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Academic Articles & Research Papers
Showing 20 of 108 academic articles
Jieyu Xie, Xingying Chen, Kun Yu, Lei Gan et al. • Energies
(2024)
In the context of rapid growth in renewable energy installations and increasingly severe consumption issues, this paper designs a 100% green electricity supplied zero-carbon integrated energy station. It aims to analyze its configuration fo...
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Open Access (DOAJ)
DOI: 10.3390/en17164111
Jingzhong ZHANG, Fei MENG, Yang SUN, Huixia YU • Zhongguo dianli
(2024)
A dual-layer robust optimization control method based on the droop principle of reactive power and voltage is proposed for renewable energy in distribution networks, considering active power uncertainties. First, in the reference-point opti...
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Open Access (DOAJ)
DOI: 10.11930/j.issn.1004-9649.202310053
Sapthak Mohajon Turjya, Mulham Fawakherji • IEEE Access
(2025)
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose diagnosis relies heavily on subjective behavioral assessments. Electroencephalography (EEG) provides an inexpensive and non-invasive method of objective biomarker detect...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3646589
Yicen Liu, Ying Chen, Prithwineel Paul, Songhai Fan et al. • Applied Sciences
(2021)
With the advancement of technologies it is becoming imperative to have a stable, secure and uninterrupted supply of power to electronic systems as well as to ensure the identification of faults occurring in these systems quickly and efficie...
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Open Access (DOAJ)
DOI: 10.3390/app11104376
Fanjie Meng • Kuwait Journal of Science
(2026)
Sports injuries significantly affect sports performance and overall health, making using accurate and reliable prognostic models imperative. Conventional algorithms for injury prediction, e.g., random forest and XGBoost, generally cannot un...
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Open Access (DOAJ)
DOI: https://doi.org/10.1016/j.kjs.2026.100589
Parul Dubey, Pushkar Dubey, Pitshou N. Bokoro • Forecasting
(2025)
Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow...
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Open Access (DOAJ)
DOI: 10.3390/forecast7020031
Hao Yi, Bo Liu, Bin Zhao, Enhai Liu • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2024)
Due to the limitations of small targets in remote sensing images, such as background noise, poor information, and so on, the results of commonly used detection algorithms in small target detection is not satisfactory. To improve the accurac...
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Open Access (DOAJ)
DOI: 10.1109/JSTARS.2023.3339235
Bing Li, Jiangtao Dong, Xile Wang, Yuqi Hou et al. • IEEE Access
(2025)
To investigate the impact of cross-grained sentiments on user feature representation and address the issue of data sparsity, this paper proposes a Personalized Recommendation Algorithm Integrating Cross-Grained Sentiment and Rating Interact...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3530431
You Li Chong, Chin Poo Lee, Shahrin Zen Muhd-Yassin, Kian Ming Lim et al. • IEEE Access
(2024)
Knowledge Graph Question Answering (KGQA) plays a crucial role in extracting valuable insights from interconnected information. Existing methods, while commendable, face challenges such as contextual ambiguity and limited adaptability to di...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3405583
Georgiana Țucudean, Marian Bucos, Bogdan Drăgulescu, Cătălin Daniel Căleanu • PeerJ Computer Science
(2024)
Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the ma...
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DOI: https://doi.org/10.7717/peerj-cs.2222
PMC: 11322986
Mahmoud S. Mayaleh, Samer A. Mayaleh • Discover Artificial Intelligence
(2026)
Abstract Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models. This study evaluates and compares the effectiveness of three data augmentation strategies: Easy Data Augm...
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Open Access (DOAJ)
DOI: 10.1007/s44163-025-00813-9
Jantima Polpinij, Manasawee Kaenampornpan, Christopher S. G. Khoo, Wei-Ning Cheng et al. • Mathematics
(2026)
Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...
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Open Access (DOAJ)
DOI: 10.3390/math14020299
Yuan Huang, Zhixing Li, Wei Deng, Guoyin Wang et al. • CAAI Transactions on Intelligence Technology
(2021)
Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text class...
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Open Access (DOAJ)
DOI: 10.1049/cit2.12033
Rui Zhao, Haofeng Hu, Yun Li, Yuze Fan et al. • Sensors
(2024)
Urban traffic congestion poses significant economic and environmental challenges worldwide. To mitigate these issues, Adaptive Traffic Signal Control (ATSC) has emerged as a promising solution. Recent advancements in deep reinforcement lear...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24196202
Supriyono Supriyono, Aji Prasetya Wibawa, Suyono Suyono, Fachrul Kurniawan • Telematics and Informatics Reports
(2024)
This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...
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DOI: https://doi.org/10.1016/j.teler.2024.100173
Aditya Malte, Pratik Ratadiya • arXiv (Cornell University)
(2019)
In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1910.07370
Rosana Abdoune, Lydia Lazib, Farida Dahmani-Bouarab, Nada Mimouni • Inteligencia Artificial
(2024)
In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...
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Open Access (DOAJ)
Ante Grgurevic, Marina Bagic Babac • IEEE Access
(2025)
In this paper, we introduce Vox Calculi, a system designed to solve mathematical problems using voice transcriptions. By leveraging state-of-the-art pretrained Automatic Speech Recognition (ASR) models, we accurately transcribe users’...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3564121
Cristian Cosentino, Simone Gatto, Pietro Liò, Fabrizio Marozzo • Future Internet
(2026)
Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi18030174
Guoyu Zuo, Minghui Zhang, Jingwei Ren, Qifei Wu et al. • CAAI Transactions on Intelligence Technology
(2026)
ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...
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Open Access (DOAJ)
DOI: 10.1049/cit2.70165