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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
Tue Jan 01 2019
Journal Name
Journal Of Pharmaceutical Sciences & Research
Evaluation of Oxidative Stress and Some Vitamins as Antioxidants in Type2 Diabetic and Nephropathic Patients.
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Background: The present study involved the following parts, the first part is evaluation of the levels of glycated hemoglobin(HbA1c), creatinine, uric acid(UA) and albumin in patients with diabetic nephropathy comparison with the group of healthy as a control group. The second part is the measurement and evaluation of oxidative stress represented in the malondihydehyde(MDA) as a biomarker of oxidative stress as well as the identification of vitamins C and E as an antioxidant in patients with diabetic nephropathy(DN) compared with the healthy group. Objective: The objective of this study is to estimate oxidative stress by calculate malondialdehyd as biomarker and evaluate some vitamins such as vit C and vit E as antioxidants in diabetic neph

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Publication Date
Tue Jun 01 2021
Journal Name
Electric Power Systems Research
Electromagnetic transient modeling of form-wound stator coils with stress grading system under PWM excitation
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The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the

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Publication Date
Sun Sep 27 2020
Journal Name
Iraqi Geological Journal
ROCK JOINTS ANALYSIS TO DETERMINE THE MAIN STRESS FIELD IN BUSTANAH STRUCTURE NORTHEAST OF IRAQ
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Joints are among the most widespread geologic structures as they are found in most each exposure of rock. They differ greatly in appearance, dimensions, and arrangement, besides they occur in quite different tectonic environments. This study is important because joints provide evidence on what kind of stress produced them (history of deformation) and also because they change the characteristics of the rocks in which they occur. The Measured data of joints from the studied area which are located in the high folded zone – Northeast of Iraq, were classified according to their relationship with the tectonic axes by projecting them stereographically using Schmidt net in GEOrient ver.9.5.0 software. The joint systems revealed the orientation of

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Publication Date
Wed Aug 26 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECT OF GAMMA RADIATION AND ETHYL METHANESULFONATE (EMS) ON POTATO SALT STRESS TOLERANCE IN VITRO
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An experiment was conducted in the Date Palm Research Units labs / College of Agricultural Engineering Sciences / University of Baghdad to assess the tolerance toward salinity stress in potato after two mutagens treatments in vitro. Potato cv. Arizona and Rivera nodal segments were irradiated with four dosages of gamma rays at 0, 10, 20, and 30 Gray and immersed in (EMS) with four concentrations included 0, 10, 20, and 30 mM. The survival rates after mutagenesis treatments were calculated and 449 lines were obtained. The lines were tested for salinity tolerance by growing in MS medium supplemented with four concentrations of NaCl at 0, 100, 150, and 200 mM and data were analyzed according to the CRD with 10 replicates and means were

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Publication Date
Fri Sep 29 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effect of Cranberry Extract against Cisplatin-Induced Nephrotoxicity by Improving Oxidative Stress in Mice
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   Cranberry (Vaccinium macrocarpon) is a North American natural fruit. consumed as food and used for health promotion and prevention of various diseases. Aim. The present study was designed to evaluate the protective effect of cranberry fruit extract on nephrotoxicity induced by cisplatin in mice by measuring selected oxidative stress markers. Methods. Twenty-eight male albino mice were used in this study. The animals were divided into 4 groups as follows: Group I [Negative Control]/orally-administered normal saline for 7 successive days; Group II [Orally-administered cranberry fruit extract alone (200 mg/kg) for 7 successive days; Group III/Mice IP injection with cisplatin (12mg/kg) on day 7 and; Group IV [Orally-administered cr

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Effect of Insecticide “Maxxthor” on Some Hematological and Oxidative Stress Parameters in Male Albino Rats
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The present study was designed to investigate the effect of different concentrations of Maxxthor on some hematological and oxidative stress parameters in male albino rats.Twenty male rats with age of 6-8 weeks and weight of 200-250gm were equally divided into four groups as follow:G1 treated with normal saline as control group,while G2,G3andG4groups were treated with(0.01,0.1,1)mg\kg body weight of Maxxthor respectively for 40 days.The following hematological parameters were measured: red blood cell(RBC),hemoglobin (Hb),white blood cell(WBC), platelets(PLT),malondialdehyde(MDA),glutathione(GSH),catalase and vitamin E. The hematological parameters results revealed highly significant(p<0.01)decreasein RBC and H,while a highly significant(p<0.

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Publication Date
Sat Jun 21 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Salivary Oxidative Stress Markers in Relation to Vascular Disease Risk of Type Two Diabetes Mellitus
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Background: Cardiovascular disease (CVD) is an important complication of type 2 diabetes mellitus (T2DM). Oxidative stress plays a major role in the development of CVD. Saliva has a diagnostic properties aiding in the detection of systemic diseases. This study aimed to assess the association between salivary oxidative stress markers and the risk of vascular disease (VD) in T2DM patients. Materials and Methods: One hundred T2DM patients and fifty apparently healthy males were enrolled in this study. Saliva sample was collected for assessment of oxidative stress markers including: lipid peroxidation plasma thiobarbituric acid-reactive substances (TBARS), uric acid (UA) and total antioxidant capacity (TAC) levels. Arterial stiffness index (ASI

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of International Society Of Preventive And Community Dentistry
The impact of dental environment stress on dentition status, salivary nitric oxide and flow rate
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Publication Date
Tue Jan 22 2019
Journal Name
Horticulturae
Variable Pulsed Irrigation Algorithm (VPIA) to Reduce Runoff Losses under a Low-Pressure Lateral Move Irrigation Machine
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Due to restrictions and limitations on agricultural water worldwide, one of the most effective ways to conserve water in this sector is to reduce the water losses and improve irrigation uniformity. Nowadays, the low-pressure sprinkler has been widely used to replace the high-pressure impact sprinklers in lateral move sprinkler irrigation systems due to its low operating cost and high efficiency. However, the hazard of surface runoff represents the biggest obstacle for low-pressure sprinkler systems. Most researchers have used the pulsing technique to apply variable-rate irrigation to match the crop water needs within a normal application rate that does not produce runoff. This research introduces a variable pulsed irrigation algorit

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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