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Thesis Title: جھود كراتشكوفسكي في اللغة العربیة وآدابھا
Author: مثنى خالد محمود الذیابات, Supervisor: غسان إسماعیل عبدالخالق, Year: 2017
Faculty: Arts, Department: Arabic Language and Literature

Abstract: تناولت الدراسة جھود كراتشكوفسكي في اللغة العربیة وآدابھا. وقد جاءت في: مقدمة،وتمھید وفصلین، وخاتمة. خصصت المقدمة للحدیث عن مشكلة الدراسة، وأھدافھا، وأھمیتھا، ومنھجھا، والدراسات السابقة التي أفادت منھا. وتناول التمھید: الاستشراق مفھومھ ونشأتھ، وحركة الاستشراق الروسي، ونبذة موجزة عن حیاة المستشرق كراتشكوفسكي. وعالج الفصل الأول: جھود كراتشكوفسكي في تحقیق التراث العربي، وذلك من خلال تناولھ دور الاستشراق في تحقیق النصوص، مفھوم التحقیق وقواعده، وكذلك آثار كراتشكوفسكي في التحقیق ومنھجیتھ فیھ. وعرض الفصل الثاني: لجھود كراتشكوفسكي في دراسة الأدب ونقده، من حیث: جھوده في الأدب العربي ونقده؛ القدیم منھ والحدیث، ومنھجھ في دراسة الأدب العربي ونقده. وأخیراً الخاتمة التي عرضت لأھم النتائج التي توصلتْ إلیھا الدراسة، وأعقبھا الباحث بقائمة المصادر والمراجع التي أفاد منھا.

Keywords: كراتشكوفسكي، الاستشراق، التحقیق، الأدب العربي.

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Thesis Title: Enhancing Associative Classification Technique for Spam Detection
Author: Mohammed A M Jarrah, Supervisor: Dr. Rasheed Al-Zubidy, Year: 2017
Faculty: Information Technology, Department: Computer Science

Abstract: Data mining techniques can extract meaning from noisy data, find out patterns in random data, and use this information to best understand trends, patterns, connection and relations between the data. Data mining has two classes (supervised and unsupervised) depending on the human management or predefining the goal. One of the hybrid techniques which combine supervised and unsupervised technique to achieve a full automated process to find hidden patterns and classify the data depending on this patterns and relations is the Associative classification AC.This technique is widely used in the world to solve many problems. In this study we propose a new enhanced associative classification approach work to increase the accuracy of it by decreasing the number of inaccurate rules that may obtained by the association rule mining by adding a second rule checking step to solve this problem and proved that by the experimental results. The proposed approach applied in the cyber security domain exactly to solve the SPAM emails problem as a SPAM detection hybrid algorithm (join link based (header) and content base). The implementation of this approach shows that the proposed approach improves the performance of the traditional approach in different aspects . For example the precision measure increased from 0.543 to 0.862 and the accuracy measure also increased from 0.721 to 0.890compared with the traditional approach.

Keywords: Data Mining, Cyber security, Association Rule Mining, Classification, Associative Classification, Enhanced Associative classification, SPAM Detection

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Thesis Title: A Wimax Uplink Scheduling Algorithm among Fixed Stations
Author: Lubna Fathi Mehdawi, Supervisor: Prof. Mohamed Bettaz, Year: 2017
Faculty: Information Technology, Department: Computer Science

Abstract: IEEE 802.16 defines WiMAX as a broadband access technology that, among others might be considered as an alternative to other broadband access technologies such as fiber optics and 4G. It is worth to mention that IEEE802.16 does not impose any scheduling technique, thus opening the way for contributions from industry and academia aiming at enhancing the Quality of Service (QoS). This thesis proposed an uplink scheduling algorithm, the aim of this work is twofold: At the theoretical level, firstly we project to deepen the study of a promising scheduling algorithm based on the Deficit Round Robin (DRR), namely the Dynamically Weighted Deficit Round Robin (DWDRR) (Andreadis et al., 2014), secondly studying different parameters especially the Queue delay to enhance the performance for different flows rate and improving the QoS. This will improve the scheduling technique to provide user with better performance with respect of different Quality of service classes. At the experimental level, we project to adapt the NS-2 simulator by functionalities able to deal with the 802.16 standard, then to use it to perform simulations, with the objective to compare our scheduling algorithm with the DWDRR, with respect to throughput, delay and fairness for various QoS connections.

Keywords: Wimax, Uplink, Scheduling, Algorithm

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Thesis Title: Using NLP for Semi Automated Class Diagram Generation from Arabic Text
Author: Linah Ghazi Al-Khatib, Supervisor: Dr. Samir Tartir, Year: 2017
Faculty: Information Technology, Department: Computer Science

Abstract: Arabic language is one of the most used languages in the world. Software requirements of an information system are written in natural language; Arabic or English. Arabic is the formal language that is used to write software requirements by the most of ministries and governmental institutions in Arab countries. In software engineering, manual analysis and design of the requirements cause variations of the obtained model due to the complexity of natural language. Using natural language processing tools in analysing and transforming requirements into models enhances knowledge extraction performance. Many approaches addressed this domain, but very little research has been developed to obtain models from requirements written in Arabic, especially class model. Also, they never use semantic approaches that utilize the domain ontologies, which produce a gap between knowledge engineering and software engineering. In this thesis, we propose an approach that solve the previous problems and automate the process of constructing a class model from Arabic requirements. The core aim of our approach is to handle Arabic user requirements transformation into class diagrams. We propose a set of identification rules to identify class diagram elements, then we combine the proposed set of identification rules, ANLP tools and domain ontologies to build a unique approach for generating UML class diagram from Arabic user requirements. Our approach is the first approach that utilizes domain ontology and Arabic natural language processing tools to generate class diagrams form the Arabic requirements. Finally, we validate our approach by performing an experiment, which involves a group of human evaluators. The results showed that our approach produces very good results as compared to the evaluators depending on the performance evaluation criteria; precision and recall. The results indicated that our proposed technique is a good candidate for extracting class diagrams from Arabic user requirements text as compared to existing approaches.

Keywords: NLP, Class Diagram, Arabic Text, Automated

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Thesis Title: A Software Feature-based Reverse Engineering Methodology
Author: Anas Adnan Alhamwieh, Supervisor: Prof. Said Ghoul, Year: 2017
Faculty: Information Technology, Department: Computer Science

Abstract: Software reverse engineering is the kernel task of software maintenance. In the past years it deals with software source code model understanding. This model is at an implementation level, detailed, language depending, and complex. Nowadays, the software reverse engineering is levered to software abstract design level, supported by feature model notations, language independent, and more simple that code reading. The recent approaches to feature based software reverse engineering face following insufficiencies: lack of a complete integrated methodology, adapted feature model, feature patterns recognition, and Graph based slicing. The works presented in this thesis propose some solutions to the above challenges through an integrated methodology. In fact, the proposed methodology starts by presenting elementary and configuration features in a uniform way by introducing specific attributes. The reverse engineering process is the supporting feature pattern recognition which allow the understandability of any feature (is it elementary?, is it a configuration and what features is it composed by?, what relations it has?, etc.). It also support software feature model slicing, not based on mathematical notations but on graphs ones which is more adapted to software reading. The slicing criteria are rich enough to allow answering questions of software maintainers. They covers the two main relations in the software feature model (AND, OR) and the two main directions (forward and backward). A comparison of this proposed methodology, based on effective criteria, with the similar works seems to be valuable and competitive (the enrichment of the feature model and feature pattern recognition were never approached and the proposed slicing technique is more general and applicable).

Keywords: Feature-based, Reverse Engineering