Electron diffraction structure analysis: structural research with low-quality diffraction data

Electron Diffraction Structure Analysis (EDSA) with data from standard selected-area electron diffraction (SAED) is still the method of choice for structure determination of nano-sized single crystals. The recently determined heavy atom structure α-Ti2Se (Albe & Weirich, 2003) is used as an example to illustrate the developed procedure for structure determination from two-dimensionally SAED data via direct methods and kinematical least-squares refinement. Despite the investigated crystallite had a relatively large effective thickness of about 230 Å as determined from dynamical calculations, the obtained structural model from SAED data was found in good agreement with the result from an earlier single crystal X-ray study (Weirich, Pöttgen & Simon, 1996). Arguments, which support the validity of the used quasi-kinematical approach, are given in the text. The influences of dynamical and secondary scattering on the quality of the data and the structure solution are discussed. Moreover, the usefulness of first-principles calculations for verifying the results from EDSA is demonstrated by two examples, whereas one of the structures was unattainable by conventional X-ray diffraction.

System Dy-Fe-O: thermodynamic properties of ternary oxides using Calvet calorimetry and solid-state electrochemical cell

The enthalpy increments and the standard molar Gibbs energies of formation-of DyFeO3(s) and Dy3Fe5O12(s) have been measured using a Calvet micro-calorimeter and a solid oxide galvanic cell, respectively. A co-operative phase transition, related to anti-ferromagnetic to paramagnetic transformation, is apparent. from the heat capacity data for DyFeO3 at similar to 648 K. A similar type of phase transition has been observed for Dy3Fe5O12 at similar to 560 K which is related to ferrimagnetic to paramagnetic transformation. Enthalpy increment data for DyFeO3(s) and Dy3Fe5O12(s), except in the vicinity of the second-order transition, can be represented by the following polynomial expressions:{H(0)m(T) - H(0)m(298.15 K)) (Jmol(-1)) (+/-1.1%) = -52754 + 142.9 x (T (K)) + 2.48 x 10(-3) x (T (K))(2) + 2.951 x 10(6) x (T (K))(-1); (298.15 less than or equal to T (K) less than or equal to 1000) for DyFeO3(s), and {H(0)m(T) - H(0)m(298.15 K)} (Jmol(-1)) (+/-1.2%) = -191048 + 545.0 x (T - (K)) + 2.0 x 10(-5) x (T (K))(2) + 8.513 x 10(6) x (T (K))(-1); (208.15 less than or equal to T (K) less than or equal to 1000)for Dy3Fe5O12(s). The reversible emfs of the solid-state electrochemical cells: (-)Pt/{DyFeO3(s) + Dy2O3(s) + Fe(s)}/YDT/CSZ//{Fe(s) + Fe0.95O(s)}/Pt(+) and (-)Pt/{Fe(s) + Fe0.95O(s)}//CSZ//{DyFeO3(s) + Dy3Fe5O12(s) + Fe3O4(s)}/Pt(+), were measured in the temperature range from 1021 to 1250 K and 1035 to 1250 K, respectively. The standard Gibbs energies of formation of solid DyFeO3 and Dy3Fe5O12 calculated by the least squares regression analysis of the data obtained in the present study, and data for Fe0.95O and Dy2O3 from the literature, are given by Delta(f)G(0)m(DyFeO3,s)(kJmol(-1))(+/-3.2)= -1339.9 + 0.2473 x (T(K)); (1021 less than or equal to T (K) less than or equal to 1548)and D(f)G(0)m(Dy3Fe5O12,s) (kJmol(-1)) (+/-3.5) = -4850.4 + 0.9846 x (T (K)); (1035 less than or equal to T (K) less than or equal to 1250) The uncertainty estimates for Delta(f)G(0)m include the standard deviation in the emf and uncertainty in the data taken from the literature. Based on the thermodynamic information, oxygen potential diagram and chemical potential diagrams for the system Dy-Fe-O were developed at 1250 K. (C) 2002 Editions scientifiques et medicales Elsevier SAS. All rights reserved.

