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Academic Articles & Research Papers
Showing 20 of 528 academic articles
Péter Wittek (2014)
Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that expla...
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Jared D. Weidman, Manas Sajjan, Camille A. Mikolas, Zachary J. Stewart et al. • Cell Reports Physical Science
(2024)
As the year-to-year gains in speeds of classical computers continue to taper off, computational chemists are increasingly examining quantum computing as a possible route to achieve greater computational performance. Quantum computers, built...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.xcrp.2024.102105
Aneesh Khole, Atharva Thakar, Avadhoot Kulkarni, Hrithik Jadhav et al. • arXiv (Cornell University)
(2023)
Computer systems have evolved over the years starting from sizable, single-user, slow, and expensive machines to multi-user, fast, cheaper, and small-sized machines. The use of multi-user computer networks has given rise to a new paradigm o...
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public-domain
DOI: https://doi.org/10.48550/arxiv.2302.03990
Vivek S Kale • CRC Press eBooks
(2018)
The origins of big data technologies come from database systems and distributed systems as well as data mining and machine learning algorithms that can process these vast amounts of data to extract the necessary knowledge. This chapter addr...
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DOI: https://doi.org/10.1201/9780429453311-9
Colin Fidge • IEEE Software
(1996)
It's difficult to determine event order in distributed systems because of the observability problem. The author discusses this problem and evaluates different strategies for determining arrival order. The author analyzed four time stamping ...
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DOI: https://doi.org/10.1109/52.542297
Farhad Foroughi, Peter Luksch (2018)
Cybersecurity solutions are traditionally static and signature-based.The traditional solutions along with the use of analytic models, machine learning and big data could be improved by automatically trigger mitigation or provide relevant aw...
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Open Access
DOI: https://doi.org/10.5121/csit.2018.80401
Jay D. Johnson, Benjamin Anderson, Brian Wright, Jimmy Quiroz et al. (2022)
As the U.S. electrifies the transportation sector, cyberattacks targeting vehicle charging could impact several critical infrastructure sectors including power systems, manufacturing, medical services, and agriculture. This is a growing are...
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Open Access
DOI: https://doi.org/10.2172/1877784
Jongkil Jay Jeong, Joanne Mihelcic, Gillian Oliver, Carsten Rudolph • IEEE International Conference on Collaboration and Internet Computing (CIC)
(2019)
Cybersecurity cannot be addressed by technology alone; the most intractable aspects are in fact sociotechnical. As a result, the 'human factor' has been recognised as being the weakest and most obscure link in creating safe and secure digit...
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Open Access
DOI: https://doi.org/10.1109/cic48465.2019.00047
Scott R. Boss, Joy Gray, Diane Joyce Janvrin • Issues in Accounting Education
(2022)
ABSTRACT In today's business world, it is essential that accountants be concerned about cybersecurity in their organizations and in the work they perform. Despite increasing importance as well as regulatory and professional emphasis, most a...
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DOI: https://doi.org/10.2308/issues-2021-001
Gregory B. White, Natalie Sjelin • IGI Global eBooks
(2021)
With the increase in cybercrimes over the last few years, a growing realization for the need for cybersecurity has begun to be recognized by the nation. Unfortunately, being aware that cybersecurity is something you need to worry about and ...
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DOI: https://doi.org/10.4018/978-1-6684-3698-1.ch003
Dipankar Dasgupta, Zahid Akhtar, Sajib Sen • The Journal of Defense Modeling and Simulation Applications Methodology Technology
(2020)
Today’s world is highly network interconnected owing to the pervasiveness of small personal devices (e.g., smartphones) as well as large computing devices or services (e.g., cloud computing or online banking), and thereby each passing minut...
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DOI: https://doi.org/10.1177/1548512920951275
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
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
Anand Handa, Ashu Sharma, Sandeep K. Shukla • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
(2019)
Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty. Examples include malware analysis, especially for zero‐day malware detection, threat a...
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DOI: https://doi.org/10.1002/widm.1306
Elias Dritsas, Μαρία Τρίγκα • Future Internet
(2025)
The proliferation of the Internet of Things (IoT) has transformed the digital landscape, enabling a vast array of interconnected devices to communicate and share data seamlessly. However, the rapid expansion of IoT networks has also introdu...
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DOI: https://doi.org/10.3390/fi17010030
Vipin Kumar • IEEE Distributed Systems Online
(2005)
Parallel and distributed data mining offer great promise for addressing cybersecurity. The Minnesota Intrusion Detection System can detect sophisticated cyberattacks on large-scale networks that are hard to detect using signature-based syst...
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DOI: https://doi.org/10.1109/mdso.2005.53
V Geetha, C.K. Gomathy, Mr.D.Sri Datta Vallab Yaratha Yagn, Sai Praneesh • INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
(2023)
Natural Language Processing (NLP) is a rapidly evolving field in the intersection of computer science, artificial intelligence, and linguistics. This article provides an overview of NLP, tracing its historical development from early rule-ba...
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Open Access
DOI: https://doi.org/10.55041/ijsrem27094
Zhiyuan Liu, Yankai Lin, Maosong Sun • Springer eBooks
(2020)
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for NLP. It also benefit related domains such as machine learning, social network analysis, semantic Web, infor...
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DOI: https://doi.org/10.1007/978-981-15-5573-2
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
Richard J. Mammone (1994)
Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...
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