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jperc-618
( الثقافة التنظيمية لرؤساء الأقسام العلمية في جامعة بغداد في ضوء معايير ادارة الجودة الشاملة من وجهة نظر التدريسيين)
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هدف البحث الى تعرف :

1- مستوى الثقافة التنظيمية لرؤساء الأقسام العلمية في كليات جامعة بغداد.

2- الأهمية النسبية لأبعاد الثقافة التنظيمية لرؤساء الاقسام العلمية  في كليات جامعة بغداد.

بلغت العينة (380) تدريسي وتدريسية من الأقسام العلمية في كليات جامعة بغداد المتمثلة بـ (كلية الهندسة، كلية العلوم، كلية الإعلام، وكلية التربية للبنات)، اعتمدت الاستبانة أداة لتحقيق أهداف البحث، استخدمت الحزمة الإحصائية (SPSS) للمعالجة الإحصائية .وكانت أهم النتائج التي توصل اليها البحث :

  1. هناك مستوى جيد من الثقافة التنظيمية يتمتع بها رؤساء الأقسام العلمية في جامعة بغداد.
  2. تركيز رؤساء القسام العلمية في جامعة بغداد على بعض أبعاد الثقافة التنظيمية  وقلة الاهتمام بالأخرى فأظهرت نتائج البحث  ان بعد( الرقابة على الأداء ) قد حصل على أعلى وزن مئوي بين الأبعاد ، في حين حصل بعد (التوجه بالنتائج ) على أقل وزن مئوي رغم انه  من الأبعاد المهمة  في العملية التعليمة الجامعية كونه يرتبط بحاجات ومتغيرات سوق العمل وحاجة المجتمع من الطاقات البشرية .

 

 

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Mon Nov 26 2018
Journal Name
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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Characterization of Biochar Produced from IRAQI Palm Fronds by Thermal Pyrolysis
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Abstract

The present paper focuses in a particular on the study of the biochar production conditions by the thermal pyrolysis of biomass from local Iraqi palm fronds, in the absence of oxygen. The biochar product can be used as soil improvers. The effect of temperature on the extent of the thermal pyrolysis process was studied in the range from 523 to 773K with a residence time of 15 minutes and nitrogen gas flow rate of 0.1 l/min. The produced biochar was characterized as will as biomass and degradation products. The results showed that the rate of biochar production decreases with the increasing in temperature, also it was noted that the normalized biochar surface area and pore size increases with the increasin

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Publication Date
Wed Jun 01 2022
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Wed Dec 13 2017
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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Installing Quality of Gratitude in Children from an Islamic Educational Perspective
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The study aimed to identify how to raise grateful children from an Islamic educational perspective. For that objective to be achieved, the researcher used both of deductive and descriptive approaches using the method of documentary research. The study's results show that children are the real wealth of the community and the foundation of cultural building; therefore, paying attention their raising is a responsibility that must be shared by everyone; gratitude is part parcel of the Islamic doctrine, which is one of the greatest virtues; the virtue of gratitude is the attitude of the believers which in turn strengthens the bonds and expands the network of positive social relationships; It is also considered a cultural significance

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
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Publication Date
Sat Oct 01 2022
Journal Name
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Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Tue Sep 04 2018
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