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Âşık Tarzı Kültür Geleneği Ve Kültür Endüstrisi Bağlamında Unkapanı Plakçılar Çarşısı (İMÇ)
No full textÇocuk Haklarının Korunmasında Bir Aktör Olarak Kamu Denetçiliği Kurumu: Tavsiye Kararlarının Etkililik Analizi
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Açık ve kapalı alan sporcularının KLOTHO, FGF23, kas kuvvetleri, antropometrik ve bazı performans ölçümlerinin değerlendirilmesi
No full textA Novel Framework Leveraging Social Media Insights to Address the Cold-Start Problem in Recommendation Systems
No full textIn today’s world, with rapidly developing technology, it has become possible to perform many transactions over the internet. Consequently, providing better service to online customers in every field has become a crucial task. These advancements have driven companies and sellers to recommend tailored products to their customers. Recommendation systems have emerged as a field of study to ensure that relevant and suitable products can be presented to users. One of the major challenges in recommendation systems is the cold-start problem, which arises when there is insufficient information about a newly introduced user or product. To address this issue, we propose a novel framework that leverages implicit behavioral insights from users’ X social media activity to construct personalized profiles without requiring explicit user input. In the proposed model, users’ behavioral profiles are first derived from their social media data. Then, recommendation lists are generated to address the cold-start problem by employing Boosting algorithms. The framework employs six boosting algorithms to classify user preferences for the top 20 most-rated films on Letterboxd. In this way, a solution is offered without requiring any additional external data beyond social media information. Experiments on a dataset demonstrate that CatBoost outperforms other methods, achieving an F1-score of 0.87 and MAE of 0.21. Based on experimental results, the proposed system outperforms existing methods developed to solve the cold-start problem
International Academic Research and Studies in the Field of Agriculture, Forestry and Aquaculture Sciences
No full textMulti-Version YOLO-Based Inventory Detection for Automated Facility Management
No full textEffective inventory tracking plays a crucial role in facility management by optimizing resource allocation, reducing operational costs, and minimizing manual effort. This study conducts a comparative analysis of multiple YOLObased deep learning models YOLOv8, YOLOv9, YOLOv11, and YOLOv12 for office inventory detection and quantification. The primary objective is to assess the performance of these models in accurately identifying and counting office supplies from image data. Since standard YOLO architectures do not include predefined categories for office inventory, a custom dataset is developed. A total of 10,000 images of common office inventory items are gathered through web crawling, and 2,000 images are manually annotated using Roboflow to facilitate model training. The dataset comprises 14 distinct office inventory classes, ensuring a broad representation of essential items. Each YOLO version is evaluated based on detection accuracy, processing speed, and computational efficiency. Comparative experimental results reveal the strengths and limitations of each model, highlighting the trade-offs between precision and inference time. The findings provide valuable insights into the most suitable YOLO architecture for real-world facility management applications, contributing to the advancement of automated inventory tracking systems
Religious Institutions and Educational Policies in Combating Violence Against Women: The Case of Türkiye
No full textViolence against women remains one of the most persistent social problems in T & uuml;rkiye, often reinforced by patriarchal interpretations of religion and cultural traditions. This study investigates the role of religious institutions and values-based education in preventing such violence by analyzing national curricula, mosque sermons, policy documents, and reports of the Presidency of Religious Affairs. Using a qualitative design based on document analysis and literature review, it examines how religious education reflects or omits gender-related themes and how institutional practices shape public awareness. The findings reveal that while formal and non-formal types of religious education promote moral values such as compassion, justice, and respect, they rarely address gender-based violence explicitly. Religious discourse tends to emphasize general moral development rather than specific strategies for preventing violence against women. The study concludes that integrating gender-sensitive content into religious curricula, promoting authentic Qur'anic teachings on equality and mercy, and providing professional training for religious personnel are essential to transforming societal attitudes. Strengthening cooperation between educational institutions, religious authorities, and policymakers will ensure that religion functions as a constructive moral resource rather than a tool for legitimizing inequality
