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Academic Articles & Research Papers
Showing 20 of 979 academic articles
Dean Brand, Domenica Dibenedetto, Francesco Petruccione • Physical Review Research
(2026)
We present a theoretical framework for a quantized memristive Leaky Integrate-and-Fire (LIF) neuron, uniting principles from neuromorphic engineering and open quantum systems. Starting from a classical memristive LIF circuit, we apply canon...
DOAJ
Open Access (DOAJ)
DOI: 10.1103/y61v-2bxf
Kamal Hossain Nahin, Jamal Hossain Nirob, Akil Ahmad Taki, Md Ashraful Haque et al. • Scientific Reports
(2025)
Abstract This paper introduces the design and exploration of a compact, high-performance multiple-input multiple-output (MIMO) antenna for 6G applications operating in the terahertz (THz) frequency range. Leveraging a meta learner-based sta...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-88174-2
Chun-Sung Jao, Chiung-Yin Chang, Kun-Han Lee, Hsiao-Hsuan Lin et al. • APL Machine Learning
(2026)
Reconstructing multidimensional vector fields from path-integrated projection data is a fundamental challenge in high-energy-density physics, particularly when experimental sources exhibit spectral broadening and shot-to-shot jitter. We pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1063/5.0331075
Maad Mijwil, Israa Ezzat Salem, Marwa M. Ismaeel • Iraqi Journal for Computer Science and Mathematics
(2023)
People in the modern era spend most of their lives in virtual environments that offer a range of public and private services and social platforms. Therefore, these environments need to be protected from cyber attackers that can steal data o...
DOAJ
Open Access (DOAJ)
DOI: 10.52866/ijcsm.2023.01.01.008
Rafał Kozik, Marek Pawlicki, Michał Choraś, Witold Pedrycz • Complexity
(2019)
Network and information security are regarded as some of the most pressing problems of contemporary economy, affecting both individual citizens and entire societies, making them a highlight for homeland security. Innovative approaches to ha...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2019/5826737
Giovanni Apruzzese, Pavel Laskov, Edgardo Montes de, Wissam Mallouli et al. • Digital Threats Research and Practice
(2022)
Machine Learning (ML) represents a pivotal technology for current and future information systems, and many domains already leverage the capabilities of ML. However, deployment of ML in cybersecurity is still at an early stage, revealing a s...
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Open Access
DOI: https://doi.org/10.1145/3545574
Fábio Eid Morooka, Adalberto Manoel Junior, Tiago F. A. C. Sigahi, Jefferson de Souza Pinto et al. • Machine Learning and Knowledge Extraction
(2023)
Applications of deep learning (DL) in autonomous vehicle (AV) projects have gained increasing interest from both researchers and companies. This has caused a rapid expansion of scientific production on DL-AV in recent years, encouraging res...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/make5030041
Aditya Kuppa, Nhien‐An Le‐Khac • IEEE Transactions on Information Forensics and Security
(2021)
Machine Learning methods are playing a vital role in combating ever-evolving threats in the cybersecurity domain. Explanation methods that shed light on the decision process of black-box classifiers are one of the biggest drivers in the suc...
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DOI: https://doi.org/10.1109/tifs.2021.3117075
Bimal Ghimire, Danda B. Rawat • IEEE Internet of Things Journal
(2022)
Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the emerging Internet of Things (IoT) has gained a lot of attention from the government, academia, and industries in recent years. Federated cybersecurity (F...
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DOI: https://doi.org/10.1109/jiot.2022.3150363
Vinden Wylde, Nisha Rawindaran, John Lawrence, Rushil Balasubramanian et al. • SN Computer Science
(2022)
In this paper, we identify and review key challenges to bridge the knowledge-gap between SME's, companies, organisations, businesses, government institutions and the general public in adopting, promoting and utilising Blockchain technology....
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DOI: https://doi.org/10.1007/s42979-022-01020-4
PMC: 8753328
Gaith Rjoub, Jamal Bentahar, Omar Abdel Wahab, Rabeb Mizouni et al. • IEEE Transactions on Network and Service Management
(2023)
The “black-box” nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create mac...
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Open Access
DOI: https://doi.org/10.1109/tnsm.2023.3282740
Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi et al. • Communications Materials
(2022)
Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials...
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DOI: https://doi.org/10.1038/s43246-022-00315-6
PMC: 9702700
Valery Dmitrievich Solovyev, Marina Ivanovna Solnyshkina, Danielle S. McNamara • Russian Journal of Linguistics
(2022)
The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic ana...
DOAJ
Open Access (DOAJ)
DOI: 10.22363/2687-0088-31326
Melissa N. Poulsen, Philip J. Freda, Vanessa Troiani, Anahita Davoudi et al. • Frontiers in Public Health
(2022)
BackgroundOpioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of O...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpubh.2022.850619
Qingxia Chen • Discover Artificial Intelligence
(2025)
Abstract This study explores the application of artificial intelligence (AI) in improving the trial efficiency of criminal cases. Using a dataset consisting of 500 criminal case records, including minor, ordinary, and complex cases, we appl...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-025-00353-2
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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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...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-025-00813-9
Cyrille YetuYetu Kesiku, Andrea Chaves-Villota, Begonya Garcia-Zapirain • Information
(2022)
The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatmen...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info13100499
Jalaj Thanaki (2017)
Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...
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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