Anomaly detection is the process of finding outlying record from a given data set. This problem has been of increasing importance due to the increase in the size of the data and the need to efficiently extract those outlying records that can have important indications in real-life problems. Anomaly detection is applied in many different sectors. There are many approaches to solve the anomaly detection problem. However, those that are more widely applicable are unsupervised approaches as they do not require labeled data. The aim of this thesis is to study a well-known anomaly detection technique ...

The aim of this thesis is to study the impact of a three-year-study of computer science at Notre Dame University on the students’ academic performances. For this reason, the GPAs of the students after their first year of study were compared with their GPAs upon graduation. To perform this, a Decision Tree, as well as Neural Networks were used. These algorithms helped us to predict the final GPA based on the first two semesters’ GPA. In addition, the most decisive courses on the student GPA were identified. For this reason, Relief algorithm was used to identify the three most important courses ...

The aim of data mining as a scientific research is developing methods to analyze large amounts of data in order to discover interesting regularities or exceptions. Typical problems, which should be resolved during developing effective data mining algorithms, arise from the large sizes of both: The data sets used in the data mining process and the patterns results sets (for example in rules) which form discovered knowledge. Scientific researchers are oriented to find the most advantageous (i.e. most effective) solutions both during the data preparation stage and exploration and finally post- ...

In this thesis, automatic segmentation of liver veins from ultrasound slices is implemented and further rendered into 3D image to assist the medical doctor to more accurately apply any study intended on the liver. The main part of this study is the texture analysis since it is the hardest problem in common. As a start, 4 different techniques in texture analysis have been introduced, the Spatial Gray-level Dependence Matrices (SGLDM), The Fourier Power Spectrum (FPS), The Gray- Level Difference Statistics (GLD), and Law's Texture Energy Measure (TEM). Each of these methods have been discussed ...

This thesis aim is defining a new meaning for microprogramming as we know it. Microprogramming was seen from two different views. In commercial applications microprogramming was treated primarily as an emulation tool. This allowed systems such as the IMB system/386 to implement both backward and forward compatibility. In military applications microprograming was considered as a tool for building optimized and fault tolerance control units. Dynamic and user microprogramming are usually used to refer to the same concept. In this thesis we will make a clear distinction between the two terms. User ...

Retail space planning is an accurate and complex process affecting the overall performance of a retail environment. Such task, confronting large retailers consisting of huge malls and hypermarkets, appears infinite in the absence of a complete automated process, starting from the store plan generation, passing by the optimal product assortment and finishing with the product-to-shelf allocation problem. Moreover, the ever-changing factors affecting the retail space planning process, such as merchandising rules, competitive strategies and consumer behavior require continuous follow-up and optimization ...

Over the last few years, LAN technologies have been driven by the need to support an increasing number of users as well as bandwidth intensive applications. As new and existing network applications evolve to embrace high-resolution graphics, video and other rich media types, pressure is growing at the desktop, the server, the hub and the switch for increased bandwidth. All this has led to new network protocols needed to support the amount of information required. In this thesis, we will briefly review conventional networking protocols and internetworking devices. Then we present a table comparing ...

In the last few years, Cloud Storage has taken a new turn in becoming the latest trend to create a huge impact in the IT world. Amazon Drive is a cloud storage mobile applications created by Amazon. This application provides online and easy access to documents, music, photos and videos saved in your cloud drive. Due to the importance and widespread of the cloud, not only regular users, but also criminals have taken advantage of the services provided by this new technology to commit digital crimes. Digital forensics is a branch of forensic sciences that aims at ...

Big data is an evolved term for large volume of unstructured, semi-structured and structured data having the potential to be used and mined for information in machine learning projects and other advanced analytics applications. Big data is the new driver of the world societal changes and economic. The world’s data collection is reaching a tipping point for major technological changes that can bring different ways in finance, decision-making, cities, managing our health, and education. Latest technological improvements in computing, data handling, data storage, and trading have transformed the ...

Cloud computing ecosystem is one of the trends currently being discussed in the domain of information technology and computing. Computing ecosystem allows smart usage of technology which means unneeded resources are saved such as power, computing resources, spaces for datacenters as well as saving huge amount of CO2 and electric circuit boards and machines. Cloud federation and its underlying techniques, is considered role model in sharing and expanding cloud business to provide better and cheaper services for end-users. In this thesis, we will survey and compare existing Identity Access Management ...