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The increasing penetration of renewable energy sources (RES) reduces power system inertia, causing severe frequency excursions following disturbances. Conventional Automatic Generation Control (AGC) using fixed-gain cont...

Federated learning (FL) in mobile edge computing (MEC) operates over wireless links with time-varying bandwidth, latency, and packet loss, which makes conventional full-model synchronization inefficient and vulnerable to...

To achieve high accuracies in deep learning-based inspection of IC markings, a large number of manually labeled images of good and defective markings are needed. In many IC production lines, only a handful of labeled ima...

Efficient UAV path planning in large and dynamic environments requires adaptive strategies that account for varying regional importance. Traditional coverage or Reinforcement Learning-based methods often suffer from redu...

Timely prediction of Intensive Care Unit (ICU) admission at hospital arrival is critical for clinical decision-making, resource allocation, and patient management, particularly during large-scale health crises such as th...

Adaptive learning systems require effective mechanisms to model students’ evolving learning states and provide personalized learning path recommendations. Traditional rule-based approaches are limited in capturing...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

Vegetation optical depth (VOD), as a key parameter of vegetation, plays an important role in the process of vegetation growth and change. The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technolog...

Forest growth and yield projection is essential for sustainable forest management planning. In Brazil, the Clutter model is widely applied for yield forecasting and commonly achieves prediction errors below 10%. However,...

Autonomous microrobotic navigation in life sciences is highly challenging due to environmental disturbances, unpredictable phenomena, diverse obstacles, and dynamic changes. These significantly limit motion of microrobot...

Industry 4.0 has brought numerous advantages, such as increasing productivity through automation. However, it also presents major cybersecurity issues, such as cyberattacks affecting industrial processes. Federated Learn...

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework ...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

This paper presents an innovative methodology for modeling and predicting high-frequency harmonic losses in the rotating field of an electrical machine powered by a frequency converter. Conventional approaches are often ...

Despite the impressive strides of large language models (LLMs) in text summarization, their effectiveness still hinges on well-crafted prompts, a process that remains labor-intensive, subjective, and difficult to scale. ...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

Even with the introduction of additional security features, the progression toward 6G and Open Radio Access Network (O-RAN) architectures expands security risks, increasing both the scale and complexity of mobile network...

This study investigates the long-term aging effects and structural degradation mechanisms of photovoltaic (PV) modules integrated into smart city furniture, with a particular focus on panels of 10 W, 25 W, and 40 W nomin...

Multimodal remote sensing image registration is a fundamental step for multisource data fusion and geospatial analysis. However, nonlinear radiometric, textural, and geometric discrepancies across modalities challenge in...

An accurate intraoperative assessment of tissue perfusion in digestive surgery is critical to prevent complications such as anastomotic leakage, an event in which a surgical connection between organs fails to heal proper...

ARM-based systems are widely deployed in edge and IoT settings, where penetration-testing tools must operate under strict memory, power, and thermal constraints, yet prior work offers limited deployment-oriented guidance...

Manual monitoring of intravenous (IV) therapy is labor-intensive and susceptible to human error, posing risks to patient safety. Existing computer vision-based approaches have addressed either drip rate estimation or flu...

This study examines the relationship between preschool children’s emotional expression and colour use in digital drawings produced during an authentic classroom activity. A total of 216 children created drawings a...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...