Technological development intersects with terrorism to a large extent, beyond the use of the Internet and social media, in order to spread ideas, obtain support and financing, and recruit new elements, to the area of tactics and techniques of terrorist attacks, and everything related to the arsenal of terrorist weapons in the present and future, while technology offers many benefits. In various fields, and contribute to achieving multiple gains for humanity, they provide extremist and terrorist organizations and elements with a set of weapons and means through which they attempt to bypass monitoring and control efforts and the restrictions imposed on the use of weapons. They also help in planning and implementing their terrorist operations,

This paper deals with the subject of demarcating as appropriate scientific techniques to rationalize consumption and to control segments of the society for the technical conduct of its handling of the product depending on the mix of elements (product and the volume of demand, Price, promotion and distribution), but inverse manner designed to adjust the working condition of balance between supply and demand and to ensure that rates continue in the marketing process properly, and therefore the research aims to shed light on some of the practices that reflect the Demarketing techniques, As well as the statement of the reality of attitudes towards the practice of those techniques through a sample survey of officials in Baghdad company for so

The research discussed the role of interrelationships between the product attributes and the individual identity of the brand and the user, starting from reviewing the identity concepts in the general design propositions and the identity from the industrial design perspective, and highlighting the role of the attributes in identifying the individual identity of the product, which would enable the user to adopt them to be representative of his identity, starting from identifying the importance of the identity being characterized by three major elements: innovating products in the user's viewpoint, viewing the user's environment, the methodology of the design language, and identifying the identity attributes in the industrial product start

BACKGROUND: Carcinoma of urinary bladder is one of the most common malignancies worldwide and constitutes a major health problem. Multiple risk factors are associated with this tumor and its prognosis will depend on different clinicopathological parameters. Over expression of P53 protein and mutant Rb gene is associated with more aggressive clinical and histopathological features of the tumor such as advanced stage and higher grade. AIM: The immunohistochemical expression of Rb gene and P53 gene will be assessed through their protein products in transitional cell carcinoma (TCC) of the urinary bladder and then will be correlated with other well-known risk factors and prognostic parameters of bladder TCC, such as grading, tumor size, smoking

In this paper, the computational method (CM) based on the standard polynomials has been implemented to solve some nonlinear differential equations arising in engineering and applied sciences. Moreover, novel computational methods have been developed in this study by orthogonal base functions, namely Hermite, Legendre, and Bernstein polynomials. The nonlinear problem is successfully converted into a nonlinear algebraic system of equations, which are then solved by Mathematica®12. The developed computational methods (D-CMs) have been applied to solve three applications involving well-known nonlinear problems: the Darcy-Brinkman-Forchheimer equation, the Blasius equation, and the Falkner-Skan equation, and a comparison between the met

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c