The aim of the study is to investigate the extent to which the teachers of Islamic education and their teachers taught the technological innovations in the universities and to test the significance of the differences between the averages of the degree of practice according to the variables: gender, experience, scientific qualification, and educational stage. To achieve these objectives, a questionnaire consisting of (20) (20) teacher and school, teachers of Islamic education in Iraqi universities.

   The results indicated that the degree of the practice of Islamic education teachers and their teachers of technological innovations was moderate, and there were statistically significant differences in the variable of

This article focuses on identity construction and social structures within the Sāmoan community as represented in Sia Figiel’s novel Where We Once Belonged. I argue that however the post/colonial Sāmoan identity is hybridized, the essence of the individual is still connected to Fa’a Sāmoa-the Sāmoan traditions and ways. However rapid are the colonial vicissitudes, the Sāmoan literature and lifestyle are developed to be a resistance platform. This resistance platform is dedicated not only to expose the colonial impact but also to assist the social and political reconstruction of post/colonial Samoa. To this end, this article studies identity construction, and the challenges that women face within Sāmoan social structures.

Low serum total adiponectin is associated with a high incidence of type 2 diabetes or coronary artery disease in the general population. Paradoxically, serum total adiponectin is elevated in patients with chronic kidney disease (CKD), such as overt diabetic nephropathy. The current study aimed to investigate whether or not  anemia to be dependently associated with serum level of total adiponectin in  non-albuminuric male patients with type 2 diabetes . The study included 42 type 2 diabetic male patients. Anemia was defined as hemoglobin (Hb) below 14.0g/dL. All the patients were without microalbuminuria, to exclude diabetic nephropathy. The diabetic patients were divided into 2 groups according to the hemoglobin level in ad

The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).

Facing the receiver (critic) problematic understanding of modern art done, which turned positive professional image to symbolic language, which gave it authenticity previous Arts advantage, and this latest progress in critical reading contemporary and several mechanisms for analyzing literary texts and plastic, including textural fabric. And we suffer from the absence of cash the recipient culture (learner), so the current search goal focused on detecting structural mechanisms formative (Goldman) reading done modern art and its role in raising criticism knowledge (learner). Defining the theoretical framework of chapter II by discussing it; the first episode dealt with the textural fabric, while the latter was accomplished Studio talk, an

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial