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OmegaSoft.co.uk
OmegaSoft Development Blog
2007 wrap up
23 December 2007 - 07:40 PM
As the 2007 year draws to a close, we can reflect on the development achievements we have reached this year and what we have brought to the public.
The major release was the lauch of the Traffic Monitor web service in June. Although the project was slightly late - last minute debugging - we lauched our website hit counter service. This free tool has already featured on websites across the internet and the popularity of the service is still growing.
The OmegaSoft Developers Sandbox community website was also lauched in the summer for PHP, XML and SQL developers. This has seen countless articles written and has made OmegaSoft API code available to developers.
In addition, we released the API code for our Interface Model Engine. The IME has been used to seperate the business and presentation logic of the OmegaSoft website since 2005. This year we released the code to the public as it's own product. This API will allow web developers to seperate the presentation layers from their code on websites of varying complexity. Since it's lauch, several updates have been made to the code.
OmegaSoft PathSearch team also updated the search engine, based on research completed in the summer. This has made the engine more reliable and scalable for future projects.
Finally, our little surprise, the Whois lookup service, for querying DNS records for domain names.
Next year, we will continue to focus on these new services and products, as well as our new plans. What to expect in 2008 will be posted soon.
Merry Christmas.
Seb Harvey
The greatest common divisor
09 July 2007 - 04:16 PM
"The greatest common divisor of a and b is written as gcd(a, b), or sometimes simply as (a, b). For example, gcd(12, 18) = 6, gcd(−4, 14) = 2 and gcd(5, 0) = 5. Two numbers are called coprime or relatively prime if their greatest common divisor equals 1. For example, 9 and 28 are relatively prime.
"The greatest common divisor is useful for reducing vulgar fractions to be in lowest terms."
-Wikipedia
Calculate GCD below:
research.omegasoft.co.uk/labs/gcd/
Seb Harvey
Traffic Monitor fixes
02 July 2007 - 06:31 PM
Just to note, the 'invisible' counter problem has been solved.
Previously, users were complaining that they could see a small 1px by 1px box on their website, when selecting the invisible style counter.
This was due to the headers on the image being wrong, telling the server to generate a Jpeg image, instead of Gif.
This has been corrected and now the transparent Gif image is really transparent, instead of black. Therefore, users cannot anylonger see the counter, or anything else on their site.
This update was done on our applications and web administrators do not need to update their codes. Changes will be automatic to users with the invisible style selected.
Seb Harvey
Royale skin for Windows XP
30 May 2007 - 11:01 PM
I've been using the Windows 'Royale' theme on Windows XP Professional recently and love it.
Released some years ago, the Royale theme, formally known as Luna, was developed by Microsoft and released via a blog posting.
It has since been removed and the theme is a bit cumbersome to find. ALthough, I was able to obtain a copy through a message board posting.
This theme is similar to the Windows XP default blue theme. Although it adds a more professional feel to your desktop. Less child like.
There is also a black version, which also looks very charming.
If you want to try out the Royale theme, you can download it here. In the Zip file, is a read me file that is helpful when using.
Seb Harvey
History of Machine Translation
12 January 2007 - 10:04 PM
Machine translation (also known as MT) enables someone to use a computer to translate a block of text automatically for them - without any human interaction.
Im just going to note some of the development steps between the first translators and where the future is going to be.
Keywords: SL, source language; TL, target language
Word-for-word translations
Takes each word in the sentence and replaces it with the counterpart.
Right away, this is obviously not the best method, as the TL might not have an eqivilent counterpart. Also, some languages have different word ordering to English. While some languages also have additional words.
A reasonable MT needs a good knowledge of both the source language and the target language. Especially their similarities and differences.
The problems you face when translating text are: Dealing with morphology, lexical ambiguity, structual ambiguity, multi-word units, language differences, dealing with meaning.
Direct MT
This method is easy to implement.
Similar to word-for-word translation techniques, but also translate phrases-to-phrase as well. And then attempts to reorder ambiguous setencces.
But the problems persit, because it does not analyse linguistic information of the SL before translation.
While it is a robust method, it only foucues on one language pair, and is quite often uni-directional.
Transfer-Based MT
Looks at the SL first of all. Capturing its lingusitic information about each sentence.
It them maps the SL and TL components with their counterparts, taking into consideration the lingustic information formally aquired.
This method is bi-directional.
It places much more focus on the required language analysis, to see what is actually being translated, so it can map it a little more accurately. It effectively examines the difference between the two languages.
Interlingual MT Systems
A step in the right direction. Produces more accurate results than previously described methods.
It uses an intermediate language between the SL and TL. Thus forcing two translations during the process.
And it is theoretically bi-directional.
This intermediate layer is known as an interlingua.
It is also rather good for translating between various language pairs.
While it is a step in the right direction, its not quite perfect, as it fails to understand ungrammatical, errornous inputs.
Example-Basedd Machine Translation (EMBT)
This is where the future is!
When humans translate something, (unless they are experts or speak more than one language natively) they will use a bilingual dictionary. Which list the SL words and the TL equivients. But it also shows different TL's for each SL word based on a select number of examples provided in the entry.
This is effectively how EBMT work. It uses a corpus of bi-lingual examples. It then puts the SL into context and looks up the appropriate TL example, based on a 'best match'.
The corpus (the multi-lexical database) groups example terms based on their semantic similarity. Esentially using translation templates to translate structually similar sentences.
EMBT is robust. It deals with problems encountered by al methods discussed previously.
It's strenghts lye in; it not being domain specific, no complex analysing rules, alignment of terms can be done automatically, supports multi languages (not just one language pair) and it can be easily intergrated into basic MT models.
While it corrects all problems identified, and offers more strengths, there does come some new weaknesses and problems not encountered by previous methods.
Such as; it needs a good range of bilingual texts (data), needs cleaning up every so often by human interaction, data may need finely aligning, calcuations can be a fairly lengthy process, as it's searching through thousands of different examples.
Simple unambiguous sentences maybe better suited for more primitive methods, as it would be more efficient - but only where the SL is fairly straight forward.
Seb Harvey
Older Blog Postings
CFG and DCG notation in Natura... 11 Jan 2007PathSearch Speed Calculator 07 Jul 2006
LiveSpace out! 19 Jun 2006
FeedView 2006 06 Jun 2006
OmegaSoft RSS reader 05 Jun 2006
Serious RSS 30 May 2006
PathSearch algorithms refined 05 Feb 2006
Real-time ranking 11 Jan 2006
Six hours after! 09 Jan 2006
RemoteDrive Development Starts... 08 Jan 2006