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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…

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…

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 …

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…

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…

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…

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…

A universally applicable “optimal photobioreactor” design has yet to be established, as the success of such systems varies depending on the algal species used, environmental conditions, and intended applications. Meanwhile, the accelerating pace of climate cha…

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…

Afet risklerinin azaltılmasında, fiziksel zarar görebilirlik düzeylerinin mekânsal olarak belirlenmesi ve görselleştirilmesi, kentsel dayanıklılığın artırılması açısından kritik bir öneme sahiptir. Bu çalışma, Amasya kent merkezinde afet kaynaklı fiziksel kırı…

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…

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…

This paper explores the role of archival study in exploring site integrity within the Historic Urban Landscape (HUL) framework, using the case of Islamic heritage sites in Java, Indonesia. In contexts where material traces have been lost or obscured, archival …

Moda endüstrisinde hızlanan üretim ve tüketim döngüsü ciddi çevresel sorunlara yol açmaktadır. Bu nedenle sürdürülebilir tasarım ve üretim uygulamaları büyük önem kazanmıştır. Temelleri 1960’lı yıllarda atılan sürdürülebilirlik hareketi, moda endüstrisinde çev…

This study investigates the return on investment (ROI) of Building Information Modelling (BIM) in the construction industry and addresses common barriers to its adoption such as high start-up costs and lack of familiarity with the technology. Despite its prove…

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…

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…

Microalgae are recognized as environmentally sustainable and biologically renewable resources for the production of high-value products such as biomass, biofuels, dietary supplements, and pharmaceuticals. However, their large-scale cultivation is highly sensit…

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…