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Araştırmacılar(207)

• Acar, Ramazan
• Ağar, Salih
• Akçay, Özge
• Akgül, Melek
• Akkurt, Nevzat
• Akkus, Sukran
• Akmaz, Düzgün
• Akpolat, Mustafa
• Aksakal, Bünyamin
• Akyol, Sinem
• Alatas, Bilal
• Alparslan, Dilek
• Anik, Kerem
• Artuğer, Fırat
• Asam, Eren
• Askin, Ali
• Aslan Sungur, Guler
• Aslan, Alper
• Aslan, Serpil
• Aşkın, A.
• Aşkın, Ali
• Aşkın, Muzaffer
• Atalar, Aydın
• Aydoğdu, Burcu
• Ayhan, Nagihan Karaaslan
• Ayikurt, P.
• Bahar, Ahmet Serhat
• Bahar, Nurdan
• Bal, Tulin
• Baloglu, Ulas Baran
• Basaran, Senay
• Baskonus, Haci Mehmet
• Batu, Ali
• Bayrambas, Kadir
• Birkan, Kubra
• Boydak, Merve
• Bozkir, Hamza
• Boztug, Ali
• Boztug, Durmus
• Buldu, G.
• Caliskan, Abuzer
• Camas, Anil Sazak
• Camas, Mustafa
• Can, Ümit
• Celik, Erkan
• Celik, Fatih
• Celik1, G.
• Cemalgil, Selim
• Cevahir, Ceren
• Cimen, Murat
• Cumurcu, Aysenur
• Dal, Murat
• Dalğıç, Aras
• Danabas, Seual
• Danabas, Seval
• Demir, Ferhat
• Demir, Veysel
• Demirbilek, Deniz
• Demirci, Ulas
• Dereli, Zeynep

• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/4701
  Upcycling Agricultural Biomass into Functional Bio-Oils through Pyrolysis: Toward Sustainable Rejuvenation of Asphalt Binder

  Furtana Yalcin, Beyza; Yilmaz, Mehmet; Yalçin, Erkut; Vural Kok, Baha

  This study investigates the feasibility of utilizing bio-oils derived from agricultural waste materials (such as straw, olive pomace, and pine cones) as rejuvenating additives in reclaimed asphalt pavement (RAP) containing bituminous mixtures, offering a sustainable and environmentally friendly approach in asphalt technology. The primary objective of the study is to enhance the physical and mechanical properties of aged binders using ecofriendly alternatives, thereby developing high-performance asphalt mixtures without harming the environment. The bio-oils, produced through pyrolysis, were evaluated in comparison with two commercial rejuvenators. Key performance criteria, including Marshall stability, moisture damage resistance (TSR), indirect tensile stiffness modulus (ITSM), and fatigue life, were tested. The results indicate that natural rejuvenators not only soften the aged binder but also effectively balance the flexibility, strength, and deformation resistance of the mixture. Notably, straw oil exhibited superior performance in terms of both high stability and extended fatigue life, while olive pomace oil demonstrated remarkable success in moisture resistance. Although commercial additives were effective to a certain extent, they failed to achieve the same level of structural compatibility and sustainability provided by natural bio-oils. In this regard, the study provides strong evidence that agricultural biomass waste can serve as a value-added solution in asphalt pavements, in alignment with the principles of the circular economy. In conclusion revealed that mixtures containing 75% RAP rejuvenated with straw oil achieved 11% higher Marshall stability and up to 14.5 times longer fatigue life compared to virgin mixtures, while olive pomace oil-based mixtures reached a TSR value of 81.5%, demonstrating superior moisture resistance.

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• MakaleAçık Erişim2026Scopus SJRQ2/r/munzur/4034
  A New Metacognitive Confidence Calculation Approach Based on Large Language Models for Natural Language Explanations

  Yilmazer Gundem, Merve; Sahin, Simay; Karakose, Mehmet

  Traditional methods used to measure metacognitive confidence rely on superficial features such as word count and ambiguity and therefore fail to adequately reflect the level of metacognitive confidence in statements. In this study, in addition to traditional text-based confidence measures, we used a Large Language Model (LLM) to directly analyze confidence and its ratio in statements. LLM-based confidence scores were calculated on statements from the e-SNLI and CoS-E open-source datasets, and the prediction performance obtained with traditional features was compared. The results indicate that traditional surface-level text features explain the variance in LLM-generated confidence scores to a limited extent, and that LLM-based scores are significantly correlated with independent researcher evaluations. This study contributes to the literature by offering a scalable and reproducible analytical framework for measuring metacognitive confidence. It is believed that the findings can be directly applied, particularly in applications where trust is critical, such as automated software test scenario generation, decision support systems, and risk management. The use of LLMs offers a framework for the LLM-based analysis of potential metacognitive confidence signals in natural language explanations by examining the sense of confidence and certainty with which statements are presented, rather than their factual accuracy.

