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Sham transcranial direct current stimulation (tDCS) is essential for causal inference but is commonly implemented as ramp-only protocols that may not ensure physiological inertness and may fail to maintain mid-session bl...

This benchmark case study introduces recently developed state-of-the-art general purpose multi-modal nonstationary reliability assessment method for marine, offshore, and naval structures, suitable for physically measure...

Advances in Artificial Intelligence (AI), particularly through Machine Learning (ML) and Deep Learning (DL), have enabled innovative solutions in industries including automotive, healthcare, and transportation. These tec...

Integration of Photovoltaic (PV) generation into oil and gas power networks has transformed fault behaviour by creating highly complex sensitivity challenges for conventional Overcurrent Relay (OCR) coordination and trip...

The article examines current approaches to optimizing the operating modes of distributed technical systems based on automation and intelligent control technologies, using the example of 10 kV electric networks. The analy...

Artificial intelligence (AI) models developed for Global Navigation Satellite System Reflectometry (GNSS-R) observations have demonstrated competitive performance in estimating geophysical parameters, especially ocean su...

Introduction. Self-excited induction generators (SEIGs) play a vital role in renewable energy systems, particularly in remote regions. However, their performance is highly sensitive to excitation capacitance, rotor speed...

Reliable low-latency delivery over satellite downlinks remains fundamentally constrained by long propagation delays, burst-correlated packet loss, and the limited effectiveness of retransmission-based recovery. Although ...

Standby techniques are widely employed in power systems to enhance safety and reliability, and are typically classified as hot, warm, or cold. Recent work has emphasized warm standby because it combines key advantages of...

As Machine Learning Operations (MLOps) adoption accelerates, systematic integration of explainability is imperative for reliability, transparency, and continuous quality assurance. This paper presents a scoping review ex...

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...

Sixth-generation (6G) mobile networks are expected to be AI-native by design, with intelligence embedded directly into the Radio Access Network (RAN) control loop through architectures such as O-RAN, near-real-time RAN I...

Abstract In order to address health monitoring issues on offshore wind turbines, while taking into account engineering know-how and constraints, we propose a robust model identification procedure based on reliability of ...

Anaerobic co-digestion of livestock waste presents a viable approach for addressing environmental challenges and reducing greenhouse gas emissions in semi-urban and rural contexts. This study focuses on the development o...

The field of artificial intelligence (AI), machine learning and intelligent automation has become pervasive in our modern digital world. It extends from business and public services to environmental management and even i...

Mobility-as-a-Service (MaaS) orchestration faces critical challenges in managing the Service Quality Index (SQI), Fleet Utilization Ratio (FUR), and Dynamic Pricing Index (DPI) under uncertain and time-varying urban dema...

ObjectiveThe conventional inversion of surface direct-current (DC) resistivity data faces challenges such as limited exploration accuracy and depth. This study aims to enhance the accuracy and reliability of exploration ...

Abstract Simulating the response of granular materials under realistic loading scenarios is essential for ensuring the reliability of geotechnical infrastructure. This task is particularly challenging because natural soi...

Sustainable infrastructure has emerged as a central pillar in addressing the complex challenges associated with rapid urbanization, population growth, and climate variability. Modern civil engineering practice increasing...

Abstract In this work, the intelligent Levenberg–Marquardt optimization approach is applied to evaluate the activation energy influence on thermo-bioconvection flow of a trihybrid nanofluid including oxytactic microbes...

The Internet of Things (IoT) has emerged as a large-scale ecosystem that integrates sensing, communication, and computation across diverse application domains. Its deployment spans smart homes, wearable devices, industri...

The complex geological environment and frequent natural disasters on the Qinghai–Tibetan plateau pose significant challenges to the reliability of the regional highway transportation network. In this paper, a severity ...

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...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...