This research addresses a problem manifested in a main question: what is the role of the digital media in marketing the artistic products? in order to determine the role played by the digital media in  the disclosure and promotion of  the artistic product, its price and places of distribution, as the basic elements of the marketing mixture. 

                This is a descriptive research in which the researcher used the survey method to check the opinions of a sample chosen according to the (proportion) method from the research community represented by instructors and students of the college of Fine Arts- University of Dayala. 

Abstract:

 In its theoretical farm, the research adobet  the subject of human resource management strategies  and the cognitive skills. It comes as result of the rapid development which considers it human resource. as main axis in organization , the research in includes ,connective analysis  , between  human resource management strategies  and cognitive skills which is considers one of the new concept that should  be  studied widly so that the organization can be able recognize it as concept and type and its importance for people in the organization.The study method was descriptive and  analytics , it identified collation of hypothesis which were by statist too

The present paper is a qualitative descriptive study. It aims to examine the macro-cultural schemata addressing the concept of violence against women in Iraq from a cognitive linguistic point of view. To meet this objective, a number of Iraqi social caricatures have been selected from two popular and active Iraqi caricaturists, Odeh Al-Fahdawi and Nasser Ibrahim. The selection and the analysis of data have been achieved following the validity and reliability procedures and the ethical considerations. To meet this objective, Sharifian’s Model (2011) of Cultural Schemata has been adopted in data analysis. The study has concluded that the macro-cultural schemata regarding the concept of violence in the selected panels reveals that violenc

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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