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Academic Articles & Research Papers
Showing 20 of 1,630 academic articles
Kavian Khosravinia, Amirkianoosh Kiani • iScience
(2023)
Summary: Pseudocapacitors outperform lithium-ion batteries in terms of charging rate and power density. However, their electrode manufacturing procedures are prolonged and environmentally unfriendly, posing a research challenge. To address ...
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Open Access (DOAJ)
DOI: 10.1016/j.isci.2023.106438
Jiaoling Qin, Jiaoling Qin, Sunzhe Li, Sunzhe Li et al. • Frontiers in Marine Science
(2023)
Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmars.2022.1113387
Dhurgham Ali Mohammed, Kalyani A. Patel • ICTACT Journal on Soft Computing
(2025)
In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...
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Open Access (DOAJ)
DOI: 10.21917/ijsc.2025.0518
Zella King, Joseph Farrington, Martin Utley, Enoch Kung et al. • npj Digital Medicine
(2022)
Abstract Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabi...
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Open Access (DOAJ)
DOI: 10.1038/s41746-022-00649-y
Qifang Bi, Katherine E Goodman, Joshua Kaminsky, Justin Lessler • American Journal of Epidemiology
(2019)
Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well...
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DOI: https://doi.org/10.1093/aje/kwz189
Hyuk Lee • Applied Sciences
(2025)
As edge computing environments become increasingly dynamic, the need for efficient job scheduling and proactive fault prevention is becoming paramount. In such environments, minimizing machine downtime and maintaining productivity are criti...
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Open Access (DOAJ)
DOI: 10.3390/app15041771
Frank Hutter, Lars Kotthoff, Joaquin Vanschoren • The Springer series on challenges in machine learning
(2019)
This open access book gives the first comprehensive overview of general methods in Automatic Machine Learning, AutoML, collects descriptions of existing AutoML systems based on these methods, and discusses the first international challenge ...
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DOI: https://doi.org/10.1007/978-3-030-05318-5
Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec)
(2011)
In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...
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DOI: https://doi.org/10.1145/2046684.2046692
Subhabrata Sengupta, Rupayan Das, Satyajit Chakrabarti • Emitter: International Journal of Engineering Technology
(2024)
Information retrieval aims to find the most important data for specific queries. The challenge is retrieving relevant data efficiently due to the large search area. Existing solutions lead to unnecessary processing costs. Additionally, iden...
DOAJ
Open Access (DOAJ)
DOI: 10.24003/emitter.v12i2.855
Qiying Yu, Wenzhong Li, Yungang Bai, Zhenlin Lu et al. • Journal of Hydrology: Regional Studies
(2025)
Study Area: The Tailan River Basin in the Aksu region and the Yulong Kashi River in the Hotan River Basin of Xinjiang are located at respective geographical coordinates of 80°21'44'' to 81°10'14'' E, 40°41'41'' to 42°15'13'' N, and 77.25° t...
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Open Access (DOAJ)
DOI: 10.1016/j.ejrh.2025.102311
Bardia Abbasi, Daniel M. Goldenholz • Epilepsia
(2019)
Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...
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Open Access
DOI: https://doi.org/10.1111/epi.16333
PMC: 9897263
Qingfeng Sun, Kai Zhang, Yuanlong Xu, Mengmei Luo et al. • BMC Infectious Diseases
(2025)
Abstract Background HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identif...
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Open Access (DOAJ)
DOI: 10.1186/s12879-025-11998-w
Marc Claesen, Bart De Moor • arXiv (Cornell University)
(2015)
We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based o...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1502.02127
Biprateep Dey, David Zhao, Brett H Andrews, Jeffrey A Newman et al. • Machine Learning: Science and Technology
(2025)
Key science questions, such as galaxy distance estimation and weather forecasting, often require knowing the full predictive distribution of a target variable Y given complex inputs X . Despite recent advances in machine learning and physic...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/2632-2153/ae1f05
Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making
(2024)
Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...
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Open Access (DOAJ)
DOI: 10.1186/s12911-024-02652-7
Ethem Alpaydın • The MIT Press eBooks
(2021)
A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars. Today, machine learning underlies a range of applications we use every day, from product ...
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Open Access
DOI: https://doi.org/10.7551/mitpress/13811.001.0001
Christian Janiesch, Patrick Zschech, Kai Heinrich • Electronic Markets
(2021)
Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of a...
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DOI: https://doi.org/10.1007/s12525-021-00475-2
Felix Menne, Felix Dörr, Julia Schräder, Johannes Tröger et al. • BMC Psychiatry
(2024)
Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patient...
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Open Access (DOAJ)
DOI: 10.1186/s12888-024-06253-6
Quang-Phuoc Nguyen, Anh-Dung Vo, Joon-Choul Shin, Cheol-Young Ock • IEEE Access
(2018)
With the advent of robust deep learning, neural machine translation (NMT) has achieved great progress and recently become the dominant paradigm in machine translation (MT). However, it is still confronted with the challenge of word ambiguit...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2018.2851281
Luciellen da Costa Ferreira, Ian Carlos Bispo Carvalho, Lúcio André de Castro Jorge, Alice Maria Quezado-Duval et al. • Frontiers in Plant Science
(2024)
Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. ...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpls.2024.1387925