Publications
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Machine learning-driven solutions for sustainable and dynamic flexible job shop scheduling under worker absences and renewable energy variability
This paper addresses the Dynamic Sustainable Flexible Job Shop Scheduling Problem (DSFJSSP) by going beyond the traditionally emphasized economic dimension — such as makespan, flow time, or resource utilization — to include human and environmental factors, along with their related disruptions. Specifically, it considers human-related constraints such as workers’ skills and ergonomic risks, as well […]
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Influence of organizational culture on sustainable mobility behaviours in higher education
Purpose -In the face of climate change, higher education institutions can play a role in fostering a sustainable future. This study aims to examine how their green organizational culture, including values, social norms and practices, affects students’ mobility choices. Specifically, the authors examine the direct impact of green organizational culture on polluting commuting behaviours, the […]
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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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BI2PV Simulator for Optimized BIPV Design in Industrial Buildings
The integration of photovoltaics (PV) into industrial buildings remains inhibited by the lack of unified tools that reconcile architectural constraints, energy performance, and economic viability. We present Industrial Building Integrated PV (BI²PV) simulator, an interactive simulator developed with MATLAB App Designer, encompassing the entire workflow: import and interpolation of NSRDB (National Solar Radiation Database) data […]
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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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PCM-Based Heat Sink Design Optimization for EV Batteries: A Reliability Approach
Effective thermal management is essential for ensuring the safety and durability of electric vehicle (EV) battery systems. This study presents a Reli-ability-Based Design Optimization (RBDO) framework for PCM-based heat sinks, simultaneously optimizing their geometry and material selection under uncertain-ties in heat load, ambient temperature, and material properties. Numerical solu-tions show drastic reductions in peak temperatures […]
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Vision Mamba-Based Dual-phase Self-supervised Framework for Neonatal Jaundice Diagnosis
Neonatal jaundice is a common and potentially serious condition that, if left undiagnosed or untreated, can lead to severe neurological complications in newborns. Existing diagnostic methods are often invasive and face limitations in accuracy, accessibility, and data availability, especially in resource-constrained environments. This study introduces NeoViM, an adapted MambaVision-based framework for neonatal jaundice classification. The […]
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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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Evaluating Deep Convolutional Neural Network Architectures for Facial Emotion Recognition in Autistic Children
Facial emotion recognition (FER) is a crucial element in supporting therapeutic interventions for children with autism spectrum disorder, particularly in developing emotional awareness and social communication skills. In this study, we present a comparative analysis of several advanced Deep Convolutional Neural Network (DCNN) architectures to evaluate their effectiveness in recognizing facial emotions in children with […]