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)

Transliteration is the process of representing words of one language into another using corresponding equivalent phonemes. For example, “Mohammed”, “Mohammad”, or “Muhammed” are three valid transliterations to the Arabic proper noun “محمد”. Transliteration from Arabic to English usually results in several different versions for the same Arabic name causing some names to have more than 40 different versions. Finding transliterated names is a problem in most languages. In English, this problem has been studied by researchers and many techniques have been developed to find transliterated names referring to the same foreign name. Techniques such as string matching and phonetic matching have been used to find similar names. However, some of these techniques were designed to find similar names of English origin and not a specific transliterated names. In this paper we review current techniques used to find variants of the same name and introduce a new technique we specifically developed to find transliterated Arabic names in English text. We developed a data set of more than 25,000 transliterated Arabic names and tested the effectiveness of current and the new technique on finding 115 names within that list. Our results show that our technique is superior to all other techniques. We also present an online system that we developed to find transliterated Arabic names on the web using our technique. arabic 8 English 57
Abdusalam F. Ahmad Nwesri, Nabila Al-Mabrouk S. Shinbir(9-2009)

Open Educational Resources become an important asset for many educational institutions. In this paper we report the analysis of our survey data on using open educational resources at the University of Tripoli (UoT) among the academic staff members. The survey data was collected electronically to assess the awareness and usage of open educational resources within the University of Tripoli. Results of our survey reveal that 90% of academic staff members surveyed are using open educational resources, but they are not contributing much to OER due to lack of support from university. arabic 8 English 56
Abdusalam F. Ahmad Nwesri(5-2019)