Abstract: A time-domain numerical model within the
framework of transmission line modeling (TLM) is developed to
simulate electromagnetic pulse propagation inside multiple
microcavities forming photonic crystal (PhC) structures. The model
developed is quite general and is capable of simulating complex
electromagnetic problems accurately. The field quantities can be
mapped onto a passive electrical circuit equivalent what ensures that
TLM is provably stable and conservative at a local level.
Furthermore, the circuit representation allows a high level of
hybridization of TLM with other techniques and lumped circuit
models of components and devices. A photonic crystal structure
formed by rods (or blocks) of high-permittivity dieletric material
embedded in a low-dielectric background medium is simulated as an
example. The model developed gives vital spatio-temporal
information about the signal, and also gives spectral information over
a wide frequency range in a single run. The model has wide
applications in microwave communication systems, optical
waveguides and electromagnetic materials simulations.
Abstract: The effect of a chiral bianisotropic substrate on the
complex resonant frequency of a rectangular microstrip resonator has
been studied on the basis of the integral equation formulation. The
analysis is based on numerical resolution of the integral equation
using Galerkin procedure for moment method in the spectral domain.
This work aim first to study the effect of the chirality of a
bianisotopic substrate upon the resonant frequency and the half
power bandwidth, second the effect of a magnetic anisotropy via an
asymptotic approach for very weak substrate upon the resonant
frequency and the half power bandwidth has been investigated. The
obtained results are compared with previously published work [11-9],
they were in good agreement.
Abstract: The solvated electron is self-trapped (polaron) owing
to strong interaction with the quantum polarization field. If the
electron and quantum field are strongly coupled then the collective
localized state of the field and quasi-particle is formed. In such a
formation the electron motion is rather intricate. On the one hand the
electron oscillated within a rather deep polarization potential well
and undergoes the optical transitions, and on the other, it moves
together with the center of inertia of the system and participates in
the thermal random walk. The problem is to separate these motions
correctly, rigorously taking into account the conservation laws. This
can be conveniently done using Bogolyubov-Tyablikov method of
canonical transformation to the collective coordinates. This
transformation removes the translational degeneracy and allows one
to develop the successive approximation algorithm for the energy and
wave function while simultaneously fulfilling the law of conservation
of total momentum of the system. The resulting equations determine
the electron transitions and depend explicitly on the translational
velocity of the quasi-particle as whole. The frequency of optical
transition is calculated for the solvated electron in ammonia, and an
estimate is made for the thermal-induced spectral bandwidth.
Abstract: In this paper, we propose a direct method based on the
real Schur factorization for solving the projected Sylvester equation
with relatively small size. The algebraic formula of the solution of
the projected continuous-time Sylvester equation is presented. The
computational cost of the direct method is estimated. Numerical
experiments show that this direct method has high accuracy.
Abstract: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.
Abstract: In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based
on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral autocoherence function of the PU signal to the generalized- likelihood ratio. From numerical results, it is confirmed that the proposed scheme provides a better spectrum sensing performance compared with the conventional spectrum sensing scheme based on the energy of the PU signals in high traffic environments.
Abstract: Numerous divergence measures (spectral distance, cepstral
distance, difference of the cepstral coefficients, Kullback-Leibler
divergence, distance given by the General Likelihood Ratio, distance
defined by the Recursive Bayesian Changepoint Detector and the
Mahalanobis measure) are compared in this study. The measures are
used for detection of abrupt spectral changes in synthetic AR signals
via the sliding window algorithm. Two experiments are performed;
the first is focused on detection of single boundary while the second
concentrates on detection of a couple of boundaries. Accuracy of
detection is judged for each method; the measures are compared
according to results of both experiments.
Abstract: Recently, the issue of machine condition monitoring
and fault diagnosis as a part of maintenance system became global
due to the potential advantages to be gained from reduced
maintenance costs, improved productivity and increased machine
availability. The aim of this work is to investigate the effectiveness
of a new fault diagnosis method based on power spectral density
(PSD) of vibration signals in combination with decision trees and
fuzzy inference system (FIS). To this end, a series of studies was
conducted on an external gear hydraulic pump. After a test under
normal condition, a number of different machine defect conditions
were introduced for three working levels of pump speed (1000, 1500,
and 2000 rpm), corresponding to (i) Journal-bearing with inner face
wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii)
Journal-bearing with inner face wear plus Gear with tooth face wear
(B&GW). The features of PSD values of vibration signal were
extracted using descriptive statistical parameters. J48 algorithm is
used as a feature selection procedure to select pertinent features from
data set. The output of J48 algorithm was employed to produce the
crisp if-then rule and membership function sets. The structure of FIS
classifier was then defined based on the crisp sets. In order to
evaluate the proposed PSD-J48-FIS model, the data sets obtained
from vibration signals of the pump were used. Results showed that
the total classification accuracy for 1000, 1500, and 2000 rpm
conditions were 96.42%, 100%, and 96.42% respectively. The results
indicate that the combined PSD-J48-FIS model has the potential for
fault diagnosis of hydraulic pumps.
