Indian Institute of Technology Bhubaneswar

About: Indian Institute of Technology Bhubaneswar is a education organization based out in Bhubaneswar, India. It is known for research contribution in the topics: Large Hadron Collider & Higgs boson. The organization has 1185 authors who have published 3132 publications receiving 48832 citations.

Periocular recognition in cross-spectral scenario

Abstract: Periocular recognition has been an active area of research in the past few years. In spite of the advancements made in this area, the cross-spectral matching of visible (VIS) and near-infrared (NIR) periocular images remains a challenge. In this paper, we propose a method based on illumination normalization of VIS and NIR periocular images. Specifically, the approach involves normalizing the images using the difference of Gaussian (DoG) filtering, followed by the computation of a descriptor that captures structural details in the illumination normalized images using histogram of oriented gradients (HOG). Finally, the feature vectors corresponding to the query and the enrolled image are compared using the cosine similarity metric to generate a matching score. Performance of our algorithm has been evaluated on three publicly available benchmark databases of cross-spectral periocular images. Our approach yields significant improvement in performance over the existing approach.

Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU: A Synergistic View Using In Situ and Satellite Observations

Abstract: In this study, the upper ocean and subsurface variability during the different phases of the cyclonic storm ROANU along the western Bay of Bengal (BoB) in May 2016 are investigated by using the moored buoys, Argos, HF radar and satellite datasets in the proximity of the cyclone track. The moored buoy observations recorded a decrease of sea surface temperature (SST) by ~ 1 °C all over the track, whereas increase in salinity by ~ 1.5 PSU was detected along with the highest wind speed of 16 m s−1, pressure drop of 14 hPa and air temperature drop of 4 °C. The cooling at the cyclone centers from the satellite data indicated higher (lower) SST drops when translation speed of the cyclone was low (high) and took more (less) time to recover to its pre-cyclone state in southern (northern) BoB. Mostly, higher SST drop was observed along the right side of the cyclone track. Interestingly, the opposite phenomenon occurred before landfall, where SST drop was higher on the left due to upwelling in the head bay as observed both from wave rider buoy (WRB) at Digha and satellite SST. The WRB near Vizag showed the maximum increase in significant wave heights by ~ 2.4 m during the passage of cyclone. Argos also captured cyclone-induced drop in temperature due to upwelling and entrainment reasonably well. In the southwestern bay, significant upwelling was observed from the Argos with drop in temperature and increase in salinity in the upper layers. However, a strong stratification was observed from Argos in the northwestern BoB due to lesser salinity and higher precipitation. The currents from in situ as well as HF radar datasets measured the increase in current magnitude during the passage of ROANU. Rotary spectral analysis showed strong inertial currents with frequency ~ 2.1 days at BD11 location, with higher amplitudes of the clockwise component during the cyclone period.

Search for t t ¯ H production in the H → b b ¯ decay channel with leptonic t t ¯ decays in proton-proton collisions at √s=13 TeV

Abstract: A search is presented for the associated production of a standard model Higgs boson with a top quark-antiquark pair ( $ \mathrm{t}\overline{\mathrm{t}}\mathrm{H} $ ), in which the Higgs boson decays into a b quark-antiquark pair, in proton-proton collisions at a centre-of-mass energy $ \sqrt{s}=13 $ TeV. The data correspond to an integrated luminosity of 35.9 fb$^{−1}$ recorded with the CMS detector at the CERN LHC. Candidate $ \mathrm{t}\overline{\mathrm{t}}\mathrm{H} $ events are selected that contain either one or two electrons or muons from the $ \mathrm{t}\overline{\mathrm{t}} $ decays and are categorised according to the number of jets. Multivariate techniques are employed to further classify the events and eventually discriminate between signal and background. The results are characterised by an observed $ \mathrm{t}\overline{\mathrm{t}}\mathrm{H} $ signal strength relative to the standard model cross section, μ = σ/σ$_{SM}$, under the assumption of a Higgs boson mass of 125 GeV. A combined fit of multivariate discriminant distributions in all categories results in an observed (expected) upper limit on μ of 1.5 (0.9) at 95% confidence level, and a best fit value of 0.72 ± 0.24(stat) ± 0.38(syst), corresponding to an observed (expected) signal significance of 1.6 (2.2) standard deviations above the background-only hypothesis.

On the accuracy versus transparency trade-off of data-mining models for fast-response PMU-based catastrophe predictors

Abstract: Summary form only given. In all areas of engineering, modelers are constantly pushing for more accurate models and their goal is generally achieved with increasingly complex, data-mining-based black-box models. On the other hand, model users which include policy makers and systems operators tend to favor transparent, interpretable models not only for predictive decision-making but also for after-the-fact auditing and forensic purposes. In this paper, we investigate this trade-off between the accuracy and the transparency of data-mining-based models in the context of catastrophe predictors for power grid response-based remedial action schemes, at both the protective and operator levels. Wide area severity indices (WASI) are derived from PMU measurements and fed to the corresponding predictors based on data-mining models such as decision trees (DT), random forests (RF), neural networks (NNET), support vector machines (SVM), and fuzzy rule based models (Fuzzy_DT and Fuzzy_ID3). It is observed that while switching from black-box solutions such as NNET, SVM, and RF to transparent fuzzy rule-based predictors, the accuracy deteriorates sharply while transparency and interpretability are improved.

A reentrant phenomenon in magnetic and dielectric properties of Dy2BaNiO5 and an intriguing influence of external magnetic field.

Abstract: We report that the spin-chain compound Dy2BaNiO5, recently proven by us to exhibit magnetoelectric coupling below its Neel temperature (TN) of 58 K, exhibits strong frequency-dependent behavior in ac magnetic susceptibility and complex dielectric properties at low temperatures (<10 K), mimicking the 'reentrant' multiglass phenomenon. Such a behavior is not known among undoped compounds. A new finding in the field of multiferroics is that the characteristic magnetic feature at low temperatures moves towards higher temperatures in the presence of a magnetic field (H), whereas the corresponding dielectric feature shifts towards lower temperatures with H, unlike the situation near TN. This observation indicates that the alignment of spins by external magnetic fields tends to inhibit glassy-like slow electric-dipole dynamics, at least in this system, possibly arising from peculiarities in the magnetic structure.