Scientific Research Publishing

A Spatio-Temporal Prediction Model for Wall Turbulence Based on Hybrid Neural Networks ()

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...

Java 26 with JVM optimizations, HTTP/3, and finally no Applet API

The current OpenJDK 26 is strategically important and not only brings exciting innovations but also eliminates legacy issues like the outdated Applet API.

A List Of All 103 AI Native Companies Nvidia’s Jensen Huang Presented

When NVIDIA CEO Jensen Huang took the stage at the SAP Center in San Jose yesterday, he delivered a two-and-a-half-hour ...
pv magazine International

New framework promises unprecedented level of cybersecurity for SCADA systems

An international research team developed CyberSentry, a software framework using advanced deep learning and optimization techniques to enhance cybersecurity in SCADA systems for power plants and ...
IEEE

Fault Estimation for Nonlinear Distributed Parameter Systems With External Disturbances Based on Full Iterative Learning

Abstract: This article introduces an innovative approach to simultaneously estimate time-domain and spatiotemporal faults in nonlinear distributed parameter systems (NDPSs)nonlinear distributed ...

conga-HPC/cBLS accelerates demanding edge designs

More consistent power for COM-HPC client platforms SAN DIEGO, CA, UNITED STATES, March 13, 2026 /EINPresswire.com/ -- ...
IEEE

Distributed Flexible Job Shop Scheduling With Heterogeneous Transportation Resources Constraints via Deep Reinforcement Learning and Graph Neural Network

Abstract: The distributed flexible job shop scheduling problem (DFJSP) has emerged as a critical challenge in the field of scheduling optimization due to its intricate resource allocation and the ...