يعتمد تطور البحث العلمي عادة على القياس. فبدون قياس لا يمكن معرفة مدى كفاءة أي نظام أو أداة مستحدثة. في هذه الورقة نعرض أدوات القياس التي يتم إستخدامها في تحديد كفاءة أنظمة إسترجاع المعلومات عموما و نركز على ما هو متوفر منها لقياس أنظمة إسترجاع النصوص العربية، ونبين مدى التطور التي أحدثه على مستوى إسترجاع النصوص العربية. تركز الورقة على عرض مجموعات الإختبار العربية المتوفرة حاليا, وتبرز القصور التي تعاني منه، وتظهر الحاجة الى وجود نجموعات اختبار عربية تتوافق مع واقع النصوص العربية الموجودة حاليا على شبكة المعلومات الدولية. كما نقوم بعرض مجموعة الإختبار التي قمنا بإعدادها لإختبار ظاهرة زيادة حجم النصوص العربية. ونبين أن زيادة الحجم في النصوص العربية يؤثر سلبا في مستوى آداء أنظمة الإسترجاع العربية. arabic 125 English 0
عبد السلام الفيتوري أحمد النويصري(10-2015)

Teaching computer programming is recognized to be difficult and a real challenge. The biggest problem faced by novice programmers is their lack of understanding of basic programming concepts. A visualized learning tool was developed and used by volunteered first-year students for two semesters. The purposes of this paper are: Firstly, to emphasize factors which directly affect the performance of our students negatively. Secondly, to examine whether the proposed tool would improve their performance and learning progression or not. This tool provides many features and enhancement which were presented to students as pre-lecture material. The results of adopting this tool were conducted using a pre-survey and post-survey questionnaire. As a result, students who used the learning tool showed better performance in their programming subject. arabic 9 English 74
Hala Shaari, Nuredin Ahmed(1-2018)

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)