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.
A laboratory experiment was carried out in the laboratories of College of Agricultural Engineering Sciences, University of Baghdad in 2017. Three factors were studied; Sorghum bicolor L. cultivars (Inqath, Rabeh and Buhoth70), primed and unprimed seed and osmotic potential (0, -5, -9, -13 bar). The aim was to improve germination and seedling growth under water stress. The results showed significant superiority of Buhoth 70 cultivar compared to others, significant superiority of primed seed compared to the unprimed, significant negative impact as long as increasing levels of osmotic potential and significant superiority of interaction treatment (Buhoth70 × primed seed × 0) compared to others in germination ratio, radicle and plumule length
... Show MoreIn this paper, we employ the maximum likelihood estimator in addition to the shrinkage estimation procedure to estimate the system reliability (
The challenge to incorporate usability evaluation values and practices into agile development process is not only persisting but also systemic. Notable contributions of researchers have attempted to isolate and close the gaps between both fields, with the aim of developing usable software. Due to the current absence of a reference model that specifies where and how usability activities need to be considered in the agile development process. This paper proposes a model for identifying appropriate usability evaluation methods alongside the agile development process. By using this model, the development team can apply usability evaluations at the right time at the right place to get the necessary feedback from the end-user. Verificatio
... Show MoreThe extraction of Eucalyptus oil from Iraqi Eucalyptus Camadulensis leaves was studded using water distillation methods. The amount of Eucalyptus oil has been determined in a variety of extraction temperature and agitation speed. The effect of water to Eucalyptus leaves (solvent to solid) ratio and particle size of Eucalyptus leaves has been studied in order to evaluate the amount of Eucalyptus oil. The optimum experimental condition for the Eucalyptus oil extraction was established as follows: 100 C extraction temperature, 200 rpm agitation speed; 0.5 cm leave particle size and 6: 1 ml: g amount of water to eucalyptus leaves Ratio.
This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
... Show MoreObjectives:This study aimed to identify women perception and experience regarding family planning(FP) methods
Methodology:Descriptive cross-sectional hospital based study,was conducted at Omer Sawi teaching hospital,from august to September 2019.Sample of 320 women, were selected randomly after their agreement.Data were collected through interview questionnaire and analyzed using a statistical package for social sciences (SPSS)and descriptive and inferential statistical methods were used.With accepted P.< 0.05.for the correlation significant.
Results:Age group between 21-25 years represent (53.1%),most common education levels were secondary school 56%.Majority of women had 2-5 children.Half of the wo
In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.
The purpose of this study is to compare the influence of three teaching methods, as represented by problem-based learning (PBL), the PBL with lecture method, and the conventional teaching on undergraduate physics students' group work skills among bachelor’s degree physics students. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The actual sample size comprises of 122 students, who were selected randomly from the physics department, college of education in iraq. Overall, the statistical results rejected null hypothesis of this study. Thus, using the PBL without or with lecture method enhances the skills of the group work among the bachelor’s degree physics studen
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