An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

In this research TiO2 nano-powder was prepared by a spray pyrolysis technique and then adds to the TiO2 powder with particle size (0.523 μm) in ratio (0, 5, 10, 15 at %) atomic percentage, and then deposition of the mixture on the stainless steel 316 L substrate in order to use in medical and industrial applications.
Structure properties including x-ray diffraction (XRD) and scanning electron microscope (SEM0, also some of mechanical properties and the effect of thermal annealing in different temperature have been studied. The results show that the particle size of a prepared nano-powder was 50 up to 75 nm from SEM, and the crystal structure of the powders (original and nano powder) was rutile with tetragonal cell. An improvement in

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa

The rapid changes in the field of transferring and exchanging information via cloud platforms have revolutionized the field of modern visual media, as cloud computing technology has greatly influenced the media institutions, providing effort, money and high-quality materials. The research included five chapters, the first came under the methodological framework for the research and the second Theoretical framework, the first two included the concept of cloud computing and the second platforms for cloud computing in the visual media and the third chapter Research procedures and the fourth chapter The sample analysis and the fifth chapter The research results were the most prominent
1. The cloud service made the benefit beyond the typic

he planning process is generally aimed at developing the city and making it meet the needs of different citizens. The green areas constitute one of the basic needs of the city and with the rapid and unusual growth in the size of cities, especially in the third world countries, which is often embodied in capitals. Which was achieved as a result of many reasons, including political, economic and social and even enshrined through some of the decisions that were issued and the city of Baghdad, but a clear example of these cities. The city and the environment are inseparable terms. The city is where people spend their lives and their daily experiences, and the environment is the center in w

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.