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This study aims to evaluate fire safety and escape route design in student dormitories. Ismail Necati Efendi KYK Dormitory and Hubbi Hatun Dormitory in Karabük province were comparatively examined in terms of space organization, user density, number and placem…

This study presents a comparative evaluation of five widely adopted blockchain consensus algorithms—Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Practical Byzantine Fault Tolerance (PBFT), and Proof of Authority (PoA)—based on en…

In this study, diabetes prediction was conducted using XGBoost, Support Vector Machines (SVM), and a Multilayer Artificial Neural Network (ANN). Attributes that cannot be biologically ‘0’ (e.g. glucose, BMI) were first marked as NaN. After filling the missing …

Author research interest is using AI tools in learning in any field connected with education. In this study proposes the idea of how to make the educational process more flexible in the post-pandemic period using the Artificial Intelligence (AI) technologies. …

We developed a series of financial social media sentiment analysis models starting with PyFin-Sentiment, a recent state-of-the-art domain-specific large language model for the financial domain. We focused on label accuracy and improvements in the quality and q…

Blokzincir teknolojileri, asimetrik şifreleme, hash algoritmaları, dağıtık yapı, akıllı sözleşmeler ve konsensüs mekanizmaları gibi kavramlara dayanır. Konsensüs mekanizmaları, blokzincir teknolojisi de dahil olmak üzere dağıtık sistemlerde, tüm düğümlerdeki v…

Sunulan çalışmada, kalp hastalığı riskinin erken ve güvenilir biçimde tahmin edilmesini sağlayan makine öğrenmesi tabanlı bir mobil uygulama geliştirilmiştir. Dokuz farklı algoritma değerlendirilmiş, en yüksek doğruluğa (%86,81) sahip olan k-NN modeline rağmen…

This study presents a Hybrid Digital-Physical Risk Management Framework designed to enhance urban climate resilience through the integration of Industry 4.0 technologies. By combining real-time IoT sensor networks, AI-based predictive analytics, and blockchain…

In this study, a classification problem is discussed to predict whether individuals' annual income levels are above $50,000. The UCI Adult Income Dataset, which is derived from the 1994 US Census (Census) data and is widely used in the field of machine learnin…

Solar photovoltaic (PV) systems are widely adopted for sustainable energy production; however, physical defects such as glass breakage significantly reduce panel efficiency and system output. In this study, a real-world case analysis was conducted on a 1003 kW…

The Designesart Collection was created as part of the master’s program in Furniture and Interior Design at the Instituto Politécnico de Castelo Branco’s Escola Superior de Artes Aplicadas, Portugal. It is a product series that values inherent Beira Baixa’s ter…

Predictive maintenance (PdM) enhances industrial operational efficiency by facilitating timely detection of equipment failures using machine learning models developed from historical maintenance data.  Real-world industrial datasets frequently exhibit signific…

Maritime vessel detection in satellite images address real time issues such as maritime security, illegal fishing and environmental monitoring, which require efficient tracking of vessels in large scale. Maritime vessel detection is challenged by limited annot…

Early detection of lung cancer remains a critical challenge in medical imaging, where accurate classification between benign and malignant pulmonary nodules can significantly impact patient outcomes. This study presents a comprehensive comparative analysis of …

The rapid growth of city populations and the increasing complexity of managing city infrastructure have led to the emergence of smart cities, which rely on advanced technologies to optimise urban services. However, one of the key challenges facing smart cities…

Accurate and transparent blood glucose forecasting is crucial for effective diabetes management. This paper presents an interpretable deep learning (DL) framework based on multi-task learning (MTL) for forecasting glucose levels at multiple prediction horizons…

The emergence of Open Finance is reshaping the global financial landscape by enabling greater data accessibility, interoperability, and innovation. However, this expanded connectivity introduces new layers of regulatory complexity, raising urgent concerns rega…

Generative Artificial Intelligence is gaining popularity every day and uses contextual data to personalize and enhance user experiences. This paper explores music generation that is conditioned on weather. It influences musical compositions by connecting MIDI …

Healthcare fraud, waste, and abuse (FWA) are among the most significant drivers of financial inefficiency in healthcare systems worldwide, with estimates suggesting they contribute to as much as 10% of total healthcare expenditures. In the United States, these…

Efficient semantic segmentation and compression of 3D point cloud data are essential for enabling scalable, real-world applications involving large-scale LiDAR environments. This work presents a lightweight hybrid framework that integrates point transformer v3…