Spectrum inference in cognitive radio networks: Algorithms and applications
Spectrum inference, also known as spectrum prediction in the literature, is a promising
technique of inferring the occupied/free state of radio spectrum from already …
technique of inferring the occupied/free state of radio spectrum from already …
Darknet as a source of cyber intelligence: Survey, taxonomy, and characterization
Today, the Internet security community largely emphasizes cyberspace monitoring for the
purpose of generating cyber intelligence. In this paper, we present a survey on darknet. The …
purpose of generating cyber intelligence. In this paper, we present a survey on darknet. The …
Vessel pattern knowledge discovery from AIS data: A framework for anomaly detection and route prediction
G Pallotta, M Vespe, K Bryan - Entropy, 2013 - mdpi.com
Understanding maritime traffic patterns is key to Maritime Situational Awareness
applications, in particular, to classify and predict activities. Facilitated by the recent build-up …
applications, in particular, to classify and predict activities. Facilitated by the recent build-up …
How does it function? characterizing long-term trends in production serverless workloads
This paper releases and analyzes two new Huawei cloud serverless traces. The traces span
a period of over 7 months with over 1.4 trillion function invocations combined. The first trace …
a period of over 7 months with over 1.4 trillion function invocations combined. The first trace …
Traffic knowledge discovery from AIS data
G Pallotta, M Vespe, K Bryan - Proceedings of the 16th …, 2013 - ieeexplore.ieee.org
Maritime Situational Awareness (ie, an effective understanding of activities in and impacting
the maritime environment) can be significantly improved by knowledge discovery of maritime …
the maritime environment) can be significantly improved by knowledge discovery of maritime …
Characterizing and mining traffic patterns of IoT devices in edge networks
As connected Internet-of-things (IoT) devices in smart homes, smart cities, and smart
industries continue to grow in size and complexity, managing and securing them in …
industries continue to grow in size and complexity, managing and securing them in …
A comparison study on stages of sleep: Quantifying multiscale complexity using higher moments on coarse-graining
It is of great interests in identifying dynamical properties of human sleep signals using
electroencephalographic (EEG) measures. Multiscale entropy (MSE) is effective in …
electroencephalographic (EEG) measures. Multiscale entropy (MSE) is effective in …
Multiscale entropy analysis of traffic time series
There has been considerable interest in quantifying the complexity of different time series,
such as physiologic time series, traffic time series. However, these traditional approaches …
such as physiologic time series, traffic time series. However, these traditional approaches …
New generalized 'Useful'entropies using weighted quasi-linear mean for efficient networking
A Singhal, DK Sharma - Mobile networks and applications, 2022 - Springer
Entropies have significant importance in the field of information and communication theory.
They have an essential role in measuring along with modeling the complexity and …
They have an essential role in measuring along with modeling the complexity and …
Quantifying the predictability of renewable energy data for improving power systems decision-making
Decision-making in the power systems domain often relies on predictions of renewable
generation. While sophisticated forecasting methods have been developed to improve the …
generation. While sophisticated forecasting methods have been developed to improve the …