FIT1016 &FIT2044 Advanced Project

Semester 2, 2012

These are zero-credit-point units designed to challenge the more advanced 1st and 2nd year students in the B. Computer Science, B. Software Engineering, B. Science majoring in Computer Science, and other related double degrees. (BBIS and BITS students with a strong interest in programming may also apply to do this unit.) This unit introduces students to a variety of topics outside the curriculum, and provides an opportunity to write programs (or, rarely, to build hardware) in an area of interest to the student and the School. The subject operates in an informal manner, and the programming tasks are designed to be interesting and challenging to advanced students. Students will typically meet with their supervisor on a weekly basis and in addition to demonstrating the results of their project, they will also give an oral presentation at the end of the semester.

 

Coordinator:.

  1. Ann Nicholson (ann.nicholson@monash.edu)
  2. Room  208.Blg 63

 

Information Session: Wednesday 25th  July, Room 135, Blg 26

 

Project

Supervisor

Student

Sensitivity Analysis for Bayesian Networks: The first part of this project will involve the student learning about Bayesian networks. The programming task is to implement an algorithm that computes a distance measure between two nodes, which can be used as a starting point for the expected influence one node exerts on the other. This distance measure can be used to rank order the nodes with respects to a particular node of interest. The next step would be to compare this ordering to that obtained by the Netica BN’s “sensitivity to findings” ranking. The programming will use the Netica Java API (see www.norsys.com).

Readings: Bayesian Artificial Intelligence, K.B. Korb and A.E. Nicholson, 2nd Edition, CRC Press, Chapters 1-4, and Section 10.4.8 – available online through the Monash library.

Ann Nicholson

Lucas Azzola

Michael Gill

Stuart Lloyd

Search Tree Maps

Guido Tack and Chris Mears

James Austin, Nicholas Smith

Rotor Cryptanalytic Expert System

Until the 1950s, rotor machines were the major machines used for commercial and military cryptography. The most famous machine, was the one used by the Germans in the second world war, was known as the German Enigma machine.  In this project the plan is to develop some software to help an expert decipher a rotor code. It will involve a student first understanding how a rotor cipher works, then understanding the algorithms which are used to decipher rotor codes, and finally develop some software that implements these algorithms.

David Albrecht

Michael

Billington, Bianca Gibson, Peter Rudd,

Stephen Prayogo

A non-linear mapping plotting tool for refracted radar range patterns

I actually have even Fortran IV source code written in 1968 which does this, for a Gerber plotter. The task is to produce a GPL tool which does this kind of (Blake) plot, with an adaptive algorithm, in a common and usable format.  Language is C preferably for portability, using Cgraph library (http://neurovision.berkeley.edu/software/A_Cgraph.html) or equivalent. The task is not trivial since the tool needs to take a nonlinear curve and represent it as a straight line, and generate nonlinear axes and arcs to correctly represent the results. I have several technical reports and papers (e.g. Blake) which explain the representation method. Most suited for a student who is mathematically inclined, or an engineer.

Carlo Kopp

Allocated but student subsequently withdrew

 

1.                   Decision Support Models onthe Popularity of Motion Pictures

 

2.                    Product Design Support Models Using Kansei Engineering and Intelligent Techniques

 

Here is a description of these projects.

Chang Joo Yun

(cjyun1@student.monash.edu)

Daniel Reddi Coronell

 

 

Chris Morris

Optical Character Recognition for Early Printed Text

Early printed texts mimicked the handwritten (manuscript) texts that

they replaced, both in the fonts employed and their use of numerous

abbreviations. Modern optical character recognition (OCR) software fails

when applied to scans of such documents. This project will seek a

solution to this problem through developing a front-end for the existing

open-source OCR software Tesseract.

 

This project is associated with the ARC Discovery Project "Ethics and

encyclopaedic culture in 13th century France: adaptation, diffusion and

contexts of innovation in the Speculum morale and its sources" and will

provide an opportunity to meet with and work with the research team for

that project.

 

Background reading:

    http://code.google.com/p/tesseract-ocr

    http://webfactotum.com/

David Squire

Ken Gee Chin, Dilpreet Singh

Android App

Shenjun Zhong

Shilong Sun, Yiu Shek, Thanh Pham

1.       Causal Discovery

2.       Creative Evolution of Complexity

A key open problem for artificial life is how to build a simulation which exhibits the kind of creativity found in natural biology. Whereas the biosphere exhibits something like exponential explosions in biodiversity following major extinction events (e.g., the "Cambrian explosion"), evolutionary artificial life so far exhibits far more modest diversity growth.

 

This project aims to further develop an existing artificial life simulation of an ecosystem so that it grows in complexity exponentially.

 

Kevin Korb

Alex Black

 

Farshid Zavareh

 




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