Preferred Language
Articles
/
_hbProoBVTCNdQwCl6KA
Discretization Fractional-Order Biological Model with Optimal Harvesting
...Show More Authors

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.

Scopus Crossref
View Publication
Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Model building using the Transformation Entropy for the Burr type –xii Distribution
...Show More Authors

Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Nov 01 2026
Journal Name
Al Kut Journal Of Economics And Administrative Sciences
Use of the Bootstrap in the logistic regression model for Breast cancer disease
...Show More Authors

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

... Show More
View Publication
Publication Date
Sun Apr 16 2023
Journal Name
Iraqi Journal For Computer Science And Mathematics
Some Methods to Estimate the Parameters of Generalized Exponential Rayleigh Model by Simulation
...Show More Authors

This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

View Publication Preview PDF
Scopus (11)
Crossref (6)
Scopus Crossref
Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
...Show More Authors

 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

... Show More
View Publication Preview PDF
Publication Date
Tue Sep 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Oxidation desulfurization of model oil using carbon composite derived from peach stone waste
...Show More Authors

     In this study, oxidative desulfurization of dibenzothiophene (DBT) with H2O2 as an oxidant was studied, whereas the catalyst used was zirconium oxide supported on Activated carbon (AC). Zirconium oxide (ZrO2) was impregnated over prepared activated carbon (AC) and characterized by various techniques such as XRD, FTIR, BET, SEM, and EDX. This composite was used as a heterogeneous catalyst for oxidation desulfurization of simulated oil. The results of this study showed that ZrO2/AC composite exhibited significant catalytic activity and stability, effectively lowering sulfur content under mild conditions. Factors such as reaction temperature (30, 40, 50, 60°C), time (5, 10, 15,20,30,60, 80 100 min), catalyst dose (0.3, 0.5,

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
...Show More Authors

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

... Show More
View Publication
Scopus Crossref
Publication Date
Wed Jul 04 2018
Journal Name
Civil Engineering Journal
Finite Element Analysis of Concrete Beam under Flexural Stresses Using Meso-Scale Model
...Show More Authors

Two dimensional meso-scale concrete modeling was used in finite element analysis of plain concrete beam subjected to bending. The plane stress 4-noded quadrilateral elements were utilized to model coarse aggregate, cement mortar. The effect of aggregate fraction distribution, and pores percent of the total area – resulting from air voids entrapped in concrete during placement on the behavior of plain concrete beam in flexural was detected. Aggregate size fractions were randomly distributed across the profile area of the beam. Extended Finite Element Method (XFEM) was employed to treat the discontinuities problems result from double phases of concrete and cracking that faced during the finite element analysis of concrete beam. Crac

... Show More
Crossref (6)
Clarivate Crossref
Publication Date
Mon Jun 01 2026
Journal Name
Statistics, Optimization & Information Computing
Predicting Public Budget Surplus and Deficit Using a Hybrid 1D-CNN–LSTM Model
...Show More Authors

The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

... Show More
Crossref (1)
Scopus Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Building Engineering
Development of gravitational search algorithm model for predicting packing density of cementitious pastes
...Show More Authors

View Publication Preview PDF
Scopus (23)
Crossref (11)
Scopus Clarivate Crossref
Publication Date
Sun Nov 01 2026
Journal Name
Magazine Aldhakwat Albedh
The impact of atheism on the individual and society, Iraq as a model
...Show More Authors

Atheists have spread in the modern era, so that atheism has become a bad phenomenon in the world in general and in Islamic societies in particular, so the research aims to study the individual and social effects left by atheism on the atheists themselves, and the research included multiple axes: atheism linguistically and idiomatically, atheism in the Qur’an Noble and Modern (and Contemporary) Atheism Statistics: and the reasons for atheism: Studying the phenomenon of atheism in Iraq as a model, then studying the effects of atheism: on the individual first, then atheism and its impact on society, then the conclusion, recommendations, sources and references

View Publication Preview PDF