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Academic Articles & Research Papers
Showing 20 of 88 academic articles
Zhihui Song, Xin Zhou, Jinchen Xu, Xiaodong Ding et al. • Scientific Reports
(2024)
Abstract In recent years, deep learning has been widely used in vulnerability detection with remarkable results. These studies often apply natural language processing (NLP) technologies due to the natural similarity between code and languag...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-63021-y
Gabriele Amante, Judit E. Sponer, Jiri Sponer, Franz Saija et al. • Entropy
(2022)
The search for the chemical origins of life represents a long-standing and continuously debated enigma. Despite its exceptional complexity, in the last decades the field has experienced a revival, also owing to the exponential growth of the...
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Open Access (DOAJ)
DOI: 10.3390/e24081012
Michael J. Butler, Marina Waldén • ePrints Soton (University of Southampton)
(1996)
The B-Method is a method for the stepwise derivation of sequential programs. In this paper we show how the B-Method can be used for designing distributed systems by embedding action systems within this method. The action system formalism is...
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Kalyan Chakradhar Regula • Advances in computational intelligence and robotics book series
(2025)
Artificial Intelligence (AI) and Cybersecurity have become deeply intertwined, shaping the future of digital safety and resilience. As AI-driven solutions enhance threat detection, automation, and response mechanisms, cybersecurity safeguar...
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DOI: https://doi.org/10.4018/979-8-3373-1142-5.ch015
Peratham Wiriyathammabhum, Douglas A. Summers-Stay, Cornelia M. Fermuller, Yiannis Aloimonos • ACM Computing Surveys
(2016)
Integrating computer vision and natural language processing is a novel interdisciplinary field that has received a lot of attention recently. In this survey, we provide a comprehensive introduction of the integration of computer vision and ...
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DOI: https://doi.org/10.1145/3009906
Jonah A. Berger, Grant M. Packard • American Psychologist
(2021)
Language can provide important insights into people, and culture more generally. Further, the digitization of information has made more and more textual data available. But by itself, all that data are just that: data. Realizing its potenti...
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Open Access
DOI: https://doi.org/10.1037/amp0000882
Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann • arXiv (Cornell University)
(2018)
Hyperbolic spaces have recently gained momentum in the context of machine learning due to their high capacity and tree-likeliness properties. However, the representational power of hyperbolic geometry is not yet on par with Euclidean geomet...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1805.09112
Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami et al. • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
(2019)
Representation learning in heterogeneous graphs aims to pursue a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This...
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Open Access
DOI: https://doi.org/10.1145/3292500.3330961
Stephan Rasp, Sebastian Lerch • Monthly Weather Review
(2018)
Abstract Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the pa...
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other-oa
DOI: https://doi.org/10.1175/mwr-d-18-0187.1
Wei Chen, Yu Liu, Weiping Wang, Erwin M. Bakker et al. • IEEE Transactions on Pattern Analysis and Machine Intelligence
(2022)
In recent years a vast amount of visual content has been generated and shared from many fields, such as social media platforms, medical imaging, and robotics. This abundance of content creation and sharing has introduced new challenges, par...
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Open Access
DOI: https://doi.org/10.1109/tpami.2022.3218591
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3646589
Andreas E. Robertson, Samuel B. Inman, Ashley T. Lenau, Ricardo A. Lebensohn et al. • npj Computational Materials
(2026)
Abstract Aleatoric uncertainties – irremovable variability in microstructure morphology, constituent behavior, and processing conditions – pose a major challenge to developing uncertainty-robust digital twins. We introduce the Variational D...
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Open Access (DOAJ)
DOI: 10.1038/s41524-026-02054-5
Shihao Zhang, Yanhui Xiao, Huawei Tian, Xiaolong Li • Cybersecurity
(2025)
Abstract Unlike single-image steganography, the scheme of payload distribution on different images plays a pivotal role in the security performance of multi-image steganography. In this paper, a novel multi-image steganography scheme: image...
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Open Access (DOAJ)
DOI: 10.1186/s42400-024-00333-6
Kai-Wei Chang, Vinod M. Prabhakaran, Vicente Ordóñez • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2019)
Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...
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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. ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math14020299
Imran Mirza, Akbar Anbar Jafari, Cagri Ozcinar, Gholamreza Anbarjafari • Information
(2025)
Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...
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Open Access (DOAJ)
DOI: 10.3390/info16050358
Hind Alamro, Takashi Gojobori, Magbubah Essack, Xin Gao • Scientific Reports
(2024)
Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-58334-x
Asefeh Asemi, Rajab Kiani Shahvandy, Mahdi Houshangi • International Journal of Information Management Data Insights
(2026)
Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jjimei.2026.100396
Jan Kinne, Robert Dehghan, Sebastian Schmidt, David Lenz et al. • International Journal of Information Management Data Insights
(2024)
While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy ...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jjimei.2024.100287
Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T. Dudley, Alberto Lavelli et al. • JMIR Medical Informatics
(2019)
BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...
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DOI: https://doi.org/10.2196/12239
PMC: 6528438