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Adaptive research systems can generate, discard, revise, and monitor trading rules faster than their selection history can be audited. We ask when such a system may promote a frozen rule to governed forward evaluation. The proposed protocol assigns each candid…

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…

Today, with the rapidly development of technology, artificial neural networks (ANN) usage as an alternative to statistical methods increase in many fields such as finance sector, medical science, defense industry, production, robot systems, image processing an…

The rapid expansion of the mobile gaming industry has underscored the need to understand user sentiment, with social media platforms like X (Twitter) providing key insights. This study applied sentiment analysis to English and Turkish tweets, utilizing the TEM…

Deep learning can provide successful results in detecting manipulations made with bot accounts on the X (Twitter) platform and preventing disinformation. As a method for applying deep learning algorithms, numerical values in the data set can be visualized and …

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…

The Internet of Vehicles (IoV) is a branch of the Internet of Things that deals with vehicle-to-vehicle communication and intelligent transport systems (ITS). But this connection is not without consequences, because the more a system exchanges information, the…

Bu çalışmada UCI Makine Öğrenmesi havuzundan alınan kardiotokogram verisinde morfolojik örüntü sınıflandırması yapılmıştır. Sınıflandırıcı olarak kompleks değerli yapay sinir ağları kullanılmıştır. Sınıflandırıcının performansı 10-katlı çapraz doğrulama yaklaş…

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…

Differentiated thyroid cancer (DTC) is the most frequent form of thyroid cancer. Although this type of cancer shows a favourable prognosis, the risk of recurrence remains a critical concern. Early and accurate prediction of the risk of recurrence is essential …

Nowadays, very large quantities of data are produced both individually and institutionally. These data must be preserved very well in order to be able to access and process them as needed. This situation necessitates data recovery services in possible disast…

The purpose of this study is to examine the software libraries and data sets used for Deep Learning architectures. Deep Learning brings a different perspective to the field of artificial intelligence. It has begun to be used an incredibly wide field in recent …

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…

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…

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 …

Word embedings are intense vector representations of words. They capture the semantic order between words. In our study, we propose a new method for classifying text by author, using word embeds and author vector space. Using each author's books, we trained th…

Multiple Birth Support Vector Machines (MB-SVM) were introduced as a powerful extension of SVM. Although the basic idea is like SVM, optimal non-parallel hyperplanes are used for each class category. One may find different implementations of this approach in t…

It is important to determine the initial level of failures of induction motors used in many industrial applications. The sudden stops of the system can be prevented with the pre-detection of the fault. The experiment mechanism was established to detect mechani…

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…

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…