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Academic Articles & Research Papers
Showing 20 of 142 academic articles
Adiah Qazi, Sadiqa Arshad, Ammad Ali Khan Jadoon • Scientific Reports
(2026)
Abstract Enterprise Resource Planning (ERP) systems serve as critical infrastructure for modern organizations, yet their security assessment lacks standardized evaluation frameworks. This study develops and applies a structured Security Mat...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-45550-w
Димитра Пантели, Keyrellous Adib, Stefan Buttigieg, Francisco Goiana-da-Silva et al. • The Lancet Public Health
(2025)
Artificial intelligence (AI) can rapidly analyse large and complex datasets, extract tailored recommendations, support decision making, and improve the efficiency of many tasks that involve the processing of data, text, or images. As such, ...
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DOI: https://doi.org/10.1016/s2468-2667(25)00036-2
PMC: 12040707
Li Zhang, Bin Zhang, Anqing Liu, Liudong Xing • Applied Sciences
(2020)
Trust assessment is of great significance to related issues such as privacy protection and rumor transmission in online social networks. At present, there are mainly two types of trust models: discrete type and continuous, type. Little work...
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Open Access (DOAJ)
DOI: 10.3390/app10175854
Zaid Ameen Abduljabbar, Vincent Omollo Nyangaresi, Ahmed Ali Ahmed, Junchao Ma et al. • Scientific Reports
(2025)
Abstract Vehicular Ad-Hoc Networks (VANETs) have facilitated the massive exchange of real-time traffic and weather conditions, which have helped prevent collisions, reduce accidents, and road congestions. This can effectively enhance drivin...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-15011-x
Iago Sestrem Ochôa, Luis Augusto Silva, Gabriel de Mello, Bruno Alves da Silva et al. • Sensors
(2019)
With the popularization of the Internet-of-Things, various applications have emerged to make life easier. These applications generate a large amount of user data. Analyzing the data obtained from these applications, one can infer personal i...
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Open Access (DOAJ)
DOI: 10.3390/s19204483
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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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. ...
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Open Access (DOAJ)
DOI: 10.3390/fi18030174
Glen Coppersmith, Ryan Leary, Patrick Crutchley, Alex B. Fine • Biomedical Informatics Insights
(2018)
Suicide is among the 10 most common causes of death, as assessed by the World Health Organization. For every death by suicide, an estimated 138 people's lives are meaningfully affected, and almost any other statistic around suicide deaths i...
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DOI: https://doi.org/10.1177/1178222618792860
PMC: 6111391
Yasir Abdelgadir Mohamed, Abdul Hakim H. M. Mohamed, Akbar Khanan, Mohamed Bashir et al. • IEEE Access
(2024)
This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclus...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3521945
Donald Shenaj, Giulia Rizzoli, Pietro Zanuttigh • IEEE Access
(2023)
Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...
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DOI: https://doi.org/10.1109/access.2023.3310400
Eirini Cholopoulou, Dimitrios E. Diamantis, Dimitra-Christina C. Koutsiou, Dimitris K. Iakovidis • IEEE Access
(2026)
Effective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, mos...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2026.3728048
Siham Essahraui, Ismail Lamaakal, Yassine Maleh, Khalid El Makkaoui et al. • IEEE Access
(2025)
Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3589938
Bayram B., Leventi N., Vodenicharova A., Lamprianidou A. et al. • Acta Medica Bulgarica
(2026)
Artificial intelligence (AI) is reshaping healthcare by enhancing diagnostic precision, treatment personalization, and overall patient care. By leveraging technologies such as machine learning, deep learning, natural language processing, an...
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Open Access (DOAJ)
DOI: 10.2478/amb-2026-0050
Pedro Teixidó, Juan Antonio Gómez-Galán, Rafael Caballero, Francisco J. Pérez-Grau et al. • Sensors
(2021)
Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The ...
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Open Access (DOAJ)
DOI: 10.3390/s21217379
Muhammad Hussain • IEEE Access
(2024)
This paper implements a systematic methodological approach to review the evolution of YOLO variants. Each variant is dissected by examining its internal architectural composition, providing a thorough understanding of its structural compone...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3378568
Ghenwa Chamouni, Filippo Lococo, Carolina Sassorossi, Nkunzi Atuhaire et al. • Frontiers in Public Health
(2025)
IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...
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Open Access (DOAJ)
DOI: 10.3389/fpubh.2025.1663298
Zhe Sun, Junping Wan, Bin Wang, Zhiqiang Cao et al. • Frontiers in Physics
(2021)
Data-driven deep learning has accelerated the spread of social computing applications. To develop a reliable social application, service providers need massive data on human behavior and interactions. As the data is highly relevant to users...
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Open Access (DOAJ)
DOI: 10.3389/fphy.2021.739259
Iraj Abedi, Mahsa Vali, Bentolhoda Otroshi, Maryam Zamanian et al. • BMC Research Notes
(2024)
Abstract Introduction Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the ...
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Open Access (DOAJ)
DOI: 10.1186/s13104-024-06693-z
Reza Shokri, Vitaly Shmatikov • ACM SIGSAC Conference on Computer and Communications Security (CCS)
(2015)
Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text. The unprecedented accuracy of deep learning methods has turned them into t...
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DOI: https://doi.org/10.1145/2810103.2813687
Jing Liu, Xuesong Hai, Keqin Li • Future Internet
(2023)
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their ...
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Open Access (DOAJ)
DOI: 10.3390/fi16010006