Energy-Effective and Secure Data Transfer Scheme for Mobile Nodes in Smart City Applications

Wireless Personal Communications - Mobile nodes are deployed at different locations in the smart city to collect meaningful information so captured data can be used as an input in different smart...     

Study of molecular structure and vibrational spectra of poly (β,-l-malic acid) [PMLA] using DFT approach

Poly (β-L-malic acid) (PMLA) is a biodegradable polymer and it has various important applications in the biomedical field. In the present work the structural and spectral characteristics of PMLA have been studied by methods of infrared, Raman spectroscopy and quantum chemistry. Electrostatic potential surface, optimized geometry, harmonic vibrational frequencies, infrared intensities and activities of Raman scattering were calculated by density functional theory (DFT) using oligomeric approach employing B3LYP with complete relaxation in the potential energy surface using 6-311++G (d, p) basis set. Based on results, we have discussed the correlation between the vibrational modes and the structure of the PMLA. A complete analysis of the experimental infrared and Raman spectra has been reported on the basis of wavenumber of the vibrational bands and potential energy distribution. The calculated HOMO and LUMO energies shows that charge transfer occur within the molecule. The calculated infrared and the Raman spectra of the polymer based on DFT calculations show reasonable agreement with the experimental results.     

Studies on synthesis and characterization of N‐alkyl terephthalamides using different amines from polyethylene terephthalate waste

This study deals with the degradation of polyethylene terephthalate (PET) waste through aminolysis with various amines. All of these degradation experiments were carried out at ambient temperature and at normal pressure. Although PET is known to be recycled in many ways, but still there is a need of development of other environment friendly recycling techniques. The amines used to study the degradation of PET waste were namely methylamine, ethylamine, and n‐butyl amine, respectively where the degradation of PET waste completes in 45 days. The aminolyzed products so obtained were characterized by using various conventional techniques such as spectroscopic techniques namely IR, NMR, and simultaneous differential scanning calorimeter (DSC). In the present research work, a useful method of PET recycling by using various amines was successfully established. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Vertically Aligned GaAs Nanowires on Graphite and Few-Layer Graphene: Generic Model and Epitaxial Growth

By utilizing the reduced contact area of nanowires, we show that epitaxial growth of a broad range of semiconductors on graphene can in principle be achieved. A generic atomic model is presented which describes the epitaxial growth configurations applicable to all conventional semiconductor materials. The model is experimentally verified by demonstrating the growth of vertically aligned GaAs nanowires on graphite and few-layer graphene by the self-catalyzed vapor-liquid-solid technique using molecular beam epitaxy. A two-temperature growth strategy was used to increase the nanowire density. Due to the self-catalyzed growth technique used, the nanowires were found to have a regular hexagonal cross-sectional shape, and are uniform in length and diameter. Electron microscopy studies reveal an epitaxial relationship of the grown nanowires with the underlying graphitic substrates. Two relative orientations of the nanowire side-facets were observed, which is well explained by the proposed atomic model. A prototype of a single GaAs nanowire photodetector demonstrates a high-quality material. With GaAs being a model system, as well as a very useful material for various optoelectronic applications, we anticipate this particular GaAs nanowire/graphene hybrid to be promising for flexible and low-cost solar cells.     

Terahertz graphene optics

The magnitude of the optical sheet conductance of single-layer graphene is universal, and equal to e ²/4? (where 2??? = h (the Planck constant)). As the optical frequency decreases, the conductivity decreases. However, at some frequency in the THz range, the conductivity increases again, eventually reaching the DC value, where the magnitude of the DC sheet conductance generally displays a sample- and doping-dependent value between ??e ²/h and 100 e ²/h. Thus, the THz range is predicted to be a non-trivial region of the spectrum for electron transport in graphene, and may have interesting technological applications. In this paper, we present the first frequency domain measurements of the absolute value of multilayer graphene (MLG) and single-layer graphene (SLG) sheet conductivity and transparency from DC to 1 THz, and establish a firm foundation for future THz applications of graphene.      

Finite element implementation of Maxwell's equations for image reconstruction in electrical impedance tomography

Traditionally, image reconstruction in electrical impedance tomography (EIT) has been based on Laplace's equation. However, at high frequencies the coupling between electric and magnetic fields requires solution of the full Maxwell equations. In this paper, a formulation is presented in terms of the Maxwell equations expressed in scalar and vector potentials. The approach leads to boundary conditions that naturally align with the quantities measured by EIT instrumentation. A two-dimensional implementation for image reconstruction from EIT data is realized. The effect of frequency on the field distribution is illustrated using the high-frequency model and is compared with Laplace solutions. Numerical simulations and experimental results are also presented to illustrate image reconstruction over a range of frequencies using the new implementation. The results show that scalar/vector potential reconstruction produces images which are essentially indistinguishable from a Laplace algorithm for frequencies below 1 MHz but superior at frequencies reaching 10 MHz.     

A New Method for Low Sensitivity Design of a Controller for a Load Following BWR Power Plant

A new method has been proposed in which the controller is approximated by two low order models, the second being the sensitivity model of the first. Thus a Kind of piecewise solution is proposed in which the system retains the same order irrespective of the number of parameters to be considered for low sensitivity design. The usefulness of the proposed technique is illustrated in the controller design for a direct cycle BWR power plant of 457 MW(thermal) with recirculation control. The mathematical model includes the reactor kinetics, hydrodynamics of the recirculation loop, pressure transients, and the load frequency control system. The response of system variables such as frequency, neutron power, and reactor pressure are plotted with the low sensitivitty controller. The sensitivity function of frequency has been plotted using the conventional and proposed low sensitivity controller for 20 per cent variation in parameter values. The method is specifically recommended for controller design of large size systems.     

Identification and Classification of Driving Behaviour at Signalized Intersections Using Support Vector Machine

When the drivers approaching signalized intersections (onset of yellow signal), the drivers would enter into a zone, where they will be in uncertain mode assessing their capabilities to stop or cross the intersection. Therefore, any improper decision might lead to a right-angle or back-end crash. To avoid a right-angle collision, drivers apply the harsh brakes to stop just before the signalized intersection. But this may lead to a back-end crash when the following driver encounters the former’s sudden stopping decision. This situation gets multifaceted when the traffic is heterogeneous, containing various types of vehicles. In order to reduce this issue, this study’s primary objective is to identify the driving behaviour at signalized intersections based on the driving features (parameters). The secondary objective is to classify the outcome of driving behaviour (safe stopping and unsafe stopping) at the signalized intersection using a support vector machine (SVM) technique. Turning moments are used to identify the zones and label them accordingly for further classification. The classification of 50 instances is identified for training and testing using a 70%–30% rule resulted in an accuracy of 85% and 86%, respectively. Classification performance is further verified by random sampling using five cross-validation and 30 iterations, which gave an accuracy of 97% and 100% for training and testing. These results demonstrate that the proposed approach can help develop a pre-warning system to alert the drivers approaching signalized intersections, thus reducing back-end crash and accidents.