Difference between revisions of "Cracking the Voynich code 2016"

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(Semester A)
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::[[File:Proposal Seminar Slides (semester 1).pdf]]
 
::[[File:Proposal Seminar Slides (semester 1).pdf]]
 
::[http://www.eleceng.adelaide.edu.au/personal/dabbott/honours/Voynich_Sem1_talk_2015.mp4 Proposal Seminar Video]
 
::[http://www.eleceng.adelaide.edu.au/personal/dabbott/honours/Voynich_Sem1_talk_2015.mp4 Proposal Seminar Video]
* Research Project Proposal and Progress Report draft ('''Week 6a - 17/04/2015 - 3:00pm''')
+
* Thesis draft 1('''22/04/2016''')
::[[File:Draft Research Project Proposal - Project 31.pdf]]
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::[[File:Thesis draft 1 Ruihang Feng.pdf]]
 
::[[Draft Research Project Proposal - Wiki Page Convert]]
 
::[[Draft Research Project Proposal - Wiki Page Convert]]
 
* Research Project Proposal and Progress Report  - only one report needed in wiki format (''' Week 12 - 05/06/2016 - 3:00pm ''')
 
* Research Project Proposal and Progress Report  - only one report needed in wiki format (''' Week 12 - 05/06/2016 - 3:00pm ''')

Revision as of 20:16, 18 October 2016

Supervisors

Masters students

Project guidelines

General project description

The Voynich Manuscript is a mysterious 15th century book that no one today know what it says or who wrote it. The book is in a strange alphabet. See details here.

Fortunately the whole book has been converted into an electronic format with each character changed to a convenient ascii character. We want you to write software that will search the text and perform statistical tests to get clues as to the nature of the writing. Does the document bear the statistics of a natural language or is it a fake?

We already have Support Vector Machine (SVM) and Multiple Discriminant Analysis (MDA) software that you can adapt for your purposes. This software is set up to test if two texts are written by the same author or not. The great thing about our software is that it is independent of language. So you could compare it against the existing writings of Roger Bacon, who is a suspected author

Useful notes

  • Download the digital Voynich from here.
  • The UN Declaration of Human Rights is translated into every language in the world and in principle you can compare the Voynich to all the existing languages for statistical proximity. Electronic access is here.

Specific tasks

Phase 1: Text investigation. The details are shown as follwoing:

  • The total number of words.
  • The frequency of words.
  • The number of simple letters.
  • The frequency of simple letters.
  • Comparing the Voynich manuscript with other known languages.
  • Find patterns in known language digits.
  • Locate similar patterns in the Voynich manuscript.
  • Search any relationship between the patterns and digits.


Phase 2: Illustrations investigations is associated to the digitals investigation. It will follow several steps:

  • Locate all the images that contains one thing that appears more than once in an image.
  • Number the time that things appears in each image.
  • Trying to search words nearby the image that may conform any digital patterns in known language digits.
  • Decode all the digits if step c is success.


Phase 3: Marginal symbol research. The tasks are shown as following:

  • Statistics for marginal stars of each page, such as the number of marginal stars, the types of stars, the location of stars.
  • Extract the characters which may stand for digits from the Voynich manuscript.
  • Statistics the characters which are extracted in the last step, such as the occurence frequency of characters.
  • Make a chart according to the order of the occurence frequency of those characters. Then make a matching between characters and digits.
  • Infer the potential relationship between characters and digits.

