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jeasiq-1142
التعلم ألمنظمي وأثره في نجاح المنظمات دراسة ميدانية في شركات وزارة الأعمار والإسكان في العراق
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The world witness quality jumps under radical change in the management and work styles, through adopting organizational learning as a process of continuous improvements in response to environmental stimulus, in the knowledge age and turbulent competitive environment the organizational success concept is shift from the view narrow for financial performance and marketshare to long term view which focus on building strategic capabilities that provide a sustainable competitive advantage.

Considering the strategic role assumed for the companies of the Ministry of Construction and Housing to play it, these companies have been chosen to be the field in which questions of this study will be tested.

These questions concern the nature of level and influence of the organizational learning and organizational’s success. The aim of this study is to answer these questions. Data collected principally by questionnaire tool from a sample of (66) managers. Results proved that companies have acceptable level of organizational learning and success; organizational learning has significant influence in companies success.

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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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