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This paper introduces a novel hybrid machine learning model that combines Long Short-Term Memory (LSTM) networks and SHapley Additive exPlanations (SHAP) to enhance bug localization across multiple software platforms. Th...

Abstract Investigations into aviation accidents aim to identify root causes and enhance safety. Despite advancements in safety measures, technology, and education, general aviation accident rates remain stable, with los...

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffi...

ABSTRACT For the spiro‐OMeTAD‐based hole‐transporting layer (HTL), despite its widespread implementation, the pragmatic deployment of perovskite solar cells remains profoundly constrained by multifaceted intrinsic ...

As smart meter technology advances, advanced metering infrastructure (AMI) enables the collection of high-resolution energy consumption data, such as 15-minute interval electricity and gas usage. While anomaly detection ...

Abstract This article presents the analysis of a hybrid, error correction-based, neural network model to predict the path loss for suburban areas at 800 MHz and 2600 MHz, obtained by combining empirical propagation model...

Additive manufacturing (AM) is a rapidly growing industrial fabrication technology. It provides engineers with a growing library of advanced materials, ranging from thermoplastics to metals and cement-based composites, e...

In response to the inaccuracy model of low-voltage power grid, a solution method based on AMI(advanced metering infrastructure) data and metering point errors of electricity meters is proposed. This method analyzes the e...

Abstract With the rapid developments of marine resource exploitation, mounts of marine engineering equipment are settled on the ocean. When it is not possible to move the damaged equipment into a dry dock, welding operat...

This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historica...

This paper presents a comprehensive review of Medium Voltage (MV) Wind Energy Conversion Systems (WECS) with the integration of Wide-bandgap (WBG) semiconductor devices. With the growing demand for high-power offshore wi...

Abstract Compared with conventional forming processes, ultrasonic-assisted forming technology with a high frequency and small amplitude can significantly improve the forming quality of materials. Owing to the advantages ...

Real-time routing on large-scale road networks remains a critical challenge for intelligent transportation systems, particularly under high query loads and increasing graph sizes. While classical shortest path algorithms...

Abstract Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this paper. By borrowing the advantages of model-driven and data-driven methods, a fault tol...

Introduction. In recent days, electric vehicles, robotics and in many control system applications, permanent magnet synchronous motors (PMSMs) are widely utilized. Problem. Due to non-linear behavior of system, external ...

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 ...

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...

Nanofluids based on transformer oil have emerged as promising candidates for improving insulation performance in high-voltage equipment. This study investigates the influence of TiO2 nanoparticles on the dielectric stren...

Introduction. Recently, multilevel inverters (MLIs) have been widely investigated for industrial and renewable energy systems as they are valuable in applications where they can produce clean, high-fidelity electrical si...

Plants are sophisticated and intelligent natural construction materials. They can be used for enhancing the stability of shallow soil slopes and minimizing surface erosion. It is evident that the use of plants can be low...

The Global Flood Awareness System (GloFAS) is a promising flood-modelling tool available for most river basins worldwide. However, it contains inherent biases, notably linked to its spatial resolution. This study propose...

Abstract The operation of a shield tunnel boring machine (TBM) in a high-strength hard rock stratum results in significant cutter damage, adversely affecting the thrust and torque of the cutter head. Therefore, it is ver...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

Abstract The brake unit bracket of a bogie frame is an important load-carrying component, particularly under emergency start/stop conditions. Conventional infinite/safe life approaches provide an over-conservative recomm...