Abstract: SDMA (Space-Division Multiple Access) is a MIMO
(Multiple-Input and Multiple-Output) based wireless communication
network architecture which has the potential to significantly increase
the spectral efficiency and the system performance. The maximum
likelihood (ML) detection provides the optimal performance, but its
complexity increases exponentially with the constellation size of
modulation and number of users. The QR decomposition (QRD)
MUD can be a substitute to ML detection due its low complexity and
near optimal performance. The minimum mean-squared-error
(MMSE) multiuser detection (MUD) minimises the mean square
error (MSE), which may not give guarantee that the BER of the
system is also minimum. But the minimum bit error rate (MBER)
MUD performs better than the classic MMSE MUD in term of
minimum probability of error by directly minimising the BER cost
function. Also the MBER MUD is able to support more users than
the number of receiving antennas, whereas the rest of MUDs fail in
this scenario. In this paper the performance of various MUD
techniques is verified for the correlated MIMO channel models based
on IEEE 802.16n standard.
Abstract: In this paper, an automated algorithm to estimate and remove the continuous baseline from measured spectra containing both continuous and discontinuous bands is proposed. The algorithm uses previous information contained in a Continuous Database Spectra (CDBS) to obtain a linear basis, with minimum number of sampled vectors, capable of representing a continuous baseline. The proposed algorithm was tested by using a CDBS of flame spectra where Principal Components Analysis and Non-negative Matrix Factorization were used to obtain linear bases. Thus, the radical emissions of natural gas, oil and bio-oil flames spectra at different combustion conditions were obtained. In order to validate the performance in the baseline estimation process, the Goodness-of-fit Coefficient and the Root Mean-squared Error quality metrics were evaluated between the estimated and the real spectra in absence of discontinuous emission. The achieved results make the proposed method a key element in the development of automatic monitoring processes strategies involving discontinuous spectral bands.
Abstract: The numerous qualities of squirrel cage induction
machines enhance their use in industry. However, various faults can
occur, such as stator short-circuits and rotor failures.
In this paper, we use a technique based on the spectral analysis of
stator current in order to detect the fault in the machine: broken rotor
bars. Thus, the number effect of the breaks has been highlighted. The
effect is highlighted by considering the machine controlled by the
Direct Torque Control (DTC). The key to fault detection is the
development of a simplified dynamic model of a squirrel cage
induction motor taking account the broken bars fault and the stator
current spectrum analysis (FFT).
Abstract: Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.
Abstract: This paper presents the use of Legendre pseudospectral
method for the optimization of finite-thrust orbital transfer for
spacecrafts. In order to get an accurate solution, the System-s
dynamics equations were normalized through a dimensionless method.
The Legendre pseudospectral method is based on interpolating
functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This
is used to transform the optimal control problem into a constrained
parameter optimization problem. The developed novel optimization
algorithm can be used to solve similar optimization problems of
spacecraft finite-thrust orbital transfer. The results of a numerical
simulation verified the validity of the proposed optimization method.
The simulation results reveal that pseudospectral optimization method
is a promising method for real-time trajectory optimization and
provides good accuracy and fast convergence.
Abstract: On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.
Abstract: In this paper we evaluated the efficacy of
photodynamic treatment of infected wounds on pig animal model by
diffuse reflectance spectrometry. The study was conducted on fifteen
wounds contaminated with Staphylococcus aureus bacteria that were
incubated for 30 min with methylene blue solution (c = 3.3 x 10-3 M)
and exposed to laser radiations (λ = 670 nm, P = 15 mW) for 15 min.
The efficiency of photodynamic inactivation of bacteria was
evaluated by microbiological exams and diffuse reflectance
spectrometry. The results of the microbiological exams showed that
the bacterial concentration has decreased from 6.93±0.138
logCFU/ml to 3.12±0.108 logCFU/ml. The spectral examination
showed that the diffuse reflectance of wounds contaminated with
Staphylococcus aureus has decreased from 5.06±0.036 % to
3.36±0.025 %. In conclusion, photodynamic therapy is an effective
method for the treatment of infected wounds and there is a correlation
between the CFU count and diffuse reflectance.
Abstract: This paper describes the development of a WLAN
propagation model, using Spectral Analyzer measurements. The
signal is generated by two Access Points (APs) on the base floor at
the administrative Communication School of ESPOL building. In
general, users do not have a Q&S reference about a wireless network;
however, this depends on the level signal as a function of frequency,
distance and other path conditions between receiver and transmitter.
Then, power density of the signal decrease as it propagates through
space and data transfer rate is affected. This document evaluates and
implements empirical mathematical formulation for the
characterization of WLAN radio wave propagation on two aisles of
the building base floor.
Abstract: In this paper, the problem of estimating the optimal
radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple-
output (MIMO) system operating in a Rayleigh fading environment
is examined. The optimisation between the radio capacity
and the theoretically achievable average channel capacity (in the
sense of information theory) per user of a MIMO single-cell SS system
operating in a Rayleigh fading environment is presented. Then,
the spectral efficiency is estimated in terms of the achievable average
channel capacity per user, during the operation over a broadcast
time-varying link, and leads to a simple novel-closed form expression
for the optimal radio capacity value based on the maximization
of the achieved spectral efficiency. Numerical results are presented to
illustrate the proposed analysis.