Deliverables

Re-check required deliverables and dates

Semester A

  • Proposal seminar ( 04/04/2016 )
File:Proposal Seminar Slides (semester 1).pdf
Proposal Seminar Video
  • Thesis draft 1(22/04/2016)
File:Thesis draft 1 Ruihang Feng.pdf
Draft Research Project Proposal - Wiki Page Convert
  • Research Project Proposal and Progress Report - only one report needed in wiki format ( Week 12 - 05/06/2016 - 3:00pm )
Research Project Proposal and Progress Report
NOTE: A .pdf version must be generated and submitted by each member via MyUni, these must clearly show the contributions of the specific member

Semester B

  • Final seminar ( Tuesday, 13/10/15, Week 10 )
File:Final Seminar Slides.pdf
  • Final Report/Thesis ( Week 11 )
Cracking the Voynich Code 2015 - Final Report
The following pdf is a copy of the separate submitted thesis version as per the new course requirements
File:Cracking the Voynich Manuscript- Using basic statistics and analyses to determine linguistic relationships.pdf
  • Poster ( Friday, 23/10/15 )
File:Poster Draft.pdf
File:Project 31 Expo Poster.pdf
  • Project Exhibition - Ingenuity 2015 ( Monday - Tuesday, 26/10/15 - 27/10/15 )
  • Labelled CD or USB stick containing your whole project directories. Only one is needed but it should contain two project directories, ie. one for each group member ( By Friday 06/11/15 )
  • YouTube video summarizing project in exciting way - add the URL to this wiki - only one needed ( By Friday 06/11/15 )
Project 31: Cracking the Voynich Code 2015
  • Optional: any number of instructional how-to YouTube videos on running your software etc.

Weekly progress and questions

This is where you record your progress and ask questions. Make sure you update this every week.

Code files, work logs, meeting minutes, etc. can also be found on the project team's Google Drive. This can be viewed below:

Approach and methodology

We expect you to take a structured approach to both the validation and the writing of the software. You should carefully design the big-picture high-level view of the software modules, and the relationships and interfaces between them. Think also about the data transformations needed.

Expectations

  • We don't really expect you to crack the Voynich, though that would be cool if you do and you'll become very famous overnight.
  • To get good marks we expect you to show a logical approach to decisively eliminating some languages and authors, and finding some hints about the statistical nature of the words.
  • In your conclusion, you need to come up with a short list of possible hypotheses and a list of things you can definitely eliminate.
  • We expect you to critically look at the conclusions of the previous work and highlight to what extent your conclusions agree and where you disagree.
  • It is important to regularly see your main supervisors. Don't let more than 2 week go by without them seeing your face briefly.
  • You should be making at least one formal progress meeting with supervisors per month. It does not strictly have to be exactly a month, but roughly each month you should be in a position to show some progress and have some problems and difficulties to discuss. On the other hand the meetings can be very frequent in periods when you have a lot of activity and progress to show.
  • The onus is on you to drive the meetings, make the appointments, and set them up.

Relationship to possible career path

Whilst the project is fascinating as you'll learn about a specific high-profile mystery—and we do want you to have a lot of fun with it—the project does have a hard-core serious engineering side. It will familiarize you with techniques in information theory, probability, statistics, encryption, decryption, signal classification, and datamining. It will also improve your software skills. The new software tools you develop may lead to new IP in the areas of datamining, automatic text language identification, and also make you rich/famous. The types of jobs out there where these skills are useful are in computer security, comms, digital forensics, internet search companies, and language processing software companies. The types of industries that will need you are: the software industry, e-finance industry, e-security, IT industry, Google, telecoms industry, ASIO, ASIS, defence industry (e.g. DSD), etc. So go ahead and have fun with this, but keep your eye on the bigger engineering picture and try to build up an appreciation of why these techniques are useful to our industry. Now go crack the Voynich...this message will self-destruct in five seconds :-)

See also

Useful papers we wrote

[1] M. Ebrahimpour, T. J. Putniņš, M. J. Berryman, A. Allison, B. W.-H.-Ng, and D. Abbott, "Automated authorship attribution using advanced signal classification techniques," PLoS ONE, Vol. 8, No. 2, Art. No. e54998, 2013, http://dx.doi.org/10.1371/journal.pone.0054998

[2] M. J. Berryman, A. Allison, and D. Abbott, "Statistical techniques for text classification based on word recurrence intervals," Fluctuation and Noise Letters, Vol. 3, No. 1, pp. L1–L12, 2003.

References and useful resources

If you find any useful external links, list them here:

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