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Ellan's Projects

ngrok icon ngrok

Introspected tunnels to localhost

nlp-sentiment-analysis icon nlp-sentiment-analysis

"citizen journalists" in the social media produce the content. This library uses Scikit-Learn and Spark MLlib to analyze the emotional sentiment of the text data.

nlp-sentiment-analysis-twitter icon nlp-sentiment-analysis-twitter

[Natural Language Processing] Using NLTK-3 and Sklearn to train different machine learning classifiers and then using an average system to produce the best optimized sentiment analysis of Twitter feeds.

node-html-pdf icon node-html-pdf

Html to pdf converter in nodejs. It spawns a phantomjs process and passes the pdf as buffer or as filename.

node-stl icon node-stl

parse stl files with Node.js and get volume, and weight

nohttp icon nohttp

NoHttp支持大文件、多文件上传、文件下载、自动维持Cookie、异步/同步请求,多种Http缓存模式,302/303重定向, 支持代理服务器.

numpy-stl icon numpy-stl

Simple library to make working with STL files (and 3D objects in general) fast and easy.

nutzwk icon nutzwk

基于Nutz的开源企业级开发框架

offlinedb icon offlinedb

An offline DB demo based on AngularJS framework and HTML5 IndexedDB

okhttp icon okhttp

An HTTP+SPDY client for Android and Java applications.

okhttputils icon okhttputils

封装了okhttp的网络框架,支持大文件上传下载,上传进度回调,下载进度回调,表单上传(多文件和多参数一起上传),链式调用,可以自定义返回对象,支持Https和自签名证书,支持cookie的持久化和自动管理,支持四种缓存模式缓存网络数据,支持301和302重定向,扩展了统一的上传管理和下载管理功能

okhttpvolleygson icon okhttpvolleygson

Sample app showcasing Android Networking with OkHttp, Volley and Gson. Check out the article to further explanation.

onlinedisk icon onlinedisk

大数据企业实训项目:基于SpringMVC+Spring+HBase+Maven搭建的Hadoop分布式云盘系统。使用Hadoop HDFS作为文件存储系统、HBase作为数据存储仓库,采用SpringMVC+Spring框架实现,包括用户注册与登录、我的网盘、关注用户、我的分享、我收到的分享等五大功能模块。其中我的网盘包括查看文件列表,多文件上传,创建文件夹,文件重命名、复制与移动、下载、在线浏览、分享等诸多功能。所使用的技术包括:SpringMVC框架、Spring框架、Maven项目管理工具、Hadoop HDFS文件系统、HBase数据库、openoffice服务、pdf2swf文件格式转换工具、flexpaper插件等。

opencv icon opencv

A Gesture-Control Application based on OpenCV on Android

optimizing-hadoop-s-mapreduce-scheduling-policies icon optimizing-hadoop-s-mapreduce-scheduling-policies

Explored the possibility of improving the real-time Hadoop scheduling. After implementing three kinds of schedulers: First-In-First-Out scheduler, Shortest Running Time scheduler and Earliest Deadline scheduler. Our results suggest that, under low and medium workload situations, Shortest Running Time Scheduler might be a good real-time Hadoop scheduler to meet the jobs’ deadline requirement, while under the high workload conditions, Earliest Deadline Scheduler is a better choice.

otter icon otter

阿里巴巴分布式数据库同步系统(解决中美异地机房)

pac4j icon pac4j

Security engine for Java (multi protocols and multi frameworks)

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