Uncertainty visualization using HDR volume rendering

In this paper, we explore a novel idea of using high dynamic range (HDR) technology for uncertainty visualization. We focus on scalar volumetric data sets where every data point is associated with scalar uncertainty. We design a transfer function that maps each data point to a color in HDR space. The luminance component of the color is exploited to capture uncertainty. We modify existing tone mapping techniques and suitably integrate them with volume ray casting to obtain a low dynamic range (LDR) image. The resulting image is displayed on a conventional 8-bits-per-channel display device. The usage of HDR mapping reveals fine details in uncertainty distribution and enables the users to interactively study the data in the context of corresponding uncertainty information. We demonstrate the utility of our method and evaluate the results using data sets from ocean modeling.

Microprocessor-based algorithm for symmetrical-components calculation

This letter presents a microprocessor-based algorithm for calculating symmetrical components from the distorted transient voltage and current signals in a power system. The fundamental frequency components of the 3-phase signals are first extracted using an algorithm based on Haar functions and then "symmetrical-component transformation is applied to obtain the sequence components. The algorithm presented is computationally efficient and fast. This algorithm is better suited for application in microprocessor-based protection schemes of synchronous and induction machines.

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.

Material uncertainty effect on vibration control of smart composite plate using polynomial chaos expansion

Polynomial Chaos Expansion with Latin Hypercube sampling is used to study the effect of material uncertainty on vibration control of a smart composite plate with piezoelectric sensors/actuators. Composite material properties and piezoelectric coefficients are considered as independent and normally distributed random variables. Numerical results show substantial variation in structural dynamic response due to material uncertainty of active vibration control system. This change in response due to material uncertainty can be compensated by actively tuning the feedback control system. Numerical results also show variation in dispersion of dynamic characteristics and control parameters with respect to ply angle and stacking sequence.

Minimum uncertainty and entanglement

We address the question, does a system A being entangled with another system B, put any constraints on the Heisenberg uncertainty relation (or the Schrodinger-Robertson inequality)? We find that the equality of the uncertainty relation cannot be reached for any two noncommuting observables, for finite dimensional Hilbert spaces if the Schmidt rank of the entangled state is maximal. One consequence is that the lower bound of the uncertainty relation can never be attained for any two observables for qubits, if the state is entangled. For infinite-dimensional Hilbert space too, we show that there is a class of physically interesting entangled states for which no two noncommuting observables can attain the minimum uncertainty equality.

MINIMUM UNCERTAINTY AND ENTANGLEMENT

We address the question, does a system A being entangled with another system B, put any constraints on the Heisenberg uncertainty relation (or the Schrodinger-Robertson inequality)? We find that the equality of the uncertainty relation cannot be reached for any two noncommuting observables, for finite dimensional Hilbert spaces if the Schmidt rank of the entangled state is maximal. One consequence is that the lower bound of the uncertainty relation can never be attained for any two observables for qubits, if the state is entangled. For infinite-dimensional Hilbert space too, we show that there is a class of physically interesting entangled states for which no two noncommuting observables can attain the minimum uncertainty equality.

Spatial Wavelet Approach to Local Matrix Crack Detection in Composite Beams with Ply Level Material Uncertainty

Wavelet coefficients based on spatial wavelets are used as damage indicators to identify the damage location as well as the size of the damage in a laminated composite beam with localized matrix cracks. A finite element model of the composite beam is used in conjunction with a matrix crack based damage model to simulate the damaged composite beam structure. The modes of vibration of the beam are analyzed using the wavelet transform in order to identify the location and the extent of the damage by sensing the local perturbations at the damage locations. The location of the damage is identified by a sudden change in spatial distribution of wavelet coefficients. Monte Carlo Simulations (MCS) are used to investigate the effect of ply level uncertainty in composite material properties such as ply longitudinal stiffness, transverse stiffness, shear modulus and Poisson's ratio on damage detection parameter, wavelet coefficient. In this study, numerical simulations are done for single and multiple damage cases. It is observed that spatial wavelets can be used as a reliable damage detection tool for composite beams with localized matrix cracks which can result from low velocity impact damage.

A simulation-based algorithm for optimal pricing policy under demand uncertainty

We propose a simulation-based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high-dimensional parameters, it uses the efficient smoothed functional gradient estimator.

Hydrochalcogenation of Symmetrical and Unsymmetrical Buta-1,3-diynes with Diaryl Dichalcogenides: Facile Entry to (Z)-1-(Organylchalcogeno)but-1-en-3-yne Derivatives

This work describes an efficient and stereoselective method for the hydrothiolation and -selenation of buta-1,3-diyne derivatives using diaryl disulfides or diselenides, respectively. In the presence of rongalite (HOCH2SO2Na) and potassium carbonate, buta-1,3-diynes undergo stereoselective addition of the thiolate or selenide anion generated in situ from diaryl disulfides or diselenides to afford the corresponding (Z)-1-sulfanyl-or (Z)-1-selanylalk-1-en-3-yne derivatives, respectively. The reaction of buta-1,3-diynes with diaryl disulfides or diselenides at higher temperature (70 degrees C) gave a mixture of monothiolation/selenation and bisthiolation/selenation products in moderate to good yields.

