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RETRIEVING DOCUMENT WITH COMPACT GENETIC ALGORITHM(CGA)
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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Use of DAF markers (DNA Amplification Fingerprint) to Assess Genetic Diversity of Rice (Oryza satival L.)
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This study was carried out to assess genetic diversity of ten cultivars of Rice (Oryza sativa L.). One of DNA markers based on Polymerase Chain Reaction (PCR) was used namely DAF markers (DNA Amplification Fingerprint). Six primers were tested, the results showed, that no amplification products using the primers OPD.14 and OPM.5. Two primers (OPX.8 and OPT.2) produced monomorphic band across all cultivars, while only two primers generated polymorphic bands. The number of total bands produced from one of them (OPN.7) were sixteen. Also this primer produced ten polymorphic profiles (DAF patterns) which were unique to the ten cultivars that could be distinguished. The number of total bands generated by primer OPX.1 were thirteen and this prim

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Gamipog: A deterministic genetic multi-parameter-order strategy for the generation of variabLE STRENGTH COVERING ARRAYS
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Publication Date
Sun Apr 30 2023
Journal Name
Sabrao Journal Of Breeding And Genetics
STUDY OF THE GENETIC DIVERSITY OF SOME GENOTYPES OF MAIZE UNDER TWO LEVELS OF NITROGEN FERTILIZATION
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The present study aimed to determine the genetic divergence of seven maize genotypes (Al-Maha, Sumer, Al-Fajr, Baghdad, 5018, 4 × 1 single hybrid, and 4 × 2 single hybrid) under two varied levels of nitrogen fertilization (92 and 276 kg N ha-1). The experiment occurred in 2022 in a randomized complete block design (RCBD) with a split-plot arrangement and three replications at the College of Agricultural Engineering Sciences, University of Baghdad, Iraq. The nitrogen fertilization levels served as main plots, with the maize genotypes allocated as the subplots. The results revealed that genetic variance was higher than the environmental variance for most traits, and the coefficient of phenotypic variation was close to the genetic va

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Publication Date
Sun Dec 01 2019
Journal Name
Indian Journal Of Ecology
Evaluation of maize hybrids, their inbred lines and estimation of genetic divergence based on cluster analysis
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Publication Date
Mon Jun 30 2025
Journal Name
Medical Journal Of Babylon
Assessment of Six Polymorphic Variants as Genetic Risks for Coronary Artery Disease: A Case–Control Study
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Abstract<sec> <title>Background:

Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.

Objective:

To assess six genetic polymorphisms and clinical risk factors in relation to early onset nondiabetic Iraqi Arab CAD patients compared to controls.

Materials and Methods:

This case–contro

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Statistical
Evaluating the performance of introduced varieties of maize (Zea Mays L.) and estimating some genetic parameters
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sci.
Evaluating the performance of introduced varieties of Maize (Zea mays L.) And estimating some genetic parameters
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Publication Date
Tue Mar 01 2022
Journal Name
Results In Engineering
Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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Publication Date
Tue Oct 01 2019
Journal Name
2019 International Conference On Electrical Engineering And Computer Science (icecos)
An Evolutionary Algorithm for Community Detection Using an Improved Mutation Operator
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
MR Brain Image Segmentation Using Spatial Fuzzy C- Means Clustering Algorithm
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conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

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