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Deep Reinforcement Learning Algorithm for Smart Data Compression under NOMA-Uplink Protocol
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
One of the highly promising radio access strategies for enhancing performance in the next generation cellular communications is non-orthogonal multiple access (NOMA). NOMA offers a number of advantages including better ...
Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Electroencephalography (EEG) based biometric systems are gaining attention for their anti-spoofing capability but lack accuracy due to signal variability at different psychological and physiological conditions. On the other ...
Machine Learning Based Cloud Computing Anomalies Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
Efficient processing of hamming-distance-based similarity-search queries over MapReduce
(
OpenProceedings.org, University of Konstanz, University Library
, 2015 , Conference Paper)
Similarity search is crucial to many applications. Of particular interest are two flavors of the Hamming distance range query, namely, the Hamming select and the Hamming join (Hamming-select and Hamming-join, respectively). ...
Iterative per Group Feature Selection for Intrusion Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Network security is an critical subject in any distributed network. Recently, machine learning has proven their efficiency for intrusion detection. By using a comprehensive dataset with multiple attack types, a well-trained ...
Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
(
John Wiley and Sons Inc
, 2021 , Article)
Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative ...
Distributed interference management using Q-Learning in cognitive femtocell networks: New USRP-based implementation
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
Femtocell networks have become a promising solution in supporting high data rates for 5G systems, where cell densification is performed using the small femtocells. However, femtocell networks have many challenges. One of ...
A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ...
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Machine learning techniques are becoming mainstream in intrusion detection systems as they allow real-time response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a ...
Structural health monitoring installation scheme using utility computing model
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
In view of intensified disasters and fatalities caused by natural phenomena, there is a pressing need for an efficient environment logging that provides structural information to administrators for a better management and ...