Publications
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Applying the technology acceptance model to risk communication dashboards: a case study
Purpose: This study examines how the design characteristics of risk communication dashboards influence user acceptance in Small and Medium-sized Enterprises (SMEs). As dashboards become essential for data-driven decision-making, identifying which visual and functional elements drive adoption is critical. The research focuses on features that most strongly affect perceived usefulness (PU) and perceived ease of use […]
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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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Safety-aware smart parking recommendations for shared micro-mobility using deep reinforcement learning
The rapid expansion of shared micro-mobility services has intensified safety concerns in dense urban environments in recent years. Traffic complexity and infrastructure limitations increase accident risks, yet safety aspects are often overlooked by operators and existing decision-support systems. Current safety-oriented approaches mainly rely on static analyzes, historical accident data, or infrastructure-based interventions, which often lack […]
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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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Coupling Pricing Decisions with Aircraft and Gate Scheduling in Airport Operations
Airlines increasingly emphasize operational flexibility to adapt schedules to fluctuating de mand. Pricing decisions directly influence expected passenger numbers, and when demand is insufficient for a large aircraft, companies may reassign a smaller one, provided capacity, aircraft–gate compatibility, and crew constraints are satisfied. Such changes require gate reassignment, making pricing, aircraft assignment, gate allocation, and […]
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A NSGA-II Approach for Energy-Efficient Flexible Flow Shop Scheduling with Renewable Energy and Storage Integration
Manufacturing industries face increasing pressure to reduce energy costs while maintai ning production efficiency. Time-of-use electricity pricing structures offer opportunities for cost reduction through strategic production scheduling. Integrating renewable energy sources such as wind and Photovoltaic, along with Energy Storage System further enhances sustainability and economic benefits. This work presents a multi-objective optimization approach using […]
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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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An innovative power converter based technique for on-site photovoltaic I-V characterization under natural irradiance
This paper presents a standalone PV curve tracer designed to extract current-voltage (I-V) and power-voltage (P-V) characteristics, as well as the five parameters of a Multiple-Diode Model (MDM) with identical diodes, effectively reducing it to a single-diode model for parameter extraction, under real sunlight conditions. The system consists of a custom-built synchronous boost converter operating […]
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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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A comparative environmental assessment of an automotive component processed by laser powder bed fusion (LPBF) versus CNC machining, with steel powder reuse impact analysis
The study reported in this paper presents a comparative life cycle assessment (LCA) of a maraging steel automotive hub carrier manufactured through using Laser Powder Bed Fusion (LPBF) metal additive manufacturing (metal AM) versus conventional Computer Numerical Controlled (CNC) machining. The manufacturing processes are modelled with primary data collected from dedicated metal AM unit and […]
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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 […]