Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Maggie X. Cheng"'
Autor:
Jia He, Maggie X. Cheng
Publikováno v:
Frontiers in Big Data, Vol 4 (2021)
In machine learning, we often face the situation where the event we are interested in has very few data points buried in a massive amount of data. This is typical in network monitoring, where data are streamed from sensing or measuring units continuo
Externí odkaz:
https://doaj.org/article/df3bebb4329a49cba35d9690a18c8885
Publikováno v:
Organizational Cybersecurity Journal: Practice, Process and People. 1:69-91
PurposePhishing attacks are the most common cyber threats targeted at users. Digital nudging in the form of framing and priming may reduce user susceptibility to phishing. This research focuses on two types of digital nudging, framing and priming, an
Autor:
Tipparat Udmuangpia, Maggie X. Cheng, Steven D. Pratscher, James W. Carson, Danielle L. Oyler, An Lin Cheng, Jane M. Armer, Mollie A. Price-Blackshear, B. Ann Bettencourt, Kathie Records
Publikováno v:
Journal of Psychosocial Oncology. 38:592-611
Young breast cancer survivors (YBCS) face unique challenges in coping with disease, distress, and relationship concerns. The purposes of this study were to understand the acceptability and feasibility of an online Mindfulness-Based Intervention (MBI)
Publikováno v:
ICC
Blockchain technology has gained growing popularity in recent years. While the technology works well for most applications, the vulnerability of the blockchain-based system is not well understood. The core part of a blockchain-based system is the con
Autor:
Maggie X. Cheng, Jia He
Publikováno v:
ICPR
In this paper, we consider the power line outage identification problem as a graph signal classification problem, where the signal at each vertex is given as a time series. We propose graph convolutional networks (GCNs) for the task of classifying si
Publikováno v:
ICPR
This paper considers the problem of sparse signal recovery where there is a structure in the signal. Efficient recovery schemes can be designed to leverage the signal structure. Following the model-based compressive sensing framework, we have develop
Publikováno v:
IEEE Transactions on Power Systems. 33:166-173
Many power systems applications such as power flow and short-circuit analysis require very large sparse matrix computations. With the increase in reliance on our electric infrastructure, power systems are continually growing in size, creating greater
Publikováno v:
Theoretical Computer Science. 660:86-101
In wireless ad hoc networks, maintaining network connectivity is very important as high level network functions all depend on it. However, how to measure network connectivity remains a fundamental challenge. For example, a network can have good overa
Publikováno v:
IEEE Internet of Things Journal. 3:979-985
When the grid topology is changed due to incidents and the state estimator is not updated with the topological change, it is considered a topology error. In this paper, we develop a new method for detecting topology errors in power grids. The propose
Publikováno v:
International Journal of Electrical Power & Energy Systems. 82:29-36
This paper presents a new framework for vulnerability analysis. Under this framework, we can identify the vulnerable components and the critical components of a power grid. Distinct from previous work, our model considers the interaction between the