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Segmentation moon images using different segmentation methods and isolate the lunar craters
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Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and geology of a Moon's surface. Therefore, it is important to study them and determine their characteristics. So, several segmentations methods were used in this study these are: K-Means, Single Feed Forward Neural Network (SFFNN), and hybrid segmentation methods. K-Means method applied with different number of clusters (k), that were used to segment Moon images and isolate lunar craters, where k=1,2,3, and 4 were used. But, all of them did not identify the boundary of craters, only K=3 gave useful results. SFFNN was also used in this work, it trained by a novel method, where weights have been replaced by masks, that create depending on the images features and targets. Thirteen lunar craters were used, ten of them utilized in training process and the last three images were used to test the performance of network. But also this method did not segment lunar images and identify the boundaries of lunar craters clearly. So, in attempt to overcome this problem, the new hybrid method was proposed, that combine the concepts of KMeans and SFFNN methods. The main advantages of the proposed hybrid method is that it does not require much data in the training process as it is known in other networks, where the K-Means cluster segmentation method gave a shortcut to correlating masks with images, which led to giving perfect results in a short time. Then, results show the proposed hybrid segmentation method was succeed to segment lunar crater and identify the craters boundaries clearly.

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Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Using Crushed Glass with Sand as a Single and Dual Filter Media for Removal of Turbidity from Drinking Water
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Publication Date
Tue Nov 15 2022
Journal Name
Journal Of Mechanical Engineering
Enhancement of Mechanical Properties and Corrosion Resistance of Cast Iron Alloy Using CO<inf>2</inf> Laser Surface Treatment
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This work aimed to study the effect of laser surface treatment on the mechanical characteristics and corrosion behaviour of grey cast iron type A159. Many technical applications used conventional surface treatment, but laser surface hardening has recently been used to enhance the surface properties of many alloys. The mechanical characteristics, including microstructure, microhardness, and wear resistance of A159 grey cast iron, were studied, in addition to corrosion behaviour. The experimental laser parameters in this work were 0.9, 1.2, and 1.5 KW power with continuous wave carbon dioxide lasers with scanning speeds of 10 and 12 mm/s were used. The results found that phase-transitional alterations in microstructure were influenced by lase

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Scopus
Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Scopus
Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
solving linear fractional programming problems (LFP) by Using denominator function restriction method and compare it with linear transformations method
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Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

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Publication Date
Fri Nov 11 2011
Journal Name
Thesis
Performance Analysis of a New Compact Magneto-Rheological Proportional Control Valve for Hydraulic Actuation Using FEM and Experimental Approach
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One of the main parts in hydraulic system is directional control valve, which is needed in order to operate hydraulic actuator. Practically, a conventional directional control valve has complex construction and moving parts, such as spool. Alternatively, a proposed Magneto-rheological (MR) directional control valve can offer a better solution without any moving parts by means of MR fluid. MR fluid consists of stable suspension of micro-sized magnetic particles dispersed in carrier medium like hydrocarbon oil. The main objectives of this present research are to design a MR directional control valve using MR fluid, to analyse its magnetic circuit using FEMM software, and to study and simulate the performance of this valve. In this research, a

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Prediction of bearing capacity, angle of internal friction, cohesion, and plasticity index using ANN (case study of Baghdad, Iraq)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Scopus
Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Measurement of radon and uranium concentration in soil samples from Babylon cement plant using nuclear track detector CR-39
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In this study, concentrations of radon and uranium were measured for twenty six samples of soil. The radon concentrations in soil samples measured by registrant alpha-emitting radon (222Rn) by using CR-39 track detector. The uranium concentrations in soil samples measured by using registrar fission fragments tracks in CR-39 track detector that caused by the bombardment of U with thermal neutrons from 241 Am-Be neutron source that has flux of 5 ×103n cm-2 s-1.
The concentrations values were calculated by a comparison with standard samples The results show that the radon concentrations are between (91.931-30.645Bq/m3).
The results show that also the uranium concentrat

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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
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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> ... Show More
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Publication Date
Sat Jun 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Histopathological and Immunohistochemical Study of Aflatoxin B1 in Freshly Slaughtered Iraqi Sheep Meat, using CD Marker of TNF-α
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The current study was conducted in Baghdad governorate (Karkh and Al-Rasafa regions) which included collecting 50 samples of freshly slaughtered sheep meat randomly collected from local slaughter areas and approved governmental slaughterhouses (25 liver and 25 ulna muscles). The results of the aflatoxin B1 detection showed that all samples were contaminated with this toxin at different concentrations ranging from 25–422 ppb and 65–492 ppb for each ulna muscles and liver, respectively. The histopathological and immunological study was conducted in meat samples containing higher and lower concentrations of the toxin. The results of the pathological study in the liver revealed that the concentration (492 ppb) caused thickening of t

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