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Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and the absolute mean square error were also used to measure the accuracy of the estimation for methods used. The important result obtained in this paper is that the optimal neural network was the Backpropagation (BP) and Recurrent neural networks (RNN) to solve time series, whether linear, semilinear, or non-linear. Besides, the result proved that the inefficiency and inaccuracy (failure) of RBF in solving nonlinear time series. However, RBF shows good efficiency in the case of linear or semi-linear time series only. It overcomes the problem of local minimum. The results showed improvements in the modern methods for time series forecasting.

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Publication Date
Sat Dec 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Experimental Work to Study the Behavior of Proppant Inside the Hydraulic Fractures and the Plugging Time
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Experiments were conducted to study the behavior of the solid particles (proppant) inside the hydraulic fracture during the formation stimulation, and study the effect of the proppant concentration on the hydraulic fracturing process, which lead to bridge and screen-out conditions inside the fractures across the fracture width that restricts fracturing fluid to flow into the hydraulic fracture. The research also studies the effect of the ratio between the fracture size and the average particles diameter “proppant", on fracture bridging. In this study two ratios were considered β= 2 and 3 ,where β=Dt / Dp where: Dt= hydraulic fracture size (width) and Dp=Average particles diameter.

This work pr

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Construction Time-Cost Optimization Modeling Using Ant Colony Optimization
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In the field of construction project management, time and cost are the most important factors to be considered in planning every project, and their relationship is complex. The total cost for each project is the sum of the direct and indirect cost. Direct cost commonly represents labor, materials, equipment, etc.
Indirect cost generally represents overhead cost such as supervision, administration, consultants, and interests. Direct cost grows at an increasing rate as the project time is reduced from its original planned time. However, indirect cost continues for the life of the project and any reduction in project time means a reduction in indirect cost. Therefore, there is a trade-off between the time and cost for completing construc

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Publication Date
Wed Aug 02 2023
Journal Name
Contemporary Trends And Issues In Science Education
Using Multi-faceted Rasch Models to Understand Middle School Students’ Argumentation Around Scenarios Grounded in Socio-scientific Issues
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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Dynamic Channel Assignment Using Neural Networks
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This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

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Publication Date
Tue Sep 05 2023
Journal Name
Pakistan Heart Journal
The Effect of Dynamic Lactic Training According to the Target Time to Develop the Achievement of 800m Runners Under 20 Years Old
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MA Mahde, HAA Kadhim, HN Tarish…, Pakistan Heart Journal, 2023 - Cited by 4

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Spectral Technique for Baud Time Estimation
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A new approach for baud time (or baud rate) estimation of a random binary signal is presented. This approach utilizes the spectrum of the signal after nonlinear processing in a way that the estimation error can be reduced by simply increasing the number of the processed samples instead of increasing the sampling rate. The spectrum of the new signal is shown to give an accurate estimate about the baud time when there is no apriory information or any restricting preassumptions. The performance of the estimator for random binary square waves perturbed by white Gaussian noise and ISI is evaluated and compared with that of the conventional estimator of the zero crossing detector.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Accumulation of Heavy Metals in Agricultural Crops and Ecological Series of Crops Placement
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The accumulation of toxic elements in vegetables and melons grown in agriculture, Brassica rapa - turnip, Solanum lycopersicum - tomato, Citrullus lanatus - watermelon, Capsicum annuum - bell pepper, Daucus carota - carrots, Cucurbita pepo - pumpkin, Cucumis melo - melon, and also Prunus armeniaca - apricot from fruit trees were analyzed. The excess of maximum allowable concentrations in agricultural crops of the element As by 1.65-1.75, Cd - 1.6-2.3, Cr -1.2-2.35, Cu -1.6-3.3, Ni - 1.16-3.53, Pb - 1.54-3.08, Al - 1.36-3.5, Sb - 2.0-33, Se - 1.1-3.3 times was established. The maximum allowable concentration of mercury in vegetables and melons was equal to 0.02 mg/kg,

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Multi-variables Multi -sites Model for Forecasting Hydrological Data Series
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A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i

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Publication Date
Fri Jun 04 2021
Journal Name
Oral Surgery
Calcifying epithelial odontogenic tumour series with unique clinical and histopathological features
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Abstract<sec><title>Background and aims

Calcifying epithelial odontogenic tumour (CEOT) is a benign odontogenic neoplasm of epithelial origin that secretes an amyloid‐like protein tending towards calcification. This study aims to describe a case series from Iraq of one of the rarest odontogenic tumours.

Materials and methods

Clinical and histopathological analysis of Calcifying epithelial odontogenic tumour cases that are archived at the oral pathology laboratory of the college of dentistry (Baghdad University) from 2000 to 2019.

Results

Six cases of CEOT were regi

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Publication Date
Mon May 01 2023
Journal Name
Clinical And Experimental Dental Research
Atypical clinical features of post COVID‐19 mucormycosis: A case series
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Abstract<sec><title>Objectives

This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.

Material and Methods

This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.

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