Learn More
In this paper, a spike detection method is introduced. Traditional morphological filter is improved for extracting spikes from epileptic EEG signals and two key problems are addressed: morphological operation design and structure elements optimization. An average weighted combination of open-closing and close-opening operation, which can eliminate(More)
As the first line of immune defense for Mycobacterium tuberculosis (Mtb), macrophages also provide a major habitat for Mtb to reside in the host for years. The battles between Mtb and macrophages have been constant since ancient times. Triggered upon Mtb infection, multiple cellular pathways in macrophages are activated to initiate a tailored immune(More)
Epileptic electroencephalogram data contains transient components and background activities. One of the transients is spike, which occurs randomly with short-duration. Spike detection in EEG is significant for clinical diagnosis of epilepsy. Since it is time consuming to scan spikes manually, an automatic spike detection method is necessary. In this paper,(More)
Epileptic seizure features always include the morphology and spatial distribution of nonlinear waveforms in the electroencephalographic (EEG) signals. In this study, we propose a novel incremental learning scheme based on nonlinear dimensionality reduction for automatic patient-specific seizure onset detection. The method allows for identification of(More)
Since the limitations of Kerberos authentication protocol for symmetric algorithm, there are many improved Kerberos protocol of RSA public key encryptions. However, the existing public key encryption system resistance in the analysis of quantum encryption has brought tremendous challenges. Braid group is a new considerable public key cryptography platform(More)
In this study, we utilize a special visual stimulation protocol, called motion reversal, to present a novel steady-state motion visual evoked potential (SSMVEP)-based BCI paradigm that relied on human perception of motions oscillated in two opposite directions. Four Newton's rings with the oscillating expansion and contraction motions served as visual(More)
For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing(More)
Black locust (Robinia pseudoacacia L.) is a tree species of high economic and ecological value, but is also considered to be highly invasive. Understanding the global potential distribution and ecological characteristics of this species is a prerequisite for its practical exploitation as a resource. Here, a maximum entropy modeling (MaxEnt) was used to(More)
In this paper a stochastic resonance (SR)-based method for recovering weak impulsive signals is developed for quantitative diagnosis of faults in rotating machinery. It was shown in theory that weak impulsive signals follow the mechanism of SR, but the SR produces a nonlinear distortion of the shape of the impulsive signal. To eliminate the distortion a(More)