Teacher education in the Global South faces increasing pressure to integrate advanced digital technologies, yet motivation alone does not guarantee implementation. Grounded in Socio-Technical Systems theory, this study proposes the Socio-Technical Architecture of Teacher Education (STATE) framework to explain this disc...
Sanjay Ranjan, V. P. Joshith· European Journal of Teacher...· 0 citations
The ‘666 = Cleopatra’ calculation: The AI considers this evidence extremely strong Francesco Carotta’s recent use of artificial intelligence to examine his long-standing linguistic and historical hypotheses represents an important shift: it transforms a controversial theory into one that can, at least in principle, be...
A.P.J. Hendriks Francesco Carotta· Zenodo (CERN European Organi...· 0 citations
Urban flooding is escalating because of climate change, rapid urbanization, land-use change, and inadequate drainage, demanding advanced spatial decision-support systems. Geospatial Artificial Intelligence (GeoAI), integrating GIS, remote sensing, and deep learning, has become a powerful approach for flood risk assessm...
Tungsten inert gas (TIG) welding of AA5083 aluminum alloy is sensitive to heat input and shielding conditions, which can lead to defects such as porosity and burn-through that compromise weld quality. Conventional non-destructive testing methods are generally performed after welding and therefore provide limited capabi...
N. Balakrishnan, Sumesh Arangot, B. Nair et al.· Materials· 0 citations
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This report examines the use of algorithmic risk assessments in law enforcement and the safeguards required when a score influences an individual's treatment. It analyses data quality, the object of prediction, classification errors, discriminatory effects and the distinction between an intermediate assessment and a de...
Sergei Khrabrykh, ARGA Observatory· Zenodo (CERN European Organi...· 0 citations
The Dynamic Explainable Framework (DEF), which couples a machine-learning detection backbone with inference-time SHAP and LIME explanations and an explanation-aware alert prioritization layer, is proposed and designed and profiled for real-time operation on benchmark traffic traces.
Muhammad Usama Nazir, Mohammed Alsuhaibani, Asri Binngadi· Scientific Reports· 0 citations
This conceptual paper aims to examine the concept of explainable artificial intelligence (XAI) as a tool for maintaining information ethics in the context of library services. It investigates the importance of XAI in the context of artificial intelligence (AI) and responsible use of AI.
A conceptual framewor...
This paper is the application companion to the TLCTC v2.6 core paper, which defines and freezes the taxonomy: ten cause-oriented threat clusters, ten axioms, the classification rules, the attack-path notation, and the two-layer (strategic/operational) model. The companion takes that taxonomy as given and shows how to p...
Bernhard Kreinz· Zenodo (CERN European Organi...· 0 citations
Artificial Intelligence (AI) is increasingly integrated into educational systems, shaping student
assessments, admissions, and personalized learning. However, ethical concerns related to
trust, fairness, transparency, accountability, and data privacy remain significant barriers to
its responsible deployment. This study...
C. Umoke· Research Journal of Pure Sci...· 4 citations· ⚡2
The cryptocurrency market, specifically Solana (SOL), exhibits extreme volatility that is difficult for conventional algorithms to predict accurately. Additionally, advanced Deep Learning models often act as black-boxes. This study implements the Temporal Fusion Transformer (TFT) architecture for robust and interpretab...
Personalized learning in AI-driven music education still faces challenges such as the difficulty of integrating multimodal learning evidence, the complexity of modeling music skill dependencies, and the lack of long-term optimization of learning pathways. To address these issues, this paper proposes a framework for opt...
Meng Lin· International Journal of Art...· 0 citations
This review critically examines the integration of AI, IoT, and HCI in smart healthcare monitoring and identifies unresolved challenges involving dataset bias, sensor reliability, model drift, human over-reliance, alarm fatigue, interoperability, regulatory compliance, and equitable access.
Swamy Tn· International Journal of Res...· 0 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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