Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, HyperLogLogs, Bitmaps.

c005-redis-3.0-annotated

带有详细注释的 Redis 3.0 代码（annotated Redis 3.0 source code）。

c099-memory

High performance native memory access for Java.

d001-linux

linux内核源代码树 Linux kernel source tree（linux内核源代码树）

d002-opennetvm

A high performance container-based NFV platform from GW and UCR.

debug-battery-historian

Battery Historian is a tool to analyze battery consumers using Android "bugreport" files.

debug-chkbugreport

A command line tool which parses and converts android bugreport files into more human readable html reports.

deepfakes_faceswap

ai-换脸from deekfakes' faceswap: https://www.reddit.com/user/deepfakes/

e002-flowmon-dpdk

每个流都监控的软件 A software Traffic Monitor based on Intel(R) DPDK

基于dpdk的简单流量测量HCMonitor is a user-mode monitor system aiming at fully monitoring traffic and accurate measurement of service latency in high concurrent network. It captures traffic with switch mirroring and calculates per-request response latency from requests input to responses output.

e003-entropy-based-anomaly-detector

基于熵的网络流量异常检测 This repository contains the source code of the entropy-based network traffic anomaly detector. It was developed as part of the activities of the research project "Performance Evaluation of Entropy-based Algorithms for Network Traffic Anomaly Detection in Cloud Computing Systems" at the Research Group of Convergent Networks (GPRC) from the Federal Institute of Education, Science and Technology of Paraíba, Campina Grande Campus, Paraíba, Brazil. The participants thank CNPQ agency for funding the project. Developers: Eduardo Jerônimo and Aleciano Lobo. Manager/Advisor: Ana Cristina Oliveira

e003-realtime-traffic-detection

实时的视频流量监控 Video surveillance units are usually the first element of a security system. While they are the most intuitive to understand and can be programmed for many tasks, they also have many vulnerabilities, such as sensitivity to light levels and large computational requirements. The article presents an application of computer vision methods to traffic flow monitoring and road traffic analysis. The application is utilizing image-processing methods using OpenCV library designed and modified to the needs of road traffic analysis. This method gives functional capabilities of the system to monitor the road, to initiate automated vehicle tracking, to measure the average speed. This system is based on stationary video cameras and an onboard arm processor running on android or linux processing the video and sending the processed data to a central server connected to wide area network or through GPRS. This software was made to save users time so that they don’t get stuck in traffic jams and avoid them beforehand as they have prior knowledge about the traffic conditions on the alternate routes, so that users could choose the route with least traffic and hence shall reach his/her destination hassle free. What users need to do is, subscribe to the routes (from their android phone) in a particular area, our software will tell the user about the traffic density in each of the alternate routes available in that area and suggest the best route with least traffic to the user. Therefore by using our software from any android device, the user will enjoy a hassle free ride towards his destination.

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