⭕ N2O: Distributed WebSocket Application Server ISO 20922

💧 Skyline N2O Demo

Design files and documentation of µHoubolt, a small and lightweight Ethanol/N2O liquid rocket sucessfully flown at EuRoC 2022.

Java и ReactJS библиотека, позволяющая создавать web приложения со сложными пользовательскими интерфейсами без глубоких знаний web технологий и frontend фреймворков. https://n2oapp.net/demo/

⭕️ N2O: Haskell Application Server

SVG WebSockets N2O Example

N2O in Haskell

N2O: Standard ML Application Server

Socket Gateway Interface

N2O: Rust Application Server

Safe, idiomatic bindings to cFE and OSAL APIs for Rust

🌐 N2O.DEV: Open Source Enterprise Frameworks

💠 EMQ: N2O over MQTT for NYNJA 1.0

online decision-making platform

N2O: Application Server

Climate change is a controversial topic of debate, where many of us do not believe in anthropogenic climate change. Because its consequences are predicted to be dire, such as mass ocean extinction and frequent extreme weather events, it is important to learn what causes the warming in order to better combat it. This project’s main objective is to predict weather and analyze various atmospheric gases that are causing harm to global warming up until now. In this study, the first challenge dwells on how to construct reliable statistical models based on climate data of few hundred years and accurately capture the relationship between temperature and potential factors such as concentrations of carbon dioxide (CO2), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), nitrous oxide (N2O), hydrofluorocarbon (HFC) and methane (CH4). We compared the performance of several mainstream machine learning algorithms on our data, which includes linear regression, random forest, and Autoregressive Integrated Moving Average (ARIMA) model to build the state-of-theart model to verify the warming of the earth and identifying factors contributing to global warming. We found that random forest outperforms other algorithms to create accurate climate models which use features including various different versions of temperature to precisely predict global temperature. But the problem that arises in the current random forest model is that it can’t forecast temperature in future so we’ve used the Autoregressive Integrated Moving Average (ARIMA) model to fill that gap. It was found that CO2 is the largest contributor to temperature change, followed by CH4, HFC, SO2 and then by CO. They all had some sorts of impact, though, meaning their release into the atmosphere should all be controlled to help restrain temperature increase, and help prevent climate change’s potential ramifications.

Notion to Obsidian migrator

Tiny omegle clone using n2o

embedded build graph runner

Example blog using N2O freamwork

Platform for creating microservices based on Spring Boot

💧 SAMPLE: Ідіоматичний N2O/NITRO приклад для інтернів

Node add-on's ala boost python

No description available

N2O: Coq Application Server

C# WebSocket Server

Minimal working examples for different N2O features with poor documentation.

Erlang front end application for the islands game

Authorization library for Synrc Erlang Stack

Nitrous - extra Emacs Lisp optimizer. Transparently makes Emacs faster.