Decision Velocity: The New Metric That's Reshaping Enterprise Data Architecture

AI has been reshaping how operations-heavy companies think about data infrastructure, and it could fundamentally reshape ...
IEEE

An Optimized Digital Implementation of the Hodgkin–Huxley Neuron Model on FPGA: Enhancing Computational Efficiency for Biomedical and Neural Applications

Abstract: This study introduces an optimized FPGA-based digital implementation of the Hodgkin-Huxley neuron model, aimed at reducing hardware complexity and energy consumption while maintaining ...
Stanford Social Innovation Review

Iterative A/B Testing for Social Impact: Rigorous, Rapid, Regular

Microsoft alone runs approximately 100,000 A/B tests each year to continuously optimize products. A famous Gmail experiment, ...
GitHub

A Python 3 headless implementation of the Capella modeling tool

capellambse allows you reading and writing Capella models from Python without Java or the Capella tool on any (reasonable) platform. We wanted to "talk" to Capella models from Python, but without any ...
The Pioneer

Govt starts process of upgrading ITIs

The Delhi Government has initiated the upgradation of its ITIs under the PM-SETU hub-and-spoke model, inviting industry ...
GitHub

The Google Ads MCP Server is an implementation of the Model Context Protocol (MCP) that enables Large Language Models (LLMs), such as Gemini, to interact directly with the ...

Copyright Google LLC. Supported by Google LLC and/or its affiliate(s). This solution, including any related sample code or data, is made available on an “as is ...
BMJ Global Health

School-based behaviour change intervention to reduce ultra-processed food consumption among adolescents: evidence from a cluster-randomised controlled tri…

Background The global surge in ultra-processed food (UPF) consumption is a major public health challenge, particularly among ...
IEEE

Design and Implementation of a Robotic Arm Remote Ultrasound Scanning System Combining Reinforcement Learning and Deep Modeling

Abstract: This study employs reinforcement learning to train a robotic arm for abdominal ultrasound scanning and utilizes a depth camera to generate a 3D model, enabling the robotic arm to undergo ...