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Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and the water quality index used to assess the quality of water for drinking purposes, in addition to finding the model based on past information to predict the quality of treated wastewater produced in each WTP using an artificial neural network (ANN) approach. The selected parameters for this study were turbidity, total hardness, total solids, suspended solids, and alkalinity. The results showed that all the WTPs possessed a high rate of efficiency in the removal of turbidity from raw water. Also, the results of the water quality index for all WTPs were classified over a study period of three years from 2015 to 2017 as being a good water quality and based on these results, the water treatment plants can be considered to be doing efficient water treatment process. The ANN model has been found at all WTPs to have a coefficient of determination (R2) for expected models was more than 0.7 to provide a WQI prediction tool that can be used with a moderate level of predictive acceptance to describe the suitability of WTP water quality for drinking purposes.

Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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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.

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models
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Abstract<p>There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn</p> ... Show More
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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Effect of Magnetized Water Treatment on some Biological Aspects for Fresh Water Snail Lymnaea lagotis (Schrank,1803)
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Exposure assays to magnetized water have so far revealed striking results. The present study was conducted to determine the effects of magnetized water treatment with in different intensities 500 , 1000 and 1500 Gauss on some biological aspects for species of freshwater Gastropod Lymnaea lagotis (Schrank, 1803) which important species in faun of aquatic habitats of Iraq. This species are considered a component of the food chain. The obtained results compared with these species which lived in the river(control). Result of these experiments showed increased significance the shell size (shell high, shell aperture length, shell aperture width and shell width) for L. lagotis with increased intensity magnetized water such as treated water with 1

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
EFFECT OF IRRIGATION UNIFORMITY AND EFFICIENCY ON WATER CONSUMPTION, YIELD OF MAIZE USING DIFFERENT IRRIGATION AND CULTIVATION METHODS
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Two field experiments were carried out for cultivating yellow maize crop Zea mays L. during the autumn planting season 2019 in two sites with soils of different textures. The first site is a loamy texture in one of the fields of the Medhatia Agriculture Division, Babylon Governorate. The second was silty loam by an alluvial mixture in one of the fields of Al-Nouriah Research Station, Ministry of Agriculture located in Al-Nouriah sub-district, Al-Qadisiyah governorate. It was found through the results that the uniformity, efficiency, and adequacy of the irrigation efficiency of the sprinkler irrigation method is better than that of the sprinkler irrigation method, and it ranged between (88.6-88.7) for uniformity and (84-86)% of the irrigatio

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Water Resource And Protection
Evaluating Water Stability Indices from Water Treatment Plants in Baghdad City
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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
Hybrid Cipher System using Neural Network
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The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Electrocoagulation for Treatment of Simulated Blowdown Water Of Cooling Tower
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This study investigates the results of electrocoagulation (EC) using aluminum (Al) electrodes as anode and stainless steel (grade 316) as a cathode for removing silica, calcium, and magnesium ions from simulated cooling tower blowdown waters. The simulated water contains (50 mg/l silica, 508 mg/l calcium, and 292 mg/l magnesium). The influence of different experimental parameters, such as current density (0.5, 1, and 2 mA/cm2), initial pH(5,7, and 10), the temperature of the simulated solution(250C and 35 0C), and electrolysis time was studied. The highest removal efficiency of 80.183%, 99.21%, and 98.06% for calcium, silica, and magnesium ions, respectively, were obtained at a current de

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