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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...

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...

Since the coefficients of variation of soil properties vary in a large range, the real reliability index for the soil slope designed using the partial factor method also fluctuates in a range. This drawback limits the ap...

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 ...

Abstract Constant stress accelerated life tests (ALTs) can be applied to obtain a high estimation accuracy of reliability measurements, but these are time-consuming tests. Progressive stress ALTs can yield failures more ...

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...

This paper discusses the determination of the reliability index of the power distribution system. The reliability of the power distribution system is strongly influenced by the duration and frequency of the disturbance, ...

This paper presents the application of Signal Detection Theory (SDT) concepts to the certification of optional systems that provide operational or system safety benefits. The method and analysis yield quantitative requir...

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...

Probabilistic analysis is an emerging field of structural engineering which is very significant in structures of great importance like dams, nuclear reactors etc. In this work a Neural Networks (NN) based Monte Carlo Sim...

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...

Aiming at improving the inversion quality of anomalies near the electrodes in boreholes, which has been a large issue interfering in the three-dimensional (3D) cross-hole electrical resistivity tomography (ERT), an inver...

The digital poultry sector faces challenges in maintaining stable incubation temperatures. Comparative evaluation between Sugeno and Tsukamoto methods has not been conducted in real-world IoT systems. This research is es...

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...

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...

The reliability of oil and gas transportation depends heavily on weld quality during pipeline construction. This study investigates the effect of gas metal arc welding (GMAW) current on API 5 L GrB pipeline weld joint. W...

The data-driven Intelligent Transportation System (ITS) provides great support to travel decisions and system management but inevitably encounters the issue of data missing in monitoring systems. Hence, network-wide traf...

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...

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...

To address the sensitivity of traditional Two-Dimensional Principal Component Analysis (2DPCA) to outliers and the breakdown of variance-reconstruction equivalence under noise, we propose an Angle-Aware Weighted 2DPCA (A...

One of the deadliest diseases that can affect children and adults is a brain tumour. A brain tumour is the abnormal growth of cells in the brain or near it. Commonly, there are two types of tumours: malignant (cancerous)...

Nutritional status of toddlers was considered a key indicator for assessing nutritional problems among children. According to the Banyuwangi Regency Health Profile, the prevalence of undernutrition based on the weight-fo...