Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

Recently, the increasing demand to transfer data through the Internet has pushed the Internet infrastructure to the nal edge of the ability of these networks. This high demand causes a deciency of rapid response to emergencies and disasters to control or reduce the devastating effects of these disasters. As one of the main cornerstones to address the data trafc forwarding issue, the Internet networks need to impose the highest priority on the special networks: Security, Health, and Emergency (SHE) data trafc. These networks work in closed and private domains to serve a group of users for specic tasks. Our novel proposed network ow priority management based on ML and SDN fullls high control to give the required ow priority to SHE dat

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

This study attempts to focus on there lation ship between employment policies andsocietal changesinIraq.Theconstruction ofoperational policyincommunitiesin crisis remains fraught with challenges and risks, especially in countries that have longoutstanding conflict sand crises, it is important in this context to achieve those policy and build the foundations of human security and poverty alleviation, unemployment, to find effective ways to help the community to achieve stability and reduce the risk of renew edorrepeat the cycleofviolence-butthatwouldrequirearadicalrethinking, including rethinking the way evaluating therisksandchallengesand management.And thatsuchaprojectshouldbe based ona clear roadmap, andthevisionsofdevelopmentanda clea

           In this paper, the homotopy perturbation method (HPM) is presented for treating a linear system of second-kind mixed Volterra-Fredholm integral equations. The method is based on constructing the series whose summation is the solution of the considered system. Convergence of constructed series is discussed and its proof is given; also, the error estimation is obtained. Algorithm is suggested and applied on several examples and the results are computed by using MATLAB (R2015a). To show the accuracy of the results and the effectiveness of the method, the approximate solutions of some examples are compared with the exact solution by computing the absolute errors.

The study aims to review the literature on the fundamental changes in Managerial Accounting (MA) in light of accelerating Digital Transformations (DT) and increasing Sustainability Requirements (SR) from 2020 to August 2025, with the purpose of informing researchers and professionals about recent developments. The study relied on a qualitative analysis of the content of a group of studies indexed in the Scopus database. The study included a literature review of topics such as artificial intelligence tools and techniques, cloud computing, linear programming, sustainability reporting, and strategic managerial accounting practices. The study results revealed that accelerated DT improves the efficiency of managerial accounting practices

In light of accelerating environmental degradation, the transition to a green economy is an imperative for achieving sustainable development. This study provides a critical analysis of the international legal and institutional framework governing this transition, revealing a significant gap between normative developments and the institutional framework on one hand, and their practical implementation on the other. The transition faces legal obstacles, including reliance on non-binding voluntary commitments and conflicts between environmental obligations and global trade and investment rules. It also reveals a significant financing gap, as financial flows to developing countries continue to lag behind commitments, in add