Copper (I) complex containing folic acid ligand was prepared and characterized on the basis of metal analyses, UV-VIS, FTIR spectroscopies and magnetic susceptibility. The density functional theory (DFT) as molecular modeling calculations was used to determine the donor atoms of folic acid ligand which appear clearly at oxygen atoms binding to hydrogen. Detection of donation sights is supported by theoretical parameters such as geometry, mulliken population, mulliken charge and HOMO-LUMO gap obtained by DFT calculations.

New complexes of Al(III) such as [Al (Ura) (Phen) (OH2) Cl ] Cl. 2H2O, [Al(Ura)2(OA)(OH2)Cl].H2O and [Al(Ura)3Cl3]H2O type, where (Ura)=Uracil, (Phen)= 1,10-Phenanthroline monohydrate and (OA)= Oxalic acid dihydrate, were prepared. The elemental microanalysis, FT.IR, electronic spectra, and magnetic susceptibility as well as the conductivity measurements are characterized. For isolated three complexes for six coordinated of Al(III) are proposed with molecular formulas that depend on the nature of (Ura), (Phen) and (OA) present. The suggested molecular structure into all complexes for aluminum ion is octahedral geometries .The antibacterial efficacy was examined from metal salt (AlCl3), ligands and metal complexes into the pathogenic bacteri

Complexes of Lanthanide ione Ln(III) =La(III) , Ce(III),Pr(III) and Nd(III) withligands of nicotinamide (na) and Benzimidazole (BIMD) have been prepared withgeneral formula [M(na)3(BIMD)3](NO3) where :M = Ln(III) = La(III) , Ce(III) , Gd(III) , Nd(III) .Na = nicotinamide = C7H6N2OBIMD = Benzimidazole = C7H6N2All compounds have been characterized by spectroscopic methods [FT-IR , UV-VIS ,AAS] , microanalysis (C.H.N) Along with conductivity measurements , solubility ,melting point , theroitical measurment by using chem office 3D prog .Model (2000) .Frome the above data the proposed moleculer structure for all complexes with its ionsis octahydral geometries

In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb

Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

In this paper, wireless network is planned; the network is predicated on the IEEE 802.16e standardization by WIMAX. The targets of this paper are coverage maximizing, service and low operational fees. WIMAX is planning through three approaches. In approach one; the WIMAX network coverage is major for extension of cell coverage, the best sites (with Band Width (BW) of 5MHz, 20MHZ per sector and four sectors per each cell). In approach two, Interference analysis in CNIR mode. In approach three of the planning, Quality of Services (QoS) is tested and evaluated. ATDI ICS software (Interference Cancellation System) using to perform styling. it shows results in planning area covered 90.49% of the Baghdad City and used 1000 mob

Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,

The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model