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Academic Articles & Research Papers
Showing 20 of 654 academic articles
Henrique M. D. Santos • Chapman & Hall/CRC eBooks
(2022)
Cybersecurity: A Practical Engineering Approach introduces the implementation of a secure cyber architecture, beginning with the identification of security risks. It then builds solutions to mitigate risks by considering the technological j...
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DOI: https://doi.org/10.1201/9780429286742
Evan M. Selinger, Albert Fox Cahn • Cambridge University Press eBooks
(2026)
In Chapter 9, we argue that cybersecurity professionals embody the ideal of the careful, systematic upgrading that Move Slow and Upgrade has been advocating for. Unlike the flashy innovations that we’ve criticized in earlier chapters, cyber...
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DOI: https://doi.org/10.1017/9781009466592.010
C. P. Gupta, K. K. Goyal • De Gruyter eBooks
(2024)
This book is designed to provide the reader with the fundamental concepts of cybersecurity and cybercrime in an easy to understand, “self-teaching” format. It introduces all of the major subjects related to cybersecurity, including data sec...
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DOI: https://doi.org/10.1515/9781683924968
• The MIT Press eBooks
(2018)
Experts from MIT explore recent advances in cybersecurity, bringing together management, technical, and sociological perspectives. Ongoing cyberattacks, hacks, data breaches, and privacy concerns demonstrate vividly the inadequacy of existi...
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DOI: https://doi.org/10.7551/mitpress/11636.001.0001
Ishaani Priyadarshini • Wiley eBooks
(2019)
This chapter contains sections titled: Introduction to Cybersecurity Cybersecurity Objectives Cybersecurity Infrastructure and Internet Architecture (NIST) Cybersecurity Roles Cybercrimes Security Models Computer Forensics Cyber Insurance F...
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DOI: https://doi.org/10.1002/9781119488330.ch1
Leonardo Ferreira, Daniel Castro Silva, Mikel Uriarte • Knowledge and Information Systems
(2023)
Abstract With the growth of CyberTerrorism, enterprises worldwide have been struggling to stop intruders from obtaining private data. Despite the efforts made by Cybersecurity experts, the shortage of skillful security teams and the usage o...
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DOI: https://doi.org/10.1007/s10115-023-01906-6
Junjian Qi, Adam Hahn, Xiaonan Lu, Jianhui Wang et al. • IET Cyber-Physical Systems Theory & Applications
(2016)
The increased penetration of distributed energy resources (DER) will significantly increase the number of devices that are owned and controlled by consumers and third‐parties. These devices have a significant dependency on digital communica...
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cc-by-nc
DOI: https://doi.org/10.1049/iet-cps.2016.0018
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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cc-by-nc-nd
DOI: https://doi.org/10.1162/coli_r_00312
George N. Bebis, Michael Georgiopoulos • IEEE Potentials
(1994)
One critical aspect neural network designers face today is choosing an appropriate network size for a given application. Network size involves in the case of layered neural network architectures, the number of layers in a network, the numbe...
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Open Access
DOI: https://doi.org/10.1109/45.329294
Martin Sundermeyer, Ralf Schlüter, Hermann Ney • Interspeech (USB)
(2012)
Neural networks have become increasingly popular for the task of language modeling.Whereas feed-forward networks only exploit a fixed context length to predict the next word of a sequence, conceptually, standard recurrent neural networks ca...
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Open Access
DOI: https://doi.org/10.21437/interspeech.2012-65
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
T. Sorsa, Heikki N. Koivo, Hannu J. Koivisto • IEEE Transactions on Systems Man and Cybernetics
(1991)
Fault detection and diagnosis is an important problem in process automation. Both model-based methods and expert systems have been suggested to solve the problem, along with the pattern recognition approach. A number of possible neural netw...
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DOI: https://doi.org/10.1109/21.108299
Omid M. Omidvar • Ablex Pub. Corp. eBooks
(1991)
Receptive field calculus, Jan J. Koenderink visual reconstruction and data fusion, D. Suter visual perception of translational and rotational motion, Jim-Shih Liaw, Irwin K. King and Michael A. Arbib neural network for recovering observer m...
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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
M.T. Hagan, H.B. Demuth • Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
(1999)
Provides a quick overview of neural networks and explains how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorit...
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DOI: https://doi.org/10.1109/acc.1999.786109
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele et al. • arXiv (Cornell University)
(2018)
In recent years, deep neural networks have revolutionized many application domains of machine learning and are key components of many critical decision or predictive processes. Therefore, it is crucial that domain specialists can understand...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1808.04260
J. Lee, Ronald C. Weger, S.K. Sengupta, Ronald M. Welch • IEEE Transactions on Geoscience and Remote Sensing
(1990)
It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery ...
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DOI: https://doi.org/10.1109/36.58972
Timothy X. Brown • IEEE Communications Magazine
(1989)
The author argues that a strong impetus for using neural networks is that they provide a framework for designing massively parallel machines. He notes that the highly interconnected architecture of switching networks suggests similarities t...
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DOI: https://doi.org/10.1109/35.41403
Lorenzo De Marinis, Marco Cococcioni, P. Castoldi, Nicola Andriolli • IEEE Access
(2019)
Photonic solutions are today a mature industrial reality concerning high speed, high throughput data communication and switching infrastructures. It is still a matter of investigation to what extent photonics will play a role in next-genera...
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DOI: https://doi.org/10.1109/access.2019.2957245
Steven Walczak • Advances in computer and electrical engineering book series
(2018)
This chapter examines the history of artificial neural networks research through the present day. The components of artificial neural network architectures and both unsupervised and supervised learning methods are discussed. Although a step...
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DOI: https://doi.org/10.4018/978-1-5225-7368-5.ch004