Browsing by Author "Hira Asim"

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    Text to Pakistan sign language automation
    (UMT Lahore, 2015) Hira Asim; Muhammad Mobeen
    In this thesis, a text to Pakistan Sign Language automation system has been proposed. The respective system takes an English input sentence and converts it into a Pakistan Sign Language sentence. By considering an effective and efficient use of storage, computation, and bandwidth, animation is an appropriate and sophisticated way to keep sign language content on the Internet. Out of all present sign language writing notation systems, HamNoSys is an efficient available notation that is not only able to convert signs into animations but also supports non-manual features such as body, head, and shoulder movements with the help of the SiGML markup language. HamNoSys basically symbolizes the gestures of signs present. The proposed system is not only capable of converting manually input text into its respective PSL version, but it also facilitates a deaf user to input any type of content from any web page. Our system is a HamNoSys-based system that is capable of generating animations of corresponding signs in PSL. As a benchmark, we took videos from PSL.org as standard gestures for our dictionary. Among all text to sign language conversion approaches, we followed a transfer-based translation approach, as we are not only translating input text into PSL but also validating and verifying the grammar of the converted sentence as well.
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    Under-graduate study recommendations using association rule mining
    (UMT.Lahore, 2018) Hira Asim
    In this research work, we are aimed to provide recommendations regarding degree programs and institutes at under-graduate level to students who have successfully passed their intermediate. In order to recommend we collected data via Google survey form regarding background study area, future goals and interests of individuals who are successfully done with their under-graduate studies for least. After the data has been collected it was being pre-proceed, visualized and analyzed for future use. Data mining technique named Association Rule Mining is applied on the data to find hidden patterns and trends in it. The results of the Association Rule Mining technique are the recommendations to the students regarding suitable under-graduate degree programs and educational institutes as per their background study stream, area of interest and future goals. Recommendations are based on the information collected where students and graduates have alike choices regarding study streams, area of interest and future goals. We are hopeful that this contribution will be a huge step forward towards the betterment of educational environment as well as a source of proper guidance for the students who are done with their intermediate and now aimed to take admission in an under-graduate program in a well reputed university in Pakistan.