Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p>
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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
Burst Header Packet Flooding Attack
K-Means Algorithm
Machine Learning
Optical Burst Switching Network
Semi-supervised Learning.
Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
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Publication Date
Fri Jun 08 2018
Journal Name
Advances In Intelligent Systems And Computing
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Publication Date
Sun Oct 13 2019
Journal Name
Spe Kuwait Oil & Gas Show And Conference
Optimization of Fracture Parameters for Hydraulic Fractured Horizontal Well in a Heterogeneous Tight Reservoir: An Equivalent Homogeneous Modelling Approach
Abstract<p>Building numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation pr</p>
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upstream oil & gas
equivalent homogeneous model
heterogeneous model
optimum number
hydraulic fracturing
simulation model
tight gas reservoir
saturation
model 1
optimization
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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
Artificial Neural Network
Iraqi Sport Sector
Predicating
Man
Pole Vault
The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t
... Show MorePublication Date
Mon Jul 22 2019
Journal Name
Journal Of Petroleum Exploration And Production Technology
Flow units and rock type for reservoir characterization in carbonate reservoir: case study, south of Iraq
Abstract<p>The current work is focused on the rock typing and flow unit classification for reservoir characterization in carbonate reservoir, a Yamama Reservoir in south of Iraq (Ratawi Field) has been selected, and the study is depending on the logs and cores data from five wells which penetrate Yamama formation. Yamama Reservoir was divided into twenty flow units and rock types, depending on the Microfacies and Electrofacies Character, the well logs pattern, Porosity–Water saturation relationship, flow zone indicator (FZI) method, capillary pressure analysis, and Porosity–Permeability relationship (R35) and cluster analysis method. Four rock types and groups have been identified in the Yamama formation de</p>
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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific
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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Using Spatial Analysis Methods to Evaluate the Soil Contamination of Baghdad City, Iraq
Abstract<p>The current study aims to identify soil pollutants from heavy metals The study utilized 40 topsoil (5 cm) samples, which adapted and divided into seven regions lies in Baghdad governorate, included (Al-Husainya,(Hs) Al-Doura (Do), Sharie Al-Matar (SM), Al-Waziria (Wz), Nharawan (Nh), Abu Ghraib (Abu) and Al-Mahmoodyia (Mh)). Spatial distribution maps of Nickel (Ni), Manganese (Mn), Lead (Pb) and Zinc (Zn) were created for Baghdad city using Geographic Information Systems (GIS). The concentrations of four heavy metals in the soil of different area of Baghdad were measured and observed using XRF instrument. The result found highest values of Pb and Zn at the middle of the Baghdad in (Wz</p>
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