Video streaming is widely available nowadays. Moreover, since the pandemic hit all across the globe, many people stayed home and used streaming services for news, education,  and entertainment. However,   when streaming in session, user Quality of Experience (QoE) is unsatisfied with the video content selection while streaming on smartphone devices. Users are often irritated by unpredictable video quality format displays on their smartphone devices. In this paper, we proposed a framework video selection scheme that targets to increase QoE user satisfaction. We used a video content selection algorithm to map the video selection that satisfies the user the most regarding streaming quality. Video Content Selection (VCS) are classified in

الذات والتحصيل الدراسي . وقد استخدمت الباحثة المنهج الوصفي التحليلي، وبلغت عينة الدراسة (500) طالبًا وطالبة، تم اختيارهم بالطريقة الطبقية العشوائية وهي تمثل (15%) من مجتمع الدراسة البالغ (3328) طالباً وطالبة من طلبة المرحلة الإعدادية واستخدمت الباحثة مقياسين تم بناء مقياس لقياس الجوهر والمظهر وتبني مقياس فاعلية الذات بعد إن قامت بترجمته وتعريبه وجعله ملائم للبيئة العراقية، كم تم استخراج درجات التحصيل الدراسي للع

Sequence covering array (SCA) generation is an active research area in recent years. Unlike the sequence-less covering arrays (CA), the order of sequence varies in the test case generation process. This paper reviews the state-of-the-art of the SCA strategies, earlier works reported that finding a minimal size of a test suite is considered as an NP-Hard problem. In addition, most of the existing strategies for SCA generation have a high order of complexity due to the generation of all combinatorial interactions by adopting one-test-at-a-time fashion. Reducing the complexity by adopting one-parameter- at-a-time for SCA generation is a challenging process. In addition, this reduction facilitates the supporting for a higher strength of cove