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...     

Bulk free radical polymerizations of methyl methacrylateunder non-isothermal conditions and with intermediate additionof initiator: Experiments and modeling

Experimental data on the monomer conversion, x_m, and the weight average molecular weight, M_w, have been generated under several isothermal and non-isothermal conditions for the polymerization of methyl methacrylate in a rheometer-reactor assembly. The non-isothermal results, in particular, can be used to provide more stringent tests of kinetic models than isothermal data alone. A simple empirical model has been used to describe this system that accounts for the gel (Trommsdorff) and glass effects. The model involves only x_m and the temperature, and is quite general. The model parameters are tuned using only three sets of isothermal data. Good agreement is found between the experimental results and model predictions for a whole variety of experimental conditions, including non-isothermal operation and with intermediate addition of initiator. Because of its generality, this model is quite suitable for use for on-line optimizing control as well as for describing industrial reactors.     

Simulation of an industrial nylon 6 tubular reactor

A commonly used energy-efficient nylon 6 reactor is simulated under steady-state conditions. The effects of various operating conditions and parameters, e.g., feed composition, temperature and flow rate, heat transfer coefficients, and reactor dimensions, on the temperature and molecular weight profiles are studied. A temperature maximum is observed in the reactor under usual conditions of operation. The maximum value of the temperature is sensitive to the feed conditions, and one has to ensure that degradation reactions speeded up at high temperatures do not affect product characteristics. The model and the numerical technique used are fairly simple and account for most of the important features of industrial reactors. Hence, these can be used in the development of digital-control algorithms in the future.     

Viscosity of bulk free radical polymerizing systems under near-isothermal and non-isothermal conditions

A viscometer-reactor assembly is used to generate data on the viscosity, η(t), of an example polymerizing system exhibiting the Trommsdorff effect, namely, the bulk free radical polymerization of methyl methacrylate (MMA), at different temperature conditions [near-isothermal and non-isothermal (near-step increase and near-step decrease in temperature)] and at two different initiator, 2,2′-azoisobutyronitrile (AIBN), concentrations. Two types of cup and bob assemblies, viz., the Haake^® SV-2 and the Haake^® HV-DIN, have been used to measure η(t) of the reaction mass, until reasonably high values of viscosity, well into the gel effect region. Only three sets of experimental data on x_m(t), M_w(t) and η(t) under near-isothermal conditions, are used to develop general correlations for the viscosity. These tuned correlations predict the values of the viscosity for a whole variety of other experimental conditions, including non-isothermal cases, reflecting that the physics of the system is well represented by them. Hence, these correlations can be used for other systems after tuning their parameters. The feasibility of on-line soft sensing is demonstrated for a few cases.