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

           Is one of the processes of educational guidance to help the individual to design educational plans that fit with the abilities and inclinations and goals.
And research aims the current instruction program heuristic therapeutic knowledge to deal with emotional disorders. And may the researcher instruct a program according to the theories of interested and competent guidance to education and has studied the large number of studies available in this field, as has been the program on a number of specialists in education and Psychology and took their views. And then was adopted the final version of the indicative program, consistent with the sample, which was built

Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

        Throughout this paper, three concepts are introduced namely stable semisimple modules, stable t-semisimple modules and strongly stable t-semisimple. Many features co-related with these concepts are presented. Also many connections between these concepts are given. Moreover several relationships between these classes of modules and other co-related classes and other related concepts are introduced.

IR, MIR, UV – Visible spectra have been studied for Cobalt chloride molecule (CoCl2. 6H2O) compound, In wide range spectra (40000 – 410) cm-1 specially MIR range. Assignment were achieved for the fundamental vibrational bands of (CoCl2 . 6H2O ) to symmetry stretching ?1 (?^+) Anti – symmetry stretching ?3(?^+), these bands are non-degenerate , and the bending band is ?2(?) is doubly degenerate thought they have activity in IR and Raman , which explain the weakness in symmetry of this molecule, the fundamental bands for the molecule are centered at the following wave numbers (615, 685, 795, 1115, 1340, 1375, 1616.35, 2091, 2386, 2410, 3364) cm-1 which are corresponding to wave lengths (16260, 14598, 12578, 8968, 7462, 7272, 6186,

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

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.

        In this paper, mixed spinel Co_0.4Zn_0.6Fe₂O₄ ferrite was synthesized by microwave-assisted combustion method. Photocatalytic activity of the as-synthesized sample was investigated against methylene blue dye at room temperature at different exposure times (60-360 min.) under visible light. Phase impurity and surface morphology which are investigated with XRD analysis and field emission- scanning electron microscopy, indicate that a cubic spinel unit cell structure with a crystilite size and lattice constant are 22.5048nm and 8.37Å, respectively. The saturation magnetization exhibited directly from the hysteresis loop is (70.20emu/g). Optical properties for the investigated ferrite

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr