This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula

In this paper, a comparison between horizontal and vertical OFET of Poly (3-Hexylthiophene) (P3HT) as an active semiconductor layer (p-type) was studied by using two different gate insulators (ZrO2 and PVA). The electrical performance output (Id-Vd) and transfer (Id-Vg) characteristics were investigated using the gradual-channel approximation model. The device shows a typical output curve of a field-effect transistor (FET). The analysis of electrical characterization was performed in order to investigate the source-drain voltage (Vd) dependent current and the effects of gate dielectric on the electrical performance of the OFET. This work also considered the effects of the capacitance semiconductor on the performance OFETs. The value

This study was performd on 50 serum specimens of patients with type 2 diabetes, in addition, 50 normal specimens were investigated as control group. The activity rate of LAP in patients (560.46 10.504) I.U/L and activity rate of LAP in healthy(10.58 4.39)I.U/L.The results of the study reveal that Leucine aminopeptidase (LAP) activity of type 2 diabetes patient s serum shows a high signifiacant increase (p < 0.001) compare to healthy subjects. Addition preparation leucine amide as substrate of LAP, identification melting point and spectra by FTIR. K

The present work utilizes polyacrylic acid beads (PAA) to remove Alizarin yellow R (AYR)] and Alizarin Red S (ARS) from its solution. The isotherms of adsorption were investigated and the factors that impact them, such as temperature, ionic strength effect, shaking effect, and wet PAA. The isotherms of adsorption of (ARS) were found obeys the Freundlich equation. The isotherms of adsorption of (AYR) were found obeys the Langmuir equation. At various temperatures, the adsorption process on (PAA) was investigated. According to our data, there is a positive correlation between the (ARS and AYR) adsorption on the PAA and temperature (Endothermic process). The computation of the thermodynamic functions (ΔH, ΔG, and ΔS) is based on the foregoi

Adsorption techniques are widely used to remove certain classes of pollutants from wastewater. Phenolic compounds represent one of the problematic groups. Na-Y zeolite has been synthesized from locally available Iraqi kaolin clay. Characterization of the prepared zeolite was made by XRD and surface area measurement using N2 adsorption. Both synthetic Na-Y zeolite and kaolin clay have been tested for adsorption of 4-Nitro-phenol in batch mode experiments. Maximum removal efficiencies of 90% and 80% were obtained using the prepared zeolite and kaolin clay, respectively. Kinetics and equilibrium adsorption isotherms were investigated. Investigations showed that both Langmuir and Freundlich isotherms fit the experimental data quite well. On the

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

     This research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and

In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficiency of cadmium b