العوامل المؤثرة في نشأة النظام السياسي الامريكي

تعد مسالة بناء الدولة احدة المواضيع المهمة في حقل الدراسات السياسية والتي تعكس مظهراً متعدد الابعاد لمبدأ الثقة المنشود بين الحاكم والمحكوم، فمنذ أمد طويل تحاول الدول تحقيق تنميتها السياسية والبحث عن مقومات ترشيد سياسي لقدراتها المؤسساتية والوظيفية بهدف تعزيز اسس التكامل والاندماج بين المجتمع السياسي والمجتمع المدني. عليه انطلق جون راولز في مفهومه لبناء الدولة المعاصرة من بناء المجتمع العادل، فالعدالة ه

Calcifying epithelial odontogenic tumour (CEOT) is a benign odontogenic neoplasm of epithelial origin that secretes an amyloid‐like protein tending towards calcification. This study aims to describe a case series from Iraq of one of the rarest odontogenic tumours.

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Few updated retrospective histopathological-based studies in Iraq evaluate a comprehensive spectrum of oro-maxillofacial lesions. Also, there was a need for a systematic way of categorizing the diseases and reporting results in codes according to the WHO classification that helps occupational health professionals in the clinical-epidemiological approach.

Objectives: to establish an electronic archiving database according to the ICD-10 that encompasses oro-maxillofacial lesions in Sulaimani city for the last 12 years, then to study the prevalence trend and correlation with clinicopathological parameters.

Subjects and Methods:  A descri

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

مثل الوعي الطبقي اعلى مراحله لدى الفكر الماركسي المعاصر عند كل من روزا لوكسمبورغ وانطونيو غرامشي، ليس مجرد انعكاس للواقع وانما يكون بصورة جدلية من طريق انعكاس الوعي على الواقع وإعادة انتاجه فبعد ان كان الوعي هو نتاج تطور الواقع اصبح أداة في تطوير الواقع، أي تأثير البنى الفوقية في البنى التحتية (المادية التاريخية) وعدت ان الوعي الطبقي الثوري يتحقق بشكل عفوي، وبذور انطلاقة هي الاضرابات الجماهيرية، وأنكرت دور