Polymers characterize a different and important class of materials through various industries, all with unique functional properties and structural attributes. Conventional models of polymer classification depend greatly on labor-intensive methods li...
This study presents a human-centric, data-driven modeling framework for the intelligent evaluation and classification of vibration-reducing (VR) gloves used in hand-transmitted vibration environments. Recognizing the trade-offs between protection and...
Battery lifetime prediction is a promising direction for the development of next-generation smart energy storage systems. However, complicated degradation mechanisms, different assembly processes, and various operation conditions of the batteries bri...
This study develops an ontology-based decision support framework to enhance sustainable polymer recycling within the circular economy. The framework, constructed in Protégé (OWL 2), systematically captures polymer categories with emphas...
Ultrasonic guided waves acquired using permanently bonded piezoelectric transducers enable large-area monitoring of composite structures. For practical structural health monitoring; however, both the location and the condition of a structural change...
Many “Industry 4.0” applications rely on data-driven methodologies such as Machine Learning and Deep Learning to enable automatic tasks and implement smart factories. Among these applications, the automatic quality control of manufacturin...
Driven by environmental concerns and aligned with the principles of the circular economy, urban plastic waste—including packaging materials, disposable items, non-functional objects, and industrial scrap—is increasingly being collected, r...