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Archive for 十一月 2012

Thought this was cool: Win+X Menu Editor – Win8 的快捷菜单编辑器

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Windows 8 已经去掉了从 Windows 95 就伴随用户的开始菜单。作为替代品,Win8 提供了 Win+X 快捷键菜单,随时弹出可用。虽然系统默认不允许编辑此菜单,Win+X Menu Editor 却正做此用,免费小巧,声称本身不会修改系统文件,避免改坏系统。@appinn

Win+X Menu Editor   Win8 的快捷菜单编辑器[图] | 小众软件

Win+X Menu Editor   Win8 的快捷菜单编辑器[图] | 小众软件 下载: 官网 | 下载 | 来自小众软件


©2012 Thruth for 小众软件 | 加入我们 | 投稿 | 订阅指南 | 反馈(图片不正常等问题)

Win+X Menu Editor   Win8 的快捷菜单编辑器[图] | 小众软件
from 小众软件 – Appinn: http://www.appinn.com/winx-menu-editor/

Written by cwyalpha

十一月 30, 2012 at 5:04 上午

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Thought this was cool: Hadoop Mortar

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I got this from Carlos Guestrin. Hadoop Mortar is an interesting software as service framework which allows running python and pig scripts on top of Hadoop:

It has a very nice “Illustrate” functionality which helps debug the code even before it is actually executed. Reminds a little the functionality of data wrangler.


from Large Scale Machine Learning and Other Animals: http://bickson.blogspot.com/2012/11/hadoop-mortar.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+blogspot%2FsYXZE+%28Large+Scale+Machine+Learning+and+Other+Animals%29

Written by cwyalpha

十一月 30, 2012 at 2:19 上午

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Thought this was cool: 医院哪个科室挣钱多??????????

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发信人: zhangmouren (张三), 信区: Joke
标 题: 医院哪个科室挣钱多??????????
发信站: 水木社区 (Tue Nov 27 22:54:54 2012), 站内

有一哥们是个肛肠科大夫,一次聚会问他为啥选择了这么个科室,哥们叹口气说道,那时还在转科,一次和医院里几个老大夫吃饭,遂打探医院哪个科室挣钱多,有说外科的,有说骨科的。这时医院一位德高望重的老主任说:屁!眼科最挣钱!—于是哥们最后选择了肛肠科!


我用无悔,刻永世爱你的碑。

※ 来源:·水木社区 http://www.newsmth.net·%5BFROM: 113.9.223.*]

from 水木社区 Joke/笑话连篇 保留区: http://www.newsmth.net/bbscon.php?bid=63&id=3071467

Written by cwyalpha

十一月 28, 2012 at 8:15 上午

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Thought this was cool: Adblock Plus 入侵 Android 擋廣告去除瀏覽器與 App 廣告

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Adblock Plus-01Adblock Plus-02

在 Firefox 與 Google Chrome 瀏覽器上最知名「擋廣告」擴充套件:「Adblock Plus」,現在不僅在電腦端有作用,今天甚至推出了一款 Android App,可阻擋 Android 各種瀏覽器中的網頁廣告以及去除 Android App 內廣告橫幅。並且我簡單測試後,確認真的有作用。

不需 Root 破解, 也不需要設定,只要安裝「 Adblock Plus 1.0 」,如果你是使用 Android 3.1 以上版本系統,那麼在 Wi-Fi 情況下可以阻擋瀏覽器、 App 內廣告。如果你有 Root 手機的話,那麼不管是哪個版本的系統,都可以在 Wi-Fi 和 3G 下阻擋廣告。其他情況可以參考:「設定方法說明」。

當然,我不會特別推薦一般用戶安裝 Android 版的「 Adblock Plus 1.0,除了因為這款 App 還在1.0的初版,使用時不確定會不會有什麼副作用外。另外,我贊成網頁上開放內容可以讓用戶自己決定要不要擋廣告(例如電腦玩物),但 App 這類以「有廣告免費版」和「付費版」模式並存的軟體,如果阻擋其廣告,是否算是一種盜版破解呢?或許這個議題值得大家好好討論。

喜歡這篇文章嗎?歡迎追蹤我的FacebookTwitterGoogle+,獲得更多有趣、實用的數位科技消息,更歡迎直接透過社群聯繫我。


from 電腦玩物: http://playpcesor.blogspot.com/2012/11/adblock-plus-10-android-app.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+playpc+%28playpc%29

Written by cwyalpha

十一月 28, 2012 at 8:15 上午

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Thought this was cool: The MongoDB NoSQL Database Blog, Introducing MongoClient

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Comments: “The MongoDB NoSQL Database Blog, Introducing MongoClient”

URL: http://blog.mongodb.org/post/36666163412/introducing-mongoclient?yey

 
 


November 27, 2012

Today we are releasing updated versions of most of the officially supported MongoDB drivers with new error checking and reporting defaults. See below for more information on these changes, and check your driver docs for specifics.

