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Academic Articles & Research Papers
Showing 20 of 32 academic articles
Muhammad Afaq Hussain, Zhanlong Chen, Biswajeet Pradhan, Sansar Raj Meena et al. • Journal of Hydrology: Regional Studies
(2025)
Study region: The National Highways 85 and 50, key routes of the China–Pakistan Economic Corridor (CPEC) in Balochistan, Pakistan. Study focus: Flooding is a natural disaster that is becoming increasingly frequent and severe. The National H...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.ejrh.2025.102718
Raenald Syaputra, Taghfirul Azhima Yoga Siswa, Wawan Joko Pranoto • Teknika
(2024)
Banjir merupakan salah satu bencana alam yang sering terjadi di Indonesia, termasuk di Kota Samarinda dengan 18-33 titik desa terdampak dari tahun 2018-2021. Penggunaan machine learning dalam mengklasifikasi bencana banjir sangat penting un...
DOAJ
Open Access (DOAJ)
DOI: 10.34148/teknika.v13i2.876
Senyefia Bosson-Amedenu, Emmanuel Ayitey, Francis Ayiah-Mensah, Luyton Asare • BMC Cancer
(2025)
Abstract Background Frailty models are extensively utilized in survival analysis to address unobserved heterogeneity among individuals. However, selecting the most robust model for survival prediction, especially in the context of high-dime...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12885-025-14040-z
H. K. Lee, Y.‐S. Choi • Electronics Letters
(2022)
Abstract Recent advancements in steady‐state visual evoked potential‐based brain‐computer interface have been made possible by the widespread use of various spatial filtering methods. Task‐related component analysis has superiority over exi...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/ell2.12540
Xiangyang Zheng, Yancai Xiao, Xinran Li • Machines
(2026)
Wind turbine (WT) misalignment fault diagnosis is constrained by critical signal processing challenges: weak fault features, intense background noise, and poor generalization. This study proposes a lightweight method for high-precision faul...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/machines14020155
Rafael Perera, Marjan Van Den Akker, Kym I E Snell, Joerg J Meerpohl et al. • BMJ Open
(2021)
Objective To explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.Study design and setting Using ...
DOAJ
Open Access (DOAJ)
DOI: 10.1136/bmjopen-2020-045572
Igor I. Baskin, David Alan Winkler, Igor V. Tetko • Expert Opinion on Drug Discovery
(2016)
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...
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DOI: https://doi.org/10.1080/17460441.2016.1201262
Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals • arXiv (Cornell University)
(2014)
We present a simple regularization technique for Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units. Dropout, the most successful technique for regularizing neural networks, does not work well with RNNs and LSTMs. In ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1409.2329
Jaehyun Lee, Jinho Kim, Woong Ko • Applied Sciences
(2019)
Electric load forecasting for buildings is important as it assists building managers or system operators to plan energy usage and strategize accordingly. Recent increases in the adoption of advanced metering infrastructure (AMI) have made b...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app9061231
Nanting Huang, Xiaoyu Li, Xin Yang, Li Xie et al. • Sensors
(2026)
The pathological mechanism of autism spectrum disorder (ASD) exhibits dual heterogeneity: abnormal local energy metabolism and brain-wide high-order topological failure. To synergistically characterize these complex signals captured by adva...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s26133997
Shijie Chen, Yu Zhang, Qiang Yang • ACM Computing Surveys
(2024)
Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...
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Open Access
DOI: https://doi.org/10.1145/3663363
Sumaya Mustafa, Mariwan Hama Saeed • Journal of Electrical Systems and Information Technology
(2025)
Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s43067-025-00273-2
Sebastian Ruder • Arrow@dit (Dublin Institute of Technology)
(2019)
The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...
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Open Access
DOI: https://doi.org/10.13025/17598
Albert Vong, Howard Yanxon, Eric Roberts, Hannah Parraga et al. • Journal of Synchrotron Radiation
(2026)
Modern synchrotron X-ray facilities generate X-ray diffraction (XRD) image data at rates that far exceed the capacity of manual analysis, yet critical processing steps such as artifact removal rely on human intervention. Rule-based algorith...
DOAJ
Open Access (DOAJ)
DOI: 10.1107/S160057752600754X
Paulo Monteiro de Carvalho Monson, Vinicius Augusto Dare de Almeida, Gabriel Augusto David, Pedro Oliveira Conceição Junior et al. • Engineering Proceedings
(2024)
Computer vision applications demand a significant amount of data for effective training and inference in many computer vision tasks. However, data insufficiency situations usually happen due to multiple reasons, resulting in computational m...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/ecsa-11-20476
Florence Choong Chiao Mei, Bryan Ng Jan Hong • Journal of Engineering Technology and Applied Physics
(2025)
Agriculture is one of the largest sectors that contribute to the economic growth of countries, including Malaysia. However, plant diseases affect the quality of the harvest and impede farmers’ maximum yield output. Therefore, early detectio...
DOAJ
Open Access (DOAJ)
DOI: 10.33093/jetap.2025.7.1.2
Yao He, Jing Yang, Shaobo Li, Jianjun Hu et al. • Complex & Intelligent Systems
(2024)
Abstract Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the pa...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s40747-024-01350-1
June‐Goo Lee, Sanghoon Jun, Young-Won Cho, Hyunna Lee et al. • Korean Journal of Radiology
(2017)
The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishin...
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cc-by-nc
DOI: https://doi.org/10.3348/kjr.2017.18.4.570
PMC: 5447633
Mingyu Kim, Jihye Yun, Yongwon Cho, Keewon Shin et al. • Neurospine
(2019)
The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learn...
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cc-by-nc
DOI: https://doi.org/10.14245/ns.1938396.198
PMC: 6945006
Peter L. Bartlett, Andrea Montanari A, Alexander Rakhlin • Acta Numerica
(2021)
The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...
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DOI: https://doi.org/10.1017/s0962492921000027