Faculty of Information Technology

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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

2021-05-04 566 0
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Programs

Major

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بكالوريوس في تقنية المعلومات
Major هندسة البرمجيات

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Who works at the Faculty of Information Technology

Faculty of Information Technology has more than 38 academic staff members

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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

Routing based on security

Even though it is an essential requirement of any computer system, there is not yet a standard method to measure data security, especially when sending information over a network. However, the most common technique used to achieve the three goals of security is encryption. Three security metrics are derived from important issues of network security in this chapter. Each metric demonstrates the level of achievement in preserving one of the security goals. Routing algorithms based on these metrics are implemented to test the proposed solution. Computational effort and blocking probability are used to assess the behavior and the performance of these routing algorithms. Results show that the algorithms are able to find feasible paths between communicating parties and make reasonable savings in the computational effort needed to find an acceptable path. Consequently, higher blocking probabilities are encountered, which is the price to be paid for such savings. arabic 3 English 22
Ibrahim Almerhag(3-2014)
Publisher's website

Developing a mobile game app themed about Libyan culture using Unity engine

This paper presents the design and implementation of an educational game App using Unity engine. The game aims to provide informative experience of Libyan traditions while keeping players entertained. Also, the game attempts to document Libyan fading traditions while being amusing and enjoyable. This game will be very first Libyan games to be launched into Google Play Store.
Khaled Mohamed khalifa Ben Hamed, Nahed Fathi M Farah, Mohamed Bashagha, Mohanned Binmiskeen(12-2020)
Publisher's website

Applying Multiple Deep Learning Models for Antipersonal Landmines Recognition

Antipersonnel landmines represent a very serious hazard endangering the lives of many people living in armed conflict counties. The huge number of human lives lost due to this phenomenon has been a strong motivation for this research. Deep Learning (DL) is considered a very useful tool in object detection, image classification, face recognition and other computer vision activities. This paper focuses on DL for the problem of landmines recognition in order to identify its type based on shape features. This research work consists of several stages: gathering a new dataset of Anti-Personnel Mines (APMs) images for training and testing purposes, employing several augmentation strategies to boost the diversity of training data, applying four different Convolutional Neural Network (CNN) models namely VGG, ResNet, MiniGoogleNet and MobileNet, and evaluating their performances on APMs recognition. In conclusion, results indicate that MiniGoogleNet exceed all of other three models in recognizing APMs with the highest accuracy rate of 97%. arabic 9 English 69
Hassan Ali Hassan Ebrahem, Abdelhamid Elwaer, Marwa Solla, Fatima Ben Lashihar, Hala Shaari, Rudwan A. Husain(7-2021)
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