Real-time monitoring of critical nodes with minimal number of Phasor Measurement Units

This paper presents a method for placement of Phasor Measurement Units, ensuring the monitoring of vulnerable buses which are obtained based on transient stability analysis of the overall system. Real-time monitoring of phase angles across different nodes, which indicates the proximity to instability, the very purpose will be well defined if the PMUs are placed at buses which are more vulnerable. The issue is to identify the key buses where the PMUs should be placed when the transient stability prediction is taken into account considering various disturbances. Integer Linear Programming technique with equality and inequality constraints is used to find out the optimal placement set with key buses identified from transient stability analysis. Results on IEEE-14 bus system are presented to illustrate the proposed approach.

Multiwalled-carbon-nanotube-induced miscibility in near-critical PS/PVME blends: assessment through concentration fluctuations and segmental relaxation

The effects of multiwalled carbon nanotubes (MWNTs) on the concentration fluctuations, interfacial driven elasticity, phase morphology, and local segmental dynamics of chains for near-critical compositions of polystyrene/poly(vinyl to methyl ether) (PS/PVME) blends were systematically investigated using dynamic shear rheology and dielectric spectroscopy. The contribution of the correlation length (xi) of the concentration fluctuations to the evolving stresses was monitored in situ to probe the different stages of demixing in the blends. The classical upturn in the dynamic moduli was taken as the rheological demixing temperature (T-rheo), which was also observed to be in close agreement with those obtained using concentration fluctuation variance, <(delta phi)(2)>, versus temperature curves. Further, Fredrickson and Larson's approach involving the mean-field approximation and the double-reptation self-concentration (DRSC) model was employed to evaluate the spinodal decomposition temperature (T-s). Interestingly, the values of both T-rheo and T-s shifted upward in the blends in the presence of MWNTs, manifesting in molecular-level miscibility. These phenomenal changes were further observed to be a function of the concentration of MWNTs. The evolution of morphology as a function of temperature was studied using polarized optical microscopy (POM). It was observed that PVME, which evolved as an interconnected network during the early stages of demixing, coarsened into a matrix-droplet morphology in the late stages. The preferential wetting of PVME onto MWNTs as a result of physicochemical interactions retained the interconnected network of PVME for longer time scales, as supported by POM and atomic force microscopy (AFM) images. Microscopic heterogeneity in macroscopically miscible systems was studied by dielectric relaxation spectroscopy. The slowing of segmental relaxations in PVME was observed in the presence of both ``frozen'' PS and MWNTs interestingly at temperatures much below the calorimetric glass transition temperature (T-g). This phenomenon was observed to be local rather than global and was addressed by monitoring the evolution of the relaxation spectra near and above the demixing temperature.

Fragment-based real-time object tracking: a sparse representation approach

Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.

Formulation of a mathematical approach to regional frequency analysis

Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

Assessing the critical concentration of NH2 terminal groups on the surface of MWNTs towards chain scission of PC in PC/SAN blends: effect on dispersion, electrical conductivity and EMI shielding

The localization and dispersion quality of as received NH2 terminated multiwall carbon nanotubes (MWNT-I) and ethylene diamine (EDA) functionalized MWNTs in melt mixed blends of polycarbonate ( PC) and poly(styrene-co-acrylonitrile) (SAN) were assessed in this study using rheo-electrical and electromagnetic interference (EMI) shielding measurements. In order to improve the dispersion quality and also to selectively localize MWNTs in the PC phase of the blends, EDA was grafted onto MWNTs by two different strategies like diazonium reaction of the para-substituted benzene ring of MWNTs with EDA ( referred to as MWNT-II) and acylation of carboxyl functionalized MWNTs with thionyl chloride ( referred to as MWNT-III). By this approach we could systematically vary the concentration of NH2 functional groups on the surface of MWNTs at a fixed concentration (1 wt%) in PC/SAN blends. XPS was carried to evaluate the % concentration of N in different MWNTs and was observed to be highest for MWNT-III manifesting in a large surface coverage of EDA on the surface of MWNTs. Viscoelastic properties and melt electrical conductivities were measured to assess the dispersion quality of MWNTs using a rheo-electrical set-up both in the quiescent as well as under steady shear conditions. Rheological properties revealed chain scission of PC in the presence of MWNT-III which is due to specific interactions between EDA and PC leading to smaller PC grafts on the surface of MWNTs. The observed viscoelastic properties in the blends were further correlated with the phase morphologies under quiescent and annealed conditions. Electromagnetic interference (EMI) shielding effectiveness in X and K-u-band frequencies were measured to explore these composites for EMI shielding applications. Interestingly, MWNT-II showed the highest electrical conductivity and EMI shielding in the blends.

A Stochastic Chemical Dynamic Approach to Correlate Autoimmunity and Optimal Vitamin-D Range

Motivated by several recent experimental observations that vitamin-D could interact with antigen presenting cells (APCs) and T-lymphocyte cells (T-cells) to promote and to regulate different stages of immune response, we developed a coarse grained but general kinetic model in an attempt to capture the role of vitamin-D in immunomodulatory responses. Our kinetic model, developed using the ideas of chemical network theory, leads to a system of nine coupled equations that we solve both by direct and by stochastic (Gillespie) methods. Both the analyses consistently provide detail information on the dependence of immune response to the variation of critical rate parameters. We find that although vitamin-D plays a negligible role in the initial immune response, it exerts a profound influence in the long term, especially in helping the system to achieve a new, stable steady state. The study explores the role of vitamin-D in preserving an observed bistability in the phase diagram (spanned by system parameters) of immune regulation, thus allowing the response to tolerate a wide range of pathogenic stimulation which could help in resisting autoimmune diseases. We also study how vitamin-D affects the time dependent population of dendritic cells that connect between innate and adaptive immune responses. Variations in dose dependent response of anti-inflammatory and pro-inflammatory T-cell populations to vitamin-D correlate well with recent experimental results. Our kinetic model allows for an estimation of the range of optimum level of vitamin-D required for smooth functioning of the immune system and for control of both hyper-regulation and inflammation. Most importantly, the present study reveals that an overdose or toxic level of vitamin-D or any steroid analogue could give rise to too large a tolerant response, leading to an inefficacy in adaptive immune function.

Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

A systematic asymptotic approach to determine the dispersion characteristics of structural-acoustic waveguides with arbitrary fluid loading

Structural-acoustic waveguides of two different geometries are considered: a 2-D rectangular and a circular cylindrical geometry. The objective is to obtain asymptotic expansions of the fluid-structure coupled wavenumbers. The required asymptotic parameters are derived in a systematic way, in contrast to the usual intuitive methods used in such problems. The systematic way involves analyzing the phase change of a wave incident on a single boundary of the waveguide. Then, the coupled wavenumber expansions are derived using these asymptotic parameters. The phase change is also used to qualitatively demarcate the dispersion diagram as dominantly structure-originated, fluid originated or fully coupled. In contrast to intuitively obtained asymptotic parameters, this approach does not involve any restriction on the material and geometry of the structure. The derived closed-form solutions are compared with the numerical solutions and a good match is obtained. (C) 2016 Elsevier Ltd. All rights reserved.