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?)

The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

Introduction: In recent decades, the endovascular treatment of cerebral arteriovenous malformations (AVMs) has advanced. However, it still carries risks of unanticipated complications. Coil migration is a reported complication of aneurysmal coiling procedures. Herein, we report a case of early intraprocedural coil migration during pressure cooker technique embolization of right thalamic AVM, discussing the management and potential explanations. The literature showed no report of coil migration after the pressure cooker technique in the form of coil-augmented Onyx injection technique (CAIT). Case description: An otherwise healthy 26-year-old female suddenly developed a severe headache with no loss of consciousness. Computed tomograp

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima

Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia