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Academic Articles & Research Papers
Showing 20 of 896 academic articles
Kristen E. Eichensehr • SSRN Electronic Journal
(2016)
Calls for public-private partnerships to address U.S. cybersecurity failures have become ubiquitous. But the academic literature and public debate have not fully appreciated the extent to which the United States has already backed into a de...
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Open Access
Sherali Zeadally, Erwin Adi, Zubair Ahmed Baig, Imran Ali Khan • IEEE Access
(2020)
Cybersecurity is a fast-evolving discipline that is always in the news over the last decade, as the number of threats rises and cybercriminals constantly endeavor to stay a step ahead of law enforcement. Over the years, although the origina...
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DOI: https://doi.org/10.1109/access.2020.2968045
Mohammad Alauthman, Ammar Almomani, Ahmad Al–Qerem, Mohammad Ali Al Khaldy et al. • Advances in information security, privacy, and ethics book series
(2024)
This chapter explores the impact of quantum computing on cybersecurity, comparing classical and quantum techniques. It provides an overview of the current quantum landscape, focusing on the threats posed by quantum algorithms to traditional...
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DOI: https://doi.org/10.4018/979-8-3693-5330-1.ch004
Bo Yan, Cheng Hong Yang, Chuan Shi, Yong Fang et al. • ACM Transactions on Knowledge Discovery from Data
(2023)
The explosive growth of cyber attacks today, such as malware, spam, and intrusions, has caused severe consequences on society. Securing cyberspace has become a great concern for organizations and governments. Traditional machine learning ba...
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Open Access
DOI: https://doi.org/10.1145/3610228
Benoît Dupont, Chad Whelan • Journal of Criminology
(2021)
‘Cybercrime’ is an umbrella concept used by criminologists to refer to traditional crimes that are enhanced via the use of networked technologies (i.e. cyber-enabled crimes) and newer forms of crime that would not exist without networked te...
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DOI: https://doi.org/10.1177/00048658211003925
Pan Singh Dhoni, Ravinder Kumar (2023)
The digital landscape of the modern world has witnessed a remarkable evolution over the past few decades, with technological advancements permeating every facet of our lives. While these innovations have brought forth unprecedented convenie...
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DOI: https://doi.org/10.36227/techrxiv.23968809.v1
Farzad Nourmohammadzadeh Motlagh, Mehrdad Hajizadeh, Mehryar Majd, Pejman Najafi et al. • International Conference on Information Systems Security and Privacy (ICISSP)
(2025)
The rise of Large Language Models (LLMs) has revolutionized our comprehension of intelligence bringing us closer to Artificial Intelligence. Since their introduction, researchers have actively explored the applications of LLMs across divers...
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DOI: https://doi.org/10.5220/0013377600003899
Alessandro Pollini, Tiziana C. Callari, Alessandra Tedeschi, Daniele Ruscio et al. • Cognition Technology & Work
(2021)
Computer and Information Security (CIS) is usually approached adopting a technology-centric viewpoint, where the human components of sociotechnical systems are generally considered as their weakest part, with little consideration for the en...
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DOI: https://doi.org/10.1007/s10111-021-00683-y
PMC: 8195225
Renáta Németh, Júlia Koltai • Intersections
(2023)
Natural language processing (NLP) methods are designed to automatically process and analyze large amounts of textual data. The integration of this new-generation toolbox into sociology faces many challenges. NLP was institutionalized outsid...
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DOI: https://doi.org/10.17356/ieejsp.v9i1.871
Yang Liu, Meng Zhang • Computational Linguistics
(2017)
Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...
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DOI: https://doi.org/10.1162/coli_r_00312
Santanu Pattanayak • Apress eBooks
(2022)
In the modern age of information and analytics, natural language processing (NLP) is one of the most important technologies out there. Making sense of complex structures in language and deriving insights and actions from it are crucial from...
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DOI: https://doi.org/10.1007/978-1-4842-8931-0_4
Mitchell P. Marcus • Proceedings of the National Academy of Sciences
(1995)
The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. R...
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Open Access
DOI: https://doi.org/10.1073/pnas.92.22.10052
PMC: 40734
Jianlin Cheng, Zheng Wang, Gianluca Pollastri • International Joint Conference on Neural Networks (IJCNN)
(2008)
Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional neural network to learn ordinal categories. Our approach is a gen...
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Open Access
DOI: https://doi.org/10.1109/ijcnn.2008.4633963
Abhijit S. Pandya, Robert B. Macy • CRC Press eBooks
(2021)
From the Publisher:
The addition of artificial neural network computing to traditionalpattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical gui...
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DOI: https://doi.org/10.1201/9780138744274
Igor I. Baskin, David Alan Winkler, Igor V. Tetko • Expert Opinion on Drug Discovery
(2016)
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...
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DOI: https://doi.org/10.1080/17460441.2016.1201262
R. Glen Donaldson, Mark J. Kamstra • Journal of Forecasting
(1996)
This paper investigates the use of Artificial Neural Networks (ANNs) to combine time series forecasts of stock market volatility from the USA, Canada, Japan and the UK. We demonstrate that combining with nonlinear ANNs generally produces fo...
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DOI: https://doi.org/10.1002/(sici)1099-131x(199601)15:1<49::aid-for604>3.0.co;2-2
Vivek Prakash Nigam, Daniel Graupe • Neurological Research
(2004)
Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced ne...
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DOI: https://doi.org/10.1179/016164104773026534
Tim Hill, Marcus J. O’Connor, William Remus • Management Science
(1996)
Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series ...
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DOI: https://doi.org/10.1287/mnsc.42.7.1082
Pooja Jain, Makarand Chintamani Deo • Ships and Offshore Structures
(2005)
The soft computing technique of neural network is being extensively used across all disciplines of ocean engineering, namely, offshore, coastal, and deep-ocean engineering including marine engineering. This paper takes a stock of the resear...
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DOI: https://doi.org/10.1533/saos.2004.0005
Danilo P. Mandic, Jonathon A. Chambers • Wiley eBooks
(2001)
New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) ...
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DOI: https://doi.org/10.1002/047084535x