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Academic Articles & Research Papers
Showing 20 of 757 academic articles
Amjad M. Al Tobi, Ishbel Duncan • Information
(2019)
Network traffic exhibits a high level of variability over short periods of time. This variability impacts negatively on the accuracy of anomaly-based network intrusion detection systems (IDS) that are built using predictive models in a batc...
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Open Access (DOAJ)
DOI: 10.3390/info10050159
Xinchen Xu, Xingpeng Liao, Gaoning Shi, Yuyang Chen et al. • Journal of Magnesium and Alloys
(2026)
Though magnesium alloys possess attractive mechanical properties, their applications are severely limited by galvanic corrosion, due to the rapid anodic dissolution and anomalous hydrogen evolution. In this work, well-tempered metadynamics ...
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Open Access (DOAJ)
DOI: 10.1016/j.jma.2026.102217
Juan Carrasquilla • Advances in Physics X
(2020)
Quantum matter, the research field studying phases of matter whose properties are intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter physics, materials science, statistical mechanics, quantum information,...
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DOI: https://doi.org/10.1080/23746149.2020.1797528
Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar et al. • IEEE Access
(2025)
This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regim...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3567410
• The MIT Press eBooks
(2012)
Foundations of Machine LearningSoon we will embark on a theoretical study of AdaBoost in order to understand its properties, particularly its ability as a learning algorithm to generalize, that is, to make accurate predictions on data not s...
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DOI: https://doi.org/10.7551/mitpress/8291.003.0006
Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials
(2026)
The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...
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Open Access (DOAJ)
DOI: 10.3390/nano16030179
Eleftheria Polychronidou, Ilias Kalamaras, Andreas Agathangelidis, Lesley-Ann Sutton et al. • BMC Bioinformatics
(2018)
Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...
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Open Access (DOAJ)
DOI: 10.1186/s12859-018-2381-1
Tim Mueller, Aaron Gilad Kusne, Rampi Ramprasad • Reviews in computational chemistry
(2016)
This chapter addresses the role that data-driven approaches, especially machine learning methods, are expected to play in materials research in the immediate future. Machine learning, an important part of artificial intelligence, has made m...
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DOI: https://doi.org/10.1002/9781119148739.ch4
Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing
(2026)
Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...
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Open Access (DOAJ)
DOI: 10.3390/rs18172862
Edoardo Bizzotto, Guido Zampieri, Laura Treu, Pasquale Filannino et al. • Computational and Structural Biotechnology Journal
(2024)
Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on...
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Open Access (DOAJ)
DOI: 10.1016/j.csbj.2024.05.040
Emily K. Makowski, Patrick C. Kinnunen, Jie Huang, Lina Wu et al. • Nature Communications
(2022)
Optimising antibody properties such as affinity can be detrimental to other key properties. Here the authors use machine learning to simplify the identification of antibodies with co-optimal levels of affinity and specificity for a clinical...
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Open Access (DOAJ)
DOI: 10.1038/s41467-022-31457-3
Yu‐Chen Lo, Stefano Rensi, Wen Torng, Russ Biagio Altman • Drug Discovery Today
(2018)
Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learn...
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DOI: https://doi.org/10.1016/j.drudis.2018.05.010
PMC: 6078794
T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale et al. • Journal of Natural Fibers
(2025)
Machine learning model coupled with graphical user interface was developed to predict mechanical properties of flax fiber. The experiment was conducted using test setup which applies constant rate of loading (CRL). Flax fiber was tested und...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/15440478.2025.2502662
G. Baaklini, G. Baaklini, R. El Hourany, M. Fakhri et al. • Ocean Science
(2022)
The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/os-18-1491-2022
Jing Wei, Xuan Chu, Xiangyu Sun, Kun Xu et al. • InfoMat
(2019)
Abstract Traditional methods of discovering new materials, such as the empirical trial and error method and the density functional theory (DFT)‐based method, are unable to keep pace with the development of materials science today due to the...
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DOI: https://doi.org/10.1002/inf2.12028
Elisabeth Källström, Tomas Olsson, John Lindström, Lars Hakansson et al. • International Journal of Prognostics and Health Management
(2018)
In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machine in combination with feature extraction and classification...
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Open Access (DOAJ)
DOI: doi:10.36001/ijphm.2018.v9i1.2693
Francesco Carnazza, Federico Carollo, Dominik Zietlow, Sabine Andergassen et al. • New Journal of Physics
(2022)
Full information about a many-body quantum system is usually out-of-reach due to the exponential growth—with the size of the system—of the number of parameters needed to encode its state. Nonetheless, in order to understand the complex phen...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/1367-2630/ac7df6
Jian Liu, Fangyu Liu, Linbing Wang • Journal of Traffic and Transportation Engineering (English ed. Online)
(2024)
The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2 emissions during pavement construction and maintenance. Additionally, the laboratory mix design process, whic...
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Open Access (DOAJ)
DOI: 10.1016/j.jtte.2023.10.002
S. Sra, S. Nowozin, Stephen J. Wright • The MIT Press eBooks
(2011)
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments ...
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DOI: https://doi.org/10.7551/mitpress/8996.001.0001
Yuchen Cao, Lan Hu, Laurent Kneip • Sensors
(2020)
Simultaneous Localisation And Mapping (SLAM) has long been recognised as a core problem to be solved within countless emerging mobile applications that require intelligent interaction or navigation in an environment. Classical solutions to ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s20092572