Indian Institute of Technology Indore

About: Indian Institute of Technology Indore is a education organization based out in Indore, Madhya Pradesh, India. It is known for research contribution in the topics: Fading & Support vector machine. The organization has 1606 authors who have published 4803 publications receiving 66500 citations.

Investigating Phosphorylation-Induced Conformational Changes in WNK1 Kinase by Molecular Dynamics Simulations.

Abstract: The With-No-Lysine (WNK) kinase is considered to be a master regulator for various cation-chloride cotransporters involved in maintaining cell-volume and ion homeostasis. Here, we have investigated...

Mitochondrial Localization of Highly Fluorescent and Photostable BODIPY-Based Ruthenium(II), Rhodium(III), and Iridium(III) Metal Complexes.

Abstract: A new N,O-based BODIPY ligand was synthesized and further utilized to develop highly fluorescent and photostable Ru(II), Rh(III), and Ir(III) metal complexes. The complexes were fully characterized by different analytical techniques including single-crystal XRD studies. The photostabilities and live cell imaging capabilities of the complexes were investigated via confocal microscopy. The complexes localized specifically in the mitochondria of live cells and showed negligible cytotoxicities at a concentration used for imaging purposes. They also exhibited high photostabilities, with fluorescence intensities remaining above 50% after 1800 scans.

Adaptive User Pairing for NOMA Systems With Imperfect SIC

Abstract: Non-orthogonal multiple access (NOMA) has been recognized as a key driving technology for the fifth generation (5G) and beyond 5G cellular networks. For a practical downlink NOMA system with imperfect successive interference cancellation (SIC), we derive bounds on power allocation factors and formulate a minimum signal-to-interference-plus-noise ratio (SINR) difference criterion for NOMA pair formation. Through extensive simulations, we show the effect of imperfect SIC on the rate performance of a NOMA pair and the trade-off with its OMA (orthogonal multiple access) counterparts. We propose an adaptive user pairing (A-UP) algorithm for achieving better user rates. Further, the proposed A-UP algorithm results in better performance than state-of-the-art NOMA pairing algorithms in the presence of SIC imperfections.

Human Emotion Classification from EEG Signals Using Multiwavelet Transform

Abstract: In this paper, we propose new features based on multiwavelet transform for classification of human emotions from electroencephalogram (EEG) signals. The EEG signal measures electrical activity of the brain, which contains lot of information related to emotional states. The sub-signals obtained by multiwavelet decomposition of EEG signals are plotted in a 3-D phase space diagram using phase space reconstruction (PSR). The mean and standard deviation of Euclidian distances are computed from 3-D phase space diagram. These features have been used as input features set for multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet and Morlet wavelet kernel functions for classification of emotions. The proposed features based on multiwavelet transform of EEG signals with Morlet wavelet kernel function of MC-LS-SVM have provided better classification accuracy for classification of emotions.