Regionalization of extreme rainfall in India

Regionalization of extreme rainfall is useful for various applications in hydro-meteorology. There is dearth of regionalization studies on extreme rainfall in India. In this perspective, a set of 25 regions that are homogeneous in 1-, 2-, 3-, 4- and 5-day extreme rainfall is delineated based on seasonality measure of extreme rainfall and location indicators (latitude, longitude and altitude) by using global fuzzy c-means (GFCM) cluster analysis. The regions are validated for homogeneity in L-moment framework. One of the applications of the regions is in arriving at quantile estimates of extreme rainfall at sparsely gauged/ungauged locations using options such as regional frequency analysis (RFA). The RFA involves use of rainfall-related information from gauged sites in a region as the basis to estimate quantiles of extreme rainfall for target locations that resemble the region in terms of rainfall characteristics. A procedure for RFA based on GFCM-delineated regions is presented and its effectiveness is evaluated by leave-one-out cross validation. Error in quantile estimates for ungauged sites is compared with that resulting from the use of region-of-influence (ROI) approach that forms site-specific regions exclusively for quantile estimation. Results indicate that error in quantile estimates based on GFCM regions and ROI are fairly close, and neither of them is consistent in yielding the least error over all the sites. The cluster analysis approach was effective in reducing the number of regions to be delineated for RFA.

Processing of EEG Signals for Study of Coupling in Brain Regions for Eyes Open and Eyes Closed Conditions

This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to measure coupling or synchrony between the frontal, parietal, occipital and temporal lobes of the cerebrum under the eyes open and eyes closed conditions. This synchrony was measured using magnitude squared coherence, Short Time Fourier Transform and wavelet based coherences. We found a pattern in the time-frequency coherence as we moved from the nasion to the inion of the subject's head. The coherence pattern obtained from the wavelet approach was found to be far more capable of picking up peaks in coherence with respect to frequency when compared to the regular Fourier based coherence. We detected high synchrony between frontal polar electrodes that is missing in coherence plots between other electrode pairs. The study has potential applications in healthcare.

Part I: High-Voltage MOS Device Design for Improved Static and RF Performance

In this paper, for the first time, the key design parameters of a shallow trench isolation-based drain-extended MOS transistor are discussed for RF power applications in advanced CMOS technologies. The tradeoff between various dc and RF figures of merit (FoMs) is carefully studied using well-calibrated TCAD simulations. This detailed physical insight is used to optimize the dc and RF behavior, and our work also provides a design window for the improvement of dc as well as RF FoMs, without affecting the breakdown voltage. An improvement of 50% in R-ON and 45% in RF gain is achieved at 1 GHz. Large-signal time-domain analysis is done to explore the output power capability of the device.

SPEECH ENHANCEMENT USING DISCRIMINATIVE RANDOM FIELDS

Speech enhancement in stationary noise is addressed using the ideal channel selection framework. In order to estimate the binary mask, we propose to classify each time-frequency (T-F) bin of the noisy signal as speech or noise using Discriminative Random Fields (DRF). The DRF function contains two terms - an enhancement function and a smoothing term. On each T-F bin, we propose to use an enhancement function based on likelihood ratio test for speech presence, while Ising model is used as smoothing function for spectro-temporal continuity in the estimated binary mask. The effect of the smoothing function over successive iterations is found to reduce musical noise as opposed to using only enhancement function. The binary mask is inferred from the noisy signal using Iterated Conditional Modes (ICM) algorithm. Sentences from NOIZEUS corpus are evaluated from 0 dB to 15 dB Signal to Noise Ratio (SNR) in 4 kinds of additive noise settings: additive white Gaussian noise, car noise, street noise and pink noise. The reconstructed speech using the proposed technique is evaluated in terms of average segmental SNR, Perceptual Evaluation of Speech Quality (PESQ) and Mean opinion Score (MOS).

Tetraphenylethene-Based Conjugated Fluoranthene: A Potential Fluorescent Probe for Detection of Nitroaromatic Compounds

This study reports the synthesis and photophysical properties of a star-shaped, novel, fluoranthene-tetraphenylethene (TFPE) conjugated luminogen, which exhibits aggregation-induced blue-shifted emission (AIBSE). The bulky fluoranthene units at the periphery prevent intramolecular rotation (IMR) of phenyl rings and induces a blueshift with enhanced emission. The AIBSE phenomenon was investigated by solvatochromic and temperature-dependent emission studies. Nanoaggregates of TFPE, formed by varying the water/THF ratio, were investigated by SEM and TEM and correlated with optical properties. The TFPE conjugate was found to be a promising fluorescent probe towards the detection of nitroaromatic compounds (NACs), especially for 2,4,6-trinitrophenol (PA) with high sensitivity and a high Stern-Volmer quenching constant. The study reveals that nanoaggregates of TFPE formed at 30 and 70% water in THF showed unprecedented sensitivity with detection limits of 0.8 and 0.5ppb, respectively. The nanoaggregates formed at water fractions of 30 and 70% exhibit high Stern-Volmer constants (K-sv=79998 and 51120m(-1), respectively) towards PA. Fluorescence quenching is ascribed to photoinduced electron transfer between TFPE and NACs with a static quenching mechanism. Test strips coated with TFPE luminogen demonstrate fast and ultra-low-level detection of PA for real-time field analysis.