Categories
Intelligent systems

FIT5047 – Intelligent Systems Week 3

Week number 3, titled ‘Knowledge Representation’ ran through propositional and first-order logic. Specific attention was paid to Inference, the prime reason for creating Knowledge Bases.

I am a little bit cloudy on the methods for attaining inferences in Knowledge Bases. The lecture slides describe ‘Inference – Resolution Refutation’. To my understanding resolution can be attained through refutation or simply by applying the inference to clauses and determining the resolvent.

There is a clear example of ‘General Resolution’ and also ‘Proof by refutation’. I understand the difference in the processes; however I do not understand why one would use resolution by refutation as opposed to general resolution.

Considering our assignment which is due next week requires this understanding and info on this seems scarce in the text book, I shall inquire at next week’s lecture.

generalresolution
General resolution - source week 3 lecture notes

resolutionbyrefutation
Resolution by refutation - source week 3 lecture notes
Categories
Adv. programming for DB apps.

FIT5059 – Adv. Prog. for DB Applications Week 3

Week 3 rolled on with Oracle form builder interface training. Although the power and ease of use that form builder presents is impressive, I think the contents of week three could be extrapolated in a simple tutorial/walkthrough. I am sure as David mentioned that the material ramps up to more complexity.

The items that were covered in the lecture:

  • Introduction to commonly used form objects
  • Creating list of values (LOV)
  • Creating radio buttons
  • Creating check boxes
  • Creating static lists
  • Creating display items
  • Form object guidelines
Next week’s topic appears to be PL/SQL which I assume is where the ‘Advanced Programming’ in Advanced Programming for DB apps comes in  >:D
form
sample of an Orcale form (web based using J2EE)
Categories
Natural computation for intell. sys.

FIT5167 – Natural Computation Week 3

Week 3 of natural computation continued our step by step unraveling of the perceptron. We dealt with the case of classification and supervised training of a single perceptron. Although the concepts and logic are quite straight forward, there was some odd math operations that we spent a lot of our time on. I am not sure why we spent so much time on drawing the discriminant of a perceptron. I can’t see how it could be a useful skill with the exception of when we need to hand draw boundaries in the exam (and learning something just to pass an exam seems nonsensical). Anyway, the tutorial was particularly good in that we did some practical calculations in excel that were closely correlated to what we learnt in the lecture.

Specifically, the process of training a perceptron was emulated. Seeing exactly how altering the Beta value changed the learning process for a perceptron was valuable, along with understanding some of the possible inefficiencies/intractabilities associated with the simple, single perception network.

I am really looking forward to when we can see how an MLP handles a large dataset, sometimes having a vision of the goal makes these simple steps much more understandable.

source week 3 lecture notes
Categories
Network security

FIT5044 – Network Security Week 3

Network security’s third lecture saw an introduction to cryptography. We actually spent the first half of the lecture finishing discussion on week 2’s topics.

First off came Private key vs Public key encryption a nice, clear, diagrammatic explanation of the difference can be for here: http://www.wdvl.com/Authoring/Tools/Tutorial/public_vs_private.html

The main difference between the two being that a public key system has both public and private keys. In a private key system, the same key is used for both encryption and decryption. A key issue here is how the key is to be distributed.

A simple example of how public key systems work:

publickey
example of simple public key system (source: lecturenotes3.pdf)