Enhanced Learning Management System (LMSs)

SAQ is Web-based software you use over the internet with a web browser. You don’t have to install any CDs, download any software, or worry about upgrades. If you use an online bank or web-based email program like Gmail, Hotmail, or Yahoo Mail then you’ve already used web-based software before. In this thesis, we had got the code of the program DimDim and made some modifications and additions, but based on conversion of this program from a special program for private transactions, banking, politician and business to new program that is more comprehensive and wider, it is not limited to banking and private transactions, but in order to be more prevalent and comprehensive to include educational transactions, e-learning, social media, political and business in addition to solve the existing program's problems in the above mentioned. Then we enhanced “DimDim” and made some modifications to be a new software called “SAQ” which has differences that one more efficient than “DimDim”, beginning firstly; the new name “SAQ” related to simulation answer and questions but “DimDim” we didn’t find any meaning for it, secondly; “SAQ” had been more secure by creating a database tables that have a user name and password for each subscriber, it prevents anyone to enter the chat room which hasn’t user name and password, thirdly; adding scalability for subscriber number which was limited by two, but in “SAQ” had been reached to one hundred, besides that; made availability to use cameras and microphones for each subscribers controlling of the number of users, subscribers using cameras and microphones, finally; the frame size of the camera which was fixed but in “SAQ” had been variable due to the number of subscribers using cameras and appear on the user interface

INCREMENTAL QUERY PROCESSING IN INFORMATION FUSION SYSTEMS

This dissertation studies the methodology and techniques of information retrieval in fusion systems where information referring to same objects is assessed on the basis of data from multiple heterogeneous data sources. A wide range of important applications can be categorized as information fusion systems e.g. multisensor surveillance system, local search system, multisource medical diagnose system, and so on. Up to the time of this dissertation, most information retrieval methods in fusion systems are highly domain specific, and most query systems do not address fusion problem with enough efforts. In this dissertation, I describe a broadly applicable query based information retrieval approach in general fusion systems: user information needs are interpreted as fusion queries, and the query processing techniques e.g. source dependence graph (SDG), query refinement and optimization are described. Aiming to remove the query building bottleneck, a novel incremental query method is proposed, which can eliminate the accumulated complexity in query building as well as in query execution. Query pattern is defined to capture and reuse repeated structures in the incremental queries. Several new techniques for query pattern matching and learning are described in detail. Some important experiments in a real-world multisensor fusion system, i.e. the intelligent vehicle tracking (IVET) system, have been presented to validate the proposed methodology and techniques