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Academic Articles & Research Papers
Showing 20 of 187 academic articles
ZHANG Lei, LI Yuewen, SHI Yi • Guangtongxin yanjiu
(2026)
Due to the dynamic monitoring capability, Distributed Acoustic Sensing (DAS) has been widely deployed in various industrial scenarios. Deep learning greatly boosts the event detection accuracy of fiber sensing systems. Nevertheless, practic...
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Open Access (DOAJ)
Shaorong Zhang, Shaorong Zhang, Qihui Wang, Benxin Zhang et al. • Frontiers in Neuroscience
(2023)
IntroductionThe time, frequency, and space information of electroencephalogram (EEG) signals is crucial for motor imagery decoding. However, these temporal-frequency-spatial features are high-dimensional small-sample data, which poses signi...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2023.1292724
Jakob Mannstadt, Arash Rahimi‐Iman • Advanced Sensor Research
(2025)
Abstract A machine‐learning (ML) non‐contact method to determine the temperature of a laser gain medium via its laser emission with a trained few‐layer neural‐network (NN) model is presented. The training of the feed‐forward NN enables the ...
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Open Access (DOAJ)
DOI: 10.1002/adsr.70009
William W. Hsieh • Cambridge University Press eBooks
(2009)
Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and th...
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DOI: https://doi.org/10.1017/cbo9780511627217
José Padarian, Budiman Minasny, Alex B. McBratney • SOIL
(2020)
Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...
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DOI: https://doi.org/10.5194/soil-6-35-2020
Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data
(2026)
Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40537-026-01475-9
Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO)
(2014)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...
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DOI: https://doi.org/10.1109/micro.2014.58
Quan Quan, Zhongqiang Zhang • Journal of Mathematics
(2022)
With the rapid development of economy and information technology, traditional manufacturing industry is facing severe challenges. Enterprises need to rectify the traditional manufacturing industry and realize the transformation from traditi...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2022/8572424
Hongyu Wang, Lin Wang, Lei Shi, Fei Wang et al. • Journal of Orthopaedic Surgery
(2026)
Background Superior labrum anterior and posterior (SLAP) lesions are a common cause of shoulder pain and instability. Accurate diagnosis remains challenging in clinical practice. This study aims to develop and evaluate radiomics models and ...
DOAJ
Open Access (DOAJ)
DOI: 10.1177/10225536261418429
Khaled Hamdaoui, Ali Benzaamia, Billal Sari Ahmed, Mohamed Elhebib Guellil et al. • Journal of Engineering and Applied Science
(2025)
Abstract This study introduces a novel, interpretable machine learning framework for predicting the compression index (Cc) of clay soils by integrating three advanced gradient boosting algorithms—XGBoost, CatBoost, and LightGBM—with SHapley...
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Open Access (DOAJ)
DOI: 10.1186/s44147-025-00727-4
S. Mostafa Mousavi, Gregory C. Beroza • Annual Review of Earth and Planetary Sciences
(2022)
Machine learning (ML) is a collection of methods used to develop understanding and predictive capability by learning relationships embedded in data. ML methods are becoming the dominant approaches for many tasks in seismology. ML and data m...
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DOI: https://doi.org/10.1146/annurev-earth-071822-100323
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
Joseph A. Cruz, David Scott Wishart • Cancer Informatics
(2006)
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, ...
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DOI: https://doi.org/10.1177/117693510600200030
PMC: 2675494
Harry Surden • Colorado Law Scholarly Commons (University of Colorado Colorado Springs)
(2014)
This Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some ...
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Musa Gün, Ahmet Akusta, Haydar Karadağ • İstanbul İktisat Dergisi
(2025)
This study aims to examine the impact of macro-financial indicators on the housing sales volume in Türkiye and evaluate the forecasting performance of traditional time-series models versus modern machine-learning algorithms. Using monthly d...
DOAJ
Open Access (DOAJ)
DOI: 10.26650/ISTJECON2025-1707729
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
Дмитро АНРДЄЄВ, Олексій ЛИГУН, Андрій ДРОЗД, Олена ПОНОЧОВНА • Компютерні системи та інформаційні технології
(2025)
Critical infrastructures are fundamental to the seamless operation of modern societies, encompassing sectors such as energy, healthcare, transportation, and communications. Ensuring their reliability, performance, continuous operation, safe...
DOAJ
Open Access (DOAJ)
DOI: 10.31891/csit-2025-2-3
Nishith Reddy Mannuru, Sakib Shahriar, Zoë Abbie Teel, Ting Wang et al. • Information Development
(2023)
This paper explores the potential impact of Generative Artificial Intelligence (Generative AI) on developing countries, considering both positive and negative effects across various domains of information, culture, and industry. Generative ...
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DOI: https://doi.org/10.1177/02666669231200628
Nitin Rane, Mallikarjuna Paramesha, Saurabh Choudhary, Jayesh Rane • Journal of Applied Artificial Intelligence
(2024)
In an increasingly complex and unpredictable world, resilience-the ability to withstand and recover from adverse conditions is essential across various sectors. This research paper investigates the transformative potential of artificial int...
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DOI: https://doi.org/10.2139/ssrn.4831911
Hoda Zamani, Mohammad H. Nadimi-Shahraki, Seyedali Mirjalili • International Journal of Computational Intelligence Systems
(2026)
Abstract —Large-scale engineering optimization problems, characterized by hundreds or thousands of decision variables, complex constraints, and highly nonlinear objective functions, present significant challenges for conventional optimizati...
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Open Access (DOAJ)
DOI: 10.1007/s44196-026-01291-2