The image of television dominates the cognitive and artistic motivations. It is the formulation of ideas and visions along with its documentary ability. It is the main element in television work as it is a story that is narrated in pictures. Therefore, attention to image building is a major point of gravity in the work structure as a whole. On the image is the element carrying all aesthetic and expressive values of news and information directly to the hints that work to stimulate and stir the imagination of the recipient to evoke mental images added to the visual images to deepen the meanings.
All visual arts carry elements and components that follow in a particular pattern to give special meanings and specific connotations. However,

The study of Shiranish Formation rocks in southern part of Iraq at Ansab area well (KH-6)
were carried out. The formation is tongued with tayarat formation, which bounded from top
and bottom, the upper tongue at thickness 49m. and tongued at depth (476-525m.) the lower
tongue at thickness 4m. tongued at (541-537m.).
The rocks of this formation were divided into three sedimentary microfacies:
1- Dolomitized formininferal Wackestone facies.
2- Dolomitized formininferal Mudstone facies.
3- Dolostone facies.
34 slides were investigated depending on mineralogical, compositional and biological
processes and compared diagenesis which reflect open marine shelf at lower part of formation
(F.Z.2) (S.M.F.8), but at the

Inhibition of T cell derived cytokine production could help suppress osteoclast differentiation in inflammatory skeletal disorders. Bisphosphonates are typically prescribed to prevent inflammatory bone loss but are not tolerated by all patients and are associated with an increased risk of osteonecrosis of the jaw. In light of this other anti-resorptives such as phytoestrogens are being considered. However the effect of phytoestrogens on T cell-induced osteoclast formation is unclear. The effect of genistein and coumestrol on activated T cell-induced osteoclastogenesis and cytokine production was therefore examined. Concentrations of genistein and coumestrol (10−7 M) previously shown to directly inhibit osteoclast formation also suppressed

In the region of the north of Iraq using the method of analyzing thin section microfacies to 38 of rockyslices which were gathered from a place near Aqra city. These slides are divided into seven microfacies depending on lithologcal component and fossils.

1) Dolostone facies.

2)Recrystallized bioclastic wackestone facies.

3) Bioclastic packstone microfacies

4)Sucrosic dolomite facies.

 5) Bioclastic grainstone in microfacies.

 According to water energy, these facies were divided to three zone:

1. a) Low energy environment.
2. b) Transitional zone.
3. c) High energy environment.

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network