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Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial voids ratio. Multi-layer perceptron training by the backpropagation algorithm was used in creating the network. It was found that both models can predict shear strength parameters for gypseous soils with good reliability. Sensitivity analysis of the first model indicated that dry unit weight and plasticity index have the most significant effect on the predicted cohesion. While in the second model, the results indicated that the gypsum content and plasticity index have the most significant effect on the predicted angle of internal friction.

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Application of Box-Behnken Method Based ANN-GA to Prediction of wt.% of Doping Elements for Incoloy 800H Coated by Aluminizing-Chromizing
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In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg

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Publication Date
Wed Aug 05 2020
Journal Name
Neuroquantology
The Influence of Some Important Parameters on the Performance Efficiency of the Compound Parabolic Solar Concentrator
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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Investigation the Optimization of Machining Parameters to Surface Roughness in Free Form Surface of Composite Material
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The aim of this research is to investigation the optimization of the machining parameters (spindle speed, feed rate, depth of cut, diameter of cutter and number of flutes of cutter) of surface roughness for free-form surface of composite material (Aluminum 6061 reinforced boron carbide) by using HSS uncoated flat end mill cutters which are rare use of the free-form surface. Side milling (profile) is the method used in this study by CNC vertical milling machine. The purpose of using ANFIS to obtain the better prediction of surface roughness values and decreased of the error prediction value and get optimum machining parameters by using Taguchi method for the best surface roughness at spindle speed 4500 r.p.m, 920mm/rev feed rate, 0.6mm de

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Publication Date
Sat Jun 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Combined Effect of Some Internal Ballisting Parameters on the Pressure Behavior of Solid Propellant Rocket Motor
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sci.
Evaluating the performance of introduced varieties of Maize (Zea mays L.) And estimating some genetic parameters
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Publication Date
Mon Aug 01 2022
Journal Name
Biochemical And Cellular Archives
EVALUATION OF THE TOXICITY OF DELTAMETHRIN INSECTICIDE ON SOME HEMATOLOGICAL PARAMETERS AND OXIDATIVE STRESS ON MICE
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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
A Review of the Stereo lithography 3D Printing Process and the Effect of Parameters on Quality
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Stereo lithography (SLA) three-dimensional (3D) printing process is a type of additive manufacturing techniques that uses digital models from computer-aided design to automatically produce customized 3D objects. Around 30 years, it has been widely utilized in the manufacturing, design, engineering, industrial sectors and its applications in dentistry for manufacturing prosthodontics are very important. The stereo lithography technology is highly regarded because it can produce items with excellent precision especially when selecting the best process parameters. This review article offers a useful and scientific summary of SLA three-dimensional printing technology and its brief history. The specific type of 3D printers which is SLA type b

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Effect of Aqueous Extract of Fig (Ficus carica) Fruit on Some Hematological Parameters in Female Rabbits
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The effect of the aqueous extract of fig (Ficus carica) fruit was studied by using different concentrations of this fruit (15, 20 and 25 mg/kg of body weight) on some hematological parameters (hemoglobin concentration, packed cell volume, white blood cell count and platelets count) in female rabbits. Twenty female rabbits were randomly divided into four groups (five animals in each group). Three groups were dosed with the concentrations mentioned above, while the last was administered with distilled water and considered as control group. These animals were orally dosed by aqueous extract using a micropipette. The results showed that there was a significant (P<0.05) increase in hemoglobin concentration and packed cell volume means for all

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Publication Date
Wed Nov 08 2023
Journal Name
Aip Conf. Proc.
Correlation of Mercury With Some Biochemical Parameters in Serum of Mothers and Their New Born Children
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