Structural investigation of resorcinol based symmetrical banana mesogens by XRD, NMR and polarization measurements

Synthesis and structural characterization of two novel symmetrical banana mesogens built from resorcinol with seven phenyl rings linked by ester and imine with a terminal dodecyl/dodecyloxy chain has been carried out. Density functional theory (DFT) has been employed for obtaining the geometry optimized structures, the dipole moments and C-13 NMR chemical shifts. The HOPM and DSC studies revealed enantiotropic B-2 and B-7 phases for the dodecyl and dodecyloxy homologs respectively. The powder X-ray studies of both the mesogens indicate the presence of layer ordering. The polarization measurements reveal an anti-ferroelectric switching for the B-2 phase of the dodecyl homolog whose structure has been identified as SmCSPA. The B-7 phase of the dodecyloxy homolog was found to be non-switchable. High resolution C-13 NMR study of the dodecyl homolog in its mesophase has been carried out. C-13-H-1 dipolar couplings obtained from the 2-dimensional separated local field spectroscopy experiment were used to obtain the orientational order parameters of the different segments of the mesogen. Very large C-13-H-1 dipolar couplings observed for the carbons of the central phenyl ring (9.7-12.3 kHz) in comparison to the dipolar couplings of those of the side arm phenyl rings (less than 3 kHz) are a direct consequence of the ordering in the banana phase and the shape of the molecule. From the ratio of the local order parameter values, the bent-angle of the mesogen could be determined in a straight forward manner to be 120.5 degrees.

Model and parameter uncertainty in IDF relationships under climate change

Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.

New symmetrical dinucleating ligand based assembly of bridged dicopper(II) and dizinc(II) centers: Synthesis, structure, spectroscopy, magnetic properties and glycoside hydrolysis

Two dinuclear copper(II) complexes Li(H2O)(3)(CH3OH)](4)Cu2Br4]Cu-2(cpdp)(mu-O2CCH3)](4)(OH)(2) (1), Cu (H2O)(4)]Cu-2(cpdp)(mu-O2CC6H5)](2)Cl-2 center dot 5H(2)O (2), and a dinuclear zinc(II) complex Zn-2(cpdp)(mu-O2CCH3)] (3) have been synthesized using pyridine and benzoate functionality based new symmetrical dinucleating ligand, N, N'-Bis2-carboxybenzomethyl]-N, N'-Bis2-pyridylmethyl]-1,3-diaminopropan-2-ol (H(3)cpdp). Complexes 1, 2 and 3 have been synthesized by carrying out reaction of the ligand H3cpdp with stoichiometric amounts of Cu-2(O2CCH3)(4)(H2O)(2)], CuCl2 center dot 2H(2)O/C6H5COONa, and Zn(CH3COO)(2)center dot 2H(2)O, respectively, in methanol in the presence of NaOH at ambient temperature. Characterizations of the complexes have been done using various analytical techniques including single crystal X-ray structure determination. The X-ray crystal structure analyses reveal that the copper(II) ions in complexes 1 and 2 are in a distorted square pyramidal geometry with Cu-Cu separation of 3.455(8) angstrom and 3.492(1)angstrom, respectively. The DFT optimized structure of complex 3 indicates that two zinc(II) ions are in a distorted square pyramidal geometry with Zn-Zn separation of 3.492(8)angstrom. UV-Vis and mass spectrometric analyses of the complexes confirm their dimeric nature in solution. Furthermore, H-1 and C-13 NMR spectroscopic investigations authenticate the integrity of complex 3 in solution. Variable-temperature (2-300 K) magnetic susceptibility measurements show the presence of antiferromagnetic interactions between the copper centers, with J = -26.0 cm(-1) and -23.9 cm(-1) ((H) over cap = -2JS(1)S(2)) in complexes 1 and 2, respectively. In addition, glycosidase-like activity of the complexes has been investigated in aqueous solution at pH similar to 10.5 by UV-Vis spectrophotometric technique using p-nitrophenyl-alpha-D-glucopyranoside (4) and p-nitrophenyl-beta-D-glucopyranoside (5) as model substrates. (C) 2015 Elsevier B.V. All rights reserved.

Uncertainty Quantification in Ultrasonic Wave Based Detection of Delamination in Composite Structures

In this paper we consider the problem of guided wave scattering from delamination in laminated composite and further the problem of estimating delamination size and layer-wise location from the guided wave measurement. Damage location and region/size can be estimated from time of flight and wave packet spread, whereas depth information can be obtained from wavenumber modulation in the carrier packet. The key challenge is that these information are highly sensitive to various uncertainties. Variation in reflected and transmitted wave amplitude in a bar due to boundary/interface uncertainty is studied to illustrate such effect. Effect of uncertainty in material parameters on the time of flight are estimated for longitudinal wave propagation. To evaluate the effect of uncertainty in delamination detection, we employ a time domain spectral finite element (tSFEM) scheme where wave propagation is modeled using higher-order interpolation with shape function have spectral convergence properties. A laminated composite beam with layer-wise placement of delamination is considered in the simulation. Scattering due to the presence of delamination is analyzed. For a single delamination, two identical waveforms are created at the two fronts of the delamination, whereas waves in the two sub-laminates create two independent waveforms with different wavelengths. Scattering due to multiple delaminations in composite beam is studied.

Damage assessment of composite plate structures with material and measurement uncertainty

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problein in damage assessment. A recently developed C-0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data. (C) 2016 Elsevier Ltd. All rights reserved.

The impact of architectural uncertainty on product introduction in dispersed environments

This research addresses product introduction dispersed across locations and companies. Mechanisms appropriate to integrate activities in collocated teams may not serve dispersed teams well. A semiconductor design licensor was studied in depth to explore how dispersed product introduction varies with uncertainty. We found that autonomous teams focused on sub-products (micro-products) were used rather than cross-functional teams in departments with high architectural uncertainty. Both types of teams were effectively dispersed across locations and companies. This suggests that small high-technology companies may find it easier to expand into new geographies and product lines than was previously believed.