Abstract: Value iteration-based approximate/adaptive dynamic programming (ADP) as an approximate solution to infinite-horizon optimal control problems with deterministic dynamics and continuous state ...

“With state-of-the-art facilities that offer more space for visitors, interactive exhibits and programming, the new Ontario Science Centre will continue five decades of tradition, inspiring the next ...

Herein, we report a detailed study of the uncatalysed and acid-catalysed anhydride exchange mechanisms using DFT simulations. Using aliphatic anhydrides as model compounds, we explored all possible ...

OpenAI is rolling out GPT-5-Codex, a new, fine-tuned version of its GPT-5 model designed specifically for software engineering tasks in its AI-powered coding assistant, Codex. The release is part of a ...

Ink is a minimal programming language inspired by modern JavaScript and Go, with functional style. Ink can be embedded in Go applications with a simple interpreter API. Ink is used to write my current ...

Abstract: An open-circuit voltage (OCV) model, which represents OCV as a function of state of charge (SOC), is essential for estimating the state of a battery. Typically, the OCV-SOC characteristic is ...

Hot or not? From AI models with API fantasies to memory-safe programming and compiled code, get the scoop on what’s in and what’s out in software development. Tides ebb and flow. Pendulums swing.

With five years of experience as a writer and editor in the higher education and career development space, Ilana has a passion for creating accessible, relevant content that demystifies the higher-ed ...

This use case showcases a demo application using CAP and Fiori elements to explain features like Side Effects, Custom Actions, Dynamic Expressions. For more info, refer the blog here and code base can ...

To solve the theoretical solution of dynamic Sylvester equation (DSE), we use a fast convergence zeroing neural network (ZNN) system to solve the time-varying problem. In this paper, a new activation ...

In this paper we present an adaptive synaptic array that can be used to improve the energy-efficiency of training machine learning (ML) systems. The synaptic array comprises of an ensemble of analog ...