Abstract: This article concerned with the translation of Quranic
verses to Braille symbols, by using Visual basic program. The
system has the ability to translate the special vibration for the Quran.
This study limited for the (Noun + Scoon) vibrations. It builds on an
existing translation system that combines a finite state machine with
left and right context matching and a set of translation rules. This
allows to translate the Arabic language from text to Braille symbols
after detect the vibration for the Quran verses.
Abstract: the cursive nature of the Arabic writing makes it
difficult to accurately segment characters or even deal with the whole
word efficiently. Therefore, in this paper, a printed Arabic sub-word
recognition system is proposed. The suggested algorithm utilizes
geometrical moments as descriptors for the separated sub-words.
Three types of moments are investigated and applied to the printed
sub-word images after dividing each image into multiple parts using
windowing. Since moments are global descriptors, the windowing
mechanism allows the moments to be applied to local regions of the
sub-word. The local-global mixture of the proposed scheme increases
the discrimination power of the moments while keeping the
simplicity and ease of use of moments.
Abstract: Australian government agencies have a natural desire
to provide migrants a wide range of opportunities. Consequently,
government online services should be equally available to migrants
with a non-English speaking background (NESB). Despite the
commendable efforts of governments and local agencies in Australia
to provide such services, in reality, many NESB communities are not
taking advantage of these services. This article–based on an
extensive case study regarding the use of online government services
by the Arabic NESB community in Australia–reports on the
possible reasons for this issue, as well as suggestions for
improvement. The conclusion is that Australia should implement
ICT-based or e-government policies, programmes, and services that
more accurately reflect migrant cultures and languages so that
migrant integration can be more fully accomplished. Specifically, this
article presents an NESB Model that adopts the value of usercentricity
or a more individual-focused approach to government
online services in Australia.
Abstract: This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.