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Bioremediation of Soil Contaminated with 2,4-D Herbicide Using Bioslurry Reactor
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Ex-situ bioremediation of 2,4-D herbicide-contaminated soil was studied using a slurry bioreactor operate at aerobic conditions. The performance of the slurry bioreactor was tested for three types of soil (sand, sandy loam and clay) contaminated with different concentration of 2,4-D, 200,300and500mg/kg soil. Sewage sludge was used as an inexpensive source of microorganisms which is available in large quantities in wastewater treatment plants. The results show that all biodegradation experiments demonstrated a significant decreases in 2,4-D concentration in the tested soils. The degradation efficiency in the slurry bioreactor decreases as the initial concentration of 2,4-D in the soils increases.A 100 % removal was achieved at initial concentration of 200mg 2,4-D/kg of sandy soil after 12 days and 92 % at 500mg 2,4-D/kg sandy soil after 14 days.Clay soil represented minimum removal efficiency among the three soils, 82 % at initial concentration of 200mg 2,4-D/kg clay soil after 12 days and 72 % for 500mg 2,4-D/kg clay soil after
14 days. Abiotic conditions were performed to investigate the desorption efficiency of the contaminant from soil to liquid phase through the three soils. In abiotic reactor the results showed that the rate of desorption for sand and sandy loam soils were nearly the same, it varied between0.102-0.135 day-1 at different initial concentration of 2,4-D. While for clay soil the desorption rate varied between 0.042- 0.031 day-1 at different initial concentration of 2,4-D. The decrease in desorption rate in clay soil refers to the characteristic of clay soil, (fine texture, high organic matter and high cation exchange capacity compared with the other soils) that may retain the 2,4-D in the organic matter and the clay minerals.

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Publication Date
Sat Sep 01 2018
Journal Name
Al-nahrain Journal For Engineering Sciences
Performance Analysis of FSO under Turbulent Channel Using OSTBC
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Free Space Optics (FSO) plays a vital role in modern wireless communications due to its advantages over fiber optics and RF techniques where a transmission of huge bandwidth and access to remote places become possible. The specific aim of this research is to analyze the Bit-Error Rate (BER) for FSO communication system when the signal is sent the over medium of turbulence channel, where the fading channel is described by the Gamma-Gamma model. The signal quality is improved by using Optical Space-Time Block- Code (OSTBC) and then the BER will be reduced. Optical 2×2 Alamouti scheme required 14 dB bit energy to noise ratio (Eb/N0) at 10-5 bit error rate (BER) which gives 3.5 dB gain as compared to no diversity scheme. Th

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Reducing settlement of soft clay using different grouting materials
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Abstract<p>Different injection material types were tried in the injection of soft clay, such as lime (L), silica fume (SF), and leycobond-h (LH). In this study, experiments were made to study the effect of injection on soft clay consolidation settlement. A sample of natural soft clayey soil was investigated in the laboratory and the sample was injected with each of the grout materials used, L, SF, L + SF, and L + SF + LH. A 20 cm<sup>3</sup> of each slurry grout was conducted into the soil, which was compacted in California Bearing Ratio (CBR) mold and cured for 7 days, and then the sample was loaded to 80 N load by a circular steel footing 60 mm in diameter. The settlement was r</p> ... Show More
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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Shadow Removal Using Segmentation Method
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Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
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Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
strong criminal capabilities، Using simulation .
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The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Sustainable ENERGY by using AI
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As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Baghdad College Of Dentistry
A Comparative Evaluation of Apical Seal Associated with Ultrasonic Retrograde Cavities Filled with Bioactive Material ( in Vitro Study )
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Background: The aim of this study was to evaluate and compare the apical microleakage around retrograde cavities prepared with ultrasonic technique and filled with (Biodentineâ„¢) Materials and methods: 40 extracted single rooted human permanent maxillary teeth with mature apices were selected. The roots were prepared chemo-mechanically using k-files with crown-down technique and then obturated with lateral condensation gutta-percha technique. Teeth were divided into four main groups according to the cavity preparation method either manual or ultrasonic technique: Group A (n=10): A class I retrograde cavity at root end was prepared with traditional handpeice equipped and placement of Biodentine with manual condensation. Group B (n=10):

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