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Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Optimization and Modeling the Performance of a Mediator-less Microbial Fuel Cell using Butler-Volmer-Monod Model
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In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m3

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Publication Date
Thu Jun 01 2017
Journal Name
American Journal Of Pharmaceutical Education
Exploring Electronic Communication Modes Between Iraqi Faculty and Students of Pharmacy Schools Using the Technology Acceptance Model
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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
The Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projects
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Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Some Lean Production Tools in selecting a Mass Customization Strategy
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   The research aims to indicate the relationship between lean production tools included seven {constant improvement , and Just in time (JIT), and the production smoothing , and quality at the source, and standardized work, Visual management, and activities 5S }  and  Mass Customization strategy for the model (Pine & Gilomer, 1997) {collaborative, adaptive, cosmetic, transparent}, as well as providing a conceptual framework and applied for variables search to clarify how they will choose a Mass Customization strategy through the lean production tools, , and recognize the reality of the practices of Iraqi industries in such a field. Moreover, aims to highlight the positive aspects that accrue to companies a

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Wed Jan 11 2023
Journal Name
Mathematical Problems In Engineering
Bayesian Methods for Estimation the Parameters of Finite Mixture of Inverse Rayleigh Distribution
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Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Limits between the Cosmological Parameters from Strong Lensing Observations for Generalized Isothermal Models
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This paper including a gravitational lens time delays study for a general family of lensing potentials, the popular singular isothermal elliptical potential (SIEP), and singular isothermal elliptical density distribution (SIED) but allows general angular structure. At first section there is an introduction for the selected observations from the gravitationally lensed systems. Then section two shows that the time delays for singular isothermal elliptical potential (SIEP) and singular isothermal elliptical density distributions (SIED) have a remarkably simple and elegant form, and that the result for Hubble constant estimations actually holds for a general family of potentials by combining the analytic results with data for the time dela

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Publication Date
Wed Aug 10 2022
Journal Name
Mathematics
Modeling and Analysis of the Influence of Fear on the Harvested Modified Leslie–Gower Model Involving Nonlinear Prey Refuge
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Understanding the effects of fear, quadratic fixed effort harvesting, and predator-dependent refuge are essential topics in ecology. Accordingly, a modified Leslie–Gower prey–predator model incorporating these biological factors is mathematically modeled using the Beddington–DeAngelis type of functional response to describe the predation processes. The model’s qualitative features are investigated, including local equilibria stability, permanence, and global stability. Bifurcation analysis is carried out on the temporal model to identify local bifurcations such as transcritical, saddle-node, and Hopf bifurcation. A comprehensive numerical inquiry is carried out using MATLAB to verify the obtained theoretical findings and und

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Wed May 18 2016
Journal Name
Al-academy
The reality of religious tourism publications design and ways of developing The upper threshold model: صادق هاشم حسن الموسوي
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Tourism is one of the most important sources of income of economic key countries in the world so are imports of tourism for some countries a source of income is not significant of the total revenues of States. Making those countries, and those countries a destination for visitors, and here should be interest in the Wealth and cultural heritage that distinguishes Islamic countries in general, and Iraq in particular, must be placed specialist studies in all areas for the development of this area of tourism, especially religious tourism to achieve a desired and desired of such research.It is the most important ways to develop tourism in general and religious tourism is of particular publications, advertising, and is important for us in this

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