A Simple Multiple Pulsewidth Modulated AC Choppe

A simple multiple pulsewidth modulated (MPWM) ac chopper using power transistors for 3-ý power control is discussed. 120ý chopping period is used for main transistors so that the circuit can accommodate resistive and lagging or leading power factor loads. Only 1-ý sensing is used for 3-ý control. An alternate economical power and control schemes for 3-ý MPWM ac choppers suitable only for resistive loads is also suggested. The experimental results for 12 choppings per cycle are given.

Amide-Based Glutathione Peroxidase Mimics: Effect of Secondary and Tertiary Amide Substituents on Antioxidant Activity

A series of secondary and tertiary amide-substituted diselenides were synthesized and studied for their GPx-like antioxidant activities using H2O2 Cum-OOH, and tBuOOH as substrates and PhSH as thiol co-substrate.The effect of substitution at the free -NH group of the amide moiety in the sec-amide-based diselenides on GPx activity was analyzed by detailed experimental and theoretical methods. It is observed that substitution at the free -NH group significantly enhances the GPx-like activities of the sec-amide-based diselenides, mainly by reducing the Se center dot center dot center dot O nonbonded interactions. The reduction in strength of the Se center dot center dot center dot O interaction upon introduction of N,N-dialkyl substituents not only prevents the undesired thiol exchange reactions, but also reduces the stability of selenenyl sulfide intermediates. This leads to a facile disproportionation of the selenenyl sulfide to the corresponding diselenide, which enhances the catalytic activity. The mechanistic investigations indicate that the reactivity of diselenides having sec-or tert-amide moieties with PhSH is extremely slow; indicating that the first step of the catalytic cycle involves the reaction between the diselenides and peroxide to produce the corresponding selenenic and seleninic acids.

Multiresolution Area-based Fractal Dimension Estimation of Signals Applied to EEG Data

In this paper, we present an approach to estimate fractal complexity of discrete time signal waveforms based on computation of area bounded by sample points of the signal at different time resolutions. The slope of best straight line fit to the graph of log(A(rk)A / rk(2)) versus log(l/rk) is estimated, where A(rk) is the area computed at different time resolutions and rk time resolutions at which the area have been computed. The slope quantifies complexity of the signal and it is taken as an estimate of the fractal dimension (FD). The proposed approach is used to estimate the fractal dimension of parametric fractal signals with known fractal dimensions and the method has given accurate results. The estimation accuracy of the method is compared with that of Higuchi's and Sevcik's methods. The proposed method has given more accurate results when compared with that of Sevcik's method and the results are comparable to that of the Higuchi's method. The practical application of the complexity measure in detecting change in complexity of signals is discussed using real sleep electroencephalogram recordings from eight different subjects. The FD-based approach has shown good performance in discriminating different stages of sleep.

Signal Characterization using Fractal Dimension

Fractal Dimensions (FD) are popular metrics for characterizing signals. They are used as complexity measuresin signal analysis applications in various fields. However, proper interpretation of such analyses has not been thoroughly addressed. In this paper, we study the effect of various signal properties on FD and interpret results in terms of classical signal processing concepts such as amplitude, frequency,number of harmonics, noise power and signal bandwidth. We have used Higuchi’s method for estimating FDs. This study helps in gaining a better understanding of the FD complexity measure for various signal parameters. Our results indicate that FD is a useful metric in estimating various signal properties. As an application of the FD measure in real world scenario, the FD is used as a feature in discriminating seizures from seizure free intervals in intracranial EEG data recordings and the FD feature has given good discrimination performance.

A comparative study of speaker adaptation methods

For the problem of speaker adaptation in speech recognition, the performance depends on the availability of adaptation data. In this paper, we have compared several existing speaker adaptation methods, viz. maximum likelihood linear regression (MLLR), eigenvoice (EV), eigenspace-based MLLR (EMLLR), segmental eigenvoice (SEV) and hierarchical eigenvoice (HEV) based methods. We also develop a new method by modifying the existing HEV method for achieving further performance improvement in a limited available data scenario. In the sense of availability of adaptation data, the new modified HEV (MHEV) method is shown to perform better than all the existing methods throughout the range of operation except the case of MLLR at the availability of more adaptation data.

Flexure of composite plates

A new higher order shear deformation theory of laminated composite plates is developed. The basic displacement variables in this theory are two partial normal displacements and two in-plane displacement parameters. The governing equations are presented in the form of four simultaneous partial differential equations. The shear deformation theories of Bhimareddy and Stevens, and of Reddy are special cases of this formulation. In their models, transverse shear strains will become zero at points in the plate where displacements are constrained to be zero such as those on fixed edges. This limitation has been overcome in the present formulation.

A knowledge-based clustering scheme

In this paper the notion of conceptual cohesiveness is precised and used to group objects semantically, based on a knowledge structure called ‘cohesion forest’. A set of axioms is proposed which should be satisfied to make the generated clusters meaningful.

Spatial correlations around a Kondo impurity

We present a method for calculating zero-frequency, spatially varying response and correlation functions around a magnetic impurity in metals. We illustrate the procedure which involves a combination of perturbative scaling and nonperturbative renormalization-group methods for the spin-(1/2) Kondo impurity. We explain the factorization of the temperature and spatial dependence of the Knight shift observed in NMR experiments.

