The aim of the research is to find out the availability of the requirements of applying the indicators of school performance system in the public schools in  Mahayel Asir educational directorate through the school planning indicator, the safety and security indicator, the active learning indicator, the student guidance indicator and determining the existence of statistically significant differences between the responses of the research community according to the variable of (scientific qualification - years of work as a principal - training courses). The questionnaire was used as a tool for data collection from the research community, which consists of all the public schools’ principals (n=180) Mahayel Asir educational directorate

The deficit of the federal budget and the structural imbalances suffered by the Iraqi economy has affected the direction of research towards suggesting steps and mechanisms can be relied upon in the near term to form a broader base of non-oil revenues aimed at achieving a balanced budget, and to proceed to reform the financial situation, In reducing their financial dictates, whether capital or operational, which lead to significant financial and economic consequences. This also requires that the Iraqi political elite have the real will, strategic vision and full awareness that the implementation of these reforms has potential social and economic effects, with long-term measures to be taken. The aim is not only to reform the finan

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

     The human epidermal growth factor receptor-2 (HER2) gene plays a critical role in breast cancer development and progression. HER2 overexpression characterizes a biologically and clinically aggressive breast cancer subtype. In this study, 60 samples from Iraqi women with breast cancer were collected and investigated for HER2 protein in the tissue by immunohistochemistry. Also, 20 samples from healthy Iraqi women were used as a control. The results showed that 18 (30 %) patients expressed the HER2 protein. A molecular study for single nucleotide polymorphism (SNP) was conducted on samples metastasizing to lymph nodes. DNA was extracted and polymerase chain reaction (PCR) was performed to amplify e

Background: CYP1A1 gene polymorphisms and tobacco smoking are among several risk factors for various types of cancers, but their influence on breast cancer remains controversial. We analyzed the possible association of CYP1A1 gene polymorphisms and tobacco smoking-related breast cancer in women from Iraq. Materials and methods: In this case-control study, gene polymorphism of CYP1A1 gene (CYP1A1m1, T6235C and CYP1A1m2, A4889G) of 199 histologically verified breast cancer patients' and 160 cancer-free control women's specimens were performed by using PCR-based restriction fragment length polymorphism. Results: Three genotype frequencies (TT, TC, and CC) of CYP1A1m1T/C appeared in 16.1, 29.6, and 54.3% of women with breast cancer, respectiv

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe