Abstract: Evaluation of contact pressure, surface and
subsurface contact stresses are essential to know the functional
response of surface coatings and the contact behavior mainly depends
on surface roughness, material property, thickness of layer and the
manner of loading. Contact parameter evaluation of real rough
surface contacts mostly relies on statistical single asperity contact
approaches. In this work, a three dimensional layered solid rough
surface in contact with a rigid flat is modeled and analyzed using
finite element method. The rough surface of layered solid is
generated by FFT approach. The generated rough surface is exported
to a finite element method based ANSYS package through which the
bottom up solid modeling is employed to create a deformable solid
model with a layered solid rough surface on top. The discretization
and contact analysis are carried by using the same ANSYS package.
The elastic, elastoplastic and plastic deformations are continuous in
the present finite element method unlike many other contact models.
The Young-s modulus to yield strength ratio of layer is varied in the
present work to observe the contact parameters effect while keeping
the surface roughness and substrate material properties as constant.
The contacting asperities attain elastic, elastoplastic and plastic states
with their continuity and asperity interaction phenomena is inherently
included. The resultant contact parameters show that neighboring
asperity interaction and the Young-s modulus to yield strength ratio
of layer influence the bulk deformation consequently affect the
interface strength.
Abstract: In this paper, we propose a texture feature-based
language identification using wavelet-domain BDIP (block difference
of inverse probabilities) and BVLC (block variance of local
correlation coefficients) features and FFT (fast Fourier transform)
feature. In the proposed method, wavelet subbands are first obtained
by wavelet transform from a test image and denoised by Donoho-s
soft-thresholding. BDIP and BVLC operators are next applied to the
wavelet subbands. FFT blocks are also obtained by 2D (twodimensional)
FFT from the blocks into which the test image is
partitioned. Some significant FFT coefficients in each block are
selected and magnitude operator is applied to them. Moments for each
subband of BDIP and BVLC and for each magnitude of significant
FFT coefficients are then computed and fused into a feature vector. In
classification, a stabilized Bayesian classifier, which adopts variance
thresholding, searches the training feature vector most similar to the
test feature vector. Experimental results show that the proposed
method with the three operations yields excellent language
identification even with rather low feature dimension.
Abstract: This paper proposes a novel frequency offset (FO) estimator for orthogonal frequency division multiplexing. Simplicity is most significant feature of this algorithm and can be repeated to achieve acceptable accuracy. Also fractional and integer part of FO is estimated jointly with use of the same algorithm. To do so, instead of using conventional algorithms that usually use correlation function, we use DFT of received signal. Therefore, complexity will be reduced and we can do synchronization procedure by the same hardware that is used to demodulate OFDM symbol. Finally, computer simulation shows that the accuracy of this method is better than other conventional methods.
Abstract: The morphological parameter of a thin film surface
can be characterized by power spectral density (PSD) functions
which provides a better description to the topography than the RMS
roughness and imparts several useful information of the surface
including fractal and superstructure contributions. Through the
present study Nanoparticle copper/carbon composite films were
prepared by co-deposition of RF-Sputtering and RF-PECVD method
from acetylene gas and copper target. Surface morphology of thin
films is characterized by using atomic force microscopy (AFM). The
Carbon content of our films was obtained by Rutherford Back
Scattering (RBS) and it varied from .4% to 78%. The power values of
power spectral density (PSD) for the AFM data were determined by
the fast Fourier transform (FFT) algorithms. We investigate the effect
of carbon on the roughness of thin films surface. Using such
information, roughness contributions of the surface have been
successfully extracted.