The preparation and characterization of innovative nanocomposites based on zinc oxide nanorods (ZNR) encapsulated by graphene (Gr) nanosheets and decorated with silver (Ag), and cupper (Cu) nanoparticles (NP) were studied. The prepared nanocomposites (ZNR@Gr/Cu-Ag) were examined by different techniques including Field Emission Scanning Electron Microscope (FESEM), Transmission electron microscopy (TEM), Atomic force microscopy (AFM), UV-Vis spectrophotometer and fluorescence spectroscopy. The results showed that the ZNR has been good cover by five layers of graphene and decorated with Ag and Cu NPs with particles size of about 10-15 nm. The ZNR@Gr/Cu-Ag nanocomposites exhibit high absorption behavior in ultraviolet (UV) region of sp

The removal of heavy metal ions from wastewater by ion exchange resins ( zeolite and purolite C105), was investigated. The adsorption process, which is pH dependent, shows maximum removal of metal ions at pH 6 and 7 for zeolite and purolite C105 for initial metal ion
concentrations of 50-250 mg/l, with resin dose of 0.25-3 g. The maximum ion exchange capacity was found to be 9.74, 9.23 and 9.71 mg/g for Cu2+, Pb2+, and Ni2+ on zeolite respectively, while on purolite C105 the maximum ion exchange capacity was found to be 9.64 ,8.73 and 9.39 for Cu2+, Pb2+, and Ni2+ respectively. The maximum removal was 97-98% for Cu2+ and Ni2+ and 92- 93% for Pb2+ on zeolite, while it was 93-94% for Cu2+, 96-97% for Ni2+, and 87-88% for Pb2+ on puroli

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

This research include design and implementation of an Iraqi cities database using spatial data structure for storing data in two or more dimension called k-d tree .The proposed system should allow records to be inserted, deleted and searched by name or coordinate. All the programming of the proposed system written using Delphi ver. 7 and performed on personal computer (Intel core i3).

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,