Electroencephalogram (EEG) signals are nonlinear time series, which are generally very
noisy, nonstationary, and contaminated with artifacts that can deteriorate classification methods…

Conventional feature extraction methods based on autoregressive and amplitude–frequency
analysis assume stationarity in the Electroencephalogram signal along short time intervals …

The vehicle to everything communication in long term evolution (LTE V2X) supports vehicle-to-vehicle
(V2V) communication directly via PC5 interface. In LTE V2X mode 4, vehicles …

The usage of deep learning is being escalated in many applications. Due to its outstanding
performance, it is being used in a variety of security and privacy-sensitive areas in addition to …

We demonstrate the effectiveness of a cooperative scheme to improve the positioning
accuracy of four users moving in a building, by using the received signal strength (RSS) …

The power control is a significant technique for suppressing co-channel interference that
severely limits the capacity and connectivity of multi-cell communication systems. In this paper, …

Adversarial attacks are a serious threat to the reliable deployment of machine learning models
in safety-critical applications. They can misguide current models to predict incorrectly by …

As the construction of malicious software has shifted from novices to commercial, malware
attacks grew considerably in frequency and traditional antivirus software fails to detect many …

A negative selection algorithm based on the hierarchical clustering of self set HC-RNSA is
introduced in this paper. Several strategies are applied to improve the algorithm performance. …

Negative Selection Algorithm (NSA) is an impor-tant artificial immune data classifiers generation
method in Artificial Immune System (AIS) research. However, with the increase of the …