DSpace Arşivi :: Ana Sayfa

İstanbul Gelişim Üniversitesi Kurumsal Açık Erişim Arşivi

DSpace@Gelişim, İstanbul Gelişim Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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Measurement Efficiency of the Top 25 Universities in Turkey with DEA
(Nexora Academic Press, 2026) Bıyıklı, Süreyya İmre; Kamil, Anton Abdulbasah
This study examines the overall technical, pure technical, and scale efficiency levels of the top 25 research-oriented Turkish universities listed in the 2018– 2019 URAP ranking by applying Data Envelopment Analysis (DEA). Relative efficiency scores were obtained using both input- and output-oriented specifications of the CCR and BCC models. The CCR results indicate that only three universities—Middle East Technical University, Bilkent University, and Bezm-i Âlem Vakıf University—operate on the overall efficiency frontier, while the remaining 22 universities exhibit varying degrees of inefficiency. Among the inefficient universities, Ege University records the lowest CCR efficiency score, ranking 25th with a value of 0.6545, whereas Istanbul Technical University achieves the highest score among the inefficient group, ranking fourth with a value of 0.9808. The BCC results reveal a broader set of technically efficient institutions. Under both input- and output-oriented BCC models, Hacettepe University, Middle East Technical University, Istanbul Technical University, Bilkent University, Bezm-i Âlem Vakıf University, and Yıldız Technical University consistently emerge as technically efficient. In addition, Marmara University is found to be technically efficient under the input-oriented BCC model, although it remains marginally below the efficiency frontier under the output-oriented specification. The scale efficiency results show that only three universities achieve full scale efficiency under both orientations, while the remaining institutions experience varying degrees of scale inefficiency. Furthermore, seven universities operate under constant returns to scale, eleven under increasing returns to scale, and seven under decreasing returns to scale. The potential improvement analysis shows that inefficient universities require different adjustment paths depending on model orientation. In particular, Ege University should reduce its PHD and ÖÜY/SAY input indicators by approximately 34.54% under the input-oriented model, while increasing its research-related output indicators under the output-oriented model. Overall, the findings suggest that inefficiency among Turkish research-oriented universities is driven by both technical and scalerelated factors, highlighting the need for institution-specific strategies aimed at improving resource allocation, research productivity, and scale optimization.
Nonlinear thermophysical dynamics of MHD hybrid nanofluids: a multiparametric fractional framework assisted by artificial neural networks
(Springer Science and Business Media B.V., 2026) Abbas, Shajar; Ramzan, Muhammad; Jan, Rashid; Abd-Elmonem, Assmaa; Abulhassan, Mawadda E. E.; Khaydarov, Ilkhom; Hayitova, Mehrigul; Mahariq, Ibrahim
The study of non-Newtonian fluids has drawn much scholarly attention because of the wide range of applications they have in industrial processes, such as plastic, lubrication systems, and in mining operations. When combined with magnetohydrodynamic effects their importance widens to more advanced technological and biomedical applications such as magnetic resonance imaging, medical diagnostics, and hyperthermia treatment. Recent investigations have proven that the addition of nanosized particles into base fluids improves the thermal performance and the heat transfer efficiency. Nevertheless, heat transfer in realistic mechanical systems is affected by a huge number of interacting physical parameters, each with different contribution to overall behavior. In the present study, a sensitivity analysis is conducted to study the effect of some important parameters, which include internal heat generation, magnetic field strength, and Casson nanofluid properties. The governing equations are derived from fundamental conservation laws and transformed into a dimensionless form for generalization. The model is generalized by using Fourier’s and Fick’s laws. Analytical treatment is achieved using the Laplace transform technique, while the Levenberg–Marquardt algorithm is employed for numerical prediction and validation. Results demonstrate high accuracy with mean-squared error values below 10−10 especially for a fractional nanofluid Casson flow model. The Levenberg–Marquardt algorithm is utilized, with 70% of the data used for training and 15% allocated for validation and testing. The findings reveal that momentum increases with decreasing fractional parameters. Table 4 gives the validity of present work with already published work.
Edge AI Frameworks for Real-Time Personalised Marketing Communication in 6G Networks
(Nexora Academic Press, 2026) Ergin, Berrin
The recent development of Artificial Intelligence (AI) has brought about dramatic changes to digital marketing, allowing personalised and real-time communication with clients. Nevertheless, with the further sophistication of AI systems, their efficiency depends on the possibility of providing personalised marketing messages in real time. The 6G networks and the Edge AI integration are an innovative solution to this issue that provides the possibility of ultra-low latency and high bandwidth to provide real-time and personalised customer experiences. The paper suggests a new Edge AI architecture that can support customised marketing communication in 6G contexts. With machine learning models, e.g., Gradient Boosting Machine (GBM), Random Forest (RF), and Support Vector Machine (SVM), the framework predicts customer engagement and loyalty, providing customised content on the basis of real-time customer data. Key metrics used to assess the performance of the proposed models were accuracy, AUC-ROC, precision, recall, and F1-score. Results show that GBM outperforms both RF and SVM in all evaluated metrics. Moreover, the low-latency features of 6G can also improve the responsiveness in real-time, which will raise brand loyalty, customer engagement, and satisfaction. The Structural Equation Modelling (SEM) demonstrated that AI communication systems have a significant influence on engagement, which, in its turn, leads to brand loyalty. This study explains why the integration of Edge AI and 6G networks can be used to streamline personalised marketing tactics and provide businesses with an edge in terms of providing customers with timely and relevant information.
The Role of the Claustrum in Sensory and Cognitive Development
(İstanbul Veteriner Hekimler Odası, 2024) Kartal, Mehmet; Üstündağ, Yasemin; Mutuş, Rıfat
The claustrum is an important complex neuronal anatomic brain structure whose evolutionary process remains elucidated. The structure in question plays a key role in cognitive and sensory performances. Although it is an increasingly researched topic, especially regarding the importance of differences in children and adults with developmental differences, it is still possible to find very few publications. There are also studies arguing that claustrum is important for the risks of conditions such as autism, depression, anxiety, and Attention Deficit Hyperactivity Disorder and their response to treatment. In this short traditional review, the general anatomical structure of the claustrum and some current research results regarding this structure will be evaluated.
Wasn’t It All Inclusive? A Qualitative Study of Hotel Customers Stealing Behaviors in All Inclusive
(Emerald Publishing, 2026) Çıkı, Kartal Doğukan; Öğretmenoğlu, Mert; Urlu, Hakan; İnan, Ramazan
The purpose of this research is to reveal the underlying reasons for stealing behavior among customers staying at all-inclusive hotels and to identify prevention strategies from the perspectives of both staff members and department managers.