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A Comparative Study for Estimate Fractional Parameter of ARFIMA Model
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      Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated first, and then the fractional integration parameter is estimated from it by a relation between them. As for direct methods, the fractional integration parameter is estimated directly without relying on Hurst's parameter, and most of them are semi parametric methods. In this paper, some of the most common direct methods were used to estimate the fraction modulus namely (Geweke-Porter-Hudak, Smoothed Geweke-Porter-Hudak, Local Whittle, Wavelet and weighted wavelet), using simulation method with different value of (d) and different size of time series. The comparison between the methods was done using the mean squared error (MSE). It turns out that the best methods to estimate the fractional parameter is (Local Whittle).

      The ARFIMA model was generated by a function programmed by the MATLAB statistical program

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Dynamics of Predator-prey Model under Fluctuation Rescue Effect
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This paper presents a novel idea as it investigates the rescue effect of the prey with fluctuation effect for the first time to propose a modified predator-prey model that forms a non-autonomous model. However, the approximation method is utilized to convert the non-autonomous model to an autonomous one by simplifying the mathematical analysis and following the dynamical behaviors. Some theoretical properties of the proposed autonomous model like the boundedness, stability, and Kolmogorov conditions are studied. This paper's analytical results demonstrate that the dynamic behaviors are globally stable and that the rescue effect improves the likelihood of coexistence compared to when there is no rescue impact. Furthermore, numerical simul

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Wed Dec 23 2020
Journal Name
2020 International Conference On Advanced Science And Engineering (icoase)
A Comparative Study Using LZW with Wavelet or DCT for Compressing Color Images
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As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

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Publication Date
Mon Jun 19 2017
Journal Name
Arabian Journal For Science And Engineering
A New Method to Tune a Fractional-Order PID Controller for a Twin Rotor Aerodynamic System
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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Between Shrinkage &Maximum likelihood Method For Estimation Parameters &Reliability Function With 3- Parameter Weibull Distribution By Using Simulation
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The 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .

In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.

Note:- ns : small sample ; nm=median sample

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Publication Date
Wed Apr 01 2020
Journal Name
Isa Transactions
Design of a Complex fractional Order PID controller for a First Order Plus Time Delay system
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
A study of Land Zoning in the base of Traffic Noise Pollution Levels using ArcGIS: Kirkuk City as a Case Study
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This study is an approach to assign the land area of  Kirkuk city [ a city located in the northern of Iraq, 236 kilometers north of  Baghdad  and 83 kilometers  south of  Erbil [ Climatic atlas of  Iraq, 1941-1970  ]  into different  multi zones by using Satellite image and Arc Map10.3,  zones of different traffic noise pollutions. Land zonings process like what achieved in this paper will help and of it’s of a high interest point for the future of Kirkuk city especially urban

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Extreme Values on Streeter-Phleps Model Parameter Estimators With Application Abstract
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Abstract

   The extremes effects in parameters readings which are BOD (Biological Oxygen Demands) and DO(Dissolved Oxygen) can caused error estimating of the model’s parameters which used to determine the ratio of de oxygenation and re oxygenation of the dissolved oxygen(DO),then that will caused launch big amounts of the sewage pollution  water to the rivers and it’s turn is effect in negative form on the ecosystem life and the different types of the water wealth.

   As result of what mention before this research came to employees Streeter-Phleps model parameters estimation which are (Kd,Kr) the de oxygenation and re oxygenation ratios on respect

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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Educational And Psychological Researches
Constructing a Scale for the Nine Types of Students Personality: Constructing a Scale for the Nine Types of Students Personality
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Abstract

The current research aims to construct a scale for the nine types of students’ personality according to Rob Fitzel model. To do this, (162) items were formed that present the nine types of personality with (18) items for each type. To test the validity of the scale, a sample of (584) students of Al-Mustansrya University were chosen. The data of their responses was analyzed by using factor analysis. The findings explored (9) factors as one factor for each type of personality with (12) items for each one. Then, the reliability of the scale was found by using the test-retest method and Alfa Cronbach method.

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