Search

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…

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…

Based on the crucial role of vocabulary in language education, the present study set out to examine preservice EFL teachers views on learning and teaching vocabulary. The main aim in so doing is to enhance teacher education programs in terms of more effective…

We are at a time when electronic systems are structured in a manner similar to the human brain.The memristor, a neuromorphic circuit designed by Chua in 1971, is a modeling of synaptic learning and associative learning. Neuromorphic circuit elements and memris…

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…

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…

Traffic flow forecasting has an important place in designing a successful intelligent transportation system. The success of the forecasting is related to the accuracy and timely acquisition of the traffic flow data. The inadequacy in the number of data has led…

Network security is becoming more and more important as a result of the growing use of the internet and technological developments. Intrusion Detection Systems (IDS) are utilized to detect attacks, preferably by monitoring real-time events. Therefore, they hol…

Inquiry-based learning is important for students to understand scientific knowledge and the working systems of scientists to develop their knowledge. For this, students should have some skills, and if they do not have, these skills need to be gained. Some of…

What makes a learner “a good learner” and how we can use this to improve the learning of the other learners have long been discussed and studied. Studies conducted throughout years have shown that “Language Learning Strategies” affect the learners in many ways…

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 …

Diabetes is a chronic disease affecting millions worldwide, necessitating early and accurate diagnosis for effective management. Traditional diagnostic methods, while reliable, often struggle with efficiency and early-stage detection. Deep learning has emerged…

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-…

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…

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. …

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 …

The study will utilize machine learning algorithms such as Random Forest, Gradient Boosting, and Support Vector Regression (SVR) on data collected from the districts of Nalgonda, Yadadri Bhuvanagiri, and Suryapet over the past two years. The project seeks to m…

Palmprint recognition (PR) has garnered significant interest due to its distinctive characteristics and potential applications as a robust and secure biometric authentication (BA) method across various domains. This paper introduces a novel approach to enhance…

This study aims to examine the feasibility and impact of conducting laboratory experiments, a fundamental component of electrical and electronics engineering education, on a virtual reality (VR)-based platform. The innovative platform, named "VR-EE Lab," provi…

Handwritten Signature Recognition (HSR) is a vital task in document authentication and verification systems. This paper proposes a novel approach for offline HSR leveraging pre-trained Convolutional Neural Network (CNN) models. CNNs have demonstrated remarkabl…