  İncele
• MakaleAçık Erişim2026/r/munzur/4545
  Predicting middle school students' academic achievement in mathematics with aAnew hybrid approach

  Dogan, Gurkan; Demiralp, Demet

  The academic achievement of middle school students is one of the critical steps in their educational journey that affects their future academic and career prospects. During this transition period, students are faced with a variety of challenges related to their families, schools, and the individual themselves. Research shows that academic performance during these formative years is critical for future educational success and overall life success. Therefore, addressing students' academic achievement, which depends on various factors during this period, is of particular importance for both institutional and individual planning and orientation in the future. In this study, a new hybrid approach based on artificial neural networks that enables automatic analysis of data on family, school, and individual factors affecting middle school students' academic achievement in mathematics is proposed. A publicly available student performance dataset was used for training and testing the proposed hybrid approach and other models. This dataset consists of data such as mathematics grades, family information, residential information, and health status information for 395 students enrolled in two public schools in the Alentejo region of Portugal. The proposed approach achieved an R2 score of 88.6% in experimental studies with this data set, providing approximately 3% higher accuracy than its closest competitor among other methods in the literature.

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  AtıfOpenAlex1

  İncele
• MakaleAçık Erişim2026/r/munzur/4263
  Piezoelectric energy harvesters in bridge structures: Evaluation of optimal placement and energy harvesting

  Sen, Bugra; Polat, Alper; Kapicioglu, Abdullah; Esen, Hikmet

  In the present study, energy is harvested from vibrations in bridge structures caused by vehicle passages using piezoelectric energy harvesters (PEHs). In order to maximize the energy harvested, it was aimed to specify the optimal locations of PEHs. In the study, energy harvesting from vibrations in bridge structures was achieved using three different vehicle loads and three different piezoelectric materials. The project of the Ku & scedil;saray & imath;-2 bridge, located in Ku & scedil;saray & imath; village in Baskil, Elaz & imath;& gbreve;, was modelled in the ANSYS program using real measurements. The bridge was analyzed for modal, harmonic, and piezoelectric energy harvesting, respectively. The type with the highest energy production was determined using three different piezoelectric materials (PZT-4, PZT-5A, and PZT-8) for a total of 9 PEHs, and a total of 13 different analyses were performed under three different vehicle loads (60 kN, 90 kN, and 120 kN) to compare the results. The maximum total power obtained from all nine PEHs was 1.484 & micro;W under the 120 kN load with PZT-5A. The maximum power obtained from a single PEH (PEH-1) was 0.49 & micro;W. This power achieved will be adequate for wireless sensor systems used for monitoring the structural health of bridges, and considering that energy harvesting through vibration is independent of meteorological elements, unlike energy sources such as solar and wind, the environmental damage caused by waste batteries in existing systems will be prevented with the dissemination of these systems. With the development of these systems, the energy needs of services such as lighting and traffic signs can be supplied. The results provide an important foundation for the development of vibration-based energy harvesting systems in bridge structures. Thus, the study stands out as an innovative step toward sustainable energy generation in structural engineering.

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• MakaleYalnız künye2026/r/munzur/6107
  Investigation of flow design and deflector plate effect in air cooled battery pack at different discharge rates

  Tuğan, Volkan; Yardımcı, Uğurcan

  In this study, the effect of different flow designs and the use of deflector plates on the thermal performance of an air cooled battery pack was investigated using the CFD method. Model A, which has a conventional single inlet flow structures, was compared with Model B, which employs dual inlets and deflector plates. In both models, 24 cylindrical 18650 lithium-ion battery cells were used, and the inlet and outlet surface areas of the battery pack were designed to be equal. Analyses performed at 3C and 4C discharge rates showed that the dual inlet flow structure and deflector plates significantly improved the cooling efficiency of the battery pack. At a 3C discharge rate, the maximum battery temperature and maximum temperature difference obtained with Model B were 1.87 K and 1.08 K lower, respectively, compared to Model A. At a 4C discharge rate, this improvement became even more pronounced, with the maximum battery temperature reduced by 2.49 K and the maximum temperature difference decreased by 1.44 K. Examination of the temperature contours revealed that, in Model A, heat accumulation occurred particularly in the rear regions, whereas Model B achieved a more homogeneous temperature distribution.

