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 controller, to manage the clustering in the sensing area of the spike ISDN-IoT. Hence, an intelligent queuing model is introduced to manage the flow table buffer capacity of the spike ISDN-IoT network, such that the quality of service (QoS) of the whole network is improved. A modified training algorithm is introduced to train the PRSNN to adjust its weight and threshold. The simulation results demonstrate that the QoS is improved by (14.36%) when using the proposed model as compared with a convolutional neural network.
While hepatitis viruses A–E are established, emerging evidence points to additional, novel viral hepatitis agents. The torqueteno virus (TTV) has garnered interest due to its prevalence among patients with hepatitis, suggesting potential hepatotropism.
This study was conducted to detect TTV antigens in individuals infected with chronic hepatitis B (HBV) and/or C (HCV) using molecular diagnostics and to explore any associations between TTV presence and demographic characteristics of the cohort.
New sports technologies have highlighted the importance of perceptual – cognitive training in order to optimize performance in sports e.g., dynamic team sport such as basketball. Augmented motor reality AMR is a new training model based on realistic movement combined with interactive virtual cues that may be useful to enhance spatial orientation and decision making. The purpose of this study was to investigate the effects of an AMR-based training program on spatial awareness and skill-based decision making in youth basketball players. Twenty-four male young basketball players aged 15.2±0.8 years were randomized to the experimental group n=12, receiving AMR training, and control group n=12, performing conventional practice. The interventi
... Show Moreew sports technologies have highlighted the importance of perceptual – cognitive training in order to optimize performance in sports e.g., dynamic team sport such as basketball. Augmented motor reality AMR is a new training model based on realistic movement combined with interactive virtual cues that may be useful to enhance spatial orientation and decision making. The purpose of this study was to investigate the effects of an AMR-based training program on spatial awareness and skill-based decision making in youth basketball players. Twenty-four male young basketball players aged 15.2±0.8 years were randomized to the experimental group n=12, receiving AMR training, and control group n=12, performing conventional practice. The interventio
... Show MoreThe aim of this research is to clarify the importance of total quality management. Total quality management considered as a cultural process covering the various aspects of activities in society that helps human well-being, as well as the development of its efficiency and ability. They also have an effective role in achieving the desired goals that will benefit humanity. The concept of total quality management in the Qur'an is a broad, comprehensive and well integrated concept that aims to improve human life economically and socially. Quality in the Qur'an is a mean to achieve human beings happiness.
In this research we will highlight a successful story of quality management from Qur'an that ensures consumer protection and support of
The present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.
The research aims to identify the role of organizational identity in improving work teams, and to suggest ways to deal with the outputs of work teams in a way that achieves the goals of the Baghdad Traffic Directorate as it is the subject of the application of the research, while the research community was represented by its officers, while the research sample was embodied in (General Director, Associate The Director General, the directors of Rusafa and Karkh traffic and their assistants, as well as the heads of the divisions and the officials of the departments) in it. The sample was (200) observations. The descriptive exploratory approach was devoted to conducting the research, relying on the questionnaire in data collection, as well as e
... Show MoreSpeech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra
Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio
... Show More