Abstract: Automatic detection of bleeding is of practical
importance since capsule endoscopy produces an extremely large
number of images. Algorithm development of bleeding detection in
the digestive tract is difficult due to different contrasts among the
images, food dregs, secretion and others. In this study, were assigned
weighting factors derived from the independent features of the
contrast and brightness between bleeding and normality. Spectral
analysis based on weighting factors was fast and accurate. Results
were a sensitivity of 87% and a specificity of 90% when the accuracy
was determined for each pixel out of 42 endoscope images.
Abstract: Most paddy rice fields in East Asia are small parcels,
and the weather conditions during the growing season are usually
cloudy. FORMOSAT-2 multi-spectral images have an 8-meter
resolution and one-day recurrence, ideal for mapping paddy rice fields
in East Asia. To map rice fields, this study first determined the
transplanting and the most active tillering stages of paddy rice and
then used multi-temporal images to distinguish different growing
characteristics between paddy rice and other ground covers. The
unsupervised ISODATA (iterative self-organizing data analysis
techniques) and supervised maximum likelihood were both used to
discriminate paddy rice fields, with training areas automatically
derived from ten-year cultivation parcels in Taiwan. Besides original
bands in multi-spectral images, we also generated normalized
difference vegetation index and experimented with object-based
pre-classification and post-classification. This paper discusses results
of different image classification methods in an attempt to find a
precise and automatic solution to mapping paddy rice in Taiwan.
Abstract: Many studies have been conducted for derivation of
attenuation relationships worldwide, however few relationships have
been developed to use for the seismic region of Iranian plateau and
only few of these studies have been conducted for derivation of
attenuation relationships for parameters such as uniform duration.
Uniform duration is the total time during which the acceleration is
larger than a given threshold value (default is 5% of PGA). In this
study, the database was same as that used previously by Ghodrati
Amiri et al. (2007) with same correction methods for earthquake
records in Iran. However in this study, records from earthquakes with
MS< 4.0 were excluded from this database, each record has
individually filtered afterward, and therefore the dataset has been
expanded. These new set of attenuation relationships for Iran are
derived based on tectonic conditions with soil classification into rock
and soil. Earthquake parameters were chosen to be
hypocentral distance and magnitude in order to make it easier to use
the relationships for seismic hazard analysis. Tehran is the capital
city of Iran wit ha large number of important structures. In this study,
a probabilistic approach has been utilized for seismic hazard
assessment of this city. The resulting uniform duration against return
period diagrams are suggested to be used in any projects in the area.
Abstract: This paper presents a simple and original method for
the generation of short monocycle pulses based on the transient
response of a passive band-pass filter. The recorded sub-nanosecond
pulses show a good symmetry and a small ringing (13 % of the peak
amplitude). Their spectral density covers the range 3.1 GHz to
10.6 GHz. The possibility to adapt the pulse spectral density to the
indoor FCC frequency mask is demonstrated with a prototype
working at a reduced frequency (FCC/1000). A detection technique is
proposed.
Abstract: PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.
Abstract: In this paper we proposed the use of Huffman
coding to reduce the PAR of an OFDM system as a distortionless
scrambling technique, and we utilize the amount saved in the
total bit rate by the Huffman coding to send the encoding table
for accurate decoding at the receiver without reducing the
effective throughput. We found that the use of Huffman coding
reduces the PAR by about 6 dB. Also we have investigated the
effect of PAR reduction due to Huffman coding through testing
the spectral spreading and the inband distortion due to HPA with
different IBO values. We found a complete match of our
expectation from the proposed solution with the obtained
simulation results.
Abstract: This paper addresses the problem of peak-to-average
power ratio (PAPR) in orthogonal frequency division multiplexing
(OFDM) systems. It also introduces a new PAPR reduction technique
based on adaptive square-rooting (SQRT) companding process. The
SQRT process of the proposed technique changes the statistical
characteristics of the OFDM output signals from Rayleigh
distribution to Gaussian-like distribution. This change in statistical
distribution results changes of both the peak and average power
values of OFDM signals, and consequently reduces significantly the
PAPR. For the 64QAM OFDM system using 512 subcarriers, up to 6
dB reduction in PAPR was achieved by square-rooting technique
with fixed degradation in bit error rate (BER) equal to 3 dB.
