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Integrating AI-driven wearable metaverse technologies into ubiquitous blended learning
No full textUbiquitous blended learning, leveraging mobile devices, has democratized education by enabling autonomous and readily accessible knowledge acquisition. However, its reliance on traditional interfaces often limits learner immersion and meaningful interaction. The emergence of the wearable metaverse offers a compelling solution, promising enhanced multisensory experiences and adaptable learning environments that transcend the constraints of conventional ubiquitous learning. This research proposes a novel framework for ubiquitous blended learning in the wearable metaverse, aiming to address critical challenges, such as multi-source data fusion, effective human–computer collaboration, and efficient rendering on resource-constrained wearable devices, through the integration of embodied interaction and multi-agent collaboration. This framework leverages a real-time multi-modal data analysis architecture, powered by the MobileNetV4 and xLSTM neural networks, to facilitate the dynamic understanding of the learner’s context and environment. Furthermore, we introduced a multi-agent interaction model, utilizing CrewAI and spatio-temporal graph neural networks, to orchestrate collaborative learning experiences and provide personalized guidance. Finally, we incorporated lightweight SLAM algorithms, augmented using visual perception techniques, to enable accurate spatial awareness and seamless navigation within the metaverse environment. This innovative framework aims to create immersive, scalable, and cost-effective learning spaces within the wearable metaverse
Počasna hoja je povezana s starostno krhkostjo pri uporabnikih domov za starejše
No full textAge-related frailty is a condition of diminished physiological reserves that increases the risk of falls, disability, hospitalisation and mortality. Frailty is usually associated with a lack of physical activity. The aim of this study was to determine whether a frail phenotype can be identified by gait speed. 94 older residents (83.6 ± 7.9 years, 68% women) from Slovenian nursing homes were included as study participants in this cross-sectional study. Frailty was assessed using Fried\u27s Frailty Phenotype Protocol and gait speed was measured over a distance of 4.5 m. We used relative risk to determine whether gait speed was an indicator of frailty. Most of the residents were pre-frail (63%) or frail (16%). Gait speed was significantly lower in the frail group by -0.21 s (U = 331.5p < 0.001) and a gait speed ≤ 0.457 m/s increased the risk of frailty by 40% (RR=1.40 (CI 1.15-1.70)p=0.0008). We suggest using gait speed as a simple indicator of potential frailty in nursing homes. Persons at risk should be included in a detailed diagnosis and advised on suitable measures. In particular, physical activity seems to prevent the occurrence of frailtyStarostno krhkost označujejo zmanjšane fiziološke rezerve, kar povečuje tveganje za padce, invalidnost, hospitalizacijo in umrljivost. Krhkost je običajno povezana tudi s pomanjkanjem telesne dejavnosti. Namen te študije je bil ugotoviti, ali je krhke starostnike mogoče prepoznati na osnovi hitrosti hoje. V prečno-presečno raziskavo je bilo vključenih 94 uporabnikov domov za starejše (83,6 ± 7,9 let, 68% žensk) v zahodni Sloveniji. Krhkost je bila določena z metodo Friedovega fenotipa krhkosti in hitrost hoje je bila izmerjena na dolžini 4.5 m. Da bi ugotovili, ali je hitrost hoje pokazatelj morebitne krhkosti, smo uporabili metodo relativnega tveganja. Večina uporabnikov je bila pred-krhkih (63%) ali krhkih (16%). Hitrost hoje je bila v skupini krhkih značilno nižja za 0.21 s (U = 331,5p < 0,001) in hitrost hoje ≤ 0,457 m/s je tista, ki poveča tveganje za krhkost za kar 40% (RR=1,40 (CI 1,15-1,70)p=0,0008). Predlagamo uporabo hitrosti hoje kot preprostega pokazatelja potencialne krhkosti v domovih za starejše. Ogrožene posameznike je potrebno vključiti v poglobljeno diagnostiko ter ustrezne intervencije, pri čemer ima telesna dejavnost pomembno vlogo pri preprečevanju krhkosti
The algebraic characterization of M-subspaces of bent concatenations and its application
No full textEvery Boolean bent function f can be written either as a concatenation f = f1|| f2 of two complementary semi-bent functions f1, f2or as a concatenation f = f1|| f2|| f3|| f4 of four Boolean functions f1, f2, f3, f4, all of which are simultaneously bent, semi-bent, or 5-valued spectra-functions. In this context, it is essential to specify conditions for these bent concatenations so that f does (not) belong to the completed Maiorana-McFarland class M#. In this article, we resolve this question completely by providing the algebraic characterization of M-subspaces for the concatenation of the form f = f1|| f2 and f = f1|| f2|| f3|| f4, which allows us to estimate ind( f ), the linearity index of f, and consequently to establish the necessary and sufficient conditions so that f is outside M#. Based on these conditions, we propose several explicit and generic design methods of specifying bent functions outside M# in the special case when f = g||h||g||(h+1), where g and h are bent functions. Moreover, we show that it is possible to even decrease the linearity index of f = g||h||g||(h+1), compared to ind(g) and ind(h), if the largest dimension of a common M-subspace of g and h is small enough (less than min{ind(g), ind(h)} − 1). This also induces iterative methods of constructing bent functions outside M# with (controllable) low linearity index. Finally, we derive a lower bound on the 2-rank of f and show that this concatenation method can generate bent functions that are provably outside M# ∪ PS# ap. In difference to the approach of Weng et al. (2007) that uses the direct sum and a bent function g outside M#, our method employs g, h ∈ M# for the same purpose
