The research aims to measure the relationship and impact of the operations of the knowledge of management of the six dimensions (diagnosis knowledge, define knowledge objectives, knowledge generation, knowledge storage, distribution of knowledge, application of knowledge) in the fiscal performance of the General Authority for taxes of the four dimensions (financial, customers (taxpayers), Operations Interior, learn and grow), the research aims also to the use of computerized programs for training and career development of the Authority that helps to add knowledge workers in the Authority, and to reach an appropriate arrangement for knowledge management processes in the Authority, as well as analysis of the reality of the Authority to get

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

تتطلب كرة القدم الحديثة تطوير الصفات البدنية والمهارية للوصول باللاعب إلى لمستويات العليا، ولما كانت هذه الصفات مرتبطة مع بعضها البعض، فانها تتطلب ان يتم تطويرها معا في نفس الوقت دون تنمية كل صفة على حده، وإن توافر الحد الأدنى من الصفات البدنية كمتطلبات أساسية للأداء المهاري يعتبر الهدف الأساسي للتخطيط لأي برنامج تدريبي، وإن الصفات البدنية لها مفهوم شاسع وواسع الاستعمال في مجال البحوث الرياضية، وقد أعطيت ع

The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.