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Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different metrics have been adopted to evaluate the proposed classifier's effectiveness: accuracy, precision, recall, Matthews Correlation Coefficient (MCC), and F1-Score. Compared with a convolutional neural network (CNN), the simulation results confirmed that the DSNN model could enhance traffic classification accuracy by 5%. The efficiency of the priority model also has been demonstrated in terms of Round Trip Time (RTT).

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Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Emergency Medicine, Trauma And Acute Care
Diagnostic ability of salivary TNF-α and RANKL to differentiate periodontitis from periodontal health (case-control study)
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Background

Periodontitis is a chronic inflammation affecting the tooth-supporting periodontal tissues. It is diagnosed by measuring periodontal parameters. However, documenting this data takes effort and may not discover early periodontitis. Biomarkers may help diagnose and assess periodontitis. This study aimed to evaluate the potential diagnostic of the salivary tumor necrosis factor-α (TNF-α) and receptor-activator of nuclear factor ĸ-B-ligand (RANKL) in distinguishing between periodontitis and healthy periodontium.

Methods

The

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Business And Technopreneurship
Assessment of Entrepreneurship Education on the Relationship Between Attitude, Subjective Norms, Perceived Behavioural Control and Entrepreneurial Intention
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Entrepreneurial events are understood to be imperious in accelerating the economic development of nations owing to a large number of jobs it creates. Thus, both developed and developing countries understand the importance of entrepreneurship education to instil student interest in entrepreneurial action. This study investigates the moderating effect of entrepreneurship education (EEP) on the relationship between attitude (ATT), subjective norms (SNMS), and perceived behavioural control (PBC) towards entrepreneurship intention (EINT) of university undergraduate students. The study population covered 794 students from all the four faculties of Northwest University Kano, that were taught a compulsory entrepreneurship education course in their

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Evaluate the Effectiveness of Agaricus bisporus (Spawn) on Control Damping – off Caused by Pythium aphanidermatum on Cucumber
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This study was conducted to test the effectiveness of Agaricus bisporus inoculums (spawn) in the ratio of (0.25, 0.5 and 1%) v/v to control Pythium aphanidermatum fungus the causal agent of damping- off disease of cucumber plant. results showed the ability of A. bisporus fungus to protect the seedlings from incidence by P. aphanidermatum . all treatments of edible fungus inoculums were significantly different from pathogen treatment after 15 day of planting and there was no significant difference found from control treatment (without pathogen) . the successful of A. bisporus was continued to protect the seedlings after 30 and 45 day after planting. The numbers of seedlings were (8, 7.25 & 7.25) respectively compared to 5.5 seedlings in con

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Publication Date
Mon Jun 01 2026
Journal Name
Wasit Journal Of Engineering Sciences
Engineering Perspectives on Rehabilitation Robotics: An Integrative Review of Control Strategies, Optimization Methods, and IoT-Enabled Platforms
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Rehabilitation robotics has developed into an interdisciplinary field which uses mechanical design and control theory and optimization techniques together with information technologies to create better recovery results for people who suffer from motor disabilities. The present review assesses rehabilitation robotics research through engineering application studies which use more than 120 peer-reviewed articles published between 2014 and 2024. The discussion covers four main areas which include control strategies that start from basic PID methods and extend to sophisticated adaptive and intelligent control systems. The study utilizes bio-inspired and metaheuristic optimization methods to enhance system functionality and develop control paths

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Tue Jul 01 2014
Journal Name
Ieee Transactions On Circuits And Systems I: Regular Papers
Crosstalk-Aware Multiple Error Detection Scheme Based on Two-Dimensional Parities for Energy Efficient Network on Chip
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Achieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Applying the WaterGEMS Software to Conduct a Comparison of the Darcy-Weisbach and Hazen-Williams Equations for Calculating the Frictional Head Loss in a Selected Pipe Network
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Darcy-Weisbach (D-W) is a typical resistance equation in pressured flow; however, some academics and engineers prefer Hazen-Williams (H-W) for assessing water distribution networks. The main difference is that the (D-W) friction factor changes with the Reynolds number, while the (H-W) coefficient is a constant value for a certain material. This study uses WaterGEMS CONNECT Edition update 1 to find an empirical relation between the (H-W) and (H-W) equations for two 400 mm and 500 mm pipe systems. The hydraulic model was done, and two scenarios were applied by changing the (H-W) coefficient to show the difference in results of head loss. The results showed a strong relationship between both equations with correlation coefficients of 0.999,

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Publication Date
Thu Mar 19 2026
Journal Name
Journal Of Petroleum Research And Studies
Improving the Reliability of Well Log Data Recorded in Oil and Gas Wells through Quality Control Approaches: A Case Study from a Southern Iraqi Field
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Quality control of well logs has always been an important objective in reservoir studies because of the key role played by well logs as input data. This study aims to make a quality control on well logs data for two wells of Yamama formation in southern Iraqi field to ensuring and enhancing the measurement accuracy. In the beginning, the calibration data of before and after surveys are applied as initial evaluation for the quality of density log in well R-1. Then, depth matching is used to fit the depth of all logs in each well. After that, the comparison between the main and repeat sections is helped to check the repeatability. Finally, all uncorrected logs are environmentally corrected to remove the effects of the borehole conditi

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