Media is one of the main and effective factors; and it is a tool of crisis management equipment. Media is one of the most dangerous, effective and decisive weapons in modern conflicts; a tool for making events and influencing their events and trends as a means of reporting as the enormous capabilities of media which help media to move very quickly, and cross borders; and overcome obstacles, through many means of audio, reading and visual. As its ability, moreover, to influence the psychological and intellectual control of communities, and behaviors.

Intelligent media is, then, used in crises management and coverage. Crises have been existed with the presence of man on Earth. Thei

Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, and make the system faster in detecting the tamper from unauthorized users. Using the two watermarking ty

The aim of the study was to know the factors analysis of scale Bar-On & Parker, post analysis is found fourteen factors for the first degree of the scale. Also we extracted five factors from the second degree.

  The scale consists of (60) items , applied on sample of (200) students (Male &Female ) age (15-18) years randomly chosen from preparatory schools . The scale unveiled satis factors  validity and reliability. An others aims is to low the  emotional  Intelligence level and  know the difference of statistical in sex , age variable and the specialization variable .The result was no difference of statistical in sex and specialization variable , but the difference appear

From the responses of Imam Abi Zakaria al-Nawawi 676 AH on the grammarians in his commentary on Sahel Muslim

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

New complexes of Cu (ll), Ni (ll), Co (ll), and Zn (ll) wi th 2-amino-5-p-Fiouro Phenyl 1, 3, 4-Thiadiazole have been synthesized. The products were isolated, studied and characterized by physical measurements, ie,(Ff-IR), UV-Vis and the melting points were determined. The new Schiff base (L) has been used to prepare some complexes. The prepared complexes were identified and their structural geometry were suggested

The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita