Showing papers by "Indian Institute of Technology Bhubaneswar published in 2014"

A survey on nature inspired metaheuristic algorithms for partitional clustering

Abstract: The partitional clustering concept started with K-means algorithm which was published in 1957. Since then many classical partitional clustering algorithms have been reported based on gradient descent approach. The 1990 kick started a new era in cluster analysis with the application of nature inspired metaheuristics. After initial formulation nearly two decades have passed and researchers have developed numerous new algorithms in this field. This paper embodies an up-to-date review of all major nature inspired metaheuristic algorithms employed till date for partitional clustering. Further, key issues involved during formulation of various metaheuristics as a clustering problem and major application areas are discussed.

The Physics of the B Factories

Abstract: This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C.

Short-term modulation of Indian summer monsoon rainfall by West Asian dust

Abstract: The Indian summer monsoon is influenced by numerous factors, including aerosol-induced changes to clouds, surface and atmospheric heating, and atmospheric circulation. An analysis of satellite data and global climate model simulations suggests that dust aerosol levels over the Arabian Sea, West Asia and the Arabian Peninsula are positively correlated with the intensity of the Indian summer monsoon.

Graphene-Based Birefringent Photonic Crystal Fiber Sensor Using Surface Plasmon Resonance

Abstract: We propose a graphene-based photonic crystal fiber (PCF) sensor based on surface plasmon resonance. Graphene helps in prevention of oxidation of the silver layer used as a plasmonic active metal. The birefringent nature of the structure allows one component of the core guided mode to be more sensitive. Further, this structure does not need filling of the voids. The structural parameter of PCF and metal thickness has been optimized. The proposed sensor shows high amplitude sensitivity of 860 RIU-1 and has a resolution as high as 4×10-5 RIU. This reported performance is higher than bimetallic (gold on silver) configuration.

Temperature dependent Raman spectroscopy of chemically derived few layer MoS2 and WS2 nanosheets

Abstract: We have systematically investigated the temperature dependent Raman spectroscopy behavior of a few layered MoS2 and WS2 nanosheets synthesized using simple hydrothermal method. Our result reveals A1g and E12g modes soften as temperature increases from 77 K to 623 K. This behavior can be explained in terms of a double resonance process which is active in single- and few layer thick nanosheets. The frequency shifts and peak broadening can provide unambiguous, nondestructive, and accurate information of a few layered MoS2 and WS2. This mechanism can also be applicable in characterizing the structural, optical, electronic, and vibrational properties of other emerging layered materials.

SPR Biosensor Based on Polymer PCF Coated With Conducting Metal Oxide

Abstract: We propose a biosensor based on photonic crystal fiber made of polymethyl methacrylate using surface plasmon resonance. The proposed sensor consists of a layer of air holes as cladding and a central hole for phase matching between plasmon mode and core guided mode. Alternate holes in the second layer coated with conducting metal oxide, i.e., indium tin oxide (ITO), contain analyte. We found that the optimized thickness of the ITO for optimum performance is 70 nm, which matches with reported result. Unlike other metal coated structures, here the resonance is around telecommunication window and can be tuned by varying the intrinsic properties of the ITO as per requirement. The proposed sensor shows refractive index sensitivity as high as 2000 nm/RIU and has resolution of 5×10-5 RIU.

A critical review of retrofitting methods for unreinforced masonry structures

Abstract: Unreinforced masonry (URM) buildings are common throughout Latin America, the Himalayan region, Eastern Europe, Indian subcontinent and other parts of Asia. It has been observed that these buildings cannot withstand the lateral loads imposed by an earthquake and often fails, in a brittle manner. Methods for retrofitting URM buildings to increase the time required for collapse and also to improve the overall strength widely vary. This review has collated information on various types of retrofitting methods either under research or early implementation. Furthermore, these methods are categorized and critically analyzed to help further understand which methods are most suitable for future research or application in developing countries. The comparison of the different methods is based on economy, sustainability and buildability and provides a useful insight. The study may provide useful guidance to policy makers, planners, designers, architects and engineers in choosing a suitable retrofitting methodology.

Wide Frequency Range Adaptive Phasor and Frequency PMU Algorithms

Abstract: The paper deals with developing and testing frequency-adaptive PMU algorithms with wider linearity range than specified in IEEE Std C37.118-1. This goal is achieved by means of three different concepts encompassing robust state-of-the-art design approaches: 1) FIR bandpass filtering, 2) extended Kalman filtering (EKF), and 3) discrete Fourier transform (DFT) demodulation with FIR low-pass smoothing. While FIR-based PMUs are linear phase with no overshoot in either phase or amplitude step responses, the adaptive EKF PMU is more computer-intensive but allows for a reduced group delay and better out-of-band interference rejection at the cost of a phase step response with overshoot. Frequency measurement performances of the various PMUs are assessed in detail. It turned out that FIR PMUs are best for meeting Std C37-118-1 metrics but they are outperformed by EKF under changing harmonics. Test results on three recent commercial PMU models further confirm that PMU algorithms meeting standard C37-118-1 can behave quite differently under dynamic conditions.

Linear antenna array synthesis using cat swarm optimization

Abstract: Antenna arrays with high directivity and low side lobe levels need to be designed for increasing the efficiency of communication systems. A new evolutionary technique, cat swarm optimization (CSO), is proposed for the synthesis of linear antenna arrays. The CSO is a high performance computational method capable of solving linear and non-linear optimization problems. CSO is applied to optimize the antenna element positions for suppressing side lobe levels and for achieving nulls in desired directions. The steps involved in the problem formulation of the CSO are presented. Various design examples are considered and the obtained CSO based results are validated by comparing with the results obtained using particle swarm optimization (PSO) and ant colony optimization (ACO). The flexibility and ease of implementation of the CSO algorithm is evident from this analysis, showing the algorithm's usefulness in electromagnetic optimization problems.

Sensitivity enhancement by air mediated graphene multilayer based surface plasmon resonance biosensor for near infrared

Abstract: Air mediated surface plasmon resonance sensor at near infrared frequency for sensitivity enhancement has been proposed. The proposed sensor utilizes the advantage of air gap between chalcogenide prism and gold film and high adsorption efficiency of graphene for enhancement of sensitivity. The thickness of air and gold film has been optimized for multiple wavelengths. Based on angular interrogation, the sensitivity of the proposed sensor can be tuned by changing the wavelength of operation in near IR and by judiciously selecting number of graphene layer. The sensitivity of the proposed sensor is 43.18°/RIU for 10 graphene layer at 700 nm where as at 1000 nm, the sensitivity is 36.14°/RIU for same number of graphene layer. We found that the sensitivity of the sensor increases linearly with sensing layer refractive index and number of graphene layer at a given wavelength. Also, we found that the detection accuracy of the proposed sensor in near IR increases by more than 290% for L = 10 as compared to conventional SPR sensor. We believe that the proposed sensor could potentially open a new possibility for high performance SPR sensing.

Design and implementation of a 2-DOF PID compensation for magnetic levitation systems.

Abstract: This paper employs a 2-DOF (degree of freedom) PID controller for compensating a physical magnetic levitation system. It is shown that because of having a feedforward gain in the proposed 2-DOF PID control, the transient performance of the compensated system can be changed in a desired manner unlike the conventional 1-DOF PID control. It is also shown that for a choice of PID parameters, although the theoretical loop robustness is the same for both the compensated systems, in real-time, 2-DOF PID control may provide superior robustness if a suitable choice of the feedforward parameter is made. The results are verified through simulations and experiments.

Enhanced field emission properties of doped graphene nanosheets with layered SnS2

Abstract: We report here our experimental investigations on p-doped graphene using tin sulfide (SnS2), which shows enhanced field emission properties. The turn on field required to draw an emission current density of 1 μA/cm2 is significantly low (almost half the value) for the SnS2/reduced graphene oxide (RGO) nanocomposite (2.65 V/μm) compared to pristine SnS2 (4.8 V/μm) nanosheets. The field enhancement factor β (∼3200 for the SnS2 and ∼3700 for SnS2/RGO composite) was calculated from Fowler-Nordheim (F-N) plots, which indicates that the emission is from the nanometric geometry of the emitter. The field emission current versus time plot shows overall good emission stability for the SnS2/RGO emitter. The magnitude of work function of SnS2 and a SnS2/graphene composite has been calculated from first principles density functional theory (DFT) and is found to be 6.89 eV and 5.42 eV, respectively. The DFT calculations clearly reveal that the enhanced field emission properties of SnS2/RGO are due to a substantial lowe...

Forecasting of currency exchange rates using an adaptive ARMA model with differential evolution based training

Abstract: To alleviate the limitations of statistical based methods of forecasting of exchange rates, soft and evolutionary computing based techniques have been introduced in the literature. To further the research in this direction this paper proposes a simple but promising hybrid prediction model by suitably combining an adaptive autoregressive moving average (ARMA) architecture and differential evolution (DE) based training of its feed-forward and feed-back parameters. Simple statistical features are extracted for each exchange rate using a sliding window of past data and are employed as input to the prediction model for training its internal coefficients using DE optimization strategy. The prediction efficiency is validated using past exchange rates not used for training purpose. Simulation results using real life data are presented for three different exchange rates for one-fifteen months' ahead predictions. The results of the developed model are compared with other four competitive methods such as ARMA-particle swarm optimization (PSO), ARMA-cat swarm optimization (CSO), ARMA-bacterial foraging optimization (BFO) and ARMA-forward backward least mean square (FBLMS). The derivative based ARMA-FBLMS forecasting model exhibits worst prediction performance of the exchange rates. Comparisons of different performance measures including the training time of the all three evolutionary computing based models demonstrate that the proposed ARMA-DE exchange rate prediction model possesses superior short and long range prediction potentiality compared to others.

Modeling isotherms, kinetics and understanding the mechanism of phosphate adsorption onto a solid waste: Ground burnt patties

Abstract: The objective of the present study was to investigate the adsorption behavior of grounded burnt patties (GBP), a solid waste generated from cooking fuel used in earthen stoves, as an adsorbent for phosphate removal from aqueous solution. The characterization of adsorbent was done by proton induced X- ray emission (PIXE), and proton induced γ-ray emission (PIGE) methods and the adsorption mechanisms by Fourier transferred infra-red spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis. The effects of adsorbent dose, contact time, initial solution concentration, agitation, etc. on the uptake of phosphate by the adsorbent in batch mode were examined. The equilibrium data were fitted to different types of adsorption isotherms and kinetic models. Freundlich isotherm model and pseudo-second-order kinetic model illustrated best fit to the data. The favorability and spontaneity of the adsorption process are established by the values of experimentally calculated parameters such as separation factor (RL), 0.03, Freundlich exponent (n), 3.57 and Gibb tm)s free energy change (΢G°), ∧1.32 kJ/mol. The presence of coexisting anions showed no competing effects on phosphate removal efficiency. Breakthrough curves obtained from column study revealed that the lower flow rate and higher bed heights result in longer column saturation time. The results of this study suggested that GBP can be used as a low cost, highly efficient adsorbent for phosphate removal from aqueous solution.

Extended range prediction of active‐break spells of Indian summer monsoon rainfall using an ensemble prediction system in NCEP Climate Forecast System

Abstract: This study analyses skill of an extended range prediction system to forecast Indian Summer Monsoon Rainfall (ISMR) 3-4 pentads in advance. A series of 45-d forecast integrations starting from 1 May to 29 September at 5-d interval for 7 years from 2001 to 2007 are performed with an ensemble prediction system (EPS) in NCEP Climate Forecast System Version 1 (CFSV1) model. The sensitivity experiments with different amount of perturbation suggest that full tendency perturbation experiment on all basic variables including humidity at all vertical level shows higher dispersion among forecast than other experiments. Spread-error relationship shows that the present EPS system is under-dispersive. The lower bound of predictability is about 10-12 d and upper bound of predictability is found to be 20-25 d for zonal wind at 850 and 200 hPa. The signal-to-noise ratio (SNR) of precipitation (500 hPa geopotential height) reveals that the predictability limit is about 15(18) d over Indian monsoon region. The monsoon zone area averaged precipitation forecasts averaged over 5-d period (pentads) up to 4 pentad lead time are also evaluated and compared with observation. The anomaly correlation coefficients (ACC) reaches zero after pentad 3 (pentad 5) lead for precipitation (dynamical variables). A probabilistic approach is developed from the EPS for extended range forecast applications. The relative operating characteristic (ROC) curves for three categories of precipitation shows that the prediction skill for active and break is slightly higher compared to that of normal category and skillful probabilistic forecasts can be generated for precipitation even beyond pentad 4 lead.

Measurement of time-dependent CP violation in B 0 → η'K 0 decays

Abstract: We present a measurement of the time-dependent CP violation parameters in B0 -> eta'K-0 decays. The measurement is based on the full data sample containing 772 x 10(6) B (B) over bar pairs collected at the Upsilon(4S) resonance using the Belle detector at the KEKB asymmetric-energy e+e- collider. The measured values of the mixing-induced and direct CP violation parameters are: sin 2 phi(eff)(1) = +0.68 +/- 0.07 +/- 0.03, A(eta'K0) = +0.03 +/- 0.05 +/- 0.04, where the first uncertainty is statistical arid the second is systernatic. The values obtained are the most accurate to date. lurthierrimore. these results are consistent with our previous measurements and with the world-average value of sin 2 phi(1) measured in B-0 -> J/psi K-0 decays.

On the Performance of Highly Sensitive and Accurate Graphene-on-Aluminum and Silicon-Based SPR Biosensor for Visible and Near Infrared

Abstract: We demonstrate the numerical analysis of surface plasmon resonance biosensor based on graphene on aluminum and silicon. Employing matrix method, it is found that the proposed sensor exhibits high imaging sensitivity ∼400 RIU−1 to 550 RIU−1 in a large dynamic range from visible to near IR region. It is observed that the application of monolayer or bilayer graphene over aluminum not only protects it from oxidation but also enhances the adsorption of biomolecules, which results in the detection of large refractive indices ranging from aqueous solution to biomolecules (refractive index 1.330 to 1.480) with overall high performance in terms of imaging sensitivity and detection accuracy.

Reliability-constrained Based Optimal Placement and Sizing of Multiple Distributed Generators in Power Distribution Network Using Cat Swarm Optimization

Abstract: This article presents optimal placement and sizing of multiple distributed generators to achieve higher overall system reliability in large-scale primary distribution networks using a novel random search algorithm known as cat swarm optimization. A composite reliability index is used as the objective function in the optimization process. Furthermore, the effect of multiple distributed generator units on power transfer capacity and power loss reduction has been observed. Extensive simulations are carried out based on three practical distribution systems to demonstrate the effectiveness of the proposed method. Further, qualitative comparisons are made with adaptive weight particle swarm optimization, particle swarm optimization with constriction factor, and binary-coded genetic algorithm to show the efficacy of the proposed method for optimal placement and sizing of distributed generators in power distribution networks.

Modeling regional aerosol and aerosol precursor variability over California and its sensitivity to emissions and long-range transport during the 2010 CalNex and CARES campaigns

Abstract: . The performance of the Weather Research and Forecasting regional model with chemistry (WRF-Chem) in simulating the spatial and temporal variations in aerosol mass, composition, and size over California is quantified using the extensive meteorological, trace gas, and aerosol measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010. The overall objective of the field campaigns was to obtain data needed to better understand processes that affect both climate and air quality, including emission assessments, transport and chemical aging of aerosols, aerosol radiative effects. Simulations were performed that examined the sensitivity of aerosol concentrations to anthropogenic emissions and to long-range transport of aerosols into the domain obtained from a global model. The configuration of WRF-Chem used in this study is shown to reproduce the overall synoptic conditions, thermally driven circulations, and boundary layer structure observed in region that controls the transport and mixing of trace gases and aerosols. Reducing the default emissions inventory by 50% led to an overall improvement in many simulated trace gases and black carbon aerosol at most sites and along most aircraft flight paths; however, simulated organic aerosol was closer to observed when there were no adjustments to the primary organic aerosol emissions. We found that sulfate was better simulated over northern California whereas nitrate was better simulated over southern California. While the overall spatial and temporal variability of aerosols and their precursors were simulated reasonably well, we show cases where the local transport of some aerosol plumes were either too slow or too fast, which adversely affects the statistics quantifying the differences between observed and simulated quantities. Comparisons with lidar and in situ measurements indicate that long-range transport of aerosols from the global model was likely too high in the free troposphere even though their concentrations were relatively low. This bias led to an over-prediction in aerosol optical depth by as much as a factor of 2 that offset the under-predictions of boundary-layer extinction resulting primarily from local emissions. Lowering the boundary conditions of aerosol concentrations by 50% greatly reduced the bias in simulated aerosol optical depth for all regions of California. This study shows that quantifying regional-scale variations in aerosol radiative forcing and determining the relative role of emissions from local and distant sources is challenging during `clean' conditions and that a wide array of measurements are needed to ensure model predictions are correct for the right reasons. In this regard, the combined CalNex and CARES data sets are an ideal test bed that can be used to evaluate aerosol models in great detail and develop improved treatments for aerosol processes.