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• MakaleAçık Erişim2026/r/munzur/6101
  Obtaining Natural Dye from Oak Tree and Examination of Dyeing Properties According to Different Methods

  Fırat, Tülay

  This study investigates the dyeing performance of a natural dye extracted from the branches and leaves of the oak tree (soredar) on muslin fabric. The plant materials were soaked in water for 24 h and subsequently boiled to obtain the dye extract. Dyeing experiments were conducted using conventional dyeing methods with and without mordanting. Copper sulphate, iron sulphate, and potassium dichromate were used as mordants to evaluate their influence on the dyeing behavior of the fabric. The color properties of the dyed samples were determined using spectrophotometric measurements based on the CIELab color system, and color strength (K/S) values were calculated using the Kubelka–Munk equation. In addition, the durability of the dyed fabrics was assessed through washing, rubbing, and light fastness tests according to relevant ISO standards. The results revealed that the type of mordant significantly affected both color strength and fastness performance. Among the tested mordants, copper sulphate produced the highest color strength, while iron sulphate also improved dye uptake compared with the non-mordanted sample. Overall, the findings demonstrate that oak-derived natural dye can be effectively applied to muslin fabric and that mordanting plays a crucial role in enhancing the color depth and durability of natural dyeing processes.

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• MakaleAçık Erişim2026/r/munzur/6097
  Dikkat Tabanlı Görsel–İşitsel Akış Füzyonu ile Sahne Sınıflandırma

  Çelik, Yusuf

  Bu çalışmada, sahne sınıflandırma görevlerinde görsel ve işitsel verilerin birlikte kullanılmasına yönelik, Gated Cross-Modal Attention Fusion Network (GCM-AFN) adı verilen çok modlu bir derin öğrenme mimarisi önerilmektedir. Önerilen yapıda, görsel akıştan EfficientNetV2 omurgası kullanılarak derin özellikler çıkarılırken, işitsel akışta MFCC tabanlı zaman-frekans temsilleri kullanılmaktadır. Her iki akıştan elde edilen özellik temsilleri, kapılı dikkat mekanizması aracılığıyla birleştirilmektedir. Model, çok kipli bilgilerin etkin biçimde bir araya getirilmesini sağlamak amacıyla yardımcı akış çıktıları ve dikkat tabanlı bir füzyon stratejisi içermektedir. Çapraz doğrulamaya dayalı deneysel sonuçlar, önerilen yaklaşımın tek akışlı modeller ve geleneksel füzyon yöntemlerine kıyasla daha yüksek doğruluk, daha düşük varyans ve sınıf bazında daha tutarlı bir performans sergilediğini göstermektedir. Elde edilen bulgular, dikkat tabanlı füzyonun görsel–işitsel sahne sınıflandırma görevlerinde etkili bir bilgi birleştirme yaklaşımı sunduğunu ortaya koymaktadır.

  İncele
• MakaleAçık Erişim2026/r/munzur/6091
  Sentiment Analysis of Monkeypox Tweets Using a Hybrid CNN-BiGRU Based Deep Learning Model

