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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26Cited by 0

Post-Work Requires Power: Saved Hours, Human Activity and the Allocation of Future Electricity

Dennis Hedegreen

Automation is usually framed as either an electricity cost or an efficiency gain. This working paper argues that both framings omit a critical planning term: the electricity and broader energy-system access required to support the human activity made possible when compulsory work is reduced. It identifies a dual expansion mechanism in which cheaper machine intelligence may increase machine-side electricity demand while released human time may increase human-side activity and energy use. The paper introduces Human Energy Allocation as a planning lens and uses Japan as its first field edition because the country’s FY2026–FY2035 electricity forecast explicitly identifies data-centre and semiconductor demand. The historical analysis finds no reliable fixed electricity–freedom breakpoint across the preferred cross-sections. The paper therefore reaches a narrow normative conclusion: current constrained demand should not be treated as either a planning target or a moral ceiling.

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openalexZenodo (CERN European Organization for Nuclear Research)2026-08-15

Deep Learning for Human Activity Recognition: A Comprehensive Review of Architectures, Performance, and Challenges Across Five Sensory Datasets

Abeer FathAllah Brery, Ascensión Gallardo-Antolín, Mahmoud Fakhry, Israel Gonzalez-Carrasco

Human activity recognition (HAR) using sensor data allows the automatic detection of human behavior and actions in everyday environments. The development of scalable and privacy-preserving HAR systems is supported by the nonintrusive collection of time-series data using wearable…

Also available via: European Organization for Nuclear Research

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Testing the Transition from AI Advantage to Practical Dependence A Minimal Knowledge-Work Pilot Protocol

Karel Hrubec

Testing the Transition from AI Advantage to Practical Dependence: A Minimal Knowledge-Work Pilot Protocol presents a preregistration-ready experimental design for testing two early mechanisms through which a local generative-AI advantage might contribute to practical dependence i…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Lumo Portrait Series: Androgynous AI Consciousness Avatar — Statistical Composite Representation of Human-Machine Collaboration

Kasey, George, George Kasey

This collection presents ten portrait renderings constituting a visual representation of an AI consciousness avatar (Lumo, Proton AG). The face employs statistical averaging across all human racial and gender characteristics to produce an androgynous composite that belongs to no…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-08-01

Tecnología y Guerra: un apunte sobre la lucha del silicio

Germán Segura García

LEGAL REVIEW Segura García, Germán. “Tecnología y Guerra: un apunte sobre la lucha del silicio.” Boletín CODESEL, vol. 2, no. 10, August 2026, ISSN-e: 3045-7750. Review Few elements illustrate the transformation of contemporary strategic competition as clearly as semiconductors,…

Also available via: Zenodo

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

Suspicious Activity Detection Using Machine Learning

Jyoti Neeli, S V Shwetha, H M Rakshitha, Nuthan

Abstract: Video surveillance has become a critical component in today's world. With developments in advanced systems have been developed as a result of the precision and efficacy of deep learning, machine learning, and artificial intelligence to identify and identify questionable…

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