101
Thesis Title: Feature Extraction Approach to Enhance Information Retrieval for Musical Media
Author: Ahmed Maher Dalli Al-juffer, Supervisor: Dr. Moayad A. Fadhil, Year: 2013
Faculty: Information Technology, Department: Computer Science

Abstract: In this research, the implementation of advanced music information retrieval system using the MATLAB software program is proposed and analyzed. This implemented system retrieves musical data based on initially pre-processing the musical data using three main techniques; Discrete Wavelet Transform (DWT), Linear Predictive Coding (LPC) and filtering function, after that, extracting seven features; energy in DWT of the high band, Energy in DWT of the low band, total energy of both bands, zero crossing rate of the high band, zero crossing rate of the low band, autocorrelation of the high band and autocorrelation of the low band from these data and then matching the extracted features with those of training musical data that are stored in a predefined database. The matching process depends on computing the Minkowski distance among musical data. Results demonstrate that the implemented music retrieval system can effectively and accurately retrieve the correct musical data based on the chosen testing data and comparing them with predefined ones.

Keywords: Discrete Wavelet Transform (DWT), Linear Predictive Coding (LPC), Filtering Function, Minkowski Distance

102
Thesis Title: An Approach to Extend WSDL-Based Data Types Specification to Enhance Web Services Understandability
Author: Fuad Sameh Ali Alshraideh, Supervisor: Dr. Samer Hanna, Year: 2013
Faculty: Information Technology, Department: Computer Science

Abstract: Web Services are important for integrating distributed heterogeneous applications. One of the problems that facing Web Services is the difficulty for a service provider to represent the datatype of the parameters of the operations provided by a Web service inside Web Service Description Language (WSDL). This problem will make it difficult for service requester to understand, reverse engineering, and also to decide if Web service is applicable to the required task of their application or not. This thesis introduces an approach to extend Web service datatypes specifications inside WSDL in order to solve the aforementioned challenges. This approach is based on adding more description to the provided operations parameters datatypes and also simplified the WSDL document in new enrichment XML-Schema.

Keywords: Web Services, Datatype, WSDL, Reverse Engineering

103
Thesis Title: A Textual Software Product Lines Design Model by Mixing Class and Feature Concepts
Author: Ola Abdel Raoof Younis, Supervisor: Prof. Said Ghoul, Year: 2013
Faculty: Information Technology, Department: Computer Science

Abstract: Designing software product line (SPL) is very important for increasing system reusability and decreasing cost and efforts for building components from scratch for each software configuration. Several approaches handled SPL engineering process with several techniques. The most famous one was done by separating the commonalities and variability for system’s components to allow configuration selection based on user defined features. These approaches deal with all software development phases, but the challenge and important phases are design and implementation. Textual notation-based approaches have been used for their formal syntax and semantics to represent system features and implementations. But these approaches are still weak in the mixing features (conceptual level) and classes (physical level) that guarantee smooth and automatic configuration generation for software releases. In this thesis, we will enhance SPL process by defining meta-features that captures the most important characteristics of feature modelling concepts, and classifying these features according to their functionalities. We will allow mixing class and feature concepts in a simple way using class interfaces and inherent features for smooth move from feature model to class model. SPL process will be enriching with a textual design and implementation methodology mixing class and feature model in new way. This methodology allows class model to be declared in a way that reflects features model concepts with consistent mixing with feature model. It enhances configuration generation process to be simpler, more coherent and complete.

Keywords: SPL, Textual Notation-Based Approaches, Conceptual Level, Physical Level

104
Thesis Title: Incremental Associative Rule Mining based on Intermediate Complete Item Set
Author: Iyad Ahmad Izzideen Aqra, Supervisor: Dr. Fadi Fayez Thabtah, Year: 2013
Faculty: Information Technology, Department: Computer Science

Abstract: Association rule mining (ARM) is one of the most important tasks in data mining that has attracted a lot of attention in the research community. The Apriori algorithm provides a creative and an intelligent way to find association rule on large database scale. Apriori is one of the most important algorithms, which aims to explore association rules. The main problem associated with Apriori is the multi scan database requires to find the rules when data gets updated every time. This problem increases complexity when databases grow over time. The discovered results from the original data are needed when mining the modified data set verifying knowledge obtained earlier. Researchers have proposed many algorithms to deal with the incremental problem. Especially in applications were changing databases constantly like banking application. These algorithms created solution to the problem in an intelligent way, such as FUP, IMSC, MAAP algorithms. The proposed algorithm in this thesis is called Incremental Apriori (INAP), and it deals with the problems described above. It is an incremental ARM that doesn’t need to rescan old database when gets update. The algorithm takes all data manipulation operation including the modifying, deleting and adding transactions into account when mine the data set and without going back to iterate over the original dataset. INAP algorithm allows us to extract knowledge with different thresholds (rule strength rate) every time without the needs to iterate over the original database meaning it solve the incremental problem in association rule.

Keywords: Association Rule Mining (ARM), FUP, IMSC, MAAP

105
Thesis Title: Software Bio-Inspired Systems: an Artificial Genome Methodology
Author: Imad Aldin Mahmoud Alshiekh, Supervisor: Prof. Said Ghoul, Year: 2013
Faculty: Information Technology, Department: Computer Science

Abstract: It is commonly held in current computer software systems that inspiration from biological entities was entirely used as inspiration of biological entities structures, emulation of their motions and reflection of their behaviors. In fact, the literatures have investigated many biological entities as a base of biological inspiration such as ants, swarms, genetics, bees, endocrine systems, and many others. However the genetics were and still the first biological inspiration, while the extensive methodologies appeared in role of mapping the real genetics into an artificial ones, but these mapping methods are still limited to reflect what happened in real genetics on the real life. This limitation is due to lacking of general framework and proper methodology for such mapping. In this thesis, we develop a kernel model that integrates the three axes of the space of the software bio-inspired systems, where these axes are Phylogeny, Ontogeny, and Epigeny, i.e. the (POE) model. We present a rebuttal of the main arguments against POE axes integration and show that they can be herein within a genome kernel to present a novel and new artificial genome model which is presented and illustrated visually by using UML diagrams along with new software modeling methodology. We also present an example of applying the proposed model to resolving common problem that happens in Operating Systems. The results show new general framework of bio-inspired software systems and new software modeling methodology. The results also show some discussions about this model, evaluations, implementations issues, related frameworks, conclusions and future perspectives.

Keywords: Biological Entities, Phylogeny, Ontogeny, Epigeny, UML, AGM (Artificial Genome Methodology)