Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs.

Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital challenges present in the deployment of EEG-based biometrics, which is stable and capable of handling the real-world scenario. One of the key challenges is the large signal variability of EEG when recorded on different days or sessions which impedes the performance of biometric systems significantly.

Impact of surface coating on electrochemical and thermal behaviors of a Li-rich LiNiMnCoO cathode.

Lithium-rich layered oxide materials are considered as potential cathode materials for future high-performance lithium-ion batteries (LIBs) owing to their high operating voltage and relatively high specific capacity. However, perceptible issues such as poor rate performance, poor capacity retention, and voltage degradation during cycling need to be improved before the successful commercialization of the material. In this report, zirconia coated LiNiMnCo8O (NMC) (where ZrO = 1.