Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Deprem Anında ve Sonrasında Dönüşebilen Tasarım Önerileri: Günlük Kullanımdan Hayat Kurtaran Birimlere(Afet ve Acil Durum Yonetimi Baskanligi (AFAD), 2025-12-30) Özmen, Nihan Muş; Kurtuluş, Vacide BetülDepremler, yıkılan binalar ve devrilen eşyalar nedeniyle meydana gelen yaralanmalarla insan hayatını ciddi şekilde tehdit etmektedir. Bu çalışma, mobilyalara kendini kurtarma alanları entegre ederek ezilme yaralanmalarını önlemeyi ve deprem sonrası barınma ihtiyaçlarını karşılamayı amaçlayan tasarım önerileri sunmaktır. 2022 Güz döneminde Abdullah Gül Üniversitesi Deneysel Tasarım Stüdyosu kapsamında yürütülen çalışma, tanınmış bir mobilya tasarım firmasıyla iş birliği içinde gerçekleştirilmiştir. Öğrenciler hem günlük yaşamda işlevsel hem de afet anlarında acil barınma alanı olarak kullanılabilecek çift amaçlı mobilya tasarımları geliştirmiştir. Projeler, deprem sırasında ve sonrasında kullanılmak üzere iki ana kategoriye ayrılmış; yaşam ve çalışma mekânlarında, dönüşebilir mobilya tasarımlarına odaklanmıştır. Bulgular, işlevsel ve uyarlanabilir tasarımlar yoluyla risk azaltma ve deprem sonrası uyum konularında yenilikçi yaklaşımları ortaya koymaktadır.Article Citation - Scopus: 5University Librarians’ Perceptions Of Artificial Intelligence, Its Application Areas İn Libraries, And The Future(University and Research Librarians Association (UNAK), 2024-12-26) Cuhadar, S.; Mert, S.; Gezer, Ç.; Helvacioğlu, E.; Arus, O.; Aslan, Ö.; Atli, S.; Gurdal, Gultekin; Erken, MehmetToday, libraries are among the institutions affected by changing technology and innovations. The popularization of artificial intelligence (AI) technologies has also begun to transform library services. In this research, a survey was conducted to determine the adjustments that university libraries in Turkey have made and plan to make during the development process of AI technologies and applications, and to identify the services they have developed specific to the relevant period. The survey was carried out with the participation of 111 university library managers from 208 university libraries in Turkey. Through the analysis of the data, the status, knowledge, and awareness levels of university libraries regarding AI technologies and applications were determined, and measures and recommendations were presented to improve deficiencies and weaknesses. This research is the first and most comprehensive study conducted in Turkey by obtaining opinions and suggestions from university library managers on artificial intelligence. The research findings revealed that university libraries use AI applications such as ChatGPT, Gemini, and Grammarly to a certain extent; however, they have needs in developing institutional policies, enhancing personnel competencies, and planning related to AI. © 2024 University and Research Librarians Association (UNAK). All rights reserved.Conference Object High Performance and Resource Efficient Low Density Parity Check Decoder Design(IEEE, 2025-06-25) Unal, BurakLow Density Parity Check (LDPC) codes have gained popularity in communication systems due to their capacity-approaching error correction performance. In this study, a highperformance LDPC decoding algorithm with extremely low resource usage is proposed. Among the hard decision class of LDPC decoders, Gallager B (GaB) provides high-performance hardware due to its computational simplicity. However, GaB suffers from poor error-correction performance. In this study, a new intrinsic computation technique for GaB called Intrinsic Gallager B (IGaB) is introduced to improve error correction performance. Our simulation results show that the IGaB algorithm provides better error correction performance compared with GaB. GaB and IGaB algorithms are implemented on Field Programmable Gate Array (FPGA) to compare hardware performance.Article Citation - Scopus: 1Kayseri İlindeki Bazı Tarihi Eserlerde Bozunma Etkilerinin Tahribatsız Deney Yöntemleriyle Değerlendirilmesi(TMMOB Chamber of Geological Engineers, 2025-06-11) Akin, Mutluhan; Akin, Muge; Akgül, Muhammed Kamilİç Anadolu’da önemli bir yerleşim merkezi olan Kayseri, farklı dönemlerden günümüze kadar gelen birçok tarihi esere ev sahipliği yapmaktadır. İlin farklı bölgelerinde özellikle yoğun yerleşimin bulunduğu alanlarda, Selçuklu Dönemi’ne ait 12. ve 14. yüzyıllar arası yapılmış çok sayıda cami, kümbet ve medrese türü tarihi esere rastlamak mümkündür. Kültürel miras niteliğindeki bu eserler çoğunlukla yakın çevrede yoğun olarak bulunan farklı renk ve dokudaki ignimbirit türü kaya malzemesi