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Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model based on the Spike Neural Network (SNN) called IoT-Traffic Classification (IoT-TCSNN) to classify IoT devices traffic. The model consists of four phases: data preprocessing, feature extraction, classier and evaluation. The proposed model performance is evaluated according to evaluation metrics: accuracy, precision, recall and F1-score and energy usage in comparison with two models: ML based Support Vector Machine IoT-TCSVM and ML based Deep Neural Network (IoT-TCDNN). The evaluations result has been shown that IoT-TCSNN consumes less energy in contrast to IoT-TCDNN and IoT-TCSVM. Also, it gives high accuracy in comparison with IoT-TCSVM.

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Publication Date
Sat Feb 25 2017
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

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Publication Date
Sun Sep 19 2021
Journal Name
Journal Of Petroleum Research And Studies
Enhancing the Rheological Properties of Water-Based Drilling Fluid by Utilizing of Environmentally-Friendly Materials
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Recently, many materials have shown that they can be used as alternatives to chemicals materials in order to be used to improve the properties of drilling fluids. Some of these materials are banana peels and corn cobs which both are considered environmentally- friendly materials. The results of the X-ray diffraction examination have proved that the main components of these materials are cellulose and hemicellulose, which contribute greatly to the increasing of the effectiveness of these two materials. Due to their distinct composition, these two materials have improved the rheological properties (plastic viscosity and yield point) and reduced the filtration of the drilling fluids to a large extent. The addition rates used for each o

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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Publication Date
Sat Apr 27 2019
Journal Name
Civil Engineering Journal
Characteristics of Traffic Accidents in Baghdad
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Road traffic accidents (RTAs) are events that suddenly, inadvertently and unexpectedly occur under unforeseen circumstances that involve at least one moving vehicle and result in one or more road users being killed or injured. Unfortunately, Iraqi governorates suffer from higher rates of traffic accident casualties compared with the rates of casualties from terrorist attacks; this situation reveals a serious and growing problem. Road traffic accidents are not easy to eradicate. However, their prevalence can be reduced to the barest minimum via periodic assessments of traffic accident characteristics and the most important aspects for road authorities to consider when designing and evaluating the performance of a road to improve traf

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Improvement of the Fault Tolerance in IoT Based Positioning Systems by Applying for Redundancy in the Controller Layer
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In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

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Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Micro-Bubble Flotation for Removing Cadmium Ions from Aqueous Solution: Artificial Neural Network Modeling and Kinetic of Flotation
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In this work, microbubble dispersed air flotation technique was applied for cadmium ions removal from wastewater aqueous solution. Experiments parameters such as pH (3, 4, 5, and 6), initial Cd(II) ions concentration (40, 80, and 120 mg/l)  contact time( 2, 5, 10 , 15, and 20min), and surfactant (10, 20and 40mg/l) were studied in order to optimize the best conditions .The experimental results indicate that microbubbles were quite effective in removing cadmium ions and the anionic surfactant SDS was found to be more efficient than cationic CTAB in flotation process. 92.3% maximum removal efficiency achieved through 15min at pH 5, SDS surfactant concentration 20mg/l, flow rate250 cm3/min and at 40mg/l Cd(II) ions initial co

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Publication Date
Sat Mar 01 2025
Journal Name
Iraqi Journal Of Physics
Design an Efficient Neural Network to Determine the Rate of Contamination in the Tigris River in Baghdad City
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This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t

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Publication Date
Wed Oct 01 2014
Journal Name
Engineering And Technology Journal
Investigating Forward kinematic Analysis of a 5-axes Robotic Manipulator using Denavit-Hartenberg Method and Artificial Neural Network
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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of Intervention Program on Nurses' Practices concerning Diet Instructions for Orthopedic Patients treated by Internal Fixation Devices
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Abstract

Objective(s): To determine the interventional program effectiveness on nurses' practices concerning diet instructions for orthopedic patients treated by internal fixation devices.

Methodology: A quantitative approach using prexperimental design is conducted to determine the effectiveness of an interventional program on nurses’ practices regarding orthopedic patients diet instruction and teaching after internal fixation implemented. The study has started from 1st of April 2022 and ended on 15th of December, 2022. The conduction of the study in Misan governorate  / Al-Zaharawy surgical hospital. A non-probability, purpo

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
The Inverse Solution Of Dexterous Robot By Using Neural Networks
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The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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