Towards a super-resolution based approach for improved face recognition in low resolution environment

Multimedia Tools and Applications - The video surveillance activity generates a vast amount of data, which can be processed to detect miscreants. The task of identifying and recognizing an object...     

Modeling of diffusional limitations in styrene acrylonitrile random bulk copolymerization

Diffusional limitations (the gel, glass, and cage effects) are manifested in several bulk free radical homopolymerizations as well as in random copolymerizations. These are associated with decreases of several orders of magnitude of the rate constants of termination, propagation, and initiation (the initiator efficiency), respectively. These phenomena have been modeled earlier using the free volume theory for the diffusivities of primary radicals, macro‐radicals, and monomer molecules, and have been applied to homopolymerizations. In this study, a similar model is developed for random bulk copolymerizations. The parameters of the model are fitted using isothermal data on styrene acrylonitrile random copolymerization carried out in small ampoules. Thereafter, best‐fit global correlations have been developed for this system. This enables the model to be used for studying non‐isothermal copolymerizations, as well as for carrying out optimization of industrial reactors, where non‐isothermal conditions are a norm. POLYM. ENG. SCI., 55:2098–2110, 2015. © 2014 Society of Plastics Engineers     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Analytical Modeling of a Triple Material Double Gate TFET with Hetero-Dielectric Gate Stack

Silicon - In this paper, we propose and develop an analytical model of a Triple material double gate Tunnel Field Effect Transistor (TM-DG TFET) with hetero-dielectric gate oxide stack comprising...     

Structural and magnetic properties of Co1+ySnyFe2-2y-xCrxO4 ferrite system

The samples of the series Co_1+ySn_yFe_{2- 2y- x}Cr_xO₄ ferrites with x = 0.0, 0.1, 0.2, 0.3, 0.4, 0.5 and y = 0.05, were prepared by the usual double sintering ceramic technique. The single- phase spinel structure of the samples was confirmed by using X- ray diffractometry technique. The lattice parameter ’a’ with an accuracy of ± 0.002 Å were determined using Bragg peaks of XRD pattern. The lattice parameter ’a’ decreases with concentration, x, which is due to the difference in the ionic radii of Cr³⁺ and Fe³⁺ ions. The X- ray intensity calculations were carried out in order to determine the possible cation distribution amongst tetrahedral (A) and octahedral [B] sites. The X- ray intensity calculations show Cr³⁺ ions occupying B site. The saturation magnetization, σ_s, and magneton number, n_B (the saturation magnetization per formula unit), measured at 300 K determined from high field hysteresis loop technique decrease with increase in concentration, x, suggesting a decrease in ferrimagnetic behaviour. Thermal variation of low field a.c. susceptibility measurements from room temperature to about 800 K exhibits almost normal ferrimagnetic behaviour and the Curie temperature, T_C determined from a.c. susceptibility data decreases with increase in x.

     

Stepwise-Graded Si3N4–SiC Ceramics with Improved Wear Properties

The processing of stepwise graded Si₃N₄/SiC ceramics by pressureless co-sintering is described. Here, SiC (high elastic modulus, high thermal expansion coefficient) forms the substrate and Si₃N₄ (low elastic modulus, low thermal expansion coefficient) forms the top contact surface, with a stepwise gradient in composition existing between the two over a depth of ∼1.7 mm. The resulting Si₃N₄ contact surface is fine-grained and dense, and it contains only 2 vol% yttrium aluminum garnet (YAG) additive. This graded ceramic shows resistance to cone-crack formation under Hertzian indentation, which is attributed to a combined effect of the elastic-modulus gradient and the compressive thermal-expansion-mismatch residual stress present at the contact surface. The presence of the residual stress is corroborated and quantified using Vickers indentation tests. The graded ceramic also possesses wear properties that are significantly improved compared with dense, monolithic Si₃N₄ containing 2 vol% YAG additive. The improved wear resistance is attributed solely to the large compressive stress present at the contact surface. A modification of the simple wear model by Lawn and co-workers is used to rationalize the wear results. Results from this work clearly show that the introduction of surface compressive residual stresses can significantly improve the wear resistance of polycrystalline ceramics, which may have important implications for the design of contact-damage-resistant ceramics.