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consul-template

Template rendering, notifier, and supervisor for @HashiCorp Consul and Vault data.

core

Home repository for .NET Core

cotd2

coursera-dl

Script for downloading Coursera.org videos and naming them.

covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

crashpy

Crash Course in Python

criterion

A cross-platform C and C++ unit testing framework for the 21st century

criticality_score

Gives criticality score for an open source project

ctf

CTF Field Guide

ctpn-tensorflow

A TensorFlow implementation of CTPN model for text detection problem

cuddly-yaml

cuddly-yaml : A housekeeping tool powered by GLib, offering threat safety and automatic garbage collection through reference counting. Define file retention periods conveniently using YAML configuration files.

curved_navigation_bar

Animated Curved Navigation Bar in Flutter

cvat

Powerful and efficient Computer Vision Annotation Tool (CVAT)

cyberchef

The Cyber Swiss Army Knife - a web app for encryption, encoding, compression and data analysis

cypress

Fast, easy and reliable testing for anything that runs in a browser.

cypress-example-kitchensink

This is an example app used to showcase Cypress.io testing.

cypress-testing-library

🐅 Simple and complete custom Cypress commands and utilities that encourage good testing practices.

cz1007_datastructures

NTU CZ1007 Data Structures

cz2005-operating-systems-experiment-3-virtual-memory

In this lab, you are required to complete a virtual memory implementation, including how to get a physical frame for a virtual page from the IPT if it exists there, how to put a physical frame/virtual page entry into TLB, and how to implement a least recently used page replacement algorithm. A software-managed TLB is implemented in Nachos. There is one TLB per machine. There is also an IPT which maps physical frames to virtual pages. Basically, the translation process first examines the TLB to see if there is a match. If so, the matching entry in the TLB will be used for address translation. If there is a miss, the IPT will be looked up. If a matching entry is found in the IPT, the entry will be used to update the TLB. A miss in the IPT means that the page will have to be loaded from disk, and a page in and page out will be performed. To decide which page to page out, a page replacement policy is used, for example, a least recently used algorithm which will be explained late on. During each lookup process, you need to perform some checking in order to make sure that you are looking up the correct entry and that the entry is valid. In order to check whether you are referencing the correct entries from the TLB, you have to check the valid bit. The TLB will get updated when an exception is raised and the required page entry isn't in it. In this case, a new entry needs to be inserted into the TLB. The new entry will be inserted into an invalid entry in the TLB or replace an existing entry if it is full. Since the TLB is small, the replacement policy for the TLB is simply FIFO. When there is a context switch between processes, e.g. the main process executing a child process, the entries in the TLB will be cleared by setting all entries to invalid. The IPT is simply implemented using an array, represented by the memoryTable (a mapping of what pages are in memory and their properties). There is one entry for each of the physical frame, and each entry contains the corresponding process id, virtual page number, and the last used field that records the tick value when the page was last accessed. The least recently used algorithms works by iterating through the memoryTable, from the beginning, to look for the entry that has been least recently used. If there is an entry that is not valid (i.e., its process is dead), the algorithm will return the index of this invalid entry. Otherwise, the algorithm will return the index of the least recently used entry (that is, the entry with the smallest last used field).

cz2006-software-engineering

NTU Computer Science - CZ2006 Software Engineering

d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

danielchudc

data-analysis

Data Science Using Python

data-science-portfolio

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

data-visualization-with-d3

Reference from https://blog.logrocket.com/data-visualization-angular-d3/

databases

Async database support for Python. 🗄

datasciencevm

Tools and Docs on the Azure Data Science Virtual Machine (http://aka.ms/dsvm)

dc-docsify-demo

This repo test out docsify functionality

deep-learning-models

Keras code and weights files for popular deep learning models.

deepprivacy

DeepPrivacy: A Generative Adversarial Network for Face Anonymization