Preferred Language
Articles
/
bsj-8819
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods
...Show More Authors

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.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
...Show More Authors

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

... Show More
Preview PDF
Scopus
Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
The Learning Style for distinguished students and their ordinary mates in the secondary stage in accordance to some variables
...Show More Authors

The current problem is summarized in what is called the development failing experience
in comprehencing the studying materials , so the students will feel worry of repeating failure
in he future , so he would seek blind keeping on heart for the studying material bond this isbad due to the forgetting in the future , one side of thesis research problem is that there is
many contradictory researches result in relation to the learning styles which impose the
nessicity to find results lessen this contradiction . the importance of the research is
summarized in the importance of the subject under the study , in that the researcher ( as in
her knowledge ) did not find a thesrs tackling the subject of the distinguished students

... Show More
View Publication Preview PDF
Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
...Show More Authors

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
The Degree to Which Princess Rahma University College Students Possess E-Learning Skills Related to Moodle from their Point of View, in Light of the Corona Crisis
...Show More Authors

This study aims to identify the degree of students of Princess Rahma University College owning e-learning skills related to MOODLE as they perceived in the of light Corona crisis. The researchers' questionnaire consisted of (37) items, distributed in three areas of e-learning skills related to the MOODLE on (147) students were chosen randomly. The results of the study showed that the degree of students 'possession of e-learning skills related to the MOODLE was significant. The results also revealed that there were statistically significant differences in the degree of students' possession of electronic learning skills related to the MOODLE due to sex in favor of females. Finally, there were no statistically significant differences in the

... Show More
View Publication Preview PDF
Publication Date
Wed Jan 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Synthesis of anti-corrosion polymers from thiadiazole
...Show More Authors
Abstract<p>One of the biggest problems facing many industries particularly oil, is the problem of corrosion, where the metal parts under the influence of the vital factors are eroded during use and storage, therefore, to lift the metal’s ability and to protect it against corrosion, corrosion inhibitors are used. For the first time in this research, polymers which contain sulfur - heterocyclic ring with a thiadiazole base were made. Anti- corrosion polymers were made on two stages, in the first stage, thiadiazole was made from hydrazine hydrate reaction to carbon disulfide, afterwards the first product was reacted with an excess of hydrazine. In the second stage, polymers were prepared by the r</p> ... Show More
View Publication
Scopus (1)
Scopus Crossref
Publication Date
Sun Dec 01 2019
Journal Name
2019 First International Conference Of Computer And Applied Sciences (cas)
A Comparison for Some of the estimation methods of the Parallel Stress-Strength model In the case of Inverse Rayleigh Distribution
...Show More Authors

View Publication
Scopus (10)
Crossref (3)
Scopus Crossref
Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Numeral Recognition Using Statistical Methods Comparison Study
...Show More Authors

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

View Publication Preview PDF
Crossref
Publication Date
Mon Mar 02 2026
Journal Name
International Journal Of Inventions In Engineering &amp; Science Technology
A Review: Campus Violence Detection Using Deep Learning Models
...Show More Authors

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

... Show More
View Publication Preview PDF
Crossref
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
...Show More Authors

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

... Show More
View Publication Preview PDF
Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Characterization of Alginate with Natural Polymers Combination for Drug Encapsulation
...Show More Authors

Alginate is one of the natural biopolymers that is widely used for drug formulations, combination of alginate with other polymers, such as gum acacia, pectin, and carrageenan can increase mechanical strength, therefore, can reduce leakage of the encapsulated active pharmaceutical ingredient from the polymer matrix. Interaction of alginate and these polymers can occur via intermolecular hydrogen bonds causing synergism, which is determined from the viscosity of polymer mixture.

Alginate was combined with gum acacia/pectin/carrageenan in different blending ratios (100:0, 75:25, 50:50, 25:75, and 0:100) with and without addition of CaCl2. The synergism effect is obtained from the design of experimental (DoE), and calculati

... Show More
View Publication Preview PDF
Scopus (12)
Crossref (8)
Scopus Crossref