Thermodynamic studies on NdFeO3(s)

The enthalpy increments and the standard molar Gibbs energy of formation of NdFeO3(s) have been measured using a hightemperature Calvet microcalorimeter and a solid oxide galvanic cell, respectively. A lambda-type transition, related to magnetic order-disorder transformation (antiferromagnetic to paramagnetic), is apparent from the heat capacity data at similar to 687 K. Enthalpy increments, except in the vicinity of transition, can be represented by a polynomial expression: {Hdegrees(m)(T)-Hdegrees(m) (298.15 K)} /J(.)mol(-1) (+/- 0.7%)=-53625.6+146.0(T/K) +1.150 X 10(-4)(T/K)(2) +3.007 x 10(6)(T/K)(-1); (298.15 less than or equal to T/K less than or equal to 1000). The heat capacity, the first differential of {Hdegrees(m)(T)-Hdegrees(m)(298.15 K)}with respect to temperature, is given by Cdegrees(pm)/J(.)K(-1.)mol(-1)=146.0+ 2.30x10(-4) (T/K) - 3.007 X 10(6)(T/K)(-2). The reversible emf's of the cell, (-) Pt/{NdFeO3(s) +Nd2O3(s)+Fe(s)}//YDT/CSZ// Fe(s)+'FeO'(s)}/Pt(+), were measured in the temperature range from 1004 to 1208 K. It can be represented within experimental error by a linear equation: E/V=(0.1418 +/- 0.0003)-(3.890 +/- 0.023) x 10(-5)(T/K). The Gibbs energy of formation of solid NdFeO, calculated by the least-squares regression analysis of the data obtained in the present study, and data for Fe0.95O and Nd2O3 from the literature, is given by Delta(f)Gdegrees(m)(NdFeO3 s)/kJ (.) mol(-1)( +/- 2.0)=1345.9+0.2542(T/K); (1000 less than or equal to T/K less than or equal to 1650). The error in Delta(f)Gdegrees(m)(NdFeO3, s, T) includes the standard deviation in emf and the uncertainty in the data taken from the literature. Values of Delta(f)Hdegrees(m)(NdFeO3, s, 298.15 K) and Sdegrees(m) (NdFeO3 s, 298.15 K) calculated by the second law method are - 1362.5 (+/-6) kJ (.) mol(-1) and 123.9 (+/-2.5) J (.) K-1 (.) mol(-1), respectively. Based on the thermodynamic information, an oxygen potential diagram for the system Nd-Fe-O was developed at 1350 K. (C) 2002 Elsevier Science (USA).

Thermodynamic properties of SmFeO3(S) and SM3R5O12(S)

The enthalpy increments and the standard molar Gibbs energy (G) of formation of SmFeO3(S) and SM3Fe5O12(s) have been measured using a Calvet micro-calorimeter and a solid oxide galvanic cell, respectively. A X-type transition, related to magnetic order-disorder transformation (antiferromagnetic to paramagnetic), is apparent from the heat capacity data at similar to673 K for SmFeO3(s) and at similar to560 K for Sm3Fe5O12(S). Enthalpy increment data for SmFeO3(s) and SM3Fe5O12(s), except in the vicinity of X-transition, can be represented by the following polynomial expressions: {H-m(0)(T) - H-m(0)(298.15 K){/J mol-(1)(+/-1.2%) = -54 532.8 + 147.4 . (T/K) + 1.2 . 10(-4) . (T/K)(2) +3.154 . 10(6) . (T/K)(-1); (298.15 less than or equal to T/K less than or equal to 1000) for SmFeO3(s), and {H-m(0)(T) - H-m(0)(298.15 K)}/J mol(-1) (+/-1.4%) = -192 763 + 554.7 . (T/K) + 2.0 . 10(-6) . (T/K)(2) + 8.161 . 10(6) - (T/K)(-1); (298.15 less than or equal to T/K less than or equal to 1000) for Sm3Fe5O12(s). The reversible emf of the solid-state electrochemical cells, (-)Pt/{SmFeO3(s) + Sm2O3(S) + Fe(s)) // YDT / CSZ // {Fe(s) + Fe0.95O(s)} / Pt(+) and (-)Pt/{Fe(s) + Fe0.95O(S)} // CSZ // {SmFeO3(s) + Sm3Fe5O12(s) + Fe3O4(s) / Pt(+), were measured in the temperature ranges of 1005-1259 K and 1030-1252 K, respectively. The standard molar G of formation of solid SmFeO3 and Sm3Fe5O12 calculated by the least squares regression analysis of the data obtained in the current study, and data for Fe0.95O and Sm2O3 from the literature, are given by: Delta(f)G(m)(0)(SmFeO3, s)/kj . mol(-1)(+/-2.0) = -1355.2 + 0.2643 . ; (1005 less than or equal to T/K less than or equal to 1570) and Delta(f)G(m)(0)(Sm3Fe5O12, s)/kj . mol(-1) (+/- 3.1) = -4891.0 + 1.0312 . (T/K); (1030 less than or equal to T/K less than or equal to 1252) The uncertainty estimates for Delta(f)G(m)(0) include the standard deviation in the emf and uncertainty in the data taken from the literature. Based on these thermodynamic data, the oxygen potential diagram for the system Sm-Fe-O was constructed at 1250 K.

