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We are pleased to present to the entire academic community and the general public the following work, which contains recent research results of a group of teachers from the Faculty of Educational Sciences in areas such a...

It is a well-known fact, accepted by most psychologists, that students assimilate knowledge in different ways. Several categories of learners have been identified: oral, visual, kinetic. This has doubtless implications f...

The network society (Van Dijk, 2020) has completely blurred the traditional difference between virtual and real life, Our day to day is increasingly characterised by our continuous connection to the Internet, Multiple da...

Laboratory practice is a fundamental aspect of computer network learning. Experiments tend to be very specific, frequently demanding changes in the local network topology and privileged access to the operating system con...

Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography (CGH). Current data-driven deep learning algorithms face the challenge that the labeled training datasets...

The rapid proliferation of Learning Management Systems (LMS) in K–12 education has generated a substantial body of research, yet how its core themes emerge, converge, and transform over time remains insufficiently unde...

Artificial Intelligence (AI) has become a key enabler of intelligent vehicular (V2X) and Unmanned Aerial Vehicle (UAV) networks. These networks face extreme mobility and rapidly changing topologies, making stable communi...

Travel behavior analysis provides critical insights to enhance the intelligence of transportation systems, enabling more accurate and efficient management of mobility services. However, it requires centralizing user-sens...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Abstract Background Bacterial diseases include any illness caused by bacteria. Bacteria are tiny microorganisms that can only be seen with a microscope. Other types of microorganisms include viruses, fungi, and some para...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Tuberculosis (TB) continues to be one of the foremost public health issues in the world, and remains the second most salient communicable cause of death after COVID-19. In 2022, TB accounted for 10.6 million new infectio...

Abstract To address the challenge of low adaptability in distribution network planning caused by significant regional differences in electricity consumption, this paper proposes a distribution network planning method bas...

Abstract Matching college students with appropriate innovative training projects is a challenging task that often relies on static assignment techniques, which overlook individual interests, skills, and learning styles. ...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...

ABSTRACT Graph contrastive learning (GCL) has emerged as a dominant paradigm for self‐supervised representation learning for attributed graph data. However, existing GCL methods heavily rely on empirical graph data aug...

In this study, a novel Quantum Self-Attention Neural Network for Multi-Model Aerial Image Classification (QSANN-MAIC) is proposed. The objective of this paper is to develop a high-performance learning framework capable o...

Optical neural networks (ONNs) have demonstrated unique advantages in overcoming the limitations of traditional electronic computing through their inherent physical properties, including high parallelism, ultra-wide band...

Recently, deep learning has yielded transformative success across optics and photonics, especially in optical metrology. Deep neural networks (DNNs) with a fully convolutional architecture (e.g., U-Net and its derivative...

Abstract Background Advanced machine learning methods combined with large sets of health screening data provide opportunities for diagnostic value in human and veterinary medicine. Hypothesis/Objectives To derive a model...

In learning environment, portfolio is used as a tool to keep track of learner’s progress. Particularly, when it comes to e-learning, continuous assessment allows greater customization and efficiency in learning process...

In this paper, we propose a new visual tracking method in light of salience information and deep learning. Salience detection is used to exploit features with salient information of the image. Complicated representations...

Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies h...