- Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
- Models and Issues in Data Stream Systems
- Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
- Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
- [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
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// | |
// _oo0oo_ | |
// o8888888o | |
// 88" . "88 | |
// (| -_- |) | |
// 0\ = /0 | |
// ___/`---'\___ | |
// .' \\| |// '. | |
// / \\||| : |||// \ | |
// / _||||| -:- |||||- \ |
ffmpeg -r 24 -pattern_type glob -i '*.JPG' -i DSC_%04d.JPG -s hd1080 -vcodec libx264 timelapse.mp4
-r 24
- output frame rate-pattern_type glob -i '*.JPG'
- all JPG files in the current directory-i DSC_%04d.JPG
- e.g. DSC_0397.JPG-s hd1080
- 1920x1080 resolution
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/* | |
Simple warning light flashing in your terminal. | |
Compile with the following arguments: | |
<YOUR COMPILER> --std=c++17 -O2 -lcurses -o warn-light warn-light.cc | |
*/ | |
#include <ncurses.h> | |
#include <stdint.h> | |
#include <unistd.h> |