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Deep Learning-Based Approach for Classifying the Severity of Metal Corrosion Using Sem Images
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Study the Inhibition Effect of Amoxicillin Drug for Corrosion of Carbon Steel in Saline Media
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          Potentiostatic polarization and weight loss methods have been used to investigate the corrosion behavior of carbon steel in sodium chloride solution at different concentrations (0.1, 0.4 and 0.6) M under the influence of temperatures ( 293, 298, 303, 308 and 313) K. The inhibition efficiency of the amoxicillin drug on carbon steel in 0.6 M NaCl has also been studied based on concentration and temperature. The corrosion rate showed that all salt concentrations ( NaCl solution) resulted in corrosion of carbon steel in varying ratio and 0.6 M of salt solution  was the highest rate (50.46 g/m².d). The results also indicate that the rate of corrosion increases at a temperature of 313 K.. Potentiodynamic polarization studi

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Sun Feb 01 2026
Journal Name
Energy
Smart buildings envelope utilise triple PCM for offset and reduce peak load using deep clustering of multi-agent control
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Publication Date
Sat Mar 07 2026
Journal Name
Solvent Extraction Research And Development, Japan
Shedding Light on Thermodynamics and Physical Properties of Deep Eutectic Solvents for Separating Toluene-Heptane Mixtures Using COSMO-RS
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A total of 150 deep eutectic solvents (DESs) with varying salt, hydrogen bond donor, and molar ratios were studied to develop a screening tool for separating toluene-heptane mixtures. The activity coefficient at infinite dilution (γ∞) of each DES was predicted using COSMO-RS, and selectivity (S∞), capacity (C∞), and performance index (PI) were calculated. Key DES properties, including density, viscosity, melting/freezing point, surface tension, and conductivity, were compiled from the literature to create a DES property library. A comprehensive screening tool with four evaluation criteria was developed, which identified ethyl triphenylphosphonium bromide:ZnCl2 (1:4) as the optimal solvent for toluene-heptane separation. Tetrabutyl- b

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Sat Jan 01 2011
Journal Name
Journal: Ibn Al-haitham Journal For Pure And Applied Sciences
A Study the effect the direction of the distribution of lighting to improve Images in different lighting by using technique adaptive histogram equalization
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Publication Date
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Comparative Evaluation of the Effect of Different Universal Adhesives and Bonding Techniques on the Marginal Gap of Class I Composite Restoration (A SEM Study)
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Background: With the increase in composite material use in posterior teeth, the concerns about the polymerization shrinkage has increased with the concerns about the formation of marginal gaps in the oral cavity environment. New generation of adhesives called universal adhesive have been introduced to the market in order to reduce the technique sensitive bonding procedures to give the advantage of using the bonding system in any etching protocol without compromising the bonding strength. The aim of the study was to study marginal adaptation of two universal adhesives (Single bondâ„¢ Universal and Prime and Bond elect) using 3 etching techniques under thermal cycling aging. Materials and Methods: Forty-eight sound maxillary first premola

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