Over the past several years, it’s become evident that MongoDB’s previous default behavior (where write messages did not wait for a return code from the server by default) wasn’t intuitive and has caused confusion for MongoDB users. We want to rectify that with minimal disruption to the MongoDB apps already in production.

History

First, I  thought it would be interesting to share the history behind the previous default behavior, and why and how we are changing it.

The old behavior goes back to the very beginning of 10gen, before Dwight and I imagined MongoDB as a stand-alone database. When we first started 10gen in the fall of 2007, we set out to build a full platform as a service stack with MongoDB as the data layer. This was a fully hosted system (still open source), that encompassed a load balancer, auto scaling application server and data tier. The application side was a full server side JavaScript environment.

Every request into 10gen was an http request.  So you can imagine a controller for doing some user analytics could act like this:

URL:  http://foo.10gen.com/show?sect=sports&page=blog1

CODE:

db.sect_views.update( 
 { _id : db.getParameter( “sect” ) } , 
 { $inc : { count : 1 } } , /*upsert*/true );
db.page_views.update( 
 { _id : db.getParameter( “page” ) } , 
 { $inc : { count : 1 } } , true );

Writes in that system did not individually wait for a response from the database.  However, the application server itself always checked the database for any errors that occurred during the entire page load (using getLastError and getPrevError) so that the user/system would be notified of any issues.  Developers could of course also call getLastError whenever they wanted.  This worked great in the platform, as we were able to control the whole access pattern.

In January of 2009, we decided for a variety of reasons to only focus on the data tier (MongoDB).  At that time, a number of people had been using MongoDB in production for almost a year as part of the full stack, and a lot more were very interested in using it standalone.

Over the course of the next few months, we wrote the initial implementations of the Java, Python, Ruby and PHP drivers.  All of those drivers used the same network protocol as the original application server, which has non-synchronous write operations.  It seemed natural to us at the time given the background, but it is clear that this is not intuitive for new users of MongoDB who had never used the full stack.

New Behavior

Going forward, the default clearly has to be to wait for the database to acknowledge all writes; that is much more intuitive. Just flipping the default however, would be backward breaking for apps in production.

The change we’re going to make is to add a new top level connection class in each driver.  For example, in Java, previously you would do:

Mongo mongo = new Mongo( “mongoserver” );

That class, Mongo, will maintain the old default, and become deprecated.

For new code, you will do:

MongoClient mongo = new MongoClient( “mongoserver” );

which will default to a WriteConcern of 1.  Everything else will be the same.

The old class will remain for quite a while (but not forever), so that we won’t break old code right now.  As another benefit, every single driver will use MongoClient so for the first time at least the top level class will have the same name across the board.  All documentation, tutorials, and sample code have been changed accordingly. 

More Information

  • For driver downloads, docs, and tutorials, please visit the drivers page on the MongoDB wiki.
  • For bug reports and feature requests please visit jira.mongodb.org.
  • For any other feedback, please leave a comment on this post or in our user forum.

We appreciate your continued support and feedback on MongoDB.

Eliot and the MongoDB Team


from Hacker News 50: http://blog.mongodb.org/post/36666163412/introducing-mongoclient?yey&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+hacker-news-feed-50+%28Hacker+News+50%29

Written by cwyalpha

十一月 28, 2012 at 7:54 上午

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Thought this was cool: Compressive Sensing Solvers in Python and the ones that ought be in Python, R,….

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Due to being featured on a the SciPyTip twitter stream yesterday, and prompted by the question of Jaidev, I went through the list of compressive solvers and tried to find the ones that were developed using Python. What developers need to realize is that the vast majority of solvers in the compressive sensing big picture page are in Matlab mostly because those are research prototypes. Python codes are somewhat rare because the field is fluctuating fast. The initial solvers were a 1000 slower than some that appeared four years later

If you are a developer, and want to be a hipster when it comes to providing some of the best algorithms out there in compressive sensing (i.e.l finding the sparsest solution to underdetermined linear systems of equations), then this blog entry is for you.