kullanılarak inşa edilmişlerdir. Genel olarak düşük dayanıma sahip ve su etkilerine karşı hassas olan bu ignimbiritler zaman içerisinde atmosferik etkenler, hava kirliği, vandalizm vb. gibi olaylar sonucunda bozunmakta ve ilksel özelliklerini kaybetmektedirler. Bu çalışmada Kayseri il merkezindeki Roma ve Selçuklu dönemlerine ait tarihi eserler ile bu eserlerde zaman içinde meydana gelen bozunma etkileri incelenmiştir. Bozunma etkilerinin gözlemsel olarak incelenmesinin yanı sıra, eserlere herhangi bir zararı bulunmayan tahribatsız deney yöntemlerinden İğne Penetrometresi, Schmidt Çekici ve P-dalga hızı deneylerinden faydalanılmıştır. Bunun yanı sıra, bozunmuş ignimbirit bloklarına ait yerinde deneylerle belirlenen değerler, aynı malzemeye ait taze örneklerin fiziko-mekanik özellikleri ile karşılaştırılmıştır. Yapılan değerlendirmeler sonucunda tarihi eserlerin taban bölümlerinde özellikle kılcallık sebebiyle pullanma ve kavlaklanma türü bozunmaların geliştiği ve ignimbiritlerin bu bölümlerde dayanımlarını önemli ölçüde kaybettiği tespit edilmiştir. İncelenen kümbetlerin bazılarına uygulanan iyileştirme çalışmalarında ise kümbetlerin çevresinde bulunan yüzey suyu drenajlarının yeterli ölçüde yapılamadığı ve yağmur ile biriken suların tarihi eserlerin daha fazla bozunmasına sebep olduğu saptanmıştır. Kültürel miras olarak değerlendirilen bu tarihi yapıların korunup gelecek nesillere aktarılması amacıyla, ignimbirit yapılarının yüzeysularına karşı duyarlılığı dikkate alınarak tarihi kümbetlerin çevresinde su drenajı iyileştirme çalışmaları yapılması önerilmektedir.Conference Object Citation - WoS: 2Citation - Scopus: 2Fine Tuning DeepSeek and Llama Large Language Models with LoRA(IEEE, 2025-06-25) Uluirmak, Bugra Alperen; Kurban, RifatIn this paper, Low-Rank Adaptation (LoRA) finetuning of two different large language models (DeepSeek R1 Distill 8B and Llama3.1 8B) was performed using the Turkish dataset. Training was performed on Google Colab using A100 40 GB GPU, while the testing phase was carried out on Runpod using L4 24 GB GPU. The 64.6 thousand row dataset was transformed into question-answer pairs from the fields of agriculture, education, law and sustainability. In the testing phase, 40 test questions were asked for each model via Ollama web UI and the results were supported with graphs and detailed tables. It was observed that the performance of the existing language models improved with the fine-tuning method.Conference Object Citation - WoS: 1Citation - Scopus: 1Prediction of Type 2 Diabetes Using Metagenomic Data and Identification of Taxonomic Biomarkers(IEEE, 2024-05-15) Temiz, Mustafa; Kuzudisli, Cihan; Yousef, Malik; Bakir-Gungor, BurcuNowadays, different molecular levels of -omics data on diseases are generated and analyzing these data with machine learning methods is one of the popular research topics. Among these data, the use of metagenomic data to facilitate the diagnosis, detection and treatment of diseases is increasing day by day. Type 2 diabetes (T2D) is a chronic disease characterized by insulin resistance and progressive dysfunction of pancreatic beta cells. While the number of people with diabetes is increasing by around 8% annually, the cost of treating the disease is rising by 18% per year. Therefore, the number of studies on the diagnosis, development and progression of T2D is increasing over time. The aim of this study is to achieve higher machine learning performance by using fewer metagenomic features and to achieve better classification performance by reducing computational costs. In this study, we compare the performance of three different methods using T2D-related metagenomic data. First, the MetaPhlAn tool is used to calculate the taxonomic species and their relative abundances in each sample. The SVM-RCE, RCE-IFE and microBiomeGSM tools used in this study are methods that perform classification by grouping and scoring features and are known to work well on complex datasets. In this study, the best results were obtained with the RCE-IFE tool with an AUC of 0.72 with an average of 125 features information. In addition, key taxonomic species identified by these tools as associated with T2D are presented in comparison to the literature.Article 3D Sampling of K-Space With Non-Cartesian Trajectories in MR Imaging(Gazi Univ, Fac Engineering Architecture, 2025-02-03) Dundar, Mehmet Sait; Gumus, Kazim Z.; Yilmaz, BulentThis study presents an innovative approach to 3D k-space sampling in MR imaging using non-Cartesian concentric shell trajectories. The method involves 32 concentric shells of varying radii, allowing for rapid data acquisition through undersampling techniques. Simulations using IDEA software demonstrate that this approach can fill the k-space in less than one second, a significant time reduction compared to traditional FLASH sequences that can take 3-4 minutes. The concentric shell model enhances imaging efficiency by minimizing artifacts and ensuring uniform k-space filling, leading to higher resolution and faster scans. This technique shows promise for clinical applications, particularly in dynamic imaging scenarios such as acute stroke and pediatric radiology, where speed and precision are critical. As illustrated in Figure A, the concentric shell trajectories enable uniform k-space filling, significantly reducing scan times and improving image quality. These results are based on the simulations conducted with IDEA software.Conference Object Citation - WoS: 1Citation - Scopus: 1The Identification of Discriminative Single Nucleotide Polymorphism Sets for the Classification of Behcet's Disease(IEEE, 2018-09) Gormez, Yasin; Isik, Yunus Emre; Bakir-Gungor, BurcuBehcet's disease is a long-term multisystem inflammatory disorder, characterized by recurrent attacks affecting several organs. As the genotyping individuals get cheaper and easier following the developments in genomic technologies, genome-wide association studies (GWAS) emerged. By this means, via studying big-sized case-control groups for a specific disease, potential genetic variations, single nucleotide polymorphisms (SNPs) are identified. Although several genetic risk factors are identified for Behcet's disease with the help of these studies via scanning around a million of SNPs, these variations could only explain up to 200/u of the disease's genetic risk. In this study, for Behcet's disease classification, via comparing all the SNPs genotyped in GWAS, with the SNPs selected via using genetic knowledge, gain ratio and information gain; both reduction in the feature size and improvement in the classification accuracy is aimed. Also, using different classification algorithms such as random forest, k-nearest neighbour and logistic regression, their effects on the classification accuracy are investigated. Our results showed that compared to other feature selection methods, with at least 81% success rate, the selection of the SNPs using the genetic information (of their GWAS p-values, indicating the significance of the SNP against the disease) provides 15% to 42% improvement in all classification algorithms. This improvement is statistically sound. While gain ratio and information gain feature selection techniques yield similar classification accuracies, the models using all SNPs could not exceed 50% accuracies and results in the worst performance.Conference Object Citation - Scopus: 2Kısa Ve Orta Mesafe Gece Yangını Tespiti(Institute of Electrical and Electronics Engineers Inc., 2017-05) Agirman, Ahmet K.; Taşdemir, Kasím; Aggirman, Ahmet KerimComputer vision methods used for night-time fire detection are limited. Existing works are for detection of distant night fires recorded from watch towers. In this paper, detection of short to mid-range night fires from video cameras are aimed. Flames in short distance flicker, grow and move more rapidly compared to ones in long distance. Features obtained by taking advantage of these distinctions let us detect fire over 90% accuracy on average in videos containing deceptive light sources like common city lights and headlights of vehicles. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 2Beyin Dalgalari ve Baş Hareketiyle Gerçek Zamanli Robotik Araba Kontrolü(Institute of Electrical and Electronics Engineers Inc., 2018-11) Oztürk, Nedime; Yilmaz, Bulent; Onver, Ahmet YasinEmotiv Epoc Headset is a portable and low-cost device. In this study, Emotiv Epoc headset was used in order to obtain real-time gyro and EEG signals. The aim of this study was to control a robotic car in real-time by using head movement and opening and closing of the eyes. The maximum and minimum amplitude of the gyro signal, and the ratios of the beta waves of O1 and O2 channel to alpha waves of the same channels were used as threshold values. These threshold values were used to determine the direction of the robotic car. Because of its low-cost and easy implementation, Arduino Uno was used to manage the robotic car. This study has shown that brain waves and head movements can control a device in real time. This system has the potential to be used in neurofeedback and brain-computer interface applications. © 2019 Elsevier B.V., All rights reserved.