Politecnio die Bari - Catalogo di prodotti della Ricerca
Not a member yet
36616 research outputs found
Sort by
Investigating Age-Related Performance and User Experience Differences in Immersive Virtual Reality Industrial Training Applications
No full textDespite the European Union’s efforts to decrease workplace accidents, statistics show an increase in accidents in the last years. Therefore, training workers is crucial to prevent injuries. The thriving of new technologies, such as Immersive Virtual Reality, can offer innovative training methods in the industrial field. However, introducing innovative technologies to a user base with an increasing average age necessitates evaluating the impact on workers across various age groups. In this contribution, we developed an IVR system to train workers to learn procedures in industrial environments. We recruited 50 participants and divided them into three age groups: young (19–33 years), middle-aged (34–48 years), and older (49–63 years). Objective (execution errors and times) and subjective metrics (User Experience Questionnaire (UEQ), System Usability Scale (SUS), and Virtual Reality Sickness Questionnaire (VRSQ)) were collected. The results showed that the young group made more mistakes than the other two groups, but there were no statistically significant differences in execution times. The SUS score was statistically significantly higher for the young group than the others, the VRSQ did not show any significant increase. For the UEQ score, young participants rated IVR experience excellently, while others rated it slightly lower
Spintronic temperature nanosensor based on the resonance response of a skyrmion-hosting magnetic tunnel junction
No full textThe increasing need for efficient thermal management in nanoelectronics requires innovative thermal sensing solutions, as conventional sensors often exhibit nonlinear responses, low sensitivity, and complex calibration. We predict a temperature dependence in the response of existing skyrmion-based spintronic diodes and propose their use as nanoscale thermal sensors. These devices leverage magnetic skyrmions - topologically protected spin textures known for their robustness, nanoscale dimensions, and low-power dynamics. We demonstrate high thermal sensitivity with a linear temperature response over a wide range. This linearity, observed in both the amplitude and frequency of the skyrmion excitation, ensures redundancy that enables precise and reliable temperature measurement. In addition, the use of multilayer systems enhances the sensitivity and robustness of the device. These results provide a foundation for skyrmion-based caloritronic devices with promising applications in spintronic sensors, thermal management, nanoelectronics, and skyrmion-caloritronics
A Multi-parameter Sensing Device for Vital Signs Monitoring
No full textIn recent years, significant advances in digital health made possible to provide more personalized and timely care, and health systems to become more efficient. With this study, we propose a multi-parameter device, at a prototypal level, which represents a convenient and efficient solution in order to accurately monitor health and collect vital data: it is able to return blood pressure values, heart rate, blood oxygen saturation levels and body temperature, relying only on two different sensors, multi-wavelength photoplethysmography (PPG) and thermal camera, combined with AI algorithms. The performances are promising, with an average relative error of less than 5% for heart rate and blood saturation, and a Mean Absolute Error of 5.08 ± 8.83 mmHg and 4.37 ± 7.08 mmHg for systolic and diastolic pressure respectively. The MLX90640 thermal camera accurately measured patients body temperature in a non-invasive and continuous manner, with a maximum absolute error equal to 0.2 ∘C
Recycled vs. Virgin Materials in Additive Manufacturing: Assessing the Risk Mitigation Potential in Uncertain Supply Scenarios
No full textThe principles of Additive Manufacturing (AM) and Circular Economy (CE) are characterized by significant potential in mitigating supply chain disruptions. However, a dearth of efficacious decision-support tools hinders the formulation of strategic responses. This study seeks to address this gap by developing a computational model that integrates Real Options Valuation (ROV) and Monte Carlo Simulation (MCS) to assess the financial and strategic implications of switching between recycled and virgin materials for AM. We have applied the model to a case study in the furniture industry, so as to provide a comprehensive analysis of the risks and benefits associated with adopting AM in uncertain supply environments, showcasing the potential to enhance supply chain responses to disruptions. The contribution of this research lies in offering a practical tool that assists companies in managing material shortages, optimizing operational costs, and making well-informed decisions regarding the adoption of AM and CE strategies in volatile market conditions
Simulazione Multi-scenario di celle a combustibile ed elettrolizzazione per la produzione di idrogeno verde
No full textGuest Editorial Special Issue on Energy-Efficient Embedded Intelligent Sensor Systems (S1)
No full textResilient Cities and Land Take Effective Management Through Sustainable Urban Planning Tools
No full textEnhancing EEG-Based Limbs Movement Classification through Advanced Machine Learning Techniques for Motor Imagery
No full textMotor Imagery (MI) mental process is a pivotal component of Brain-Computer Interface (BCI) systems, facilitating interaction with external environments for individuals with motor impairments. This study aims to evaluate motor imagery classification beyond hand movements, incorporating foot tasks, using simpler Machine Learning (ML) models (XGBoost, LightGBM, RandomForest) with a small number of Electroencephalogram (EEG) channels (8-11) and without data augmentation. Specifically, we propose the MIRA system, capable of performing rehabilitation tasks. The experimental results show that the adopted models perform well on the correct hand/left-hand classification, achieving accuracy, recall, precision, and F1 scores of approximately 73% for both classes. However, the dataset is unbalanced in the hand/foot task, resulting in precision, recall, and F1 values for the foot class ranging from 15% to 41 %, despite an average accuracy of 77%. The proposed system opens new avenues for research and practical applications to improve the quality of life of individuals with motor impairment
Wavelength Division Multiplexing in the Mid-Infrared via Fluoride Optical Fibers
No full textResearch interest in mid-infrared wavelengths is increasing due to its broad applicability in optical spectroscopy, chemical detection, thermal imaging, medicine, and light generation [1,2]. However, progress in mid-infrared fiber-based laser technology remains limited due to the absence of essential commercially available components that are widely accessible in silica-based optical fiber systems [3,4]