Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

Seismic inversion technique is applied to 3D seismic data to predict porosity property for carbonate Yamama Formation (Early Cretaceous) in an area located in southern Iraq. A workflow is designed to guide the manual procedure of inversion process. The inversion use a Model Based Inversion technique to convert 3D seismic data into 3D acoustic impedance depending on low frequency model and well data is the first step in the inversion with statistical control for each inversion stage. Then, training the 3D acoustic impedance volume, seismic data and porosity wells data with multi attribute transforms to find the best statistical attribute that is suitable to invert the point direct measurement of porosity from well to 3D porosity distribut

The ability of A.hydrophila isolates (63 isolates) to form biofilm, was studied and the results showed that fifty six isolates (88.8%) gave positive results in Congo red agar, while 51 isolates ( 80.7%) gave positive results in Christensen method, sixty isolates( 95.2%) produced biofilm on Polystyrene microtiter plates. Results revealed that all drinking water isolates produced biofilm (18 isolates )and 42 raw water isolates produced biofilm (depending on Polystyrene microtiter plates test). The more two efficient isolates(one isolated from drinking water DW, and other isolated from raw watervRW) which produced biofilm was chosen to study the effect of different values of temperature and disinfectants on the ability of A.hydrophila to ad

This study examined the adsorption behavior of anionic dye (orange G) from aqueous solution onto the raw and activated a mixture of illite, kaolinite and chlorite clays from area of Zorbatiya (east of Iraq).The chemical treatment involved alkali and acid activation. The alkali activation obtained by treated the raw clay (RC) with 5M NaOH (ACSO) and the acid activation founded by treated it with 0.25M HCl (ACH) and 0.25M  (ACS). The thermal treatment carried out by calcination the produce activated clay at 750^oC for acid activation and 105^oC for alkali activation. Batch

The Reversed  Phase High Performance Liquid  Chromatography (RP-HPLC) has been used for the separation of  Poly aromatic hydrocarbons(PAHs) by using column Reprosil 100 C 18 which  was found to be a suitable one for this purpose. The result showed that using mobile phase of (Acetonitrile-water) Reversed Phase HPLC , flow rate  of (1.2 ml/min) , column temperature (30CËš) and wave length of (254nm), give a complete separation with a good resolution . The total separation time was less than 20 min. The result of the study showed that the vegetables of Baghdad city were   polluted by poly aromatic hydrocarbons(PAHs) in different places where samples taken because of drainage  of the heavy water ,ind

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Background: This study aimed to determine the amount of fluoride in commercially available bottled drinking water in Al-Basra city, Iraq Materials and Methods: Eleven brands of bottled drinking water were obtained from supermarkets in Al-Basra city, Iraq. Five samples of 10 ml. were taking from each one of brands and the fluoride was determined by using fluoride ion selective electrode. Results: The highest fluoride concentration was present in BADIOT brand (1.174 mg/L) while the lowest was in Barakat brand (0.038 mg/L). One way ANOVA test showed a highley significant difference among different commercially branded types. Coclusions: Bottled water available in Al-Basra city contains less concentration of fluoride ion than normal values

 The concentration of radon gas in the samples for drinking water and wells in the same place from selected homes in which wells were built in the Hay-al-Bayaa region of Baghdad was measured, by using a CR-39 nuclear track detector. It turns out that the maximum value of the concentration of radon in drinking water was 3.83 Bq/L, and the lowest was 2.30 Bq/L. As for the estimation of radon gas concentration in well water samples, the highest value was 5.6 Bq/L, while the lowest one was 3.1 Bq/L. In order to assess the committed effective dose received by the public due to the inhalation of radon gas. The highest value of the annual effective dose in drinking water was recorded in Al-Bayaa region, which is equal to 14.30 μSv/y, while th

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p