Publications
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Enhancing decision-making in Industry 5.0 through adaptive human–machine interfaces: A systematic literature review
In the dynamic landscape of Industry 5.0, adaptive human–machine interface (HMI) plays a pivotal role in shaping decision-making processes. This study constitutes a systematic literature review focusing on adaptive HMI in Industry 5.0, exploring their applications and implications within the decision-making context. The research objectives are structured around key questions, addressing the manifestation of adaptive […]
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DRAGON: A Dynamic Risk-Aware Graph Optimization Network for Adaptive Building Evacuation Using Graph Convolutional Network and Q-Learning
Efficient evacuation route planning in dynamic environments remains a major challenge, particularly when environmental risks and accessibility conditions change rapidly during emergencies. Traditional shortest-path algorithms, while effective in static graphs, often fail to adapt to evolving conditions, leading to suboptimal or unsafe evacuation guidance. This study aims to develop an adaptive and intelligent evacuation routing […]
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ADAP-GNN: Adaptive property-aware graph neural network for intrusion detection in IoT networks
New and sophisticated attacks are threatening Internet of Things (IoT) networks, compromising the security and trustworthiness of devices. Consequently, Network Intrusion Detection Systems (NIDS) have become critical for protecting these networks, and AI-based NIDS have emerged as a promising solution. A relatively new subfield of deep learning, Graph Neural Networks (GNNs), has further advanced this […]
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A Literature Review of Public Transport OD Matrix Estimation
Origin–Destination matrices (ODms) are a fundamental input for public transport planning and optimization, as they characterize travel demand across a network. Traditionally estimated from user surveys, ODms are now increasingly inferred from large-scale automatically collected data, such as Automated Fare Collection (AFC), Automated Passenger Counting (APC), and Automated Vehicle Location data (AVL). This review focuses […]
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Hybrid Modeling of a Lithium-Ion Battery Using an Extended Shepherd Model Enhanced with an MLP Neural Network Model
Exact modeling of lithium‐ion batteries is essential for the optimal design and functioning of contemporary energy storage systems. This research introduces a hybrid modeling approach that integrates an extended Shepherd equivalent circuit model (ECM) with a multilayer perceptron (MLP) neural network to improve voltage prediction precision. The ECM parameters are determined utilizing the Red‐Tailed Hawk […]
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Robust Pitch-Angle Control of Floating Offshore Wind Turbines Using Optimized Active Disturbance Rejection Control
This paper presents a robust pitch-angle control strategy for a floating offshore wind turbine (FOWT) based on an optimized active disturbance rejection controller (OADRC). The suggested controller uses the Red-Tailed Hawk (RTH) optimization algorithm to automatically adjust the ADRC parameters. This makes the system better at rejecting disturbances and more robust overall. The optimization process […]
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How interlayer interfaces affect hygro-mechanical ageing in 3D-printed PLA
3D printing, or additive manufacturing, has emerged as a versatile technology enabling the efficient fabrication of complex, customized components. However, despite its numerous advantages, the long-term durability of printed parts, particularly under humid conditions, remains a key concern, especially for polymer-based materials like polylactic acid (PLA). Previous studies have demonstrated that water diffusion into PLA […]
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Optimization of adhesion properties of PLA on cork substrate via FDM: A Taguchi experiment design
This study investigates the optimization of interfacial adhesion between polylactic acid (PLA) and cork substrates using fused deposition modeling (FDM), a topic scarcely explored in the literature. The research question seeks to identify FDM parameters that most strongly influence adhesion strength and microstructural porosity in PLA–cork laminated structures. Cork, a lightweight, elastic, and sustainable material, […]
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HiFEL-OCKT: Hierarchical federated edge learning with objective congruence and multi-level knowledge transfer for IoT ecosystems
The explosive growth of Internet of Things (IoT) data and the demand for real-time decisions necessitate edge intelligence to overcome the latency and bandwidth limitations of cloud-only processing. Real-world IoT ecosystems are characterized by their high heterogeneity, which results from a wide variety of devices, sensors, environments, data, tasks, and resources, posing significant communication and […]
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Multi-objective electric vehicle charging scheduling under stochastic duration uncertainty
The ongoing electrification of the transport sector, driven by the numerous advantages of electric vehicles (EVs), introduces new challenges related to charging logistics, particularly due to long charging durations and uncertain conditions, posing significant negative impacts on grid stability and user satisfaction. While existing literature on EV charging scheduling often assumes deterministic charging durations, real-world […]
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FedWKD: Federated learning weighted aggregation with knowledge distillation for IoT forecasting
Federated Learning (FL) has emerged as a promising solution for decentralized Machine Learning (ML) that does not have direct access to datasets in a centralized manner. However, the traditional FL methods are prone to overfitting and model drift at the client level and server divergence during classic aggregation in case of heterogeneous, non-independent and identically […]
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Influence of Minor Coarse Aggregate Fractions on Hardfill Strength: A Case Study of Mallegue-Amont Dam
This study examines the influence of low proportions (< 2.5% by mass) of 40/63 mm gravel on the shear strength of hardfill used in the Mallegue-Amont Dam (Tunisia). To address the coarse nature of the material, a custom medium-scale direct shear apparatus was developed, despite its nonstandard dimensions. Nine mixtures with varying sand-to-gravel ratios were […]