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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
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Studying the contribution of components and type of spiral galaxy NGC 6946 using digital image processing
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NGC 6946 have been observed with BVRI filters, on October 15-18,
2012, with the Newtonian focus of the 1.88m telescope, Kottamia
observatory, of the National Research Institute of Astronomy and
Geophysics, Egypt (NRIAG), then we combine the BVRI filters to
obtain an astronomical image to the spiral galaxy NGC 6946 which
is regarded main source of information to discover the components of
this galaxy, where galaxies are considered the essential element of
the universe. To know the components of NGC 6946, we studied it
with the Variable Precision Rough Sets technique to determine the
contribution of the Bulge, disk, and arms of NGC 6946 according to
different color in the image. From image we can determined th

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Improving Reverse Engineering Processes by using Articulated Arm Coordinate Measuring Machine
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The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Applied Spectroscopy
Evaluation of Stability Constant for Vitamin B1 Depending on Stoichiometric Curves by Visible Spectroscopy
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Applied Spectroscopy
Evaluation of Stability Constant for Vitamin B1 Depending on Stoichiometric Curves by Visible Spectroscopy
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The measurement of vitamin B1 in pure and pharmaceutical formulations was proposed by using a straightforward and sensitive spectrophotometric approach. Sulfacetamide (SFA) is diazotized, then coupled with vitamin B1 in alkaline media to produce a colored azo dye complex with a stability constant of 5.597 × 105 L/mol. The product is stable, with a maximum absorption wavelength of 489.5 nm, molar absorptivity of 10108 L/mol∙cm, Sandell's sensitivity of 0.0334 μg/cm2, detection limit of 0.0135 μg/mL, and Beer's law being observed over the concentration range of 0.2–20.0 μg/mL. The stability constant and stoichiometry of the produced azo dye were calculated using the continuous variation (Job's) and mole ratio methods. The suggested ap

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Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
Theoretical spectroscopic studies of potential energy curves and Fortran parabola for beryllium oxide molecule
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    Theoretical spectroscopic  studies of  beryllium oxide has been  carried out, potential energy curves for ground states X1Σ+ and exited states A1Π , B1Σ+ by using two functions Morse and  and Varshni compared with experimental results. The potentials of this molecule are agreement with experimental results. The Fortrat Parabola corrcponding to  and branches were determind in the range 1<J<20 for the (0-0) band. It was found that for electronic transition  A1Π- X1Σ+  the bands head lies in  branche of  Fortrat p

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Publication Date
Wed May 29 2019
Journal Name
Iraqi Journal Of Physics
Improvement the efficiency of SnO2/n-Si detector by engraving method using a CNC machine
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Tin oxide was deposited by using vacuum thermal method on silicon wafer engraved by Computer Numerical Controlled (CNC) Machine. The inscription was engraved by diamond-made brine. Deep 0.05 mm in the form of concentric squares. Electrical results in the dark were shown high value of forward current and the high value of the detection factor from 6.42 before engraving to 10.41 after engraving. (I-V) characters in illumination with powers (50, 100, 150, 200, 250) mW/cm2 show Improved properties of the detector, Especially at power (150, 200, 250) mW/cm2. Response improved in rise time from 2.4 μs to 0.72 μs and time of inactivity improved 515.2 μs to 44.2 μs. Sensitivity angle increased at zone from 40o to 65o.

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Publication Date
Sun Dec 01 2019
Journal Name
Al- Mohtaref Journal
Impact of The Use of Electronic Concept Mapping Strategy in Learning and Retaining Some of The Skills of The Ground-Moving Carpet in Women's Artistic Gymnastics
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The study aimed to identify the use of the electronic concept maps method in learning some of the skills of the floor exercises in the artistic gymnastics for third graders ,as well as to identify the best group between the two research groups (experimental And the officer to learn and retain some of the skills of the floor exercises in the artistic gymnastics of the research subject , and the experimental method was used and included the sample research on students of the collage of Physical Education and Sports Sciences/University of Baghdad, third grade, and has selected (10) Students for each group of The experimental and controlling groups randomly by lottery and after the completion of the period of implementation of the experiment wh

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
The Degree of Using Computers in Administrative Jobs and the Obstacles of Usage in Public Education Schools in Sharoorah Governorate: Saudi Arabia
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This study aimed to identify the degree of use computers in administrative functions (planning, organization, controlling, and evaluation) among school leaders and assistants in public education schools in Sharoorah governorate ، as well as to identify obstacles of  use computers in administrative functions from the perspective of school leaders and assistants male and female in public schools during the academic year 1439-1440, the study sample  (66) school leaders and assistants, males (58), a and females (44), , and to answer the questions of the study, the researchers developed a questionnaire consisting of  (60) items, has been verified sincerity and persistence, and data analysis was used frequencies, percentages an

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Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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