A comparative performance assessment of a set of multiobjective algorithms for constrained portfolio assets selection

Abstract: This paper addresses a realistic portfolio assets selection problem as a multiobjective optimization one, considering the budget, floor, ceiling and cardinality as constraints. A novel multiobjective optimization algorithm, namely the non-dominated sorting multiobjective particle swarm optimization (NS-MOPSO), has been proposed and employed efficiently to solve this important problem. The performance of the proposed algorithm is compared with four multiobjective evolution algorithms (MOEAs), based on non-dominated sorting, and one MOEA algorithm based on decomposition (MOEA/D). The performance results obtained from the study are also compared with those of single objective evolutionary algorithms, such as the genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and particle swarm optimization (PSO). The comparisons of the performance include three error measures, four performance metrics, the Pareto front and computational time. A nonparametric statistical analysis, using the Sign test and Wilcoxon signed rank test, is also performed, to demonstrate the superiority of the NS-MOPSO algorithm. On examining the performance metrics, it is observed that the proposed NS-MOPSO approach is capable of identifying good Pareto solutions, maintaining adequate diversity. The proposed algorithm is also applied to different cardinality constraint conditions, for six different market indices, such as the Hang-Seng in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA, Nikkei 225 in Japan, and BSE-500 in India.

Advection, moistening, and shallow-to-deep convection transitions during the initiation and propagation of Madden-Julian Oscillation

Abstract: Using observations from the 2011 AMIE/DYNAMO field campaign over the Indian Ocean and a high-resolution regional model simulation, the processes that lead to the rapid shallow-to-deep convection transitions associated with the initiation and eastward propagation of the Madden-Julian Oscillation (MJO) are examined. By tracking the evolution of the depth of several thousand individual model simulated precipitation features, the role of and the processes that control the observed midtropospheric moisture buildup ahead of the detection of deep convection are quantified at large and convection scales. The frequency of shallow-to-deep convection transitions is found to be sensitive to this midlevel moisture and large-scale uplift. This uplift along with the decline of large-scale drying by equator-ward advection causes the moisture buildup leading to the initiation of the MJO. Convection scale moisture variability and uplift, and large-scale zonal advection play secondary roles.

Syntheses and structural investigation of some alkali metal ion-mediated LVVO2− (L2− = tridentate ONO ligands) species: DNA binding, photo-induced DNA cleavage and cytotoxic activities

Abstract: Eight alkali metal ion-mediated dioxidovanadium(V), [{VVO2L1−6}A(H2O)n]∝, complexes for A = Li+, Na+, K+ and Cs+, containing tridentate aroylhydrazonate ligands coordinating via ONO donor atoms, are described. All the synthesised ligands and the metal complexes were successfully characterised by elemental analysis, IR, UV-Vis and NMR spectroscopy. X-ray crystallographic investigation of 3, 5–7 shows the presence of distorted NO4 coordination geometries for LVO2− in each case, and varying μ-oxido and/or μ-aqua bridging with interesting variations correlated with the size of the alkali metal ions: with small Li+, no bridging-O is found but four ion aggregates are found with Na+, chains for K+ and finally, layers for Cs+. Two (5) or three-dimensional (3, 6 and 7) architectures are consolidated by hydrogen bonding. The dioxidovanadium(V) complexes were found to exhibit DNA binding activity due to their interaction with CT-DNA by the groove binding mode, with binding constants ranging from 103 to 104 M−1. Complexes 1–8 were also tested for DNA nuclease activity against pUC19 plasmid DNA which showed that 6 and 7 had the best DNA binding and photonuclease activity; these results support their good protein binding and cleavage activity with binding constants ranging from 104 to 105 M−1. Finally, the in vitro antiproliferative activity of all complexes was assayed against the HeLa cell line. Some of the complexes (2, 5, 6 and 7) show considerable activity compared to commonly used chemotherapeutic drugs. The variation in cytotoxicity of the complexes is influenced by the various functional groups attached to the aroylhydrazone derivative.

Field emission properties of ZnO nanosheet arrays

Abstract: Electron emission properties of electrodeposited ZnO nanosheet arrays grown on Indium tin oxide coated glass substrates have been studied. Influence of oxygen vacancies on electronic structures and field emission properties of ZnO nanosheets are investigated using density functional theory. The oxygen vacancies produce unshared d electrons which form an impurity energy state; this causes shifting of Fermi level towards the vacuum, and so the barrier energy for electron extraction reduces. The ZnO nanosheet arrays exhibit a low turn-on field of 2.4 V/μm at 0.1 μA/cm2 and current density of 50.1 μA/cm2 at an applied field of 6.4 V/μm with field enhancement factor, β = 5812 and good field emission current stability. The nanosheet arrays grown by a facile electrodeposition process have great potential as robust high performance vertical structure electron emitters for future flat panel displays and vacuum electronic device applications.