However, the PAPR is reduced at the expense of only -15 dB out-ofband
spectral shoulder re-growth below the in-band signal level. The
proposed adaptive SQRT technique is superior in terms of BER
performance than the original, non-adaptive, square-rooting
technique when the required reduction in PAPR is no more than 5
dB. Also, it provides fixed amount of PAPR reduction in which it is
not available in the original SQRT technique.
Abstract: Automatic methods of detecting changes through
satellite imaging are the object of growing interest, especially
beca²use of numerous applications linked to analysis of the Earth’s
surface or the environment (monitoring vegetation, updating maps,
risk management, etc...). This work implemented spatial analysis
techniques by using images with different spatial and spectral
resolutions on different dates. The work was based on the principle
of control charts in order to set the upper and lower limits beyond
which a change would be noted. Later, the a contrario approach was
used. This was done by testing different thresholds for which the
difference calculated between two pixels was significant. Finally,
labeled images were considered, giving a particularly low difference
which meant that the number of “false changes” could be estimated
according to a given limit.
Abstract: Semiconductor materials with coatings have a wide range of applications in MEMS and NEMS. This work uses transfermatrix method for calculating the radiative properties. Dopped silicon is used and the coherent formulation is applied. The Drude model for the optical constants of doped silicon is employed. Results showed that for the visible wavelengths, more emittance occurs in greater concentrations and the reflectance decreases as the concentration increases. In these wavelengths, transmittance is negligible. Donars and acceptors act similar in visible wavelengths. The effect of wave interference can be understood by plotting the spectral properties such as reflectance or transmittance of a thin dielectric film versus the film thickness and analyzing the oscillations of properties due to constructive and destructive interferences. But this effect has not been shown at visible wavelengths. At room temperature, the scattering process is dominated by lattice scattering for lightly doped silicon, and the impurity scattering becomes important for heavily doped silicon when the dopant concentration exceeds1018cm-3 .
Abstract: This work presents a fusion of Log Gabor Wavelet
(LGW) and Maximum a Posteriori (MAP) estimator as a speech
enhancement tool for acoustical background noise reduction. The
probability density function (pdf) of the speech spectral amplitude is
approximated by a Generalized Laplacian Distribution (GLD).
Compared to earlier estimators the proposed method estimates the
underlying statistical model more accurately by appropriately
choosing the model parameters of GLD. Experimental results show
that the proposed estimator yields a higher improvement in
Segmental Signal-to-Noise Ratio (S-SNR) and lower Log-Spectral
Distortion (LSD) in two different noisy environments compared to
other estimators.
Abstract: In this paper, an analytical modeling is presentated to
describe the channel noise in GME SGT/CGT MOSFET, based on
explicit functions of MOSFETs geometry and biasing conditions for
all channel length down to deep submicron and is verified with the
experimental data. Results shows the impact of various parameters
such as gate bias, drain bias, channel length ,device diameter and gate
material work function difference on drain current noise spectral
density of the device reflecting its applicability for circuit design
applications.
Abstract: Fourier transform infrared (FT-IR) spectroscopic imaging
is an emerging technique that provides both chemically and
spatially resolved information. The rich chemical content of data
may be utilized for computer-aided determinations of structure and
pathologic state (cancer diagnosis) in histological tissue sections for
prostate cancer. FT-IR spectroscopic imaging of prostate tissue has
shown that tissue type (histological) classification can be performed to
a high degree of accuracy [1] and cancer diagnosis can be performed
with an accuracy of about 80% [2] on a microscopic (≈ 6μm)
length scale. In performing these analyses, it has been observed
that there is large variability (more than 60%) between spectra from
different points on tissue that is expected to consist of the same
essential chemical constituents. Spectra at the edges of tissues are
characteristically and consistently different from chemically similar
tissue in the middle of the same sample. Here, we explain these
differences using a rigorous electromagnetic model for light-sample
interaction. Spectra from FT-IR spectroscopic imaging of chemically
heterogeneous samples are different from bulk spectra of individual
chemical constituents of the sample. This is because spectra not
only depend on chemistry, but also on the shape of the sample.
Using coupled wave analysis, we characterize and quantify the nature
of spectral distortions at the edges of tissues. Furthermore, we
present a method of performing histological classification of tissue
samples. Since the mid-infrared spectrum is typically assumed to
be a quantitative measure of chemical composition, classification
results can vary widely due to spectral distortions. However, we
demonstrate that the selection of localized metrics based on chemical
information can make our data robust to the spectral distortions
caused by scattering at the tissue boundary.