Vibrational spectra of fluorene, 1-methylfluorene and 1,8-dimethylfluorene

In this paper, we report the gas phase infrared spectra of fluorene and its methylated derivatives using a heated multipass cell and argon as a carrier gas. The observed spectra in the 4000-400 cm(-1) range have been fitted using the modified scaled quantum mechanical force field (SQMFF) calculation with the 6-311G** basis. The advantage of using the modified SQMFF method is that it scales the force constants to find the best fit to the observed spectral lines by minimizing the fitting error. In this way we are able to assign all the observed fundamental bands in the spectra. With consecutive methyl substitutions two sets of bands are found to shift in a systematic way. The set of four aromatic C-H stretching vibrations around 3000 cm(-1) shifts toward lower frequencies while the single most intense aromatic C-H out-of-plane bending mode around 750 cm(-1) shifts toward higher frequencies. The reason for shifting of aromatic C-H stretching frequency toward lower wave numbers with gradual methyl substitution has been attributed to the lengthening of the C-H bonds due to the +I effect of the methyl groups to the ring current as revealed from the calculations. While the unexpected shifting of the aromatic C-H out-of-plane bend toward higher wave numbers with increasing methyl substitution is ascribed to the lowering of the number of adjacent aromatic C-H bonds on the plane of the benzene ring with gradual methyl substitutions. (C) 2013 Elsevier B.V. All rights reserved.

MULTI-PITCH TRACKING USING GAUSSIAN MIXTURE MODEL WITH TIME VARYING PARAMETERS AND GRATING COMPRESSION TRANSFORM

Grating Compression Transform (GCT) is a two-dimensional analysis of speech signal which has been shown to be effective in multi-pitch tracking in speech mixtures. Multi-pitch tracking methods using GCT apply Kalman filter framework to obtain pitch tracks which requires training of the filter parameters using true pitch tracks. We propose an unsupervised method for obtaining multiple pitch tracks. In the proposed method, multiple pitch tracks are modeled using time-varying means of a Gaussian mixture model (GMM), referred to as TVGMM. The TVGMM parameters are estimated using multiple pitch values at each frame in a given utterance obtained from different patches of the spectrogram using GCT. We evaluate the performance of the proposed method on all voiced speech mixtures as well as random speech mixtures having well separated and close pitch tracks. TVGMM achieves multi-pitch tracking with 51% and 53% multi-pitch estimates having error <= 20% for random mixtures and all-voiced mixtures respectively. TVGMM also results in lower root mean squared error in pitch track estimation compared to that by Kalman filtering.

Improved design methodology for the development of electrically actuated MEMS structures

A comprehensive design flow is proposed for the design of Micro Electro Mechanical Systems that are fabricated using SOIMUMPs process. Many of the designers typically do not model the temperature dependency of electrical conductivity, thermal conductivity and convection coefficient, as it is very cumbersome to create/incorporate the same in the existing FEM simulators. Capturing these dependencies is very critical particularly for structures that are electrically actuated. Lookup tables that capture the temperature dependency of electrical conductivity, thermal conductivity and convection coefficient are created. These look up tables are taken as inputs for a commercially available FEM simulator to model the semiconductor behavior. It is demonstrated that when temperature dependency for all the above mentioned parameters is not captured, then the error in estimation of the maximum temperature (for a given structure) could be as high as 30%. Error in the estimated resistance value under the same conditions is as high as 40%. When temperature dependency of the above mentioned parameters is considered then error w.r.t the measured values is less than 5%. It is evident that error in temperature estimates leads to erroneous results from mechanical simulations as well.

On Whitespace Identification Using Randomly Deployed Sensors

This work considers the identification of the available whitespace, i.e., the regions that do not contain any existing transmitter within a given geographical area. To this end, n sensors are deployed at random locations within the area. These sensors detect for the presence of a transmitter within their radio range r(s) using a binary sensing model, and their individual decisions are combined to estimate the available whitespace. The limiting behavior of the recovered whitespace as a function of n and r(s) is analyzed. It is shown that both the fraction of the available whitespace that the nodes fail to recover as well as their radio range optimally scale as log(n)/n as n gets large. The problem of minimizing the sum absolute error in transmitter localization is also analyzed, and the corresponding optimal scaling of the radio range and the necessary minimum transmitter separation is determined.

Optimal Linear Glauber Model

Contrary to the actual nonlinear Glauber model, the linear Glauber model (LGM) is exactly solvable, although the detailed balance condition is not generally satisfied. This motivates us to address the issue of writing the transition rate () in a best possible linear form such that the mean squared error in satisfying the detailed balance condition is least. The advantage of this work is that, by studying the LGM analytically, we will be able to anticipate how the kinetic properties of an arbitrary Ising system depend on the temperature and the coupling constants. The analytical expressions for the optimal values of the parameters involved in the linear are obtained using a simple Moore-Penrose pseudoinverse matrix. This approach is quite general, in principle applicable to any system and can reproduce the exact results for one dimensional Ising system. In the continuum limit, we get a linear time-dependent Ginzburg-Landau equation from the Glauber's microscopic model of non-conservative dynamics. We analyze the critical and dynamic properties of the model, and show that most of the important results obtained in different studies can be reproduced by our new mathematical approach. We will also show in this paper that the effect of magnetic field can easily be studied within our approach; in particular, we show that the inverse of relaxation time changes quadratically with (weak) magnetic field and that the fluctuation-dissipation theorem is valid for our model.

Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.