlama ii) Televizyon programları gibi akan veri üzerinde de çalışabilmek üzere, önerilen yöntemin gerçek zamanda çalışması. Bu bağlamda, veri geldikçe gerçek zamanlı olarak işlenecektir. iii) Geliştirilen yöntemlerin etkinliğinin gerçek uygulamalarda kullanımı. Projenin çıktıları olan modelleme, çıkarım ve model seçimi yöntemleri; işaret işleme, yapay öğrenme ve istatistik alanlarında temel metodolojik katkılar yapmaktatır. Bunun dışında çıktılar, bilgi madenciliği, biyoinformatik, sistem biyolojisi, yer bilimleri, karmaşık sistemler, algılayıcı ağları, finans veya akustik konularındaki büyük veri öbeklerinin incelendiği çalışmaları destekleyecektir. Bu bağlamda, MEF Üniversitesi bünyesinde yerli ve uluslararası alanda süren işbirliklerinin sürdürülmesi ve geliştirilmesi de planlanmaktadır.
Citation - WoS: 30
Citation - Scopus: 27
Drivers of Cultural Success: the Case of Sensory Metaphors
(2015) Berger, Jonah; Akpınar, Ezgi
Why do some cultural items catch on and become more popular than others? Language is one of the basic foundations of culture. But what leads some phrases to become more culturally successful? There are multiple ways to convey the same thing and phrases with similar meanings often act as substitutes, competing for usage. A not so friendly person, for example, can be described as unfriendly or cold. We study how the senses shape cultural success, suggesting that compared with their semantic equivalents (e.g., unfriendly person), phrases which relate to senses in metaphoric ways (e.g., cold person) should be more culturally successful. Data from 5 million books over 200 years support this prediction: Sensory metaphors are used more frequently over time than are their semantic equivalents. Experimental evidence demonstrates that sensory metaphors are more memorable because they relate more to the senses and have more associative cues. These findings shed light on how senses shape language and the psychological foundations of culture more broadly.
Evaluating Large Language Models in Data Generation for Low-Resource Scenarios: A Case Study on Question Answering
(International Speech Communication Association, 2025) Arisoy, E.; Menevşe, M.U.; Manav, Y.; Özgür, A.
Large Language Models (LLMs) are powerful tools for generating synthetic data, offering a promising solution to data scarcity in low-resource scenarios. This study evaluates the effectiveness of LLMs in generating question-answer pairs to enhance the performance of question answering (QA) models trained with limited annotated data. While synthetic data generation has been widely explored for text-based QA, its impact on spoken QA remains underexplored. We specifically investigate the role of LLM-generated data in improving spoken QA models, showing performance gains across both text-based and spoken QA tasks. Experimental results on subsets of the SQuAD, Spoken SQuAD, and a Turkish spoken QA dataset demonstrate significant relative F1 score improvements of 7.8%, 7.0%, and 2.7%, respectively, over models trained solely on restricted human-annotated data. Furthermore, our findings highlight the robustness of LLM-generated data in spoken QA settings, even in the presence of noise. © 2025 International Speech Communication Association. All rights reserved.
Citation - WoS: 52
Citation - Scopus: 60
De-Europeanisation in Turkey: the Case of the Rule of Law
(Taylor & Francis, 2016) Saatçioğlu, Beken
This article investigates the political dynamics shaping the post-2010 ‘de-Europeanisation’ of Turkey’s judicial system, particularly regarding judicial independence and rule of law. The analysis suggests the limits of conventional Europeanisation accounts emphasising causal factors such as European Union (EU) conditionality and the ‘lock-in effects’ of liberal reforms due to the benefits of EU accession. The article argues that the Justice and Development Party’s (AKP’s) bid for political hegemony resulted in the reversal of rule of law reforms. De-Europeanisation is discussed in terms of both legislative changes and the government’s observed discourse shift.

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