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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 Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Tue Mar 01 2016
Journal Name
International Journal Of Engineering Research And Advanced Technology (ijerat)
Speeding Up Back-Propagation Learning (SUBPL) Algorithm: A New Modified Back_Propagation Algorithm
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The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Foreign Channels Speaking in Arabic and their Role in Addressing Middle East Issues: عبد الله حسين حسن
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This research aims at identifying the nature of addressing the Middle East issues in the talk shows in the foreign channels speaking in Arabic "France 24, a model", and identifying the extent of interest of the channel in addressing middle east issues in the talk shows, the nature of the guests and the hosts, methods of addressing the issues, and the technical features that characterize the presenter of the research sample program. This research is considered an analytical descriptive study. It depends on the analysis of the content of the series of the weekly talk show "a week from the world" on the French channel (France 24) during the period (August 1/July 31 2018).
The most important results indicated that the foreign channels sp

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Publication Date
Sun Dec 03 2017
Journal Name
Anbar Journal Of Agricultural Sciences
Effect of seeds priming treatments in viablity and vigour of soybean (glycine max l.) seeds under salinity stress
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Two factorial experiments were conducted. One of them was laboratory experiment which was carried out at the Laboratory of Agriculture and Marshes College, University of Thi-Qar during laboratories of certification and test of seeds office in Thi-Qar governorate–Nassiriyah district during 2015. The other was conducted at the lath house with used the pots during spring season of 2016. The aim was to investigate the effect of soybean seeds priming before sowing on seed vigour and seedling growth characteristics under salinity stress. The design of Lab. experiment was (CRD) while for the other experiment was (RCBD) with four replications. Each experiment consisted of two factors. The first factor included seeds soaking treatments for 24 hour

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Prevalence of Posttraumatic Stress Symptomatology and Distribution of Attachment Patterns 1 and 5 Months after a Terrorist Attack
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As a consequence of a terrorist attack, people may experience posttraumatic stress disorder (PTSD) and lack of feeling secure in relationships. This longitudinal study aimed to examine the prevalence of PTSD symptoms over time, the relationship between adult attachment styles and PTSD, as well as their association with degree of exposure, and finally to consider the distribution and the trajectory of attachment styles. The sample consisted of 235 students (M=125, F=110) who were exposed to different levels of trauma intensity in response to a bombing attack. Participants were recruited and assessed approximately 1 month and 5 months after the attack using a battery of questionnaires. Findings revealed, as expected, that 79.5% of the part

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Publication Date
Mon Jan 01 2018
Journal Name
Iraqi Journal Of Agricultural Sciences, 2018, 49(2), Pp. 179–187
Estimation of some genetic parameters for grain yield and its components of maize under watered and water stress
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Publication Date
Fri Jul 01 2016
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
STUDY THE EFFECT OF DIFFERENT TYPES OF STRESS ON SOME BLOOD CONSTITUENTS AND PLASMA BIOCHAMICALS IN MALE RATS
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    The objective of this work was to determine and compare the physiological changes in some: blood components (packed cell volume and hemoglobin) and plasma biochemical parameters (glucose, total protein, albumin, cholesterol and triglycerides) under 3 day of different types of stress: water deprivation, starvation, overcrowding and handling stress. Twenty five male Wister rats weighted 100-120 gm, were divided randomly into five groups: control, water deprivation, starvation, overcrowding and handling stress. On the third day of stress the animals anesthetized for blood collection; the results of blood component revealed a significant increase in PCV and a significant decrease in Hb of water deprivation group and starva

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Prevalence of Posttraumatic Stress Disorder (PTSD) among the Iraqi Repatriated Prisoners of the Iran-Iraq War, 1980-1988
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Objective: To determine the prevalence of Posttraumatic Stress Disorder (PTSD) among Iraqi repatriated
prisoners of Iran-Iraq war, and the relationship with demographic factors.
Methodology: A descriptive study was carried out from Oct. 18th, 2009 through Jan. 10th, 2010. A nonprobability
based snowball sampling technique was used to recruit 92 Iraqi repatriated prisoners of war
(IRPOWs) who had visited Ministry of Human Rights. A data collection instrument was constructed that
consisted of six demographic characteristics, and eight items to measure the level of PTSD in POWs. Data were
collected with the constructed instrument during a brief interview. Data were analyzed through the application of
descriptive statist

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Advanced Joining Processes
Coupled Eulerian–Lagrangian prediction of thermal and residual stress environments in dissimilar friction stir welding of aluminum alloys
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The evaluation of residual stresses (RS) induced by the friction stir welding (FSW) process is crucial in anticipating the performance of the welded structure. The existence of such residual stresses within a friction stir welded structure may lead to excessive distortion and weakness to afford the applied external loads. To assess quantitatively the effect of these residual stresses generated by FSW process, the current paper implements a Coupled Eulerian–Lagrangian (CEL) finite element simulation to analyze both thermal and subsequent resulted remaining stress environments in dissimilar friction stir welding of AA6061-T6 and AA2024-T3 alloys. The thermal analysis step was conducted first and followed by a mechanical analysis step in whi

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