This research is aimed at identifying the communicative habits and the impact of the content on the communicative process, especially the youth audience, which is one of the most important categories to which the advertisement is directed, as young people face life with passion and aspiration that make then responsive to all the influences used by the media in designing advertisements which use all the techniques and methocls to attract young people, such as relying on drama , artistic tricks, musical phrases and advertising slogans that respond to the desire of young people in entertainment.
The research aims to identify the reflection of television advertising and its impact on the development of the cognitive abilities of universi

The current study investigates the role of smart sports bracelets on physical and motor skills development among youth volleyball players, closing the research gap of wearable technology in sport training. Understanding the necessity of up-to-date training measures of handicaps for perfection of athletic performance, the research is focused on comparison of the effect of strength, agility and flexibility achieved with the use of smart sports bracelet with real time feedback (test group) and without (control group). The research adopted a quasi-experimental design through a sample of (12) players et al.-Karkh Sports Club, (6) of them were in the experimental group (who used the smart bracelet) and (6) of them were in the control group (who u

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

The research aims to study the reliability of government institutions, including the audit directors, which are one of the most important oversight formations in the Ministry of Construction, Housing and Public Municipalities, on which the responsibility for comprehensive auditing of all the Ministry's (municipalities) formations falls on the Managing the Audit Program according to the specification (ISO 19011: 2018) to improve the audit performance which requires compliance with the application of the audit management system in accordance with the standard Specification (ISO 19011: 2018), depending on the methodology of the case study, and using of checklists, which were chosen ac

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Praise be to God, Lord of the Worlds, who has made His way for His servants who know in the depths and who are devoted to Him at all times and times, so He has delivered to Himself their pain from two exiles, and His prayers and peace are the perfect trust in the presence of the pearl of charity of existence. Possessor of great intercession and praiseworthy status until the day of meeting and eternity, and upon his family and companions, the people of tomorrow, steadfastness, generosity, and generosity, and after that

For a long period of time, I have been asking myself: Why did he attack so many contemporary books, especially Sufism? Why this unlimited financial expenditure on printing, binding, beautifying and enticing readers?

The study focused on the identification of the natural relation between the organizational components, and the most important is the organizational structure, which not hid its effect on each function and operation of the organizational structure through commanding the individual craters and its forms according to the requirement of these function, also it has relation with an organic synthesis that between the dimensions of the organic synthesis and the practice side in the commission of Integrity.

The problem of the research pensioned in some questions about hypothesis and theoretical parts, in which they go a mention about the hypothesis questions is to use all the knowledge's in this atmosphere and th

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

This research focuses on the epidemic of Job burnout and seeks to achieve sustainable preeminence among the employees of the University of Baghdad. It also identifies the meaning of the differences between the two genders of males and females according to the variables, and it also does the correlation between the two variables. First, the two researchers developed a test of job burnout that incorporates 18 items, which has been proven to be statistically fit. Moreover, they developed a competitive superiority measure consisting of 22 items in it, and its psychometric properties confirm their fit. The two tools were applied to a sample of 120 employees who were randomly selected from six colleges at the University of Baghdad, alongside univ