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A Modified 2D-Checksum Error Detecting Method for Data Transmission in Noisy Media
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In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum method and Modified 2D-Checksum. In 2D-checksum method, summing process was done for 7×7 patterns in row direction and then in column direction to result 8×8 patterns. While in modified method, an additional parity diagonal vector was added to the pattern to be 8×9. By combining the benefits of using single parity (detecting odd number of error bits) and the benefits of checksum (reducing the effect of 4-bit errors) and combining them in 2D shape, the detection process was improved. By contaminating any sample of data with up to 33% of noise (change 0 to 1 and vice versa), the detecting process in first method was improved by approximately 50% compared to the ordinary traditional two dimensional-parity method and gives best detection results in second novel method 

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Publication Date
Sun Oct 02 2011
Journal Name
Journal Of Educational And Psychological Researches
The Effect of a consulting program for decreasing withdrawal behavior of the children with autism of kindergarten
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       unacceptable social behaviors, particularly withdrawal behavior that appears in children with autism represent a major problem hindering the process of communication with those around them and therefore the process of mergence  with them be difficult.

     The withdrawal causes a real affect deficit for children with autism limits the possibility of development of their intellectual and mental growth due to their solitude and the weakness of their focus in the acquisition of pedagogical skills and lack the necessary social skills to maintain the relations of friendship and enjoyment of them.

      withdrawal children fail to participate

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Publication Date
Sat May 01 2010
Journal Name
College Of Education Journal, Al-mustansiriyah University
Artin Characters for the Special Linear Group SL(2,p) where p is a prime number  19
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Publication Date
Wed Nov 02 2016
Journal Name
Ibn Al-haitham Jour. For Pure & Appl. Sci.
Synthesis, Spectroscopic and Adsorption Studies of Cobalt (II) Complex for a ligand β-enaminone Derived from Sulfamethoxazole
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This paper concerns is the preparation and characterization of a bidentate ligand [4-(5,5- dimethyl-3-oxocyclohex-1-enylamino)-N-(5-methylisoxazol-3-yl) benzene sulfonamide]. The ligand was prepared from fusing of sulfamethoxazole and dimedone at (140) ºC for half hour. The complex was prepared by refluxing the ligand with a bivalent cobalt ion using ethanol as a solvent. The prepared ligand and complex were identified using Spectroscopic methods. The proposed tetrahedral geometry around the metal ions studied were concluded from these measurements. Both molar ratio and continuous variation method were studied to determine metal to ligand ratio (M:L). The M to L ratio was found to be (1:1). The adsorption of cobalt complex was carried out

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Publication Date
Mon Jan 13 2020
Journal Name
Day 3 Wed, January 15, 2020
Numerical Simulation of Gas Lift Optimization Using Genetic Algorithm for a Middle East Oil Field: Feasibility Study
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<p>Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t</p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Environmental Nanotechnology, Monitoring & Management
Synthesis of nano-magnetite and magnetite/synthetic geopolymer nano-porous composite for application as a novel adsorbent
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In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between Methods of Laplace Estimators and the Robust Huber for Estimate parameters logistic regression model
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The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

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Publication Date
Sun Oct 01 2023
Journal Name
Medical Journal Of Babylon
Urokinase-type plasminogen activator receptor as a predictive marker for cardiac disease among type 2 diabetic patients
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Abstract<sec> <title>Background:

Type 2 diabetes mellitus is a progressive and chronic disease manifested by β-cell dysfunction and improved insulin resistance. Higher levels of urokinase-type plasminogen activator receptors have been found to predict morbidity and mortality among diabetic patients with cardiac disease.

Objective:

This study aims to explore the role of serum urokinase-type plasminogen activator receptor levels as a prognostic marker among type 2 diabetic Iraqi patients.

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Publication Date
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn: 1683 - 3597 , E-issn : 2521 - 3512)
Evaluating the Clinical Outcomes of Three Medication Regimens for Treating a Sample of Iraqi Persistent Asthmatic patients
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Abstract     Asthma is a complex disease defined by chronic airway inflammation and airflow limitation causing variable respiratory symptoms which include shortness of breath (SOB), wheezing, chest tightness and cough. Asthma guidelines advocate adding a second long acting bronchodilator to medium doses of inhaled corticosteroids (ICS) rather using high doses of ICS alone to control moderate to severe persistent asthma. The aim of this study was to evaluate the clinical outcomes of three medication regimens indicated for Iraqi patients suffering from persistent asthma.      This study was interventional randomized clinical study conducted on a sample of adult Iraqi asthmatic patients in Baghdad City. The study com

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