Publications
-
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 […]
-
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, […]
-
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 […]
-
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 […]
-
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 […]
-
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 […]
-
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 […]
-
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 […]
-
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 […]
-
Predictive maintenance under uncertainty in smart hospitals: Decision support with belief functions
Modern hospitals increasingly depend on interconnected biomedical devices and Internet of Medical Things (IoMT) infrastructures to guarantee patient safety and continuity of care. Yet, Predictive Maintenance within Prognostics and Health Management (PHM) remains difficult to deploy in healthcare because data are heterogeneous, incomplete and sometimes contradictory, and because safety-critical decision making requires explicit uncertainty handling […]
-
Natural Fiber Composites for Sustainable Model Rocketry: Bamboo and Jute as Alternatives to Fiberglass
The search for sustainable alternatives to synthetic composites has become increasingly relevant in aerospace engineering education and student rocketry. Fiberglass is widely used for rocket fuselages due to its favorable balance of performance and cost, but it is energy-intensive, non-biodegradable, and environmentally burdensome. This study provides the first demonstration of natural fiber composites applied to […]
-
Knowledge Distillation with Enhanced Lightweight STGCN for Gait Disorders Recognition
Gait recognition is essential for the early diagnosis and monitoring of movement disorders such as Knee Osteoarthritis (KOA) and Parkinson’s Disease (PD). This study presents a new method for skeleton-based gait recognition. Our approach combines Spatio-Temporal Graph Convolutional Networks (STGCN) and Long Short-Term Memory (LSTM) layers to analyze movement data. The STGCN blocks capture spatial […]