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Large-scale brain network model and multi-band electroencephalogram rhythm simulations
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Publication Date
Mon Apr 17 2023
Journal Name
Day 2 Tue, April 18, 2023
Development of a Multi-Completion Gas and Downhole Water Sink-Assisted Gravity Drainage (MC-DWS-AGD) to Improve Oil Recovery and Reduce Water Cut in Reservoirs with Strong Water Aquifers
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Abstract<p>Gas and downhole water sink assisted gravity drainage (GDWS-AGD) is a promising gas-based enhanced oil recovery (EOR) process applicable for reservoirs associated with infinite aquifers. However, it can be costly to implement because it typically involves the drilling of multiple vertical gas-injection wells. The drilling and well-completion costs can be substantially reduced by using additional completions for gas injection in the oil production wells through the annulus positioned at the top of the reservoir. Multi-completion-GDWS-AGD (MC-GDWS-AGD) can be configured to include separate completions for gas injection, oil, and water production in individual wells. This study simulates</p> ... Show More
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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Educational And Psychological Researches
The Effect of the Addie and Shayer Model on the Achievement of Fifth Grade Students and their Attitudes towards History: The Effect of the Addie and Shayer Model on the Achievement of Fifth Grade Students and their Attitudes towards History
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Abstract

The current research aims to examine the effect of the Adi and Shayer model on the achievement of fifth-grade students and their attitudes toward history. To achieve the research objective, the researcher has adopted two null hypotheses. 1) there is no statistically significant difference at the level of (0.05) between the average score of students of the experimental group who study the history of Europe and modern American history according to the model of Addie and Shayer, and the average scores of the students of the control group who study the same subjects according to the traditional method in the test of post-achievement. 2) There was no statistically significant difference at the level (

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Publication Date
Fri Sep 01 2017
Journal Name
Global Journal Of Pure And Applied Mathematics
Solution of Modified Kuznetsov Model with Mixed Therapy
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In this paper two modifications on Kuznetsov model namely on growth rate law and fractional cell kill term are given. Laplace Adomian decomposition method is used to get the solution (volume of the tumor) as a function of time .Stability analysis is applied. For lung cancer the tumor will continue in growing in spite of the treatment.

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Geological Journal
Geological Model for Mauddud Reservoir Khabaz Oil Field
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The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Mon Jun 22 2015
Journal Name
International Journal Of Industrial Management
Regression Factors of Small Businesses Performance: Conceptual Model
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This study represents an attempt to develop a model that demonstrates the relationship between HRM Practices, Governmental Support and Organizational performance of small businesses. Furthermore, this study assay to unfold the socalled “Black Box” to clarify the ambiguous relationship between HRM practices and organizational performance by considering the pathway of logical sequence influence. The model of this study consists two parts, the first part devoted to examining the causal relationships among HRM practices, employees’ outcomes, and organizational performance. The second part assesses the direct relationship between the governmental support and organizational performance. It is hypothesized that HRM practices positively influ

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Engineering Geology And Hydrogeology
Assessing Pullout Resistance of Earth Reinforced Embankment Model
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- The sandy soil with high gypsum content (usually referred to as gypseous soil) covers vast area in south, east, middle and west regions of Iraq, such soil possess a type of cohesive forces when attached with optimum amount of water, then compacted and allowed to cure, but losses its strength when flooded with water again. Much work on earth reinforcement was published which concentrate on the gain in bearing capacity in the reinforced layer using different types of cohesive or cohesion less soil and various types of reinforcement such as plastic, metal, grids, and synthetic textile. Little attention was paid to there enforce gypseous soil. The objective of this work is to study the interaction between such soil and reinforcement strips

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Publication Date
Sat May 28 2022
Journal Name
Abstract And Applied Analysis
Discretization Fractional-Order Biological Model with Optimal Harvesting
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In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined; also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.

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