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This study attempts to address the issue that present cross-modal image synthesis algorithms do not capture the spatial and structural information of human tissues effectively. As a consequence, the resulting photos include flaws including fuzzy edges and a poor signal-to-noise ratio. The authors offer a cross-sectional technique that combines residual modules with generative adversarial networks. The approach incorporates an enhanced residual initial module and attention mechanism into the generator network, reducing the number of parameters and improving the generator’s feature learning capabilities. To boost discriminant performance, the discriminator employs a multiscale discriminator. A multilevel structural similarity loss is included in the loss function to improve picture contrast preservation. On the ADNI data set, the algorithm is compared to the mainstream algorithms. The experimental findings reveal that the synthetic PET image’s MAE index has dropped while the SSIM and PSNR indexes have improved. The experimental findings suggest that the proposed model may maintain picture structural information while improving image quality in both visual and objective measures. The residue initial module and attention mechanism are employed to increase the generator’s capacity for learning, while the multiscale discriminator is utilized to improve the model’s discriminative performance. The enhanced method in this study can maintain the structure and contrast information of the picture, according to comparative experimental findings using the ADNI dataset. The produced picture is hence more aesthetically similar to the genuine print.

This paper presents an analysis solution for systems of partial differential equations using a new modification of the decomposition method to overcome the computational difficulties. Convergence of series solution was discussed with two illustrated examples, and the method showed a high-precision, being a fast approach to solve the non-linear system of PDEs with initial conditions. There is no need to convert the nonlinear terms into the linear ones due to the Adomian polynomials. The method does not require any discretization or assumption for a small parameter to be present in the problem. The steps of the suggested method are easily implemented, with high accuracy and rapid convergence to the exact solution, compared with other methods that can be used to solve systems of PDEs.

Mobile ad hoc networks (MANET) have been seen as a related advancement to Group Key Management (GKM) applications. Remembering the true objective to guarantee amass applications and disallow uncertified clients from getting to the correspondence data that cannot be anchored by a remote MANET, including IP multicast, the singular gathered data content must remain encoded by a typical shared gathering key. Key administration is required to anchor the assurance of gathering the key and to safeguard those gathering data. GKM framework is associated with the remote system condition partners with three issues: execution, security, and system versatility. This article focuses on the Unmanned Aerial Vehicle (UAV)-mobile backbone node (MBN) remote system performance. The UAV-MBN Network condition is a military system that includes a proposal to group an important administrative structure. A half-and-half gathering key administration technique, which works on each target of UAV-MBN, is included in an arrangement to start two basic remote gathering key administration difficulties: (1) operational performance and (2) multiple-enrollment development. By working with minimal small-scale key administration, this strategy can diminish the execution cost associated with the key administration along with the increment operational execution of remote GKM. Scaled-down key organization is carried out in the context of these movement units. The key administration approach also restricted the operational procedure and decreased the operation’s cost in terms of key generation, figuring, and associated correspondence. Overall, the HGKM strategy that has been introduced enhances the operational process and functions effectively in reasonable remote areas.

In this paper the mathematical model of moisture content in soil have been designed in the form of three-dimensional nonlinear PDEs. The analytical solution of model equation has been obtained by using the combine LA-transform with decomposition method. The accuracy and efficiency of suggested method is illustrated by three problems.

In this study, some electrical properties (electrical conductivity, specific resistance, molar conductivity and degree of dissociation) were measured for natural polymer SMR20 with (molecular weight 350168 gm/mol) and impurities 5% ZnO nanoparticle, the polymer that have been used in Babylon tyres Factory. The aim of this study was to test the efficiency of the polymer in electrical industry under Iraqi environment conditions specially under the high temperature degrees so that the measures were under different temperature degrees (25, 35, 45, and 55) πc.Results revealed that most electrical properties increased with increasing of concentrations of polymer solved in toluene and temperature degrees except the specific resistance property which declined under high concentrations and temperature. The nanoparticle which was used in this study significantly enhanced the electrical properties. These results could be attributed to the binding between polymer molecules itself from one side and also the binding between polymers and solvent and with nanoparticle molecules from the other sides. Because of these limited changes, the polymer would be suitable and safe to be used in the electrical industry, while the remarkable enhancement of electrical properties enable the polymer for using in super generations industry.