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bsj-8819
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods
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Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of the study is the generated data sets obtained on the basis of theoretical stress relaxation curves. Tables of initial data for training models for all samples are presented, a statistical analysis of the characteristics of the initial data sets is carried out. The total number of numerical experiments for all samples was 346020 variations. When developing the models, CatBoost artificial intelligence methods were used, regularization methods (Weight Decay, Decoupled Weight Decay Regularization, Augmentation) were used to improve the accuracy of the model, and the Z-Score method was used to normalize the data. As a result of the study, intelligent models were developed to determine the rheological parameters of polymers included in the generalized non-linear Maxwell-Gurevich equation (initial relaxation viscosity, velocity modulus) using generated data sets for the EDT-10 epoxy binder as an example. Based on the results of testing the models, the quality of the models was assessed, graphs of forecasts for trainees and test samples, graphs of forecast errors were plotted. Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. The constructed models have passed the quality assessment according to the following metrics: MAE, MSE, RMSE, MAPE. The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. Model performance estimates obtained during testing are valid.

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Publication Date
Wed Oct 31 2018
Journal Name
Heat Transfer-asian Research
Comparative study on heat transfer enhancement of nanofluids flow in ribs tube using CFD simulation
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Publication Date
Sun Dec 04 2022
Journal Name
Jordan Journal Of Biological Sciences
The Biological Effect of ZnO Nanoparticles Produced by Using Petroselinum crispum Extract against Candida spp
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Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important rol

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Publication Date
Wed Sep 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Correlation of Penetration Rate with Drilling Parameters For an Iraqi Field Using Mud Logging Data
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This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering Science And Technology
CORROSION of STEEL REINFORCEMENT in INTERNALLY CURED SELF-COMPACTING CONCRETE USING WASTE BRICK and THERMOSTONE
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Internal curing is a method that has been advised to decrease the primary age cracking, mainly of concrete mixes using low (water to cementitious materials - w/cm) ratios corresponding to the self-compacting concrete-(SCC). This research aims to study the effect of the internal curing using saturated lightweight aggregate- (LWA) on the steel reinforcing corrosion in SCC. In this research, crushed bricks or thermostone were partially replaced by (20%) by the weight of sand and volumetrically measured. The results showed that the steel reinforcement of internally cured concrete showed a slight increase in corrosion up to 300 days of exposure to the saline solution (containing 3.5% NaCl). The ability of using the crushed bricks or thermostone

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Electrical properties of pure NiO and NiO:Au thin films prepared by using pulsed laser deposition
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The electrical properties of pure NiO and NiO:Au Films which are
deposited on glass substrate with various dopant concentrations
(1wt.%, 2wt%, 3wt.% and 4wt.%) at room temperature 450 Co
annealing temperature will be presented. The results of the hall effect
showed that all the films were p-type. The Hall mobility decreases
while both carrier concentration and conductivity increases with the
increasing of annealing temperatures and doping percentage, Thus,
indicating the behavior of semiconductor, and also the D.C
conductivity from which the activation energy decrease with the
doping concentration increase and transport mechanism of the charge
carriers can be estimated.

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Publication Date
Sun Jun 21 2020
Journal Name
Baghdad Science Journal
Spectrophotometer Determination of Cefixime in pure form and pharmaceutical preparation by Using Cloud point Extraction
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Two simple methods spectrophotometric were suggested for the determination of Cefixime (CFX) in pure form and pharmaceutical preparation. The first method is based without cloud point (CPE) on diazotization of the Cefixime drug by sodium nitrite at 5Cº followed by coupling with ortho nitro phenol in basic medium to form orange colour. The product was stabilized and measured 400 nm. Beer’s law was obeyed in the concentration range of (10-160) μg∙mL-1 Sandell’s sensitivity was 0.0888μg∙cm-1, the detection limit was 0.07896μg∙mL-1, and the limit of Quantitation was 0.085389μg∙mL-1.The second method was cloud point extraction (CPE) with using  Trtion X-114 as surfactant. Beer

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Publication Date
Sun Jul 23 2023
Journal Name
Water
Evaluation of Water Quality Index (WQI) in and around Dhaka City Using Groundwater Quality Parameters
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Groundwater quality deterioration due to anthropogenic natural activities and its immense utilization in various sectors is considered a great concern. The aim of this study is to determine the groundwater quality parameters at various sources in and around Dhaka city and compare them with Bangladesh drinking water standards. In this study, six groundwater quality parameters (pH, DO, COD, TS, TDS, and arsenic) and ten groundwater samples are analyzed to determine the water quality. The collected samples have maximum and minimum pH values of 6.9 and 6.4, respectively. Maximum and minimum DO values are 0.3 and 0.1 mg/L, respectively. The arsenic concentration is 0 mg/L for all collected groundwater samples. The maximum and minimum COD

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Advanced Pharmacy Education And Research
Co-surfactant effect of polyethylene glycol 400 on microemulsion using BCS class II model drug
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Synthesis and Evaluation of Platinum Nanoparticles Using F. Carica Fruit Extract and Their Antimicrobial Activities
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Abstract

In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G

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Publication Date
Mon Jun 01 2020
Journal Name
Colloids And Surfaces A: Physicochemical And Engineering Aspects
Removal of antibiotic tetracycline using nano-fluid emulsion liquid membrane: Breakage, extraction and stripping studies
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