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Modeling and Forecasting Periodic Time Series data with Fourier Autoregressive Model
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Most frequently used models for modeling and forecasting periodic climatic time series do not have the capability of handling periodic variability that characterizes it. In this paper, the Fourier Autoregressive model with abilities to analyze periodic variability is implemented. From the results, FAR(1), FAR(2) and FAR(2) models were chosen based on Periodic Autocorrelation function (PeACF) and Periodic Partial Autocorrelation function (PePACF). The coefficients of the tentative model were estimated using a Discrete Fourier transform estimation method. FAR(1) models were chosen as the optimal model based on the smallest values of Periodic Akaike (PAIC) and Bayesian Information criteria (PBIC). The residual of the fitted models was diagnosed to be white noise. The in-sample forecast showed a close reflection of the original rainfall series while the out-sample forecast exhibited a continuous periodic forecast from January 2019 to December 2020 with relatively small values of Periodic Root Mean Square Error (PRMSE), Periodic Mean Absolute Error (PMAE) and Periodic Mean Absolute Percentage Error (PMAPE). The comparison of FAR(1) model forecast with AR(3), ARMA(2,1), ARIMA(2,1,1) and SARIMA( 1,1,1)(1,1,1)12 model forecast indicated that FAR(1) outperformed the other models as it exhibited a continuous periodic forecast. The continuous monthly periodic rainfall forecast indicated that there will be rapid climate change in Nigeria in the coming yearly and Nigerian Government needs to put in place plans to curtail its effects.

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
The Dynamics of A Square Root Prey-Predator Model with Fear
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An ecological model consisting of prey-predator system involving the prey’s fear is proposed and studied. It is assumed that the predator species consumed the prey according to prey square root type of functional response. The existence, uniqueness and boundedness of the solution are examined. All the possible equilibrium points are determined. The stability analysis of these points is investigated along with the persistence of the system. The local bifurcation analysis is carried out. Finally, this paper is ended with a numerical simulation to understand the global dynamics of the system.

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Teen-Computer Interaction: Building a Conceptual Model with Thoughts- Emotion-Behaviour
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Teen-Computer Interaction (TeenCI) stands in an infant phase and emerging in positive path. Compared to Human-Computer Interaction (generally dedicated to adult) and Child-Computer Interaction, TeenCI gets less interest in terms of research efforts and publications. This has revealed extensive prospects for researchers to explore and contribute in the region of computer design and evaluation for teen, in specific. As a subclass of HCI and a complementary for CCI, TeenCI that tolerates teen group, should be taken significant concern in the sense of its context, nature, development, characteristics and architecture. This paper tends to discover teen’s emotion contribution as the first attempt towards building a conceptual model for TeenC

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Mon Feb 01 2016
Journal Name
International Journal Of Transportation Engineering And Traffic System, Ijtets
Comparative Modeling of Pavement Surface Texture Variables Using ANN and SPSS Software
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The health of Roadway pavement surface is considered as one of the major issues for safe driving. Pavement surface condition is usually referred to micro and macro textures which enhances the friction between the pavement surface and vehicular tires, while it provides a proper drainage for heavy rainfall water. Measurement of the surface texture is not yet standardized, and many different techniques are implemented by various road agencies around the world based on the availability of equipment’s, skilled technicians’ and funds. An attempt has been made in this investigation to model the surface macro texture measured from sand patch method (SPM), and the surface micro texture measured from out flow time (OFT) and British pendul

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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Modeling of the Effect of MgO and ZrO2 on Sintering of Alumina
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  This research  studyies the effect of MgO and ZrO2 as additives in sintering Al2O3 . The experimental results are modeled using ( L2 _ regression) technique , sintered density and grain size rate measurments were  accounted by utilizing experimental results of undoped , MgO doped and ZrO2  doped alumina impregrated with spherical large pores in final stage of sintering . The effect of each additive is inhibitian of the grain growth and increasing the densification rate which enhances the kinietics of densification and the removal of large and small pores.

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Integration between hydrochemical and physical data with geographic information systems (GIS) for selecting the best locations groundwater wells in Baghdad city
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Publication Date
Tue Sep 19 2017
Journal Name
Journal Of Neoplasm
The stage of breast cancer at the time of diagnosis: correlation with the clinicopathological findings among Iraqi patients
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Background: Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality among women in Iraq forming 23% of cancer related deaths. The low survival from the disease is a direct consequence to the advanced stages at diagnoses. Aim: To document the composite stage of breast cancer among Iraqi patients at the time of diagnosis; correlating the observed findings with other clinical and pathological parameters at presentation. Patients and Methods: A retrospective study enrolling the clinical and pathological characteristics of 603 Iraqi female patients diagnosed with breast cancer. The composite stage of breast cancer was determined according to UICC TNM Classification System of Breast Cancer and the Ameri

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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
The Influence of Anodization Time With The Electrochemical Cell Design on The Fabrication Process of Porous Silicon Nanostructures
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     The influence of anodization time with the electrochemical cell design on the fabrication process of porous silicon (PS) nanostructures based on two electrochemical anodization cells (designed single tank cell and double tank cell) with two anodization times (10 and 30 minutes) was studied. Atomic force Microscopy (AFM) characterization had revealed three types of pores, mesopores, mesopore fill of mesopores, and macropore fill of mesopores were obtained from designed single tank cell with (10 and 30 minutes) of anodization time, whilst for double tank cell has not revealed precise information about the size and type of pores. Pores formation have been further approved by current-voltage (I-V) measurement and pho

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi Parametric Logistic Regression Model with the Outputs Representing Trapezoidal Intuitionistic Fuzzy Number
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In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulati

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