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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…

Brain tumor is a progressive disease that significantly affects human life. These diseases can reduce the quality of life by causing losses in motor and cognitive functions. Since the chance of treatment decreases when not diagnosed early, advanced technologie…

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 …

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…

Diabetic retinopathy is the leading cause of blindness among diabetic patients. It occurs when the light-sensitive tissue in the retina is damaged. According to WHO statistics, the current global prevalence of diabetic retinopathy is approximately 103 million …

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. …

Market democratization through conversational AI represents a critical frontier in financial technology, yet cryptocurrency analysis remains dominated by institutional players with sophisticated toolchains. We introduce AICrypto-Assistant, the first open-sourc…

This paper examines the development of sustainable architectural design strategies in office buildings from 1970 to the present. Drawing on literature, policies, and historical examples, it traces the transformation of sustainability from a loosely defined env…

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…

Robust object detection and classification in dynamic industrial scenarios is still a challenge, in particular if the system has to work in real-time on mid-ranged hardware. Classical vision-based methods have difficulties to cope with low/weak illumination, r…

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…

The COVID-19 pandemic has necessitated the development of rapid, accurate, and automated diagnostic tools to assist healthcare professionals in patient screening and management. This comprehensive study presents a detailed comparative analysis of ten state-of-…

Yapay zeka (YZ), tasarım sürecinden karar destek sistemlerine, maliyet analizinden malzeme tespitine kadar pek çok alanda kullanılmakta; tarihi yapılarda ise malzeme bozulmalarının tespiti, restorasyon süreçlerinin iyileştirilmesi ve kültürel varlıkların belge…

This study presents a comprehensive overview of biophilic design research that incorporates ecological considerations, specifically focusing on energy efficiency, thermal comfort, and sustainability. While biophilic design has traditionally emphasized human we…

This study offers a comparative analysis of construction risk management practices in the United Kingdom (UK) and Türkiye, focusing on regulatory frameworks, technological integration, and practical methodologies. The UK, utilizing the Construction (Design and…

Bu çalışmada, el yazısı karakterlerin tanınmasına yönelik derin öğrenme tabanlı bir model geliştirilmiştir. Model, farklı sayıda çıkış sınıfı (karakter) için test edilmiş; yalnızca 10 karakterin sınıflandırıldığı senaryoda %96 doğruluk oranı elde edilirken, sı…

Bitkilerde hastalıkların erken teşhisi, tarımsal verimliliğin artırılması ve ürün kayıplarının önlenmesi açısından büyük öneme sahiptir. Bu çalışmada, tarımsal üretimde önemli kayıplara yol açan bitki yaprak hastalıklarının erken teşhisine yönelik bir yapay ze…

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…

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…

With the help of ability to imitate the biological nervous system, Spiking Neural Networks (SNNs) architectures have become popular recently. In order to benefit at the maximum level from the low power consumption, event-based structure and parallelization fea…