This is an empirical investigation of the tribal power in Iraq and its consequences on the socio-political system. A theoretical background concerning thestate kinship, tribe and tribal involvement in politics has been displayed with example of tribal power over people within the social context. Socio-anthropological method of data collection has been used, including a semi-structured interview with a sample of 120 correspondents. The outcome revealed that the feeble and corrupted state (government) play a vital role in encouraging the tribe to be dominant. The people of Iraq are clinging to the tribe regardless of whether they believe in it or not. Although they are aware that the tribe is a pre-state organisation and marred shape of ci

A collection of 118 specimens of Iraqi phasianid birds belong to four species was examined
for haematozoa. Results show that 21.2% of them were infected with one or more of four
species of blood parasites; Haemoproteus danilewskyi, H. santosdiasi, Plasmodium sp. and
microfilaria. Haemoproteus danilewskyi is reported here for the first time in Iraq.

This study attempts to provide an approach analysis for the news, depending on the bases and principles which conceptuality semiotic researchers of this field first of them «A. J. Gremas» for the theory of «narrative discourse analysis», to more clarify we tried to apply it on a published press- news, to concludes the most important steps and methods that are necessary to follows gain more understanding of the press- news.

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

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

The impact of management control systems (MCS) on organizations performance empirical research has been the subject of numerous studies during the past decade in developed and emerging economies. In the contemporary competitive, complex and changing global business environment, firms are being challenged to adopt business models that enable them to address the strategic uncertainties and risks they face in their business environments. The main issue of this study is that management accounting researchers argue that one of the ways firms can continually rejuvenate themselves to survive and succeed in these complex and uncertain environments is to understand the role of management control systems in Formulating a b

The textile industries play a prominent role in reviving the national economy, but they are currently suffering from several problems, including the high costs of their activities, the low quality of their production processes, and accordingly, the hexagonal diffraction approach came to help analyze production activities to determine which of them are the most expensive and do not have a benefit or cost greater than Its benefit as a result of waste and losses that accompany its implementation. And by applying to the Iraqi mechanical carpet factory, the research reached several conclusions, the most important of which is the presence of several sources of waste and loss, such as activities and operations that do not add value, whi

AI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A

The efforts in designing and developing lightweight cryptography (LWC) started a decade ago. Many scholarly studies in literature report the enhancement of conventional cryptographic algorithms and the development of new algorithms. This significant number of studies resulted in the rise of many review studies on LWC in IoT. Due to the vast number of review studies on LWC in IoT, it is not known what the studies cover and how extensive the review studies are. Therefore, this article aimed to bridge the gap in the review studies by conducting a systematic scoping study. It analyzed the existing review articles on LWC in IoT to discover the extensiveness of the reviews and the topics covered. The results of the study suggested that many re