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Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.

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Publication Date
Tue Dec 31 2024
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
Extraction and preconcentration of many metals ions by using CPE technique
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Cloud point extraction is a simple, safe, and environmentally friendly technique for preparing many different kinds of samples. In this review, we discussed the CPE method and how to apply it to our environmental sample data. We also spoke about the benefits, problems, and likely developments in CPE. This process received a great deal of attention during preconcentration and extraction. It was used as a disconnection and follow-up improvement system before the natural mixtures (nutrients, polybrominated biphenyl ethers, pesticides, polycyclic sweet-smelling hydrocarbons, polychlorinated compounds, and fragrant amines) and inorganic mixtures were examined and many metals like (silver, lead, cadmium, mercury, and so on). We also find

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Scopus (5)
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Publication Date
Tue Dec 31 2024
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
Extraction and preconcentration of many metals ions by using CPE technique
...Show More Authors

Cloud point extraction is a simple, safe, and environmentally friendly technique for preparing many different kinds of samples. In this review, we discussed the CPE method and how to apply it to our environmental sample data. We also spoke about the benefits, problems, and likely developments in CPE. This process received a great deal of attention during preconcentration and extraction. It was used as a disconnection and follow-up improvement system before the natural mixtures (nutrients, polybrominated biphenyl ethers, pesticides, polycyclic sweet-smelling hydrocarbons, polychlorinated compounds, and fragrant amines) and inorganic mixtures were examined and many metals like (silver, lead, cadmium, mercury, and so on). We also find

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Publication Date
Sun Jan 01 2017
Journal Name
Pakistan Journal Of Biotechnology
Role of bio fertilization on wheat and water productivity under water scarcity
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Field experiment was conducted by using two fertilization systems (i.e.) biofertilizers (inoculation with Pseudomonas putida and with Azotobacter chroococcum and non - inoculation) and chemical fertilization (100%, 50% and 25% of recommended by Ministry of Agriculture) to study the influence of these system and interaction on water and grain yield productivity, some growth phytohorones and number of bacterial cells in soil rizosphere of root of wheat crop under water scarcity. The result showed that the integrate fertilization (inoculation with Pseudomonas putida and Azotobacter chroococcum bacterial + 50% of the recommended chemical fertilizer) recorded 5.70 and 5.55 t ha-1, respectively with reducing the chemical fertilizer app

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Scopus (10)
Scopus
Publication Date
Fri Jul 19 2024
Journal Name
Baghdad Science Journal
An Analytical Comparison of the Behavior of Machine Learning and Deep Learning in Stock Market Prediction
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Mon Jul 01 2024
Journal Name
Iranian Journal Of Catalysis (ijc)
Preparation, characterization, and antioxidant activity of novel metal (Mn (II), Ni (II), Pd (II), Pt (IV)) complexes: Application of Pd complex in Suzuki-Miyaura cross-coupling reaction
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Publication Date
Sat Sep 02 2023
Journal Name
Al-khwarizmi Engineering Journal (alkej)
Numerical Investigations on Heat Flow of Nanofluids in Ribs Tube Configurations
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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Effect of the Mechanical and Thermal Stresses of Rotating Blades
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         Rotating blades are the important parts in gas turbines. Hence, an accurate mathematical estimation (F.E.M) of the stresses and deformations characteristics was required in the design applications to avoid failure. In recent year’s there are researchers interest in the effect of temperature on solid bodies has greatly increased, The main of this study investigated the thermal and rotational effects.  So, the thermal stresses due to high pressure and temperature are studies, also determine the steady state stresses and deformations of rotating blades due to mechanical effect. Many parameters such as thickness and centre of rotating are investigated in this paper. The

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Publication Date
Fri Jan 01 2016
Journal Name
Iosr Journal Of Applied Physics (iosr-jap)
Influence of concentration on the structural, optical and electrical properties of TiO 2 : CuO thin film Fabricate by PLD
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In this work, Titanium oxide thin films doped with different concentration of CuO (0,5,10, 15,20) %wt were prepared by pulse laser deposition(PLD) technique on glass substrates at room temperature with constant deposition parameter such as : pulse (Nd:YAG), laser with λ=1064 nm, constant energy 800 mJ , repetition rate 6 Hz and No. of pulse (500). The structure , optical and electrical properties were studied . The results of X-ray diffraction( XRD) confirmed that the film grown by this technique have good crystalline tetragonal mixed anatase and rutile phase structure, The preferred orientation was along (110) direction for Rutile phase. The optical properties of the films were studied by UV-VIS spectrum in the range of (360-1100)

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Photocatalytic removal of methylene blue dye by using of ZnS and CdS
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Photocatalytic degradation of methylene blue was studied using CdS and ZnS as catalyst. The photocatalytic activity of the specimen was studied by exposing to UV-radiation. The result shows that the degradation efficiency of the dye for CdS micro-particles was 92% after 7 hours and for ZnS micro-particles was 88.29% for the same time interval.

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