Let  be a right module over a ring  with identity. The semisecond submodules are studied in this paper. A nonzero submodule  of   is called semisecond if    for each . More information and characterizations about this concept is provided in our work.

Let  be a module over a commutative ring  with identity. Before studying the concept of the Strongly Pseudo Nearly Semi-2-Absorbing submodule, we need to mention the ideal  and the basics that you need to study the  concept of the Strongly Pseudo Nearly Semi-2-Absorbing submodule. Also, we introduce several characteristics of the Strongly Pseudo Nearly Semi-2-Absorbing submodule in classes of multiplication modules and other types of modules. We also had no luck because the ideal  is not a Strongly Pseudo Nearly Semi-2-Absorbing ideal. Also, it is noted that  is the Strongly Pseudo Nearly Semi-2-Absorbing ideal under several conditions, which is this faithful module, projective module, Z-regular module and content module and non-si

We present the concept of maps Γ- periodi2 on Γ -near-ring S. Our main goal is to research and explore the presence and mapping traits such as h Γ –hom anti-Γ –hom, Γ –α-derivations of Γ -periodi2 on Γ- near-rings.

 Anew mathematical formula was proposed to describe the behavior of the extinction coefficient as a function of ambient temperature and wavelengths for some of infrared materials. This formula was derived depending on some experimental data of transmittance spectrum versus wavelengths for many ambient temperatures. The extensive study of the spectrum characteristics and depending on Bose-Einstein distribution led to derive an equation connecting the extinction coefficient or the absorption coefficient with the ambient temperature and wavelengths of the incident rays. The basic assumption in deriving process is the decreasing in transmittance value with the increasing temperature which is only due to the changing in extinction coeffi

     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

The concept of a 2-Absorbing submodule is considered as an essential feature in the field of module theory and has many generalizations. This articale discusses the concept of the Extend Nearly Pseudo Quasi-2-Absorbing submodules and their relationship to the 2-Absorbing submodule, Quasi-2-Absorbing submodule, Nearly-2-Absorbing submodule, Pseudo-2-Absorbing submodule, and the rest of the other concepts previously studied. The relationship between them has been studied, explaining that the opposite is not true and that under certain conditions the opposite becomes true. This article aims to study this concept and gives the most important propositions, characterizations, remarks, examples, lemmas, and observations related to it. In the en

The impact of mental training overlap on the development of some closed and open skills in five-aside football for middle school students, Ayad Ali Hussein, Haidar Abedalameer Habe

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa