Computepowercoin

An in-depth analysis of the convergence of Big Data and Cloud Computing, exploring challenges, opportunities, and design principles for scalable data processing.

An analysis of a cloud-based architecture for parameter sweep execution in urban flood risk modelling, enabling large-scale simulations with cost-effective computational power.

Introduces CoRE-Learning, a theoretical framework incorporating time-sharing computational resource concerns and machine learning throughput into learning theory.

Comprehensive technical documentation and resources about computepowercoin technology and applications.

Analysis of a deterministic spectral method for the Boltzmann equation, focusing on high-performance computing implementation, second-order accuracy, and applications to non-equilibrium flows.

Analysis of integrating Quantum Key Distribution (QKD) with ETSI MEC standards to secure federated edge computing against quantum threats.

A novel robust Model Predictive Control framework combining steady-state awareness with tube-based design for systems with limited computational resources and external disturbances.

Analysis of using ML surrogate models to accelerate simulations of HEP computing workflows, overcoming the accuracy-scalability trade-off in tools like DCSim.

An in-depth analysis of traditional Visual Question Answering models (BidGRU, GRU, BidLSTM, CNN) under computational constraints, focusing on efficiency, accuracy for numerical questions, and optimization strategies.

Analysis of the Universal Basic Computing Power (UBCP) proposal, a policy initiative to provide free, universal access to AI computational resources to counter centralization and foster inclusive AI development.