The fundamental problem in determining the role of television programs in broadcasting the culture of community for peace through studying almosamig kareem program by studying the topics addressed in this program. It is a descriptive study and it follows the approach survey method.  In this study, the spatial framework is limited to the program of almosamih kareem on YouTube, while the temporal framework is concerned with the episodes that are raised on YouTube from the second half of 2014 to 2015 of almosamih kareem program. The fundamental problem in determining the role of television programs in broadcasting the culture of community for peace through studying almosamig kareem program by studying the topics addressed in this

The research aims to diagnose the shortcomings and weaknesses in applying the dimensions of the quality of work life and the extent of their impact on employees’ attitudes and behaviors, and thus their relationship to enhancing their core competencies. The scientific value of the research stems from highlighting the importance of the dimensions of the quality of professional life in improving the productive efficiency of workers in the public sector and raising the level of organizational performance. Because the quality of working life plays an important role in enhancing the core competencies of employees in the public sector, it can also be an incentive or a disincentive for any employee by adapting to the economic and social condition

يهدف البحث إلى تشخيص أوجه القصور ونقاط الضعف في تطبيق أبعاد جودة الحياة الوظيفية ومدى تأثيرها على اتجاهات وسلوكيات الموظفين، وبالتالي علاقتها بتعزيز مقدراتهم الجوهرية. وتنبع القيمة العلمية للبحث من إبراز أهمية أبعاد جودة حياة العمل في تحسين الكفاءة الإنتاجية للعاملين في القطاع العام ورفع مستوى الأداء التنظيمي. ولأن جودة الحياة العملية تلعب دوراً مهماً في تعزيز المقدرات الأساسية للموظفين في القطاع الع

Abstract:

Viral marketing has become one of the modern strategies adopted by organizations in the marketing of products and services. The idea of viral marketing focuses on the social relations between individuals and groups. As a result of the technological development, most organizations have resorted to using the Internet and its applications and social media to market and promote their products. To reach the largest number of consumers to display their products and services in many ways, including text, audio, visual or video and thus affect the behavior of the consumer.

The problem of the study was the following question (do viral marketing technologies have an impact on consumer behavior?)

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings