The research aims to know the reverberation of the the electronica news bulletin of the ministry of higher education and scientific research  in the newspapers of: (AL-Taakhi, AL-Zaman, ALAdala,AL-Sabah and Baghdad) for period from 2^nd October 2011 to 1^st November 2011 to explain its activity and advantage for the other newspapers and to show the importance which the newspapers showed for the study of the news subject in the bulletin, as well as,to show the proportional differences in which the newspapers interested in the subjects of the published news, and to reach to the results which lead us to good conclusions for the service of decision owner and open new horizons for the researchers to expanding in the s

This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

The aim of this paper is to present a weak form of -light functions by using -open set which is -light function, and to offer new concepts of disconnected spaces and totally disconnected spaces. The relation between them have been studied. Also, a new form of -totally disconnected and inversely -totally disconnected function have been defined, some examples and facts was submitted.

In this research TiO2 nano-powder was prepared by a spray pyrolysis technique and then adds to the TiO2 powder with particle size (0.523 μm) in ratio (0, 5, 10, 15 at %) atomic percentage, and then deposition of the mixture on the stainless steel 316 L substrate in order to use in medical and industrial applications.
Structure properties including x-ray diffraction (XRD) and scanning electron microscope (SEM0, also some of mechanical properties and the effect of thermal annealing in different temperature have been studied. The results show that the particle size of a prepared nano-powder was 50 up to 75 nm from SEM, and the crystal structure of the powders (original and nano powder) was rutile with tetragonal cell. An improvement in

    Biomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS