There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network simulates to estimate the concentration of heavy metals. The third aim is to develop a conceptual theory of training stage of neural networks from the perspective of functional analysis and optimization methods. Within this formulation, learning means to solve a variational problem by minimizing a performance function associated to the neural network. The choice of the objective functional depends on the particular application. On the other side, we suggest modification of the performance function to improve the generalization of the suggested networks and to treat the early stopping and local minima problems. The fourth aim is to compare the performance of aforementioned algorithms with regard to predicting ability. Then applied the suggested technique to estimate the concentration of heavy metals such as: Copper(Cu), Lead(Pb), Cadmium(Cd), Cobalt(Co), Zinc(Zn) and Nickel(Ni) in Baghdad soils. First, sixty four soil samples were selected from a phytoremediated contaminated site located in some zones in Baghdad city (residential, industrial, commercial, agricultural and main roads). Second, a series of measurements were performed on the soil samples and analyzed measuring of concentrations for heavy metals using devices such as : Atomic Absorption Spectrophotometer (AAS), X-Ray Fluorescence (XRF) and Inductively Coupled Plasma-Mass Spectrometry (ICP- MS) to get initial concentrations for those heavy metals. Third, simulate and train the suggested networks to get the concentration of heavy metals. The performance of the suggested networks was compared with the traditional laboratory inspecting using the training and test data sets. The results of this book show that the suggested networks trained on experimental measurements can be successfully applied to the rapid and accuracy estimation of concentration of heavy metals. Finally, we suggest some methods for the treatment of contaminated soil by using some herbal plants
A novel analytical method is developed for the determination of azithromycin. The method utilizes continuous flow injection analysis to enhance the chemiluminescence system of luminol, H2O2, and Cr(III). The method demonstrated a linear dynamic range of 0.001–100 mmol L-1 with a high correlation coefficient (r) of 0.9978, and 0.001–150 mmol L-1 with a correlation coefficient (r) of 0.9769 for the chemiluminescence emission versus azithromycin concentration. The limit of detection (L.O.D.) of the method was found to be 18.725 ng.50 µL−1 based on the stepwise dilution method for the lowest concentration within the linear dynamic range of the calibration graph. The relative standard deviation (R.S.D. %) for n = 6 was less than 1.2%
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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This paper presents a comparison between the electroencephalogram (EEG) channels during scoliosis correction surgeries. Surgeons use many hand tools and electronic devices that directly affect the EEG channels. These noises do not affect the EEG channels uniformly. This research provides a complete system to find the least affected channel by the noise. The presented system consists of five stages: filtering, wavelet decomposing (Level 4), processing the signal bands using four different criteria (mean, energy, entropy and standard deviation), finding the useful channel according to the criteria’s value and, finally, generating a combinational signal from Channels 1 and 2. Experimentally, two channels of EEG data were recorded fro
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In this study; the genus of Sinoxylon Duftschmid, 1825 (Coleoptera, Bostrichidae) was revised. There were 3 species registered in our investigations: S. anale Lesne, 1897; S. ceratoniae (Linnaeus, 1758) and S. muricatum (Olivier, 1790), the last species was redescribed as being found for the first time for the Iraqi faunal insects. Key to the species were constructed and supported by figures of the main diagnostic characters and some morphological features.
The present work deals with five species of parasitic Hymenoptera belonging to Pteromalidae, Eupelmidae and Eurytornidae which have been reared from brachid beetles. A new species, Eurytoma irakensis is described and the species, Bruchocida orientalis Crawford is recorded for the first time from Iraq.
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Plastic soil exhibits unfavorited geotechnical properties (when saturation), which causes negative defects to engineering structures. Different attempts (included various materials) were conducted to proffer solutions to such defects by experimenting in practical ways. On one hand, these attempts aimed to improve the engineering characteristics of plastic soil, and on the other hand, to use problematic waste materials as a stabilizer, like cement kiln dust, and to reduce environmental hazards. This paper explored the shrinkage, plasticity, and strength behavior of plastic soil enhanced with cement dust. The cement dust contents were 0%, 5%, 10%, 15% and 20% by dry weight of soil. An experimental series of shrinkage and p
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The construction of embankment for roadway interchange system at urban area is restricted due to the large geometry requirements, since the value of land required for such construction is high, and the area available is limited as compared to rural area. One of the optimum solutions to such problem is the earth reinforcement technique which requires a limited area for embankment construction. Gypseous soil from Al-Anbar governorate area was obtained and subjected to various physical and chemical analysis to determine it is properties. A laboratory model box of 50x50x25 cm was used as a representative embankment; soil has been compacted in five layers at maximum dry density (modified compaction) and an aluminum reinforcement strips were i
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