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Development Binary Search Algorithm
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There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case complexity of Search) is O(log2 n) (pronounce this "big-Oh-n" or "the order of magnitude"), if we search in a list consists of (N) elements. In this research the number of comparison is reduced to triple by using Triple structure, this process makes the maximum number of comparisons is O(log2 (n)/3+1) if we search key in list consist of (N) elements.

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Positron Interactions with Some Human Body Organs Using Monte Carlo Probability Method
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In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Adsorption of Congo Red Dye from Aqueous Solution onto Natural and Modified Bauxite Clays
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The adsorption behavior of congo red dye from its aqueous solutions was investigated onto natural and modified bauxite clays. Both bauxite and modified bauxite are primarily characterized by using, FTIR, SEM, AFM, and XRD. Several variables are studied as a function of adsorption including contact time, adsorbent weight, pH, ionic strength, particle size and temperature under batch adsorption technique. The absorbance of the solution before and after adsorption was measured spectrophotometrically. The equilibrium data fit with Langmuir model of adsorption and the linear regression coefficient R2 is found to be 0.9832 and 0.9630 for natural and modified bauxite respectively at 37.5°C which elucidate the best fitting isotherm model. The gene

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Cox proportion hazard model for patients with hepatitis disease in Iraq
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Cox regression model have been used to estimate proportion hazard model for patients with hepatitis disease recorded in Gastrointestinal and Hepatic diseases Hospital in Iraq for (2002 -2005). Data consists of (age, gender, survival time terminal stat). A Kaplan-Meier method has been applied to estimate survival function and hazerd function.

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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
On Controllability of Impulsive Fractional Integro-differential Nonlocal System with State
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      This paper is concerned with the controllability of a nonlinear impulsive fractional integro-differential nonlocal control system with state-dependent delay in a Banach space. At first, we introduce a mild solution for the control system by using fractional calculus and probability density function. Under sufficient conditions, the results are obtained by means of semigroup theory and the Krasnoselskii fixed point theorem. Finally, an example is given to illustrate the main results.

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between robust methods in canonical correlation by using empirical influence function
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       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Strong Differential Sandwich Results for Analytic Functions Associated with Wanas Differential Operator
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    In this article, we introduce and study two new families of analytic functions by using strong differential subordinations and superordinations associated with Wanas differential operator/. We also give and establish some important properties of these families.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Evaluation the Effects of Three Types of Pomegranate Fruit Extracts on Some Biochemical Markers and Cytogenetic Parameters in Mice Administrated With Iron Dextran to Iron Overload
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This study designed to evaluate the deleterious effects of iron overloaded on organs weights , enzyme activity of liver and bilirubin, iron concentration, total iron binding capacity in serum and on bone marrow cells proliferation in mice.
The obtained results showed non significant differences in organ weights (spleen and kidney) in group 1 that treated with three parts extracts of pomegranate except the decreasing in spleen weight subgroup 1-4 , significant increasing in liver and kidney weight in all animals treated with iron dextran (group 2) in comparison with their weights of organs in negative control (group 1). While significant increasing in iron concentrations in serum of animal administrated peel and juice in comparison wit

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
Momentum Ranking Function of Z-Numbers and its Application to Game Theory
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After Zadeh introduced the concept of z-number scientists in various fields have shown keen interest in applying this concept in various applications. In applications of z-numbers, to compare two z-numbers, a ranking procedure is essential.  While a few ranking functions have been already proposed in the literature there is a need to evolve some more good ranking functions.  In this paper, a novel ranking function for z-numbers is proposed- "the Momentum Ranking Function"(MRF). Also, game theoretic problems where the payoff matrix elements are z-numbers are considered and the application of the momentum ranking function in such problems is demonstrated.

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Image Compression Using Deep Learning: Methods and Techniques
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     In recent years images have been used widely by online social networks providers or numerous organizations such as governments, police departments, colleges, universities, and private companies. It held in vast databases. Thus, efficient storage of such images is advantageous and its compression is an appealing application. Image compression generally represents the significant image information compactly with a smaller size of bytes while insignificant image information (redundancy) already been removed for this reason image compression has an important role in data transfer and storage especially due to the data explosion that is increasing significantly. It is a challenging task since there are highly complex unknown correlat

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