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A Novel Flow Priority and Continuity Control Mechanism in SDN Network
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In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate precedence level for the data traffic flow. The control and modification of the DSCP bits directly impact the priority assigned to data packets, thereby shaping the traffic flow continuity accordingly. The evaluation and performance analysis of the proposed network were conducted using the Mininet simulator and the MATLAB platform. The outcomes of the comprehensive testing demonstrate that the implementation of our novel priority management technique has successfully reduced queuing delay and minimized packet loss. As a result, the overall data traffic continuity has been significantly enhanced. The obtained results demonstrate that the traffic flow continuity, handled by the Software-Defined Networking (SDN) controller with the support of DSCP modification, has increased by approximately 65% when implementing the proposed priority management based on DSCP bits modification in the SDN network.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Novel Study of Cyproheptadine Hydrochloride Precipitate Formed by Potassium hexacyanoferrate and Sodium nitroprusside using Atomic Force Microscopy
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Atomic Force Microscope is an efficient tool to study the topography of precipitate. A study using Continuous Flow Injection via the use of Ayah 6SX1-T-2D Solar cell CFI Analyser . It was found that Cyproheptadine –HCl form precipitates of different quality using a precipitating agent's potassium hexacyanoferrate (III) and sodium nitroprusside. The formed precipitates are collected as they are formed in the usual sequence of forming the precipitate via the continuous flow .The precipitates are collected and dried under normal atmospheric pressure. The precipitates are subjected to atomic force microscope scanning to study the variation and differences of these precipitates relating them to the kind of response to both precipitates give

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Tue Sep 01 2020
Journal Name
Ain Shams Engineering Journal
Estimating server utilization rate in single server queuing models using an approximate solution of stiff fluid flow model
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Publication Date
Sat Mar 05 2022
Journal Name
Mathematical Methods In The Applied Sciences
Double‐diffusive convection on peristaltic flow of hyperbolic tangent nanofluid in non‐uniform channel with induced magnetic field
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Consequence of thermal and concentration convection on peristaltic pumping of hyperbolic tangent nanofluid in a non‐uniform channel and induced magnetic field is discussed in this article. The brief mathematical modeling, along with induced magnetic field, of hyperbolic tangent nanofluid is given. The governing equations are reduced to dimensionless form by using appropriate transformations. Exact solutions are calculated for temperature, nanoparticle volume fraction, and concentration. Numerical technique is manipulated to solve the highly non‐linear differential equations. The roll of different variables is graphically analyzed in terms of concentration, temperature, volume fraction of nanoparticles, axial induced magnetic fie

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Publication Date
Tue Aug 03 2021
Journal Name
Key Engineering Materials
Numerical Investigation of New Cooling Method for Clinker Flow in Opposite Direction with Airflow at Different Height Ratios
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Several parameters affect the properties of Portland cement and one of these parameters is the cooling rate of the clinker. If the effectiveness of the cooling method of the clinker increases, a good enhancement in the properties of Portland cement will be found. Depending on the new cooling method suggestion by Nasr et. al. [20], the counter pattern of air clinker flow was studied using (FLUENT 6.3.26). The dimensions of the cooling room in grate cooler, the constant mass flow rate of both clinker and air, different height ratios, and different clinker porosity were considered in this numerical work. The results show that the heat transfers in the first half of the cooling room (0 < X < 0.9 m) is larger than that in the secon

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Publication Date
Mon Mar 30 2026
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Ciprofloxacin adsorption via compressed wood activated carbon with ZnCl&lt;sub&gt;2&lt;/sub&gt; activating agent from simulated wastewater: Mechanism studying
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      The current study objective is to synthesize activated carbon (AC) from compressed wood using the ZnCl2 activating agent and to assess the ciprofloxacin (CIP) elimination efficiency in simulated wastewater. The produced AC was characterized using multiple techniques, including SEM, BET, FTIR, AFM, and XRD. The adsorbent demonstrates high adsorption performance, achieving 91% removal of CIP within 5 hours at an initial pollutant concentration of 100 mg/L with an AC dose of 2 g/L. Experimental data correspond to the Freundlich isotherm model (R² = 0.995) as well as the Langmuir competitive fitting (R² = 0.99), while the root mean square error (RMSE) equation best fits the Langmuir model. Moreover, the pseudo-second-order

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Publication Date
Thu Sep 01 2016
Journal Name
Archives Of Toxicology
Effect of natural uranium on the UMR-106 osteoblastic cell line: impairment of the autophagic process as an underlying mechanism of uranium toxicity
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Publication Date
Sat Jan 01 2022
Journal Name
Revista Iberoamericana De PsicologÍa Del Ejercicio Y El Deporte
THE EFFECT OF TRAINING NETWORK TRAINING IN TWO WAYS, HIGH INTERVAL TRAINING AND REPETITION TO DEVELOP SPEED ENDURANCE ADAPT HEART RATE AND ACHIEVE 5000 METERS YOUTH
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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Detection of wheat damping off and root rot disease pathogenic fungi and it bio control by pseudomonas fluorescens
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This study was conducted to determine the fungal cause and bio control of damping off and root rot of wheat plants by using pseudomonas fluorescens under greenhouse and field conditions. Results showed isolation of eight species from the soil and roots to deferent region of Baghdad government. Rhizoctonia solani (Rs) and Fusarium solani (Fs) were the predominant damping off fungus with frequency 60 and 52% respectively. Led the using of bacteria formulations such as crud suspension , pure bacteria filtration and pure living cells in culture medium inhibit all type fungi with rates ranging from 84-96% , 80- 93% and 75-88% respectively. Rs and Fs were more pathogenesis under greenhouse conditions, with incidence of 80 and 68% and disease s

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