192 karma · joined August 14, 2007
Asking for a friend who uses XFS on LVM for disk heavy applications like database, file server, etc.
This book was a great read back in the day of what goes into a "modern" filesystem design
https://archive.org/details/practical-file-system-design
"Practical File System Design" was technical but also readable. Straight from the man who designed BFS which makes it more of an accomplishment IMO.* work out. I like free weights and bike riding or running for cardio. I recommend the local YMCA as these tend to be more community driven and less profit motivated pickup centers
* cook. this has several benefits. it can be challenging and relaxing while providing necessary sustenance at a price point cheaper than going out. can also be a social thing.
* take a class / learn something. it can be work related, semi work related or something else. I like the free educational videos on the webs. lately I've been getting back into math which is semi work related but in the past I have taken language classes at the local community college.
* outdoor activities or team sports. Did you have a favorite thing to do outside as a child or teen? Maybe you could take it up again or try something new. basketball, soccer (football if you are not in USA), surfing, geocaching, ultimate frisbee, bicycling, golf?
* amateur radio. getting a license is easy if you are at all technical and it opens up some doors for mucking with WIFI or LORA, SDR, and more. hams are an aging group but they are friendly, knowledgeable and desperately want their hobby to survive.
* maker projects. there are many projects already documented on the web or you can build your own. kind of amazing what one person can do with a raspberry pi, some basic electronic parts, and a bit of code.
* volunteer. so many organizations need skilled people. can you mentor people on computer skills or something else?
The M2 was being designed and prototypes built in 1995-1996. M2 featured a dual core powerpc and was designed to ship with a DVD player making it truly the next generation player. The plans to the device were sold to Matsushita, they demoed it at E3 in 1996 but failed to bring it to market.
3DO suffered a lot of the same troubles as Nuon except about 5 years earlier. 3DO went out of the hardware business in 1996 but continued publishing some very successful and revolutionary game titles before finally going out of business completely in 2003.
Point being this has all happened before, and it will happen again.
Pipes was a basic web "agent". It made basic programming available to the everyman much like HyperCard. Perhaps is just needed a runtime UI that matched the excellence of its design time interface.
Yahoo is focussing on mobile yet here they had this custom agent building tool that could easily be re-purposed to mobile to make a killer platform for Yahoo users.
Hopefully they will opensource the first generation perl version.
Some of my favourite flow based programming links follow.
Surprised nobody has mentioned noflow node.js workflows:
https://github.com/noflo/noflo
Also this (untested) will convert your yahoo pipes into Node.js https://github.com/neyric/pipes2js
and this one (also untested) will do the same in python: https://github.com/ggaughan/pipe2py
There is also python pypes which has a yahoo pipes like frontend with a stackless based backend. http://pyvideo.org/video/400/pycon-2011--large-scale-data-conditioning--amp--p
https://github.com/fullscale/pypes
Other python flow based programming tools https://wiki.python.org/moin/FlowBasedProgramming
http://www.kamaelia.org/Home.html (BBC research)
http://www.ruffus.org.uk/index.html
Wireit is a javascript pipes like frontend http://neyric.github.io/wireit/docs/
As you can see I loved pipes and I canhttp://datadesk.latimes.com/posts/2013/12/natural-language-p...
The LA Times article has some generic python NLTK code. They used a MaxEnt classifier instead of CRF.
http://pando.com/2013/09/09/rpx-and-the-complicated-business-of-stockpiling-patents-for-good-not-evil/
RPX and Intellectual Ventures bought the Kodak patent portfolio together: http://www.iam-magazine.com/blog/detail.aspx?g=4d1024d9-1e6c-43fa-8f78-a123f22575da
http://www.ipwatchdog.com/2012/12/19/kodak-sells-patents-to-intellectual-ventures-rpx-for-525-million/id=31737/
RPX and Intellectual Ventures own a common NPE holding company RPX-LV: http://www.plainsite.org/flashlight/rpxlv-acquisition-llc/
RPX was sued by Kaspersky Labs for extortion: http://www.scribd.com/doc/56754406/RPX-Criminal-Complaint
RPX cannot be trusted anymore than Intellectual Ventures. RPX is playing the same game as Intellectual Ventures. There is a better than good chance that RPX and Intellectual Ventures are working together as evidenced by their co-ownership of patent property and shared personnel history. The Kaspersky complaint raises the specter of RPX (with or without Intellectual Ventures) playing a good cop, bad cop style extortion racquet.How does that insurance look now?
Buyer beware!
http://openrefine.org/
is like a GUI version of csvkit.It can do external look ups, fuzzy matching, and has its own programming languages Jython and GREL.
https://github.com/hjhart/the_rotten_pirate http://pyvideo.org/video/425/pycon-2011--how-to-kill-a-patent-with-python
Part I (5 mins): The USPTO as a data source.* The full-text of each patent is available from the USPTO (and now from Google.) What does this data look like? How can it be harvested and normalized to create data structures that we can work with?
Part II (15 mins, in two parts):* Once the patents have been cleaned and normalized, they can be turned into data structures that we can use to evaluate their relationship to other documents. This is done in two ways - by modeling each patent as a document vector and a graph node.
Part IIA (7 mins): Patents as document vectors.* Once we have a patent as a data structure, we can treat the patent as a vector in an n-dimensional space. In moving from a document into a vector space, we will touch on normalization, stemming, TF/IDF, Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA).
Part IIB (7 mins): Patents as technology graphs.* This will show building graph structures using the connections between patents - both the built-in connections in the patents themselves as well as the connections discovered while working with the patents as vectors. We apply some social network analysis to partition the patent graph and find other documents in the same technology space.
Part III (5 mins): What have we built?* Now that we have done all this analysis, we can see some interesting things about the patent database as a whole. How does the patent database act as a map to the world of technology? And how has this helped with the original problem - finding better prior art?I think pHash also has functions for fingerprinting music but might not be as precise since pHash is not strictly focused on music.
http://www.mactech.com/articles/mactech/Vol.08/08.07/Paralat...
Recently started using Vagrant http://vagrantup.com/ to configure virtual machines with VirtualBox and Chef. Awesome. I recommend this combo to all devs.
Code Rush documentary from PBS. Details 98-99 when Netscape released their source.
These things all have to be dealt with and should not be thrown over the wall and "let the sysadmin deal with it." That's where the value of the OS and infrastructure is a set of code and config files which are kept in source control next to our code and versioned with it is so valuable. Run "vagrant up" and a fresh consistant build every time. Then develop in php, python, perl, ruby or brainfuck if you want.
I see that is has a plug in system for other provision systems like Puppet, but the chef support works great out of the box.
I was hoping to contribute to the project by integrating fog the ruby library which talks to many cloud systems including EC2 so someone could build an image via Chef or Puppet, dev and test in their image, then provision and upload to the cloud. Could probably do this without integrating with vagrant by building a clever rake or capistrano script.
"On the other end of the spectrum, languages like Chinese, Japanese, and Korean have thousands of characters."
This is not exactly true. Chinese has an iconic lexicon where each glyph is a single word. Both Cantonese and Mandarin speakers both use the same lexicon, but have different pronunciations. There are several lexicons (pinyin, big5, ancient) and thousands of glyphs in each.Japanese has three lexicons; hiragana, katagana, and kanji. Kanji is the oldest and adapted from Chinese. Glyphs are iconic. Hiragana and katagana were developed in Japan and are phonetic. Together they form most of what you see as Japanese text today. I think katagana is used more for foreign, non-Chinese words. There is also romanji which is essentially English letters. Anyway, apart from kanji which is Chinese, there are less than 100 hiragana and katagana glyphs.
Korean is even simpler. They too borrowed from the Chinese and occasionally still use some Chinese glyphs, but the official lexicon is Hangul. Hangul is phonetic and has 24(?) basic glyphs. Some glyphs can be combined into compound glyphs called double consonants and double vowels making about 40 glyphs total. A Korean word can be written by breaking it down into syllables, combining glyphs to form a syllable super-glyph, then putting those together to form a word.
The explanation of unicode and python3 is great. I just wanted to clear up the misconception stated in the first paragraph. Nothing more to see here...
pythoncard is like hypercard but it has all the power of python behind it. I have used it to write little desktop apps and been quite happy with the ease of development (particularly when adding new features after some months) and the performance. I never tried making an exe, but it should be possible.
2) This is a great idea for time based data. You age out the tables and create a merge table which is a logical view of all the tables together. You can get tricky and use compressed myisam tables for the older, static data since it will never change.