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Modeling Social Networks using Data Mining Approaches-Review
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     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this article. Afterward a watchful evaluation of these papers, it has beeniscovered that numerous data extraction approaches were utilized with social media data to report a number of various research goals in several fields of industrial and service. Though, implementations of data mining are still raw and require more work via industry and academic world to prepare the work sufficiently. Bring this analysis to a close. Data mining is the most important rule for uncovering hidden data in large datasets, especially in social network analysis, and it demonstrates the most important social media technology.

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solving Optimal Control Linear Systems by Using New Third kind Chebyshev Wavelets Operational Matrix of Derivative
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In this paper, a new third kind Chebyshev wavelets operational matrix of derivative is presented, then the operational matrix of derivative is applied for solving optimal control problems using, third kind Chebyshev wavelets expansions. The proposed method consists of reducing the linear system of optimal control problem into a system of algebraic equations, by expanding the state variables, as a series in terms of third kind Chebyshev wavelets with unknown coefficients. Example to illustrate the effectiveness of the method has been presented.

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
GEOMETRY OPTIMIZATION OF COUPLING ALLIN -METFORMIN USING DFT/B3LYP MOLECULAR MODELLING TECHNIQUE: GEOMETRY OPTIMIZATION OF COUPLING ALLIN -METFORMIN USING DFT/B3LYP MOLECULAR MODELLING TECHNIQUE
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This researchpaper includes the incorporation of Alliin at various energy levels and angles 

With Metformin using Gaussian 09 and Gaussian view 06. Two computers were used in this work. Samples were generated to draw, integrate, simulate and measure the value of the potential energy surface by means of which the lowest energy value was (-1227.408au). The best correlation compound was achieved between Alliin and Metformin through the low energy values where the best place for metformin to b

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Publication Date
Mon Mar 20 2023
Journal Name
Sustainability
The Economic Impacts of Using Renewable Energy Technologies for Irrigation Water Pumping and Nanoparticle Fertilizers on Agri-Food Production in Iraq
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While traditional energy sources such as oil, coal, and natural gas drive economic growth, they also seriously affect people’s health and the environment. Renewable energies (RE) are presently seen as an efficient choice for attaining long-term sustainability in development. They provide an adequate response to climate change and supply sufficient electricity. The current situation in Iraq results from a decades-long scarcity of reliable electricity, which has impacted various industries, including agriculture. There are diverse prospects for using renewable energy sources to address the present power crisis. The economic and environmental impacts of renewable energy systems were investigated in this study by using the solar pumpi

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Nonlinear Ritz Approximation for the Camassa-Holm Equation by Using the Modify Lyapunov-Schmidt method
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          In this work, the modified Lyapunov-Schmidt reduction is used to find a nonlinear Ritz approximation of Fredholm functional defined by the nonhomogeneous Camassa-Holm equation and Benjamin-Bona-Mahony. We introduced the modified Lyapunov-Schmidt reduction for nonhomogeneous problems when the dimension of the null space is equal to two.  The nonlinear Ritz approximation for the nonhomogeneous Camassa-Holm equation has been found as a function of codimension twenty-four.

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Publication Date
Mon May 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving System of Linear Fredholm Integral Equations of Second Kind Using Open Newton-Cotes Formulas
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In this paper, the linear system of Fredholm integral equations is solving using Open Newton-Cotes formula, which we use five different types of Open Newton-Cotes formula to solve this system.  Compare the results of suggested method with the results of another method (closed Newton-Cotes formula)    Finally, at the end of each method, algorithms and programs developed and written in MATLAB (version 7.0) and we give some numerical examples, illustrate suggested method

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
Analysis of Morphological Features of Sargalu Region in Sulaymaniyah Governorate, North of Iraq, by using Geographic Information System
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It is an ideal area of research to examine related indicators to anticipate relative tectonic activities, where there is a broad range of geological formations with elements of different sedimentary rocks. This study includes assessing and evaluating the relative tectonic activities within the Sargalu area by using a morphometric approach, which involved the use of different indices that can explain and help understanding the geometry, development level, lithology, and structural disturbance on a sub-basinal level. The research was accomplished by using ArcGIS 10.5 hydrology tools to design the drainage system of each studied stream. The Advanced Spaceborne Thermal Emission Radiometer (ASTER) satellite imagery data and the Digital Elevat

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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Reliability of the multipeg™ transducer in measuring dental implant stability by using a resonance frequency analysis device (Osstell®): An observational clinical study
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Background: Measuring implant stability is an important issue in predicting treatment success. Dental implant stability is usually measured through resonance frequency analysis (RFA). Osstell® RFA devices can be used with transducers (Smartpeg™) that correspond to the implants used as well as with transducers designed for application with Penguin® RFA devices (Multipeg™). Aims: This study aims to assess the reliability of a MultiPeg™ transducer with an Osstell® device in measuring dental implant stability. Materials and Methods: Sixteen healthy participants who required dental implant treatment were enrolled in this study. Implant stability was measured by using an Osstell® device with two transducers, namely, Smartpeg™ and M

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Assessing of Some Toxic Heavy Metals Levels and Using Geo Accumulation Index in Sediment of Shatt Al-Arab and the Iraqi Marine Region
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Mercury, arsenic, cadmium and lead, were measured in sediment samples of river and marine environmental of Basra governorate in southern of Iraq. Sixteen sites of sediment were selected and distributed along Shatt Al-Arab River and the Iraqi marine environment. The samples were distributed among one station on Euphrates River before its confluence with Tigris River and Shatt Al-Arab formation, seven stations along Shatt Al-Arab River and eight stations were selected from the Iraqi marine region. All samples were collected from surface sediment in low tide time. ICP technique was used for the determination of mercury and arsenic for all samples, while cadmium and lead were measured for the same samples by using Atomic Absorption Spectrosc

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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