Zobrazeno 1 - 10
of 537
pro vyhledávání: '"A. J. Michaels"'
Autor:
Jack Kolenbrander, Ethan Husmann, Christopher Henshaw, Elliott Rheault, Madison Boswell, Alan J. Michaels
Publikováno v:
Journal of Cybersecurity and Privacy, Vol 4, Iss 3, Pp 546-571 (2024)
When personal information is shared across the Internet, we have limited confidence that the designated second party will safeguard it as we would prefer. Privacy policies offer insight into the best practices and intent of the organization, yet most
Externí odkaz:
https://doaj.org/article/0aa64aeed83f408ea248626738013f94
Autor:
Elliott Rheault, Mary Nerayo, Jaden Leonard, Jack Kolenbrander, Christopher Henshaw, Madison Boswell, Alan J. Michaels
Publikováno v:
Journal of Cybersecurity and Privacy, Vol 4, Iss 3, Pp 572-593 (2024)
In most open-source intelligence (OSINT) research efforts, the collection of information is performed in an entirely passive manner as an observer to third-party communication streams. This paper describes ongoing work that seeks to insert itself int
Externí odkaz:
https://doaj.org/article/cd1187efb4a844e78e4fe7caaf404a40
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 1699-1719 (2024)
The use of transfer learning (TL) techniques has become common practice in fields such as computer vision (CV) and natural language processing (NLP). Leveraging prior knowledge gained from data with different distributions, TL offers higher performan
Externí odkaz:
https://doaj.org/article/17be79b1859f4f8593d083d7aa40496b
Autor:
William H. Clark, Alan J. Michaels
Publikováno v:
Telecom, Vol 5, Iss 3, Pp 632-651 (2024)
The data used during training in any given application space are directly tied to the performance of the system once deployed. While there are many other factors that are attributed to producing high-performance models based on the Neural Scaling Law
Externí odkaz:
https://doaj.org/article/f25e0009ea4941aa8ee49a12eb22baee
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 2, Pp 1210-1242 (2024)
Transfer learning (TL) techniques, which leverage prior knowledge gained from data with different distributions to achieve higher performance and reduced training time, are often used in computer vision (CV) and natural language processing (NLP), but
Externí odkaz:
https://doaj.org/article/43187fdd23d745d98281d08a5e5ec009
Autor:
Ashton L. Sigler, Scott B. Thompson, Logan Ellwood-Digel, Adithan Kandasamy, Mary J. Michaels, Dean Thumkeo, Shuh Narumiya, Juan C. Del Alamo, Jordan Jacobelli
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
Lymphocyte trafficking and migration through tissues is critical for adaptive immune function and, to perform their roles, T cells must be able to navigate through diverse tissue environments that present a range of mechanical challenges. T cells pre
Externí odkaz:
https://doaj.org/article/8d8a242143d24c529f8431db63d56272
Publikováno v:
Journal of Obstetrics and Gynaecology, Vol 44, Iss 1 (2024)
AbstractBackground Coronavirus (COVID-19) pandemic has affected the training and wellbeing of obstetrics and gynaecology (O&G) trainees. The aim of this review is to offer a worldwide overview on its’ impact on the mental health of O&G trainees, so
Externí odkaz:
https://doaj.org/article/3bf36d5d2db3482782f115ca4f04953c
Publikováno v:
IEEE Access, Vol 12, Pp 80327-80344 (2024)
Performance of radio frequency machine learning (RFML) models for classification tasks such as specific emitter identification (SEI) and automatic modulation classification (AMC) have improved greatly since their introduction, especially when measure
Externí odkaz:
https://doaj.org/article/ff17706b2a594d7eac6f6adfa6eacb69
Publikováno v:
Sensors, Vol 24, Iss 11, p 3574 (2024)
Transfer learning (TL) techniques have proven useful in a wide variety of applications traditionally dominated by machine learning (ML), such as natural language processing, computer vision, and computer-aided design. Recent extrapolations of TL to t
Externí odkaz:
https://doaj.org/article/4757a137f2864f30aabd65ce4a872816
Publikováno v:
Sensors, Vol 24, Iss 7, p 2113 (2024)
The timely delivery of critical messages in real-time environments is an increasing requirement for industrial Internet of Things (IIoT) networks. Similar to wired time-sensitive networking (TSN) techniques, which bifurcate traffic flows based on pri
Externí odkaz:
https://doaj.org/article/a0c799ed7b7247f89e6afa4dcf0be8d7