  Can, Umit

  Recently, epidemics have disrupted people's lives. Following the COVID-19 pandemic, cases of monkeypox, a rare disease, began to appear worldwide. These incidents raised societal tension and anxiety. Understanding public attitudes, sentiments, and perceptions regarding the epidemic is essential for developing and implementing effective policies and countermeasures. Online social media platforms are essential venues for expressing feelings and views. In particular, Twitter provides valuable information for measuring societal sentiment. Machine learning and deep learning methods have recently been widely used in social network analysis. Deep learning models, which deliver strong performance, particularly on complex and nonlinear problems, are used in natural language processing and text mining. In this study, a Convolutional Neural Network Bidirectional Gated Recurrent Unit (CNN-BiGRU) hybrid deep learning model was developed by combining a CNN and a BiGRU and applied for the monkeypox sentiment analysis. The dataset was labeled as positive, negative, or neutral with Valence Aware Dictionary and sEntiment Reasoner (VADER). In addition, FastText and Term Frequency-Inverse Document Frequency (TF-IDF) word-embedding methods were used for feature extraction, and the performance of machine-learning and deep-learning methods was evaluated separately. As a result of the experimental studies, the FastText-CNN-BiGRU model obtained the highest results with 0.9382 accuracy, 0.9347 macro precision, 0.9367 macro recall, 0.9355 macro F-score, and 0.9875 macro ROC-AUC. The FastText-CNN model was the second most successful, achieving 0.9303 accuracy, 0.9268 macro precision, 0.9280 macro recall, 0.9271 macro F-score, and 0.9862 macro ROC-AUC. The FastText-BiGRU model was the third most successful, achieving 0.9262 accuracy, 0.9224 macro precision, 0.9255 macro recall, 9236 macro F-score, and 0.9838 macro ROC-AUC.

  İncele
• MakaleAçık Erişim2026/r/munzur/6075
  Afet Hazırlığında Stratejik Adım: Tunceli Merkez İlçesi Toplanma Alanlarının AHP ile Analizi

  Ogedey, Aysenur

  Tunceli, zorlu arazi yapısı ve sert iklim koşulları nedeniyle yaşamın güç olduğu bir bölgedir. Kar yağışlarının yoğun olduğu kış ayları ve düşük sıcaklıklar, engebeli topoğrafya ile birleşerek çeşitli afet risklerini artırmaktadır. Bu koşullar, bölgede afet ve acil durum yönetiminin özel planlama ve hazırlık gerektirdiğini göstermektedir. Bu çalışmada, Tunceli’deki toplanma alanlarının değerlendirilmesi amacıyla Çok Kriterli Karar Verme yöntemlerinden Analitik Hiyerarşi Süreci kullanılmıştır. Analitik Hiyerarşi Süreci, ana ve alt kriterler arasındaki önceliklerin belirlenmesine olanak sağlayarak afet yönetimi süreçlerinde karar vermeyi sistematik hâle getirmektedir. Analiz sonuçları, ana kriterler arasında en yüksek ağırlığa sahip faktörün “toplanma alanı güvenliği” olduğunu (0,707) ortaya koymuştur. Alt kriterler kapsamında ise “toplanma alanı özelliği” içinde “erişim ve tahliye kolaylığı” (0,559) ve “erişim” ana kriteri altında “tabela, kroki ve işaretleme ile yer belirleme” (0,550) öne çıkmaktadır. Bulgular, Analitik Hiyerarşi Süreci’nin Tunceli’de afet toplanma alanlarının güvenlik ve erişilebilirlik odaklı planlamasında etkili bir araç olduğunu göstermektedir. Çalışma, ayrıca afet yönetimi uygulamalarında bilimsel ve sistematik karar verme yöntemlerinin önemini vurgulamaktadır.

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• MakaleAçık Erişim2026/r/munzur/5985
  Effect of Source Parameter Variability on RVT-Based Site Response Analysis: A Case Study for the Aegean Region of Türkiye

  Icen, Abdullah

  This study investigates the influence of source parameter variability specifically stress drop and anelastic attenuation on site response analysis using the Random Vibration Theory (RVT) framework. Site amplifications were computed for a representative site in the Aegean region of Türkiye using four different source parameter sets based on regional literature. A single set of randomized Vs profiles was used to account for subsurface variability, while varying source models enabled the evaluation of epistemic uncertainty in site amplification. The epistemic uncertainty associated with source parameters, expressed as τsource, peaks at approximately 0.04 s, reflecting the sensitivity of high-frequency site response to stress drop and attenuation. The study provides a regionally calibrated quantification of source-parameter-driven epistemic uncertainty for the Aegean region. The findings emphasize the need to account for source-related uncertainty in seismic hazard assessment. Unlike most previous RVT-based studies, this work explicitly isolates and quantifies the effect of stress drop and attenuation on site amplification, highlighting a novel contributor to epistemic uncertainty. Future work should incorporate Monte Carlo simulation of source parameters to support PSHA applications.

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