Eamonn O'Brien-Strain

LinkedIn

date: '2004-08-08 12:31:45' layout: post slug: how-to-read-smalltalk-if-you-are-a-java-or-c-programmer status: publish ref: http://www.squeak.org/ title: How to read Smalltalk if you are a Java or C++ programmer. wordpress_id: '38' categories: Programming

My programming language trajectory has been BASIC –> FORTRAN –> Pascal –> C –> C++ –> Java with a few diversions such as Perl and Python. On the way I have become a firm convert to object-oriented programming, and as such I always found my lack of knowledge in Smalltalk was a big gap.

Now that I sit near Alan Kay and have been impressed by Squeak and Croquet I have felt it was time to fill in that gap in my knowledge.

However, I did find initially that the syntactical differences of Smalltalk were a barrier to my understanding, one of the reasons I have created my own Java-Smalltalk cheatsheet.

So I was delighted to find Wilf LaLonde's tutorial, I Can Read C++ and Java But I Can’t Read Smalltalk.

date: '2004-08-08 13:41:14' layout: post slug: spatial-orientation-of-desktops status: publish ref: http://arstechnica.com/paedia/f/finder/finder-1.html title: Spatial Orientation of Desktops wordpress_id: '39' categories: Futzing

John Siracusa has an written an excellent article on what, in his opinion, makes a good desktop shell, concentrating mostly on the Macintosh finder.

As an experiment I have set up my Windows XP folder options to to match his recommendations as much as possible.

  1. In the folder context menu:

    • Do view->thumbnails in each folder.

    • Turn off the auto-arrange and the align to grid.

  2. In the folder view→toolbars menu desect all toolbars

  3. In the Folder Options panel

    • General tab: select “Use Windows classic folders”

    • General tab: select “Open each folder in its own window”

    • View tab: uncheck “Display the full path in the title bar”

    • View tab: check “Remember each folder's view setting”

    • View tab: check “Restore previous folder windows at logon”

    • View tab: click apply to all folders

It's like I have a brand new GUI on my operating system! Let's see how well I like it after using it for a while.

date: '2004-08-06 13:37:52' layout: post slug: some-nice-looking-java-software status: publish ref: http://geosoft.no/software/index.html title: Some nice looking Java software wordpress_id: '37' categories: Programming

GeoSoft – Geotechnical Software Services has some nice looking GPLed Java software.

date: '2004-10-05 10:24:13' layout: post slug: mount-st-helens-volcanocam status: publish ref: http://www.fs.fed.us/gpnf/volcanocams/msh/ title: Mount St. Helens VolcanoCam wordpress_id: '47' categories: Science image: http://www.fs.fed.us/gpnf/volcanocams/msh/images/mshvolcanocam.jpg image-text: Live image

Mount St. Helens VolcanoCam – Mount St. Helens National Volcanic Monument

date: '2004-08-05 09:51:39' layout: post slug: non-linear-dimensionality-reduction-techniques-for-unsupervised-feature-extraction status: publish ref: https://web.archive.org/web/20041010053416/http://webhost.ua.ac.be/visielab/debacker/papers/dimred/dimred.html title: Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction wordpress_id: '36' categories: Programming

Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction

Overview of some techniques for dimensionality reduction.

Update: The above HTML version is missing parts of some formulas. To see them see the compressed postscript version.

  • * *

Update 2019-09-13: Converted to PDF

date: '2004-08-04 17:22:51' layout: post slug: charles-stewarts-congressional-data-page status: publish ref: http://web.mit.edu/17.251/www/data_page.html title: Charles Stewart's congressional data page wordpress_id: '35' categories: Society

Lots of raw data of congressional roll call votes on Charles Stewart's congressional data page. I've got some ideas of some data mining I want to try out on this data.

date: '2004-07-28 18:34:00' layout: post slug: mathematica-eye-candy status: publish title: Mathematica Eye Candy wordpress_id: '33' categories: Programming

[http://obrain.com/~eob/blogPics/historySpace2.gif] I have been working on a little project that involves data mining some personal history. One of the things I have been trying is using principal component analysis to reduce the dimensionality of my data to something I can get an intuitive feel for, so that I can try to ficure out what are the best automated methods for pattern recognition. This image is an example reduced from sixteen variables to three. It's impressive what you can do in Mathematica.

date: '2004-07-27 09:44:54' layout: post slug: applet-demos-of-wolfram-cellular-automota status: publish ref: http://sjsu.rudyrucker.com/nksapplets.htm title: Applet Demos of Wolfram Cellular Automota wordpress_id: '31' categories: Science

Rudy Rucker and his class have done a good job of providing applet versions of some of the cellular automota from Stephen Wolfram's amazing book book “A New Kind of Science”.

I read the book when it first came out. It is nice to be reminded again at how amazing it all is.

date: '2004-07-26 15:31:21' layout: post slug: sdforum status: publish ref: http://www.sdforum.org/SDForum/Templates/Calendar.aspx title: SDForum wordpress_id: '30' categories: Programming

Some interesting technical events sponsored by the SDForum.

I am giving my self a crash course on some data mining techniques for a project I am working on. Here are some things I found useful.

In Matteo Matteucci's site at Politechnico di Milano is a nice little introductory tutorial on clustering algorthms, complete with interactive demos. A similar page is Tariq Rashid's University of Bristol page

Also François Labelle at McGill has a nice overview of reducing the dimensionality of multivariate data using Principal Component Analysis, also with interactive demos which give a nice intuitive feel for the technique. Mathematica supports principal component analysis, so given a data matrix with the each observation in a row, and each column a dimension I found could do the following to get a nice two dimensional view of the multi-dimensional data:

    <<Statistics`MultiDescriptiveStatistics`
    rotated = PrincipalComponents[Transpose[data]];
    rotated2d = Table[ {rotated〚i,1〛, rotated〚i,2〛}, {i,1,n}];
    ListPlot[rotated2d]