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jeasiq-1893
Comparison Branch and Bound Algorithm with Penalty Function Method for solving Non-linear Bi-level programming with application
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The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Partial Least Squares and Principal Components Methods by Simulation
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Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, whe

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Science And Research (ijsr)
The Linear Delay Fourth Order Eigen-Value Problems Solved By the Collocation Method
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Publication Date
Sun Jul 01 2012
Journal Name
Baghdad University College Of Education Ibn Al-haitham
Numerical Solution of Linear System of Fredholm Integral Equations Using Haar Wavelet Method
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The aim of this paper is to present the numerical method for solving linear system of Fredholm integral equations, based on the Haar wavelet approach. Many test problems, for which the exact solution is known, are considered. Compare the results of suggested method with the results of another method (Trapezoidal method). Algorithm and program is written by Matlab vergion 7.

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Anemia and The Level of IL-6 in Children Infected with Entamoeba histolytica and Giardia lamblia
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The relation between anemia and inflammatory immune response has lately had much attention. This research was conducted from October 2018 until April 2019, including  (110) children below 12 years from both gender in some Hospitals, Primary Health care centers, Public Primary Schools and Kindergarten in Baghdad, Iraq. The objective of this study is to determine the possible correlation between iron deficiency anemia and inflammatory immune response  among children infected with Entamoeba  histolytica or Giardia  lamblia. Blood samples were taken from all groups to measure  hemoglobin level, serum iron, total iron binding capacity (TIBC), mean corpuscular volume (MCV), and mean corpuscular  hemoglobin concentration

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Fri Jul 31 2020
Journal Name
Iraqi Geological Journal
APPLICATION OF TRIANGLES METHOD FOR QUANTITATIVE ESTIMATION OF MARL RESERVE IN EUPHRATES FORMATION, MIDDLE OF IRAQ
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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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Publication Date
Wed Jun 01 2022
Journal Name
Jordan Journal Of Biological Sciences
Comparison of the Folate and Homocysteine Levels with A80G -RFC1 Gene Polymorphism between the Sample of Iraqi Children with and without Down Syndrome
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Many international studies indicated that the polymorphisms of some genes disturbed the folate homocysteine (Hcy) metabolism and increased the vulnerability to Down syndrome (DS). We aimed to measure the serum levels of folate and Hcy in DS children and compare the levels with age and sex-matched apparently normal healthy children. We also aimed to study the A80G polymorphism of the gene reduced folate carrier (RFC1) in the DS children as a risk factor. Forty children with DS (24 were boys, and 16 were girls) with the age range between 5-13 years, and 26 normal healthy children (16 boys and ten girls) were included in this study. The results show that the highest genotype in the control group was AG (53.85%) followed by AA and GG (30.

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
The history of non-fungible crypto tokens (NFTs) art In the Kingdom of Saudi Arabia
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This research is concerned with documenting and chronicling the art of NFTs art in the Saudi artistic cultural scene, the importance of which stems from the lack of scientific sources that document this field until the preparation of this research and aims to trace historically the emergence of the field of NFTs art in the Kingdom of Saudi Arabia in the arts sector through the experiences of Saudi artists. The most prominent events for the culture, arts and technology sector, and other Saudi sectors. The research dealt with the history of the emergence of the field of NFTs art, which extends from the history of digital arts, and reviewed the most famous works of NFTs art.
As a result of the technical revolution and the artistic move

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