In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, with a
good degree of accuracy reaching 97.26, 95.92 and 86.43% respectively. These ANN models could be used as a support for workers in operating the filters in water treatment plants and to improve water treatment process. With the use of ANN, water systems will get more efficient, so reducing operation cost and improving the quality of the water produced.
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreTwo different oxidative desulfurization strategies based on oxidation/adsorption or oxidation/extraction were evaluated for the desulfurization of AL-Ahdab (AHD) sour crude oil (3.9wt% sulfur content). In the oxidation process, a homogenous oxidizing agent comprising of hydrogen peroxide and formic acid was used. Activated carbons were used as sorbent/catalyst in the oxidation/adsorption process while acetonitrile was used as an extraction solvent in the oxidation/extraction process. For the oxidation/adsorption scheme, the experimental results indicated that the oxidation desulfurization efficiency was enhanced on using activated carbon as catalyst/sorbent. The effects of the operating conditions (contact time, temperat
... Show MoreAs s widely use of exchanging private information in various communication applications, the issue to secure it became top urgent. In this research, a new approach to encrypt text message based on genetic algorithm operators has been proposed. The proposed approach follows a new algorithm of generating 8 bit chromosome to encrypt plain text after selecting randomly crossover point. The resulted child code is flipped by one bit using mutation operation. Two simulations are conducted to evaluate the performance of the proposed approach including execution time of encryption/decryption and throughput computations. Simulations results prove the robustness of the proposed approach to produce better performance for all evaluation metrics with res
... Show MoreIn this paper, a method for hiding cipher text in an image file is introduced . The
proposed method is to hide the cipher text message in the frequency domain of the image.
This method contained two phases: the first is embedding phase and the second is extraction
phase. In the embedding phase the image is transformed from time domain to frequency
domain using discrete wavelet decomposition technique (Haar). The text message encrypted
using RSA algorithm; then Least Significant Bit (LSB) algorithm used to hide secret message
in high frequency. The proposed method is tested in different images and showed success in
hiding information according to the Peak Signal to Noise Ratio (PSNR) measure of the the
original ima
In this paper, An application of non-additive measures for re-evaluating the degree of importance of some student failure reasons has been discussed. We apply non-additive fuzzy integral model (Sugeno, Shilkret and Choquet) integrals for some expected factors which effect student examination performance for different students' cases.
This study investigates the effects of Al-Doura oil refinery effluent, in Baghdad city, on the water quality of the Tigris River using the Canadian Water Quality Index (CCME WQI) and Rivers Maintaining System (1967). Water samples were collected monthly from Tigris River at three stations, which are Al-Muthanna Bridge (upstream), Al-Doura Refinery (point source), and Al–Zafaraniya city (downstream) from October 2020 to April 2021. Fourteen water quality parameters were studied, namely pH (6.50-8.10), Water Temperature (WT) (5.00-27.00 °C), Electrical Conductivity (EC) (877.00-1192.00 μs/cm), Dissolved Oxygen (DO) (5.03-7.57 mg/L), Biological Oxygen demand (BOD) (0.53-2.23 mg/L), Total Dissolved S