Faculty of Information Technology

More ...

About Faculty of Information Technology

Faculty of Information Technology

The Faculty of Information Technology is one of the most recent faculties at the University of Tripoli, as it was established in pursuant to the former General People's Committee for Higher Education Decision No. 535 of 2007 regarding the creation of Information Technology Faculties in the main universities in Libya.

 

Upon its establishment, the Faculty consisted of three departments: Computer Networks Department, Computer Science Department and Software Engineering Department. It now includes five departments: Mobile Computing Department, Computer Network Department, Internet Technologies Department, Information Systems Department and Software Engineering Department.

 

The Faculty’s study system follows the open semester system by two (Fall and Spring) terms per year. The Faculty began to actually accept students and teach with the beginning of the Fall semester 2008. It grants a specialized (university) degree in information technology in any of the aforementioned disciplines. Obtaining the degree requires the successful completion of at least 135 credit hours. Arabic is the language of study in the college, and English may be also used alongside it. It takes eight semesters to graduate from the Faculty if Information Technology.

 

The Faculty aspires to open postgraduate programs in the departments of computer networks and software engineering in the near future.

Facts about Faculty of Information Technology

We are proud of what we offer to the world and the community

69

Publications

38

Academic Staff

1710

Students

159

Graduates

Faculty of Information Technology News

2021-05-04 579 0
More News

Programs

بكالوريوس في تقنية المعلومات
Major هندسة البرمجيات

...

Details
Major

...

Details
Major

...

Details

Who works at the Faculty of Information Technology

Faculty of Information Technology has more than 38 academic staff members

staff photo

Dr. Mohamed Abdeldaiem Abdelhadi Mahboub

الدكتور محمد عبدالدائم عبدالهادى احد اعضاء هيئة التدريس بقسم نظم المعلومات, كلية تقنية المعلومات ,تخصصه الدقيق, نظم استرجاع البيانات ودرجته العلمية استاذ مشارك.

Publications

Some of publications in Faculty of Information Technology

biometrics:standing throughout emerging technologies

Biometrics technologies have been around for quite some time and many have been deployed for different applications all around the world, ranging from small companies' time and attendance systems to access control systems for nuclear facilities. Biometrics offer a reliable solution for the establishment of the distinctiveness of identity based on "who an individual is", rather than what he or she knows or carries. Biometric Systems automatically verify a person's identity based on his/her anatomical and behavioral characteristics. Biometric traits represent a strong and undeviating link between a person and his/her identity, these traits cannot be easily lost or forgotten or faked, since biometric systems require the user to be present at the time of authentication. Some biometric systems are more reliable than others, yet they are neither secure nor accurate, all biometrics have their strengths and weaknesses. Although some of these systems have shown reliability and solidarity, work still has to be done to improve the quality of service they provide. Presented is the available standing biometric systems showing their strengths and weaknesses and also emerging technologies which may have great benefits for security applications in the near future.
Abdulmonam Omar Ahmed Alaswad(0-2008)
Publisher's website

OPTIMIZATION SEGMENTATION AND CLASSIFICATION FROM MRI OF BRAIN TUMOR AND ITS LOCATION CALCULATION USING MACHINE LEARNING AND DEEP LEARNING APPROACH

The manual detection and classification finding correct location and identifying type of tumor becomes a rigorous and hectic task for the radiologists. Medical diagnosis via image processing and machine learning is considered one of the most important issues of artificial intelligence systems. Deep learning has been used successfully in supervised classification tasks in order to learn complex patterns. The main contributions of this paper are as create a more generalized method for brain tumor classification using deep learning a variety of neural networks were constructed based on the preprocessing of image data., analyze the application of tumorless brain images on brain tumor classification and empirically evaluate neural networks on the given datasets with per image accuracy and per patient accuracy. And also presents an efficient image segmentation using machine learning algorithm with some optimization techniques to detect brain tumors. arabic 19 English 128
Mohamed Abdeldaiem Abdelhadi Mahboub(3-2019)
Publisher's website

Performance Evaluation of Multimedia Streaming Applications in MPLS Networks Using OPNET

This paper describes the place of MPLS in current state-of-the-art networking as a quality of service means through performing performance analysis of VoIP and video conferencing applications by comparing the effect of different protocols (OSPF, IS-IS, EIRGP) and the effect of various queuing techniques (PQ, WFQ, MWRR) in order to find the good combination of MPLS, routing, and queuing type that provides efficient suitable quality of service levels. The obtained results illustrate a competent combination of MPLS with queuing discipline, and routing could be achieved for each application, such as MPLS and EIGRP with WFQ queuing is an efficient arrangement for video conferencing application
Azeddien M. Sllame, Reema A. Saad, Mariam Abojella Msaad(5-2021)
Publisher's website