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PERFORMANCE EVALUATION OF FIELD AND GENETIC FOR SOME SIXTH RADIO GENERATION MUTANTS IN TOMATO
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The study was conducted at the fields of the Department of Horticulture and Landscape Gardening, College of Agriculture, University of Baghdad " Abu Ghraib" during the growing seasons 2013-2014 to Evaluate the Vegetative growth , yield traits and genetic parameter of some tomato mutants. Results showed significantly increased of plant height in M6-2 mutant 245cm in Comparison with M6- 3 130 cm . M6-4 mutant significantly increasing of floral clusters 13 . Mutant M6-3 showed significantly increasing the average of, fruit weight 125.9g and plant yield 7.17 kg.plant-1 as comparison with M6-2 which showed decreasing of average of fruit weight and plant yield 79.40g and 4.38 kg.plant-1 respectively. Also results showed the highest Genetic variation components in plant height and average of fruit weight. The highest percentage of heritability in the broad sense plant height, floral clusters and average of fruit weight Analysis Hierarchical clustering showed that mutant was distributed in two groups the first group included mutants with M6-3 and M6-4 , while the second group included mutants M6-2 and M6-1.

Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
355nm Wavelength Generation of Nd:YAG Laser Using Olive Oil
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 This project introduces a prospective material for photonic laser applications. The material is olive oil which is classified as organic compound, having a good nonlinear optical properties candidate to be used in photonic applications. A high purity sample of olive oil has been used. The theoretical calculation to generate third harmonic wave using olive oil has been determine using MATLAB program. THG (λ=355nm) intensity has been determined at two cases of sample thicknesses 1mm and 10mm. The minimum threshold incident intensity to obtain THG intensity are equal Iω=7530 mW/cm2 at L=1mm and Iω= 6220 mW/cm2 at L=10mm. The possibility of generation of third harmonic in olive oil inside

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Performance Series Performance Metrics (*) A case study in the General Company for Cotton Industries
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The problem of the research is focused on importance limited of Iraq industrial companies in application of scientific measurements of supply chains performance,  The research sought to achieve a group of goals, the most important are , identifying the strengths and weaknesses in the reality of supply chain in General Company for Cotton Industries, The data and information required are gathered from the dependence company, records through the field observations and personal interviews, the research used some quantitative indicators to measure of supply chain performance, The research reached to many conclusions , the most outstanding among them is the existence of a strong inverse correlatio

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Synthesis, Identification and evaluation of antibacterial activity of some new substituted N-benzyl-5-Bromo Isatin
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This research includes synthesis of new heterocyclic derivatives of N-benzyl-5-bromoisatin. New 1, 2, 4-triazole, oxazoline and thiazoline derivatives of [N-benzyl-5-bromo-3-(Ethyliminoacetate)-indole-2-one] (2) have been synthesized. The preparation process started by the reaction of 5-bromoisatin with sodium hydride in dimethylformamide (DMF) at 0°C, gave suspension of sodium salt of 5-bromoisatin and subsequent reaction with benzylchloride to give N-benzyl-5-bromoisatin (1). Compound (1) reacted with ethylglycinate (Schiff base) obtained the intermediate compound (2) which reacted with different reagents in two ways. The first way, compound (2) reacted with (hydrazine hydrate, semicarbazide, phenylsemicarbazide and thiosemicarbazide)

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Publication Date
Mon Aug 01 2022
Journal Name
Biochemical And Cellular Archives
EVALUATION OF THE TOXICITY OF DELTAMETHRIN INSECTICIDE ON SOME HEMATOLOGICAL PARAMETERS AND OXIDATIVE STRESS ON MICE
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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Fri Jan 30 2026
Journal Name
Journal Of Juridical And Political Science
Criminal protection of the internal state security in light of the fourth generation wars
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The research deals with a very important topic, which is social security viewed in the context of criminal protection for state security and the challenges it faces after a decisive change in the methods of war. The research also presents a different division of the generations of wars. We limit ourselves to four of them based on the change in the strategic war objectives and not just the means of committing them. This is because these means are not suitable for describing the real changes in the patterns of wars and the goals that it seeks to achieve. The research stresses the importance of putting the concept of state security in its correct framework, which is part of social security, so that the interest of the political system and the

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Publication Date
Tue Apr 01 2025
Journal Name
Sustainable Materials And Technologies
Current developments in the use of nanotechnology to enhance the generation of sustainable bioenergy
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Publication Date
Wed Aug 04 2021
Journal Name
Membranes
Model Based Simulation and Genetic Algorithm Based Optimisation of Spiral Wound Membrane RO Process for Improved Dimethylphenol Rejection from Wastewater
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Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG

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