The concept of fully pseudo stable Banach Algebra-module (Banach A-module) which is the generalization of fully stable Banach A-module has been introduced. In this paper we study some properties of fully stable Banach A-module and another characterization of fully pseudo stable Banach A-module has been given.

Singing has significant importance being a major basis for the expressive and cultural production of the societies and a real companion that reflects their artistic career and is strongly connected to the reality of the peoples and the production of the individuals, who are geniuses of arts and culture.
Rural singing represents one of the most well-known artistic singing styles in Iraq, which truly embodied the Iraqi national identity. However, it remained confined to the countryside and did not spread due to the lack of mass media and the recording technologies at that time. It has been pure virgin singing art. The theoretical framework is divided into three axes:

• The Iraqi singing heritage in the twentieth century, a hi

has experienced a step-change since the inception of ambient mass spectrometry removed the requirement for samples to be investigated under vacuum conditions. Approaches based on surface– plasma interactions are especially promising, including PADI. Whilst the mechanisms involved in generating PADI spectra still need to be unravelled, PADI shows significant promise to become a valuable and versatile tool in the instrumental arsenal available to the surface analyst

The current research deals with spatial relations as a tool to link urban landmarks in a homogeneous composition with monumental sculptures, by identifying these landmarks and the extent of their impact on them, which constitutes an urgent need to evaluate the appropriate place and its effects on them, so that this analytical study is a critical approach adopted in artistic studies of monumental models in Arabcapitals .The current research came in four chapters, the first chapter of which dealt with the research problem, its importance and the need for it, then its objectives that were determined in revealing the spatial relations and their impact on

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med