TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/9
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Article Kiminle Konuşuyorum Ben?: Sohbet Robotlarının Belleği ve Kişiselleştirilmiş Sohbet Etkileşimi üzerine(2025) Güregen, Esra Pelin; Ecem, Ergül; Eyrek, AysunDeveloped by OpenAI in 2022, ChatGPT is a chatbot based on a large language model that has evolved beyond generating human-like dialogue to become a versatile tool producing a wide range of content, from official documents to literary texts. Research indicates that users often feel as though they are communicating with a human during their interactions with artificial intelligence. In 2024, OpenAI introduced the “conversational memory” feature to ChatGPT, enabling the system to store and process past interactions with users. This innovation allows the chatbot to refer to previous conversations and generate more personalized and contextually appropriate responses. At the same time, it raises ongoing debates regarding its implications for human experience and agency. This study aims to examine the impact of ChatGPT’s conversational memory feature on user experience. Employing a qualitative approach, semi-structured in-depth interviews were conducted with 30 ChatGPT users, divided into two groups: those who use the conversational memory feature and those who do not. The findings reveal that participants who utilized the memory feature described their interactions as more personalized, consistent, and emotionally engaging. In contrast, participants who refrained from using the feature reported more transactional and utilitarian experiences, often citing concerns related to data privacy and user autonomy. The study highlights that chatbots are no longer perceived merely as technical tools; rather, they are seen as digital agents capable of addressing users’ emotional needs. This study also underlines the need for studies on human-artificial intelligence interaction, digital connectedness, and trust in technological systems.Article Evaluation of Cutting-Edge Object Detection Architectures on Multi-Object and Single-Object Datasets(2026) Parlak, CevahirThis study focuses on the performance evaluation of cutting-edge object detection models, namely, YOLO12X, Mask R-CNN, RT-DETR-X, and RF-DETR-Large on the Open Images (Multi-Object) and LaSOT (Single-Object) datasets. Current cutting-edge trend applications involve CNN-based and Transformer-based object detection models. CNN-based models can use one-pass (YOLO family) or two-pass (R-CNN family) implementations. One-pass object detection models can be faster but suffer from accuracy compared to the two-pass models. Transformer-based models can use Detection Transformers or Vision Transformers. Transformer-based models are gaining popularity, and their performance surpasses CNN-based models. This study evaluates YOLO12X, Mask R-CNN from CNN-based family, and RT-DETR-X, RF-DETR-Large transformer-based architectures in terms of accuracy and time on the Open Images and the LaSOT datasets. All models are the largest available models and pretrained on COCO dataset. Transformer-based models incorporate special types of self-attention and pose significant improvement both on accuracy and speed. The experimental results demonstrate that attention and transformer-based models perform better than the traditional CNN-based object detectors and YOLO12X is the fastest method with a far margin. On the LaSOT dataset, RT-DETR-X posts 0.8804 IoU, 0.7047 F1-score, 0.6597 mAP@0.5, 28.64 fps whereas YOLO12X achieves 0.8572 IoU, 0.6657 F1-score, 0.5357 mAP@0.5, and 49.78 fps.Other Blokzincir Teknolojisi Bilgiye Erişimde Nasıl Kullanılır? Mevcut Durum ve Potansiyeller(2020) Çetin, BelginFinans sektörünün gereksinimi olarak gündeme gelen blokzincir teknolojisi hakkında sonzamanlarda başta sağlık olmak üzere eğitim, hukuk, yayıncılık sektörü, bilimsel bilişim ve bilgiyönetimi gibi alanlarda da bahsedilmeye başlanmıştır.Makale, teknolojinin özellikle bilgi yönetimi üzerine etkilerinin yanı sıra bilimsel bilişim, açık verive açık bilim konuları üzerindeki etkilerini açıklamaya çalışmaktadır.