Anomalous X-ray scattering study of local structures in the superionic conducting glass (AgBr)0.4 (Ag2O)0.3 (GeO2)0.3

The local structural information in the near-neighbor region of superionic conducting glass (AgBr)0.4(Ag2O)0.3(GeO2)0.3 has been estimated from the anomalous X-ray scattering (AXS) measurements using Ge and Br K absorption edges. The possible atomic arrangements in the near-neighbor region of this glass were obtained by coupling the results with the least-squares variational method so as to reproduce two differential intensity profiles for Ge and Br as well as the ordinary scattering profile. The coordination number of oxygen around Ge is found to be 3.6 at a distance of 0.176 nm, suggesting the GeO4 tetrahedral unit as the probable structural entity in this glass. Moreover, the coordination number of Ag around Br is estimated as 6.3 at a distance of 0.284 nm, suggesting an arrangement similar to that in crystalline AgBr.

Two-dimensional flow past circular cylinders using finite volume lattice Boltzmann formulation

In this article, an extension to the total variation diminishing finite volume formulation of the lattice Boltzmann equation method on unstructured meshes was presented. The quadratic least squares procedure is used for the estimation of first-order and second-order spatial gradients of the particle distribution functions. The distribution functions were extrapolated quadratically to the virtual upwind node. The time integration was performed using the fourth-order RungeKutta procedure. A grid convergence study was performed in order to demonstrate the order of accuracy of the present scheme. The formulation was validated for the benchmark two-dimensional, laminar, and unsteady flow past a single circular cylinder. These computations were then investigated for the low Mach number simulations. Further validation was performed for flow past two circular cylinders arranged in tandem and side-by-side. Results of these simulations were extensively compared with the previous numerical data. Copyright (C) 2011 John Wiley & Sons, Ltd.

On the Selection of Optimum Savitzky-Golay Filters

Savitzky-Golay (S-G) filters are finite impulse response lowpass filters obtained while smoothing data using a local least-squares (LS) polynomial approximation. Savitzky and Golay proved in their hallmark paper that local LS fitting of polynomials and their evaluation at the mid-point of the approximation interval is equivalent to filtering with a fixed impulse response. The problem that we address here is, ``how to choose a pointwise minimum mean squared error (MMSE) S-G filter length or order for smoothing, while preserving the temporal structure of a time-varying signal.'' We solve the bias-variance tradeoff involved in the MMSE optimization using Stein's unbiased risk estimator (SURE). We observe that the 3-dB cutoff frequency of the SURE-optimal S-G filter is higher where the signal varies fast locally, and vice versa, essentially enabling us to suitably trade off the bias and variance, thereby resulting in near-MMSE performance. At low signal-to-noise ratios (SNRs), it is seen that the adaptive filter length algorithm performance improves by incorporating a regularization term in the SURE objective function. We consider the algorithm performance on real-world electrocardiogram (ECG) signals. The results exhibit considerable SNR improvement. Noise performance analysis shows that the proposed algorithms are comparable, and in some cases, better than some standard denoising techniques available in the literature.

