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التعلم التعاوني وأثره على التحصيل والاتجاه نحو الحاسب الآلي عند طلبة كلية التربية بجامعة بغداد
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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 بالطريقة التقليدية. وقد استخدم في هذه الدراسة مقياسان: الأول اختبار لقياس التحصيل الدراسي، والآخر استبانة لقياس الاتجاه نحو الحاسب الآلي. وقد تضمنت استبانة الاتجاه أربعة محاور، هي: الرأي تجاه الحاسب، القلق من الحاسب، والوعي بأهمية الحاسب، والخوف من دراسة المقرر. وقد تم تطبيق المقياسين مرتين: الأولى في بداية الفصل الدراسي، والذي نتج عنه عدم وجود فروق ذات دلالة إحصائية بين الطلبة سواء في معلوماتهن عن الحاسب، أو في اتجاههن نحوه، أو في خوفهن من دراسة مقرر الحاسب الآلي، ولكن ظهر تخوف كبير من قبل أغلبية أفراد العينة في محور الخوف من دراسة المقرر. أما التطبيق الثاني فكان في نهاية الفصل الدراسي، وأظهرت النتائج وجود فروق ذات دلالة إحصائية في كل من مستوى تحصيل الطلبة، وفي الثلاثة محاور الأولى من مقياس الاتجاه نحو الحاسب وذلك لصالح المجموعة التجريبية. أما المحور الرابع "الخوف من دراسة المقرر" فلم يظهر فرق ذو دلالة إحصائية بين المجموعتين يمكن إرجاعه إلى أسلوب التعلم، غير أن الفرق ظهر في ارتفاع متوسط الدرجات لأغلب أفراد العينة ما بين بداية الفصل الدراسي ونهايته، الأمر الذي أكد على أن مجرد تعلم الحاسب بغض النظر – عن الطريقة المتبعة – ساعد في تقليل الخوف من الدراسة عن الحاسب الآلي. أما الأسلوب التعاوني فكان عاملاً مساعداً في زيادة التحصيل الدراسي وبناء اتجاه جيد نحو الحاسب الآلي.

 

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
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This Study aimed To know The relation between Types of blood and health problems which human Suffered from , and the effect of food intake on health.
Samples of study contained 269 person aged between 30 – 70 years which choiced randomly for sex , we are take all in formation about samples of study by form paper contian sex , age, type of blood , weight (kg) , height (cm) , smoking or.not , sporting or not, problems in digestive tract , sensitivity for foods , heart problems , ratio of cholesterol in blood , Sinusitis , Asthma , diabetic meliuts , arritable bowel syndrome , diaherra , problems in kidney and urination , hypertension , anemia , alternation in liver function , arthritis with form record in daily food intake and its ade

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Journal Name
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Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
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Wed Apr 01 2020
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