Preferred Language
Articles
/
vhhKMJQBVTCNdQwCegPy
A Novel Flow Priority and Continuity Control Mechanism in SDN Network
...Show More Authors

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.

Scopus Crossref
View Publication
Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
...Show More Authors

Scopus (1)
Scopus
Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Transmitter Zigbee System based on Wireless Sensor Network of IEEE 802.15.4 Standard
...Show More Authors

Abstract

 

Zigbee is considered to be one of the wireless sensor networks (WSNs) designed for short-range communications applications. It follows IEEE 802.15.4 specifications that aim to design networks with lowest cost and power consuming in addition to the minimum possible data rate. In this paper, a transmitter Zigbee system is designed based on PHY layer specifications of this standard. The modulation technique applied in this design is the offset quadrature phase shift keying (OQPSK) with half sine pulse-shaping for achieving a minimum possible amount of phase transitions. In addition, the applied spreading technique is direct sequence spread spectrum (DSSS) technique, which has

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Performance assessment of biological treatment of sequencing batch reactor using artificial neural network technique.
...Show More Authors

Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

... Show More
Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
...Show More Authors

View Publication Preview PDF
Scopus (12)
Crossref (12)
Scopus Crossref
Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
...Show More Authors

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
...Show More Authors

View Publication
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Nurses' Practices toward the Control of Patients’ Complications at the Respiratory Care Unit in Baghdad Teaching Hospitals
...Show More Authors

Objective(s): To evaluate nurses' practices who work in respiratory intensive care units to control the
complications of patients admitted at this unit and determine the relationship between nurses' sociodemographic
characteristics and their practices.
Methodology: A descriptive study was carried out at Respiratory Care Unit at Baghdad teaching hospitals that
started from February 22th, 2013 to August 30th, 2013. A purposive "non-probability" sample of (70) nurses who
work in Respiratory Care Unit was selected from Baghdad teaching hospitals. The data were collected through the
use of constructed questionnaire that consists of two parts; (l) Demographic data form that consists of 7items and
(2) nurses' practice form

... Show More
View Publication Preview PDF
Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
The diagnostic value of Paraoxonase (PON 1) enzyme activity in the diagnosis of knee joint osteoarthritis: case control study
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
Comparative Study in Attitudes towards the Covid-19 Vaccine According to Locus of Control (Internal - External) of University Students
...Show More Authors

Abstract

The current research aims to identify the attitudes towards the Covid-19 vaccine and the Locus of Control (internal, external) among university students, to identify the significance of the difference in attitudes towards the Covid-19 vaccine, the significance of the difference in the Locus of Control (internal, external) according to the gender variable (male, female), and to identify the significance of the difference in students’ attitudes towards Covid-19 vaccine according to the Locus of Control (internal, external). To achieve the objective of the research, the researcher developed two scales, a scale of (20) items to identify the attitudes toward a covid-19 vaccine, and a scale of the locus of c

... Show More
View Publication Preview PDF
Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
...Show More Authors

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

... Show More
View Publication Preview PDF
Scopus (3)
Crossref (1)
Scopus Crossref