Analytical Models of the Performance of C-V2X Mode 4 Vehicular Communications
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Updated
Oct 7, 2019 - MATLAB
Analytical Models of the Performance of C-V2X Mode 4 Vehicular Communications
OkHttp Analytical library to get stats like average network speed. Also get global callbacks for network errors and successes. Can be used for logging errors to Fabric or Firebase analytical tools
Analytical Models of the Performance of IEEE 802.11p Vehicle to Vehicle Communications
Trident is a tool to analytically model the Silent-Data Corruption (SDC) rate of a program, to replace expensive fault injection experiments. Please refer to our papers at DSN 2018 for more details (links in the README)
Analytical R Tools for Mass Spectrometry
Generate and manipulate semi-analytic models of planet wakes
A python-package containing analytical solutions for the groundwater flow equation
Standardised tables for doing cross agency work in the IDI - NOTE: Currently being updated due to IDI SAS Grid and Windows 10 migration
Analytical understanding and applying parameter optimization, regression with gradient descent to predict water quality levels across Indian waters.
TRIQS-based Stochastic Optimization Method for Analytic Continuation
Analytical performance model of LTE-V2X Mode 3 scheduling based on adaptive spatial reuse of radio resources
PyAbsorp is a python module that has the main focus to help estimate the Sound Absorption Coefficient using analytical models.
A Hebrew Analytical Lexicon based on ETCBC (4c) data
Fast analytical implementation of batch eigen-decomposition for 3x3 symmetric matrices with Pytorch. > 250x faster than regular Pytorch implementation of batch eigen-decomposition on GPU.
Computing gravity and gravity gradient tensor of polyhedrons with polynomial density constrasts (up to cubic order)
PALM: A Efficient Performance Simulator for Tiled Accelerators with Large-scale Model Training
Quetzal - Analytical web apps, fast, easy and real-time using Elixir. No Javascript required.
Calculate various beam optics functions from TfsDataframes
🐍🤯 Utilising Python w/ Pandas and Jupyter to create Dataframes to read in 1994 US Census data to compile an Analytical Base Table (ABT) which displays a Categorical and Continuous Data Quality Report. Dealing with Data Quality Issues (DQIs) such as Cardinality Issues, Outliers and Missing Values.
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