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Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique
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The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlation equal to 0.99798. The sensitivity analysis for outputs of ANN signified that the relative importance of initial pH equal to 38 % and it is the influential parameter in the treatment process, followed by initial concentration, agitation speed, biosorbent dosage, time and temperature

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Publication Date
Wed Feb 01 2023
Journal Name
Chemical Data Collections
Removal of diclofenac from aqueous solution on apricot seeds activated carbon synthesized by pyro carbonic acid microwave
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Pharmaceuticals have been widely remaining contaminants in wastewater, and diclofenac is the most common pharmaceutical pollutant. Therefore, the removal of diclofenac from aqueous solutions using activated carbon produced by pyrocarbonic acid and microwaves was investigated in this research. Apricot seed powder and pyrophosphoric acid (45 wt%) were selected as raw material and activator respectively, and microwave irradiation technique was used to prepare the activated carbon. The raw material was impregnated in pyrophosphoric acid at 80◦C with an impregnation ratio of 1: 3 (apricot seeds to phosphoric acid), the impregnation time was 4 h, whereas the power of the microwave was 700 watts with a radiation time of 20 min. A series o

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Publication Date
Mon Jun 29 2015
Journal Name
Separation Science And Technology
An acidic injection well technique for enhancement of the removal of copper from contaminated soil by electrokinetic remediation process
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Sun Mar 08 2015
Journal Name
All Days
Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
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Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin</p> ... Show More
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating concentration of toxic ions Arsenic in water by using Photonic Crystal Fiber based on Surface Plasmon Resonance (SPR)
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In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Wed Dec 15 2021
Journal Name
Journal Of Physics: Conference Series
Pretreated Fishbone as Low Cost-Adsorbent for Cationic Dye Adsorption from Aqueous Solutions: Equilibrium, Optimization, Kinetic and Thermodynamic Study
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The present study investigated the use of pretreated fish bone (PTFB) as a new surface, natural waste and low-cost adsorbent for the adsorption of Methyl green (MG, as model toxic basic dye) from aqueous solutions. The functional groups and surface morphology of the untreated fish bone (FB) and pretreated fish bone were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM) and Energy dispersive X-ray spectroscopy (EDS),respectively. The effect of operating parameters including contact time, pH, adsorbent dose, temperature, and inorganic salt was evaluated. Langmuir, Freundlich and Temkin adsorption isotherm models were studied and the results showed that the adsorption of basic dye followed Freundlich iso

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Pretreated Fishbone as Low Cost-Adsorbent for Cationic Dye Adsorption from Aqueous Solutions: Equilibrium, Optimization, Kinetic and Thermodynamic Study
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Abstract<p>The present study investigated the use of pretreated fish bone (PTFB) as a new surface, natural waste and low-cost adsorbent for the adsorption of Methyl green (MG, as model toxic basic dye) from aqueous solutions. The functional groups and surface morphology of the untreated fish bone (FB) and pretreated fish bone were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM) and Energy dispersive X-ray spectroscopy (EDS), respectively. The effect of operating parameters including contact time, pH, adsorbent dose, temperature, and inorganic salt was evaluated. Langmuir, Freundlich and Temkin adsorption isotherm models were studied and the results showe</p> ... Show More
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