A Savitzky-Golay Filtering Perspective of Dynamic Feature Computation

We address the classical problem of delta feature computation, and interpret the operation involved in terms of Savitzky- Golay (SG) filtering. Features such as themel-frequency cepstral coefficients (MFCCs), obtained based on short-time spectra of the speech signal, are commonly used in speech recognition tasks. In order to incorporate the dynamics of speech, auxiliary delta and delta-delta features, which are computed as temporal derivatives of the original features, are used. Typically, the delta features are computed in a smooth fashion using local least-squares (LS) polynomial fitting on each feature vector component trajectory. In the light of the original work of Savitzky and Golay, and a recent article by Schafer in IEEE Signal Processing Magazine, we interpret the dynamic feature vector computation for arbitrary derivative orders as SG filtering with a fixed impulse response. This filtering equivalence brings in significantly lower latency with no loss in accuracy, as validated by results on a TIMIT phoneme recognition task. The SG filters involved in dynamic parameter computation can be viewed as modulation filters, proposed by Hermansky.

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.

Temporal Envelope Fit of Transient Audio Signals

We address the problem of temporal envelope modeling for transient audio signals. We propose the Gamma distribution function (GDF) as a suitable candidate for modeling the envelope keeping in view some of its interesting properties such as asymmetry, causality, near-optimal time-bandwidth product, controllability of rise and decay, etc. The problem of finding the parameters of the GDF becomes a nonlinear regression problem. We overcome the hurdle by using a logarithmic envelope fit, which reduces the problem to one of linear regression. The logarithmic transformation also has the feature of dynamic range compression. Since temporal envelopes of audio signals are not uniformly distributed, in order to compute the amplitude, we investigate the importance of various loss functions for regression. Based on synthesized data experiments, wherein we have a ground truth, and real-world signals, we observe that the least-squares technique gives reasonably accurate amplitude estimates compared with other loss functions.

Optimal synthesis of adjustable planar four-bar crank-rocker type mechanisms for approximate multi-path generation

This paper deals with an optimization based method for synthesis of adjustable planar four-bar, crank-rocker mechanisms. For multiple different and desired paths to be traced by a point on the coupler, a two stage method first determines the parameters of the possible driving dyads. Then the remaining mechanism parameters are determined in the second stage where a least-squares based circle-fitting procedure is used. Compared to existing formulations, the optimization method uses less number of design variables. Two numerical examples demonstrate the effectiveness of the proposed synthesis method. (C) 2013 Elsevier Ltd. All rights reserved.

Learning from positive and unlabelled examples using maximum margin clustering

Learning from Positive and Unlabelled examples (LPU) has emerged as an important problem in data mining and information retrieval applications. Existing techniques are not ideally suited for real world scenarios where the datasets are linearly inseparable, as they either build linear classifiers or the non-linear classifiers fail to achieve the desired performance. In this work, we propose to extend maximum margin clustering ideas and present an iterative procedure to design a non-linear classifier for LPU. In particular, we build a least squares support vector classifier, suitable for handling this problem due to symmetry of its loss function. Further, we present techniques for appropriately initializing the labels of unlabelled examples and for enforcing the ratio of positive to negative examples while obtaining these labels. Experiments on real-world datasets demonstrate that the non-linear classifier designed using the proposed approach gives significantly better generalization performance than the existing relevant approaches for LPU.

Projection-based atom selection in orthogonal matching pursuit for compressive sensing

For compressive sensing, we endeavor to improve the atom selection strategy of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlying support set progressively through iterations, we use a least squares solution based atom selection method. From a set of promising atoms, the choice of an atom is performed through a new method that uses orthogonal projection along-with a standard matched filter. Through experimental evaluations, the effect of projection based atom selection strategy is shown to provide a significant improvement for the support set recovery performance, in turn, the compressive sensing recovery.

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO-OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator. (C) 2013 Elsevier GmbH. All rights reserved.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America