On prequantization to reduce errors in double phase holograms

Prequantization has been forwarded as a means to improve the performance of double phase holograms (DPHs). We show here that any improvement (even under the best of conditions) is not large enough to help the DPH to compete favourably with other holograms.

Non-linear dynamic analysis of rotors by finite element method

Non-linear natural vibration characteristics and the dynamic response of hingeless and fully articulated rotors of rectangular cross-section are studied by using the finite element method. In the formulation of response problems, the global variables are augmented with appropriate additional variables, facilitating direct determination of sub-harmonic response. Numerical results are given showing the effect of the geometric non-linearity on the first three natural frequencies. Response analysis of typical rotors indicates a possibility of substantial sub-harmonic response especially in the fully articulated rotors widely adopted in helicopters.

How Good is the Assumption About Visible Surface Reflectance in MODIS Aerosol Retrieval Over Land? A Comparison With Aircraft Measurements Over an Urban Site in India

In this paper, we discuss the measurements of spectral surface reflectance (rho(s)(lambda)) in the wavelength range 350-2500 nm measured using a spectroradiometer onboard a low-flying aircraft over Bangalore (12.95 degrees N, 77.65 degrees E), an urban site in southern India. The large discrepancies in the retrieval of aerosol propertiesover land by the Moderate-Resolution Imaging Spectroradiometer (MODIS), which could be attributed to the inaccurate estimation of surface reflectance at many sites in India and elsewhere, provided motivation for this paper. The aim of this paper was to verify the surface reflectance relationships assumed by the MODIS aerosol algorithm for the estimation of surface reflectance in the visible channels (470 and 660 nm) from the surface reflectance at 2100 nm for aerosol retrieval over land. The variety of surfaces observed in this paper includes green and dry vegetations, bare land, and urban surfaces. The measuredreflectance data were first corrected for the radiative effects of atmosphere lying between the ground and aircraft using the Second Simulation of Satellite Signal in the Solar Spectrum (6S) radiative transfer code. The corrected surface reflectance in the MODIS's blue (rho(s)(470)), red (rho(s)(660)), and shortwave-infrared (SWIR) channel (rho(s)(2100)) was linearly correlated. We found that the slope of reflectance relationship between 660 and 2100 nm derived from the forward scattering data was 0.53 with an intercept of 0.07, whereas the slope for the relationship between the reflectance at 470 and 660 nm was 0.85. These values are much higher than the slope (similar to 0.49) for either wavelengths assumed by the MODIS aerosol algorithm over this region. The reflectance relationship for the backward scattering data has a slope of 0.39, with an intercept of 0.08 for 660 nm, and 0.65, with an intercept of 0.08 for 470 nm. The large values of the intercept (which is very small in the MODIS reflectance relationships) result in larger values of absolute surface reflectance in the visible channels. The discrepancy between the measured and assumed surface reflectances could lead to error in the aerosol retrieval. The reflectance ratio (rho(s)(660)/rho(s)(2100)) showed a clear dependence on the N D V I-SWIR where the ratio increased from 0.5 to 1 with an increase in N V I-SWIR from 0 to 0.5. The high correlation between the reflectance at SWIR wavelengths (2100, 1640, and 1240 nm) indicated an opportunity to derive the surface reflectance and, possibly, aerosol properties at these wavelengths. We need more experiments to characterize the surface reflectance and associated inhomogeneity of land surfaces, which play a critical role in the remote sensing of aerosols over land.

Sodium santalbate-dimethyl sulfate inclusion complex

A molecular inclusion complex has been obtained from the major acetylenic acid, santalbic acid (octadec-11-en-9-ynoic acid ortrans-11-octadecen-9-ynoic acid) of the seed oil ofSantalum album L. by a simple treatment of its sodium salt with dimethyl sulfate. Aqueous solutions (0.5–1%) of the complex produce good lather and have efficient cleansing (detergent) action on grease and dirt particles.

A computationally efficient technique for data-clustering

A computationally efficient agglomerative clustering algorithm based on multilevel theory is presented. Here, the data set is divided randomly into a number of partitions. The samples of each such partition are clustered separately using hierarchical agglomerative clustering algorithm to form sub-clusters. These are merged at higher levels to get the final classification. This algorithm leads to the same classification as that of hierarchical agglomerative clustering algorithm when the clusters are well separated. The advantages of this algorithm are short run time and small storage requirement. It is observed that the savings, in storage space and computation time, increase nonlinearly with the sample size.

Learning with symmetric label noise: The importance of being unhinged

Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2008] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing. This ostensibly shows that convex losses are not SLN-robust. In this paper, we propose a convex, classification-calibrated loss and prove that it is SLN-robust. The loss avoids the Long and Servedio [2008] result by virtue of being negatively unbounded. The loss is a modification of the hinge loss, where one does not clamp at zero; hence, we call it the unhinged loss. We show that the optimal unhinged solution is equivalent to that of a strongly regularised SVM, and is the limiting solution for any convex potential; this implies that strong l2 regularisation makes most standard learners SLN-robust. Experiments confirm the unhinged loss’ SLN-robustness.