Here is a list of current solvers written in Python. As noted yesterday, while L1 solvers are OK to see “if compressive sensing work” on small problems, they become slow when it comes to larger ones. For that you really need to look at the AMP solvers I mentioned yesterday. Hence I am also adding another list of solvers that ought to be implemented because:they are among the most optimal and their coding complexity is very much reduced compared to earlier solvers. 

An element of the compressive sensing framework relies on the building of dictionaries from training signals, for that there is:
Please also note that a C++ implementation of several solvers in KL1P (incuding AMP solvers). Here are the list of algorithms that ought to be implemented in Python or other languages:

GAMP mostly because this is an AMP solver that is continually supported by several researchers, Turbo AMP for imaging seems to do weill for images, SL0 because it is very simple in terms of coding complexity and BSBL as it seems to provide good results even when the signals are not sparse. If you do implement any of these algorithms please do let me know and I’ll feature them on the blog and the big picture.

Image Credit: NASA/JPL/Space Science Institute

W00077074.jpg was taken on November 21, 2012 and received on Earth November 23, 2012. The camera was pointing toward SATURN at approximately 1,136,886 miles (1,829,640 kilometers) away, and the image was taken using the CB2 and CL2 filters. 



Join our Reddit Experiment, Join the CompressiveSensing subreddit and post there !
Liked this entry ? subscribe to Nuit Blanche’s feed, there’s more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.


from Nuit Blanche: http://nuit-blanche.blogspot.com/2012/11/compressive-sensing-solvers-in-python.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+blogspot%2FwCeDd+%28Nuit+Blanche%29

Written by cwyalpha

十一月 27, 2012 at 8:05 上午

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Thought this was cool: GraphChi visual toolkit – or understanding your data

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A few weeks ago I wrote about Orange d4d data of cellular user behavior in Africa.
The data of phone call patterns is given as a text file in the following format:
20000 20003
20000 20005
20000 20008
20000 20011
20000 20012
1052 20000
20001 20006
20002 20009
20002 20010
1052 20002 
 


With the following format:
[calling user] [receiving user]\n

Since there are hundreds of thousands of phone calls it is very hard to understand what is actually the network structure. I decided to write a quick visual tool that will help user examine their graphs and understand better their structure.

Here is how you can try it out:
1. Checkout GraphChi from mercurial using the instructions here.
2. # cd graphchi; bash install.sh; make parsers; make ga
3. # cd toolkits/visual
4. Run the visual toolkit to create a sub graph representation. You will need to input the graph input file name, and the number of edges to extract. It is recommended to display less than 1000 edges or else the plot may be slow.
 # bash make_data.csv.sh -f [input graph name] -n [number of lines]
 For example, you can use the sample graph provided:
   # bash make_data.csv.sh -f `pwd`/sample_graph -n 1000
5. # firefox index.html

Here are some examples of the images I got when playing with orange data:

As you can see different kinds of users emerge very clearly.. the red nodes are the “seed” users where the graph was traversed from. Each edge is a phone call connection. We can see different users:
1) unsocial – rarely makes phone calls..
2) small network – few calls to neighbors
3) nagging – often calls to call centers (highly connected neighbors)
4) social – connected to a lot of friends which are interconnected together

Next I tried the same visualization on some twitter data I have. Each link is a twit or retwit directed to a certain user.

Next I looked at some phone calls data from a large European country. The graph captures only several minutes time span. It is interesting to see that from the gray node in the middle the is a 6 hop link of someone who called someone who called someone in a very short time.

And here is a sample webpage which shows the output of the visualization.

Advanced features:
1) It is possible to traverse a graph starting from a set of seed nodes.
Use the command line –s XXX for example: -s 12
or -s 192,31990,2312

2) When selecting a seed node, specify the number of hops to traverse using -h XX command. For example, -h 3 will traverse 3 hops around the sets of seed nodes.

3) If your input file is not in sparse matrix market format, but in [from] [to] format, you need
to specify an upper limit on the number of graph nodes using -o XX command.

How does your data look like? I would love any feedback from people who are trying to visualize their own graphs… let me know if you have any questions about the setup.

Credits: I am using the great d3.js package for performing the visualization. Thanks to Tyler Johnson, Shingo Takamatsu and Ali Bagheri Garakani from UW for teaching me how to deploy d3.js!


from Large Scale Machine Learning and Other Animals: http://bickson.blogspot.com/2012/11/graphchi-visual-toolkit-or.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+blogspot%2FsYXZE+%28Large+Scale+Machine+Learning+and+Other+Animals%29

Written by cwyalpha

十一月 27, 2012 at 8:05 上午

发表在 Uncategorized