An ergonomic evaluation using a deep learning approach for assessing postural risks in a virtual reality-based smart manufacturing context.

This study proposes an integrated ergonomic evaluation designed to identify unsafe postures, whereby postural risks during industrial work are assessed in the context of virtual reality-based smart manufacturing. Unsafe postures were recognised by identifying the displacements of the centre of mass (COM) of body keypoints using a computer vision-based deep learning (DL) convolutional neural network approach. The risk levels for the identified unsafe postures were calculated using ergonomic risk assessment tools rapid upper limb assessment and rapid whole-body assessment. An analysis of variance was conducted to determine significant differences between the vertical and horizontal directions of postural movements associated with the most unsafe postures. The findings assess the ergonomic risk levels and identify the most unsafe postures during industrial work in smart manufacturing using DL method. The identified postural risks can help industry managers and researchers acquire a better understanding of unsafe postures.

This study aims to identify unsafe postures and calculate risk levels in a VR-based smart manufacturing context. Deep learning is applied to identify unsafe postures by detecting COM displacements and risk levels are calculated using ergonomic risk assessment tools. Results revealed the most unsafe body postures, crucial for workers' safety.

Surface Electronic States Induced High Terahertz Conductivity of Co3O4 Microhollow Structure.

Herein, we report the observation of unusual electronic and magnetic phases in traditional antiferromagnetic Co3O4 micromaterials and modulation of their properties on a temperature scale. In particular, we demonstrate a comparative low-energy carrier dynamics of Co3O4 microflower and microhollow flower (MHF) structures of same average size of 2 µm to unravel the ground-state information induced by surface electronics across the insulator-semiconductor transition using terahertz (THz) time domain spectroscopy. Interestingly, the THz optical constants of these structures are found to exhibit remarkably distinct features both as a function of frequency and temperature. Detailed study reveals that the partial metallization through large two-dimensional surface electronic states of MHF structure enables to achieve significantly higher carrier dynamics in contrast to its wide-band-gap solid counterparts and the magnetic measurements reconfirm the presence of these surface states by indicating ferromagnetism in Co3O4 MHF structures. Moreover, the simultaneous existence of insulator-semiconductor and antiferromagnetic-paramagnetic transitions near the Néel temperature points out the significant role of magnetically active Co2+ ions at the tetrahedral site of Co3O4 normal spinel structure in determining the conduction dynamics instead of 3d band related to Co3+ ions at octahedral site. Finally, we demonstrate that the continuous modulation of temperature-controlled charge transport coupled with intrinsic phase transition in Co3O4 microstructures has the potential to design efficient analog-like THz modulator, filter, and sensor. We believe that these outcomes can stimulate new opportunities toward next-generation caloritronics-based ultrafast energy-efficient transition-metal oxide electronics having both economic and environmental significance.