هدفت هذه الدراسة إلى مقارنة أثر أسلوب التعلم التعاوني بالأسلوب التقليدي في التحصيل الدراسي، وعلاقته بالاتجاه نحو الحاسب الآلي عند طلبة كلية التربية بجامعة بغداد خلال دراستهم لمقرر الحاسب الآلي وقد تضمنت إجراءات الدراسة استخدام الأسلوب التجريبي، وذلك بتوزيع أربع شعب دراسية على مجموعتين: "مجموعة تجريبية" يتم تدريسها باستخدام أسلوب التعلم التعاوني، والمجموعة الثانية: "مجموعة ضابطة" يتم تدريسها بالطريق

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w

Some new norms need to be adapted due to COVID-19 pandemic period where people need to wear masks, wash their hands frequently, maintain social distancing, and avoid going out unless necessary. Therefore, educational institutions were closed to minimize the spread of COVID-19. As a result of this, online education was adapted to substitute face-to-face learning. Therefore, this study aimed to assess the Malaysian university students’ adaptation to the new norms, knowledge and practices toward COVID-19, besides, their attitudes toward online learning. A convenient sampling technique was used to recruit 500 Malaysian university students from January to February 2021 through social media. For data collection, all students

A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

The apoptotic activity of methionine γ- lyase from Pseudomonas putida on cancer cell lines was indicated by measuring the concentration of cytochrome c in the supernatants of cell lines. The result revealed high concentration of cytochrome c in the supernatants of cancer cell lines (RD, AMGM and AMN3) respectively while the concentration of anti-apoptotic protein (Bcl-2) was very low.

المقدمة :يعد سرطان المثانة من بين أكثر أنواع السرطانات انتشارًا في جميع أنحاء العالم، حيث تم الإبلاغ عن 549,393 حالة جديدة في عام 2018 وما يقرب من ٪3 من جميع تشخيصات السرطان الجديدة و ٪2.1 من جميع وفيات السرطان ناتجة عن سرطان المثانة البولية. الاهداف: تهدف هذه الدراسة إلى استكشاف كفاءة وظائف الجهاز البولي بواسطة اجراء اختبارات وظائف الكلى ومستويات الايونات لمرضى سرطان المثانة. المنهجية: تم تحديد جميع الافراد الم

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu