Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
(18)
(11)
Publication Date
Sat Oct 04 2025
Journal Name
Modern Sport
Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p>
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(17)
Publication Date
Sat Jun 01 2019
Journal Name
Synthetic Metals
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(5)
Publication Date
Tue Mar 16 2021
Journal Name
2021 4th International Conference On Energy Conservation And Efficiency (icece)
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(3)
Publication Date
Sun Dec 30 2018
Journal Name
Advances In Remote Sensing And Geo Informatics Applications
Publication Date
Tue Sep 02 2014
Journal Name
Arab J Sci Eng
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(2)
Publication Date
Tue Oct 01 2019
Journal Name
2019 12th International Conference On Developments In Esystems Engineering (dese)
(2)
(2)
Publication Date
Sun Jan 08 2017
Journal Name
International Journal Of Information Technology And Computer Science
Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
MODELING DEATH RATE OF THE COVID-19 PANDEMIC IN IRAQ
Coronavirus
Beta regression model
Maximum likelihood method
Death rate
Mortality rate
Publication Date
Tue Aug 02 2022
Journal Name
Karbala International Journal Of Modern Science
Performance Simulation for Adaptive Optics Technique Using OOMAO Toolbox
Adaptive Optics (AO)
OOMAO
Strehl R atio (SR)
Full Turbulence
Residue Turbulence
Noise.
The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process
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