Finding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.

Technically, mobile P2P network system architecture can consider as a distributed architecture system (like a community), where the nodes or users can share all or some of their own software and hardware resources such as (applications store, processing time, storage, network bandwidth) with the other nodes (users) through Internet, and these resources can be accessible directly by the nodes in that system without the need of a central coordination node. The main structure of our proposed network architecture is that all the nodes are symmetric in their functions. In this work, the security issues of mobile P2P network system architecture such as (web threats, attacks and encryption) will be discussed deeply and then we prop

The aim of this paper is to construct cyclic subgroups of the projective general linear group over  from the companion matrix, and then form caps of various degrees in . Geometric properties of these caps as secant distributions and index distributions are given and determined if they are complete. Also, partitioned of  into disjoint lines is discussed.

This study was conducted for the purpose of exploring the relationship between positive thinking and academic achievement in art history. And it relates to the student’s personality, intelligence, abilities and economic and social level. The sample of the study consisted of (40) male and female students from the first stage students - Department of Art Education in the Faculty of Fine Arts / Morning Study, A positive thinking questionnaire was applied to them, and the study found that there is no positive relationship between positive thinking and academic achievement in art history.   

Although the term' tautology' predicts negative connotation, it is often employed by poets and lyric writers to communicate more implied meanings. Through the use of tautological expressions, they exchange ideas, give more possibilities to readers to detect the meaning behind the tautological words and thus suggest details not openly communicated in the poem. Ten American song lyrics and ten American poems have been selected to be the data for the study. Data analysis is conducted on the basis of three steps:(i) identifying the type of tautology used ,(ii) detecting the syntactic realization of the tautology  and (iii) finding the functions of the use of tautology in these lyrics and poems. The study concludes that song lyrics and p

Paronomasia is a recognized rhetorical device by which poets could play with words that are similar or identical in form but different in meaning. The present study aims to identify paronomasia in Arabic and English. To achieve the aim of the study, a corpus of selected verses chosen from two famous figures in Arabic and English literatures and analyzed thoroughly. The analysis of data under investigation reveals that paronomasia is a crucial aid used by poets to portrait the real world as imaginative. It further shows that the concept of paronomasia in English is not the same as in Arabic. In English, there are echoes of the Arabic jinās, i.e., there are counterpart usages of similar devices, yet English rhetoricians have not defined or c

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