MSBNx What's New 6/16/2010 - The MSBNx sample code is now available for C# 4 and VS2010: SamplesCSharp2010.zip 9/20/2007 - The MSBNx sample code is now available in C#: SamplesCSharp.zip 1/31/2007 -- The first time you run MSBNx under Windows Vista, you'll get this pop-up message: "DLL Self-registration failed for HMMAddinLib.dll". Click "OK" and ignore the message. 9/10/2001 -- If you get a Run-Time 13 error when you try to run MSBNx, check the FAQs for a fix. 08/02/2001 -- Before installing a new version, you must uninstall the previous version. 08/02/2001 - Reading models from the WinMine tool not supported for now. 08/01/2001 - Released version 1.4.0.2 - changes the default Value of Information measure for diagnosis to entropic. MSBNx MSBNx is a component-based Windows application for creating, assessing, and evaluating Bayesian Networks, created at Microsoft Research. Comments and Questions Please email dtg-msbn@microsoft.com with your comments or questions. Background Recommendations Assessment
UI Browser The ultimate assistant for GUI Scripting and Accessibility UI Browser is the ultimate assistant for Apple's AppleScript GUI Scripting and Accessibility technologies. It helps you to explore, monitor, and control the User Interface elements of most Mac OS X applications running on your computer. Choose an application in UI Browser's Target menu to browse its UI elements, or use the built-in Screen Reader or press a hot key to read any application's UI elements on the screen under the mouse. Then use UI Browser to perform actions on the selected UI element, get and set its attributes, send keystrokes to the target application, and observe notifications when any of the target's UI elements change. Use UI Browser to test the target while you write GUI Scripting scripts or while you add accessibility features to applications you are developing, and you can be confident they will work as expected. UI Browser 2.4.3 includes minor bug fixes. UI Browser may be purchased for $55.00 US. NEW RELEASE!
Octave GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. Octave is distributed under the terms of the GNU General Public License. March 7, 2014 — Octave 3.8.1 Released Version 3.8.1 is a bug fixing release and is now available for download. One of the biggest new features for the Octave 3.8.x release series is a graphical user interface. Given the length of time and the number of bug fixes and improvements since the last major release Octave, we also decided against delaying the release any longer. We need your help. We hope you find Octave to be useful. February 26, 2013 — Google Summer of Code
About Scratch - Scratch Wiki Who Uses Scratch? Scratch is designed especially for ages 8 to 16, but is used by people of all ages. Millions of people are creating Scratch projects in a wide variety of settings, including homes, schools, museums, libraries, and community centers. Around the World Scratch is used in more than 150 different countries and available in more than 40 languages. Quotes The Scratch Team has received many emails from youth, parents, and educators expressing thanks for Scratch. Learn More About Scratch Learn to Code, Code to Learn The ability to code computer programs is an important part of literacy in today’s society. Scratch in Schools Students are learning with Scratch at all levels (from elementary school to college) and across disciplines (such as math, computer science, language arts, social studies). Research The MIT Scratch Team and collaborators are researching how people use and learn with Scratch (for an introduction, see Scratch: Programming for All). Support and Funding
List of Queueing Theory Software This page gives a list of queueing theory software. The list was compiled by Dr. Myron Hlynka of the University of Windsor, who welcomes any additions to the list. Octave-Forge - Extra packages for GNU Octave (added June 10, 2014) Java Modelling Tools(added June 10, 2014) Solutions to Queueing Systems (added June 10, 2014) Queueing Theory Calculator. Go/return to Myron Hlynka's Queueing Theory Page. How to use the Bayes Net Toolbox This documentation was last updated on 29 October 2007. Click here for a French version of this documentation (last updated in 2005). To define a Bayes net, you must specify the graph structure and then the parameters. We look at each in turn, using a simple example (adapted from Russell and Norvig, "Artificial Intelligence: a Modern Approach", Prentice Hall, 1995, p454). Graph structure Consider the following network. To specify this directed acyclic graph (dag), we create an adjacency matrix: N = 4; dag = zeros(N,N); C = 1; S = 2; R = 3; W = 4; dag(C,[R S]) = 1; dag(R,W) = 1; dag(S,W)=1; We have numbered the nodes as follows: Cloudy = 1, Sprinkler = 2, Rain = 3, WetGrass = 4. In Matlab 6, you can use logical arrays instead of double arrays, which are 4 times smaller: dag = false(N,N); dag(C,[R S]) = true; ... However, some graph functions (eg acyclic) do not work on logical arrays! You can visualize the resulting graph structure using the methods discussed below. node_sizes = [4 2 3 5];
AHP (Analytical Hierarchy Process) Analytical Hierarchy Process (AHP) is a process that helps us pick up one of the options of a list of choices. Each choice has a few parameters attached to it and we can set the weights of each parameter and have AHP pick the best choice from the list of choices. I will show this in the following example. Analytical Hierarchy Process for College Selection The strength of AHP is that it takes into account many different parameters for many alternatives and gives the result that best matches the parameters. Following is are 2 tables that give the lists of preferences and colleges: We will use AHP to help us come to a conclusion as to which college a student should pick. Data Collection for Preferences The preference matrices for the colleges were made using the data from rankings and rating found on a website. Note: the data used in this example is obsolete The data collected is not in the format we needed for AHP calculations. Pair-wise Matrix Creation This table holds great value to it. i.