19684 research outputs found
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A Review of Resource Allocation for Maximizing Performance of IoT Systems
No full textResource allocation is critical for maximizing the performance of Internet of Things (IoT) systems, in which devices with limited resources work together to complete diverse tasks. This paper provides a detailed overview of existing resource management solutions in IoT contexts, with a particular emphasis on AI techniques, heuristic/metaheuristic approaches, 5G/6G, digital twins, and blockchain. We evaluate the potential advantages and limitations of several resource allocation techniques and frameworks suggested in the literature. Our findings illustrate the potential of advanced AI and decentralized approaches to solving critical difficulties in IoT systems, including security and privacy preservation, communication overhead reduction, energy consumption, real-time performance improvement, and scalability enhancement. Furthermore, the ramifications of these discoveries were examined, as well as potential possibilities for future research in this vital field of study.</p
Unveiling higher education students’ experiences of using artificial intelligence:a cross-institutional qualitative study unveiling higher education students’ experiences of using artificial intelligence: a cross-institutional qualitative study
No full textHigher Education (HE) has yet to fully embrace the potential of artificial intelligence (AI), likely due to lack of funding, a general reticence to take risks or adopt innovations, limited empirical research and theoretical groundings, together with an emerging understanding of the role of such technology in HE (Wheeler, 2019; McGrath et al., 2024). Lack of digital literacy (such as AI literacy) among educators and students also poses a significant barrier (Lincoln and Kearney, 2019 cited in Essien, Bukoye, O’Dea & Kremantzis, 2024; Mah & Groß, 2024; Tully et al., 2025). Those who use AI in education may fail to recognise the constructivist and developmental nature of learning, imposing instead behaviourism-based teaching methods and an objectivist epistemology (Bates et al., 2020). Research on AI in education is developing as AI technology evolves (McGrath et al., 2024). There is a tendency to focus on the negative implications of AI in learning and teaching, but there are calls for greater consideration of its strengths (Bates et al., 2020). Research tends to favour positivist paradigms (Budhathoki et al., 2024; Zhao et al., 2024) over understanding students’ subjective experiences of engaging with AI, which offers important insights into its potential impact in enhancing and hindering learning. Consequently, a team of researchers from four UK-based HE institutions are exploring students’ experiences of using AI in their studies. Following delivery of an learning development themed AI workshop, used partly as a recruitment strategy, we are using a qualitative approach that allows for sensitivity to the social processes in which experiences are embedded (Creswell, 2009). Thematic analysis will give rise to themes that capture how students are using AI, possible barriers to accessing it, and affective dimensions that may hinder/facilitate engagement. By sharing these themes, we hope to provide a more granular perspective, unearthing nuanced and authentic insights from students from multiple institutions into how they are (or are not) using AI. The findings will have implications for how learning developers can best support the use of AI to enhance learning while addressing accessibility, inclusivity, and affective considerations
a secret language (2025)
No full textTwelve Polaroid prints, fading as a result of age and the experimental nature of their chemical structure. When the 'Impossible Project' revived the Polaroid instant photograph in 2008, they had to re-invent the technology, and these early prints are wonderfully distressed. Photographs in a grid are glyphs that describe a secret language
Management development, making it all worthwhile:introducing a tripartite system of transfer grounded in the relationships inherent in an apprenticeship model of delivery
No full textThis study investigates the link between the tripartite actors involved in an apprenticeship and the known variables identified in successful transfer of training. A new systems-based model of transfer is proposed which integrates the pre training environment, learning phase and post training environment with the tripartite actors inherent in an apprenticeship. The model was applied to a L5 management apprenticeship delivered to an open cohort. This is a qualitative explorative study which applied thematic analysis to reflective reports completed by learners during the apprenticeship. Six themes have been identified which demonstrate how the apprenticeship generates a holistic transfer climate. The tripartite actors and known transfer variables interact at multiple stages in this system to multiply the effect of each, leading to positive transfer. The study contributes to the literature by refocusing researchers’ attention on the systems approach to transfer whilst also adding to the slow but growing knowledge supporting the impact of apprenticeships on management learning
Identifying alternations in historical corpus data:the genitive alternation in Old English
No full textThis article revisits the diachrony of the genitive alternation, the alternation between ’s and prepositional phrases headed by of in Present-Day English. It is usually assumed to have developed around 1400CE. For Old English (c.650CE–1000CE), a different alternation between pre-modifying and post-modifying genitive-case marked noun phrases is suggested to be the genitive alternation. Building on descriptions of competition between genitive-case marked noun phrases (GEN) and prepositional phrases with of (OF) in Old English, and unpicking some of the preconceptions about the alternation in Old English, we propose a bottom-up method for systematically identifying possible alternation between OF and GEN in the York-Toronto-Helsinki Parsed Corpus of Old English Prose (Taylor et al. 2003). Our findings indicate that there is plausibly an alternation in Old English that stands in continuity with Present-Day English, and suggest a more complex diachrony for the alternation characterized by continuity and discontinuity in the alternants and the envelope of variation
Nondestructive structural health monitoring of composite wind turbine blades using acoustic emission
No full textStructural Health Monitoring (SHM) is critical to guarantee that composite wind turbine blades (WTBs) operate efficiently and reliably. Effective SHM can diminish downtime, lower maintenance costs, and increase energy production, while providing industrial systems with improved safety. This study introduces a novel, simplified approach to nondestructive SHM for glass-fibre reinforced composite (GFRC) blades, utilizing Acoustic Emissions (AE). To identify damage sources, AE signals generated by laboratory testing of damaged GFRC blades are captured and processed into Red, Green and Blue spectrograms, allowing for representing more characteristics of the raw data. A custom-designed machine learning model is then used to extract features from these spectrograms, enabling damage detection. This method provides a practical SHM solution for WTBs in operation, incorporating a sensor network for real-time monitoring
Data for: Sorption of Arsenate on Cerium Oxide: A Simulated Infrared and Raman Spectroscopic Identification
No full textThis repository provides additional supporting data for the paper in Environ. Sci.: Nano: https://doi.org/10.1039/D4EN00894D Sorption of Arsenate on Cerium Oxide: A Simulated Infrared and Raman Spectroscopic Identification Khoa Minh Ta, Deyontae O. Wisdom, Lisa J. Gillie, David J. Cooke, Runliang Zhu, Mário A. Gonçalves, Stephen C. Parker, and Marco Molinar
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