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KVL releases new open source to visualize supercomputer simulations

KAUST ·

KAUST's Visualization Core Lab (KVL) has released inshimtu, a pseudo in situ visualization system for scientists working with large datasets and supercomputer simulations. Inshimtu simplifies the implementation of in situ visualization by using existing simulation output files without requiring changes to the simulation code. It helps scientists determine if implementing a full in situ visualization into their code is worthwhile. Why it matters: This open-source tool can improve the efficiency of supercomputing research in the region by allowing researchers to assess the value of in situ visualization before fully committing to it.

Towards a Deep Learning Pain-Level Detection Deployment at UAE for Patient-Centric-Pain Management and Diagnosis Support: Framework and Performance Evaluation

arXiv ·

This paper introduces a deep learning framework for automated pain-level detection, designed for deployment in the UAE healthcare system. The system aims to assist in patient-centric pain management and diagnosis support, particularly relevant in situations with medical staff shortages. The research assesses the framework's performance using common approaches, indicating its potential for accurate pain level identification.

KAUST Ph.D. student wins Three Minute Thesis competition

KAUST ·

KAUST Ph.D. student Muhammad Akram Karimi won the Three Minute Thesis competition at the IEEE MTT International Microwave Symposium in Boston. Karimi's presentation, titled "Making Materials Smart Using Microwaves," detailed his research on low-cost in situ microwave sensors. His work, in collaboration with Saudi Aramco, focuses on detecting water fraction in oil using sensors printed directly on pipes. Why it matters: This award recognizes innovative research at KAUST and highlights the potential of microwave sensor technology for applications in the oil and water industries within the region.