In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO₂ as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H₂O₂, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest deg

 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, K_oc, of 147 L/kg which is more moveable than XXXX, and another one

The m-consecutive-k-out-of-n: F linear and circular system consists of n sequentially connected components; the components are ordered on a line or a circle; it fails if there are at least m non-overlapping runs of consecutive-k failed components. This paper proposes the reliability and failure probability functions for both linearly and circularly m-consecutive-k-out-of-n: F systems. More precisely, the failure states of the system components are separated into two collections (the working and the failure collections); where each one is defined as a collection of finite mutual disjoint classes of the system states. Illustrative example is provided.

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

  Abstract    

In this study, the effect of carboxylic methyl cellulose (CMC), and sodium dodcyl benzene sulfonate (SDBS) as an aqueous solution on the drag reduction was investigated. Different concentrations of (CMC) and (SDBS) such as (50, 100, 150, 200, 250, 300, 350, 400, 450, and 500 ppm) were used to analyze the aqueous solution properties, including surface tension, conductivity, and shear viscosity. The optimum four concentrations (i.e., 50, 100, 200, and 300 ppm) of fluid properties were utilized to find their effect on the drag reduction. Two different PVC pipe diameters (i.e., 1" and 3/4") were used in this work. The  results showed that blending CMC with SDBS gives

The aim of this research is to measure and analyze the gap between the actual reality and the requirements of the environmental management system in the middle refineries company/refinery cycle according to ISO14001: 2015, as well as to measure the availability of a clean production strategy and test the relationship and impact between the availability of the requirements of the standard and a clean production strategy for the actual reality in the company.

The research problem was determined by the extent to which the requirements of the environmental management system are applied according to ISO14001: 2015 in the middle refineries company? To what extent are the required clean production strategies ava

The current research dealt with (the deliberative dimension of the visual sign in the contemporary Iraqi poster) in an attempt to identify the importance of the contemporary poster and the role of the international dimension of the visual sign of exceptional importance.
What is the international dimension of the visual mark?
- What is the effect of the visual label on the contemporary Iraqi poster?

The current research aims to identify the pragmatic dimension in the contemporary Iraqi poster.
Across the temporal and spatial research boundaries of the year (2000-2020) in Iraq. The limits of the objective research The limits of this study on the pragmatics in the visual sign and the determination of the relationship betwee

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability