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Mengyuan Zhu, Jiawei Wang, Xiao Yang, Yu Zhang et al. • Eco-Environment & Health
(2022)
With the rapid increase in the volume of data on the aquatic environment, machine learning has become an important tool for data analysis, classification, and prediction. Unlike traditional models used in water-related research, data-driven...
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DOI: https://doi.org/10.1016/j.eehl.2022.06.001
PMC: 10702893
Julia Westermayr, Philipp Marquetand • Chemical Reviews
(2020)
Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculati...
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DOI: https://doi.org/10.1021/acs.chemrev.0c00749
PMC: 8391943
Vijay K. Vemuri • Journal of Information Technology Case and Application Research
(2020)
Advances in Artificial intelligence and machine learning have developed beyond the theoretical realm. In fact, several day-to-day applications are currently in use. Although artificial intelligence......
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DOI: https://doi.org/10.1080/15228053.2020.1766224
Ral Garreta, Guillermo Moncecchi • International Linear Collider
(2013)
The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this...
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Kaiyang Qu, Fei Guo, Xiangrong Liu, Yuan Lin et al. • Frontiers in Microbiology
(2019)
Microorganisms are ubiquitous and closely related to people's daily lives. Since they were first discovered in the 19th century, researchers have shown great interest in microorganisms. People studied microorganisms through cultivation, but...
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DOI: https://doi.org/10.3389/fmicb.2019.00827
PMC: 6482238
Subrata Chakraborty, Biswajeet Pradhan • Sensors
(2024)
Machine learning (ML) models have experienced remarkable growth in their application for multimodal data analysis over the past decade [...]...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24092874
Shobhit K. Patel, Juveriya Parmar, Vijay Katkar, Fahad Ahmed Al-Zahrani et al. • Alexandria Engineering Journal
(2022)
The solar spectrum energy absorption is very important for designing any solar absorber. The need for absorbing visible, infrared, and ultraviolet regions is increasing as most of the absorbers absorb visible regions. We propose a metasurfa...
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Open Access (DOAJ)
DOI: 10.1016/j.aej.2022.03.080
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Van-Ngoc Pham, Huu-Dao Do, Thi Phuong Khue Nguyen, Van-Khanh Tran et al. • Tạp chí Khoa học và Công nghệ
(2026)
This study develops a data-driven framework using Extreme Gradient Boosting (XGBoost) to predict the Indirect Tensile Strength (ITS) of cement-treated clayey soils. Using 180 specimens with five input variables - cement content, curing time...
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Open Access (DOAJ)
DOI: 10.31130/ud-jst.2026.24(7B).582E
Ziad F. Doughan, Sari S. Itani • IEEE Access
(2025)
This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RD...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3641537
Ady Suwardi, Fuke Wang, Kun Xue, Ming‐Yong Han et al. • Advanced Materials
(2021)
Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been ham...
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DOI: https://doi.org/10.1002/adma.202102703
Marco Fiorucci, Marina Khoroshiltseva, Massimiliano Pontil, Arianna Traviglia et al. • Pattern Recognition Letters
(2020)
The application of Machine Learning (ML) to Cultural Heritage (CH) has evolved since basic statistical approaches such as Linear Regression to complex Deep Learning models. The question remains how much of this actively improves on the unde...
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DOI: https://doi.org/10.1016/j.patrec.2020.02.017
Marco Barreno, Blaine A. Nelson, Russell Sears, Anthony D. Joseph et al. • ACM Asia Conference on Computer and Communications Security (ASIA CCS)
(2006)
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. However, machine learning algorithms themselves can be a targe...
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DOI: https://doi.org/10.1145/1128817.1128824
Sheena Angra, Sachin Ahuja • International Conference on Big Data Analytics and Computational Intelligence (ICBDAC)
(2017)
Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data m...
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DOI: https://doi.org/10.1109/icbdaci.2017.8070809
Matthias Seeger • International Journal of Neural Systems
(2004)
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...
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Open Access
DOI: https://doi.org/10.1142/s0129065704001899
Nishant Shukla • CERN Document Server (European Organization for Nuclear Research)
(2018)
Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...
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A. Boehnlein, M. Diefenthaler, Nobuo Sato, M. Schram et al. • Reviews of Modern Physics
(2022)
Nuclear physics deals with complex systems, large datasets, and complicated correlations between parameters, which makes the field suitable for the application of machine learning techniques. Machine learning can help classify and analyze d...
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Open Access
DOI: https://doi.org/10.1103/revmodphys.94.031003
Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler et al. • Chemical Reviews
(2022)
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better unde...
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DOI: https://doi.org/10.1021/acs.chemrev.2c00061
Xiuhua April Si, Jinxiang Xi • Journal of Nanotheranostics
(2021)
Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jnt2030007
Heming Jia, Marjan Kordani, Iman Ahmadianfar, Arvin Samadi Koucheksaraee et al. • Engineering Applications of Computational Fluid Mechanics
(2026)
Precise forecasting of water quality indices (WQI) is essential for safeguarding ecosystems, human health, and sustainable water resource management. This study presents an innovative approach for evaluating river Water Quality Indices usin...
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Open Access (DOAJ)
DOI: 10.1080/19942060.2025.2602582