Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality

<p><span>Medium access control (MAC) protocol design plays a crucial role to increase the performance of wireless communications and networks. The channel access mechanism is provided by MAC layer to share the medium by multiple stations. Different types of wireless networks have different design requirements such as throughput, delay, power consumption, fairness, reliability, and network density, therefore, MAC protocol for these networks must satisfy their requirements. In this work, we proposed two multiplexing methods for modern wireless networks: Massive multiple-input-multiple-output (MIMO) and power domain non-orthogonal multiple access (PD-NOMA). The first research method namely Massive MIMO uses a massive numbe

Abstract:

Research Topic: Ruling on the sale of big data

Its objectives: a statement of what it is, importance, source and governance.

The methodology of the curriculum is inductive, comparative and critical

One of the most important results: it is not permissible to attack it and it is a valuable money, and it is permissible to sell big data as long as it does not contain data to users who are not satisfied with selling it

 Recommendation: Follow-up of studies dealing with the provisions of the issue

Subject Terms

Judgment, Sale, Data, Mega, Sayings, Jurists

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.

  In this paper, the concept of normalized duality mapping has introduced in real convex modular spaces. Then, some of its properties have shown which allow dealing with results related to the concept of uniformly smooth convex real modular spaces. For multivalued mappings defined on these spaces, the convergence of a two-step type iterative sequence to a fixed point is proved