Cambodia is not alone in facing capacity limitations in the production and timely release of key official statistics needed for data-driven policy decisions. This paper demonstrates that combining ...
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Secure data warehousing in ERP environments: An AI-based multimodal threat detection framework by Emmanuel Philip Nittala
In an era where data has become one of the most valuable assets for organizations, protecting that data is a strategic ...
The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...
Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but ...
COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework that enables accurate thermal field inversion in chiplet-based packaging ...
Data quality problems are systemic in agriculture, the researchers note. Historical reliance on local practices, fragmented ...
Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...
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