Abstract: Breast carcinoma is the most common form of cancer
in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is
a common method for staging breast carcinoma. The interpretation
of m-FISH images is complicated due to two effects: (i) Spectral
overlap in the emission spectra of fluorochrome marked DNA probes
and (ii) tissue autofluorescence. In this paper hyper-spectral images of
m-FISH samples are used and spectral unmixing is applied to produce
false colour images with higher contrast and better information
content than standard RGB images. The spectral unmixing is realised
by combinations of: Orthogonal Projection Analysis (OPA), Alterating
Least Squares (ALS), Simple-to-use Interactive Self-Modeling
Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied
on the data to reduce tissue autofluorescence and resolve the spectral
overlap in the emission spectra. The results show that spectral unmixing
methods reduce the intensity caused by tissue autofluorescence by
up to 78% and enhance image contrast by algorithmically reducing
the overlap of the emission spectra.
Abstract: In this paper we present an enhanced noise reduction method for robust speech recognition using Adaptive Gain Equalizer with Non linear Spectral Subtraction. In Adaptive Gain Equalizer method (AGE), the input signal is divided into a number of subbands that are individually weighed in time domain, in accordance to the short time Signal-to-Noise Ratio (SNR) in each subband estimation at every time instant. Instead of focusing on suppression the noise on speech enhancement is focused. When analysis was done under various noise conditions for speech recognition, it was found that Adaptive Gain Equalizer method algorithm has an obvious failing point for a SNR of -5 dB, with inadequate levels of noise suppression for SNR less than this point. This work proposes the implementation of AGE when coupled with Non linear Spectral Subtraction (AGE-NSS) for robust speech recognition. The experimental result shows that out AGE-NSS performs the AGE when SNR drops below -5db level.
Abstract: The liquid cargo contained in a partly-filled road tank
vehicle is prone to dynamic slosh movement when subjected to
external disturbances. The slosh behavior has been identified as a
significant factor impairing the safety of liquid cargo transportation.
The laboratory experiments have been conducted for analyzing fluid
slosh in partly filled tanks. The experiment results measured under
forced harmonic excitations reveal the three-dimensional nature of
the fluid motion and coupling between the lateral and longitudinal
fluid slosh at resonance. Several spectral components are observed
for the transient slosh forces, which can be associated with the
excitation, resonance, and beat frequencies. The peak slosh forces
and moments in the vicinity of resonance are significantly larger than
those of the equivalent rigid mass. Due to the nature of coupling
between sloshing fluid and vehicle body, the issue of the dynamic
fluid-structure interaction is essential in the analysis of tank-vehicle
dynamics. A dynamic pitch plane model of a Tridem truck
incorporated the fluid slosh dynamics is developed to analyze the
fluid-vehicle interaction under the straight-line braking maneuvers.
The results show that the vehicle responses are highly associated
with the characteristics of fluid slosh force and moment.
Abstract: Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).
Abstract: This research proposes an algorithm for the simulation
of time-periodic unsteady problems via the solution unsteady Euler
and Navier-Stokes equations. This algorithm which is called Time
Spectral method uses a Fourier representation in time and hence
solve for the periodic state directly without resolving transients
(which consume most of the resources in a time-accurate scheme).
Mathematical tools used here are discrete Fourier transformations. It
has shown tremendous potential for reducing the computational cost
compared to conventional time-accurate methods, by enforcing
periodicity and using Fourier representation in time, leading to
spectral accuracy. The accuracy and efficiency of this technique is
verified by Euler and Navier-Stokes calculations for pitching airfoils.
Because of flow turbulence nature, Baldwin-Lomax turbulence
model has been used at viscous flow analysis. The results presented
by the Time Spectral method are compared with experimental data. It
has shown tremendous potential for reducing the computational cost
compared to the conventional time-accurate methods, by enforcing
periodicity and using Fourier representation in time, leading to
spectral accuracy, because results verify the small number of time
intervals per pitching cycle required to capture the flow physics.
Abstract: The solitary wave solution of the quadratic nonlinear Schrdinger equation is determined by the iterative method called Petviashvili method. This solution is also used for the initial condition for the time evolution to study the stability analysis. The spectral method is applied for the time evolution.
Abstract: Acoustic Imaging based sound localization using microphone
array is a challenging task in digital-signal processing.
Discrete Fourier transform (DFT) based near-field acoustical holography
(NAH) is an important acoustical technique for sound source
localization and provide an efficient solution to the ill-posed problem.
However, in practice, due to the usage of small curtailed aperture
and its consequence of significant spectral leakage, the DFT could
not reconstruct the active-region-of-sound (AROS) effectively, especially
near the edges of aperture. In this paper, we emphasize the
fundamental problems of DFT-based NAH, provide a solution to
spectral leakage effect by the extrapolation based on linear predictive
coding and 2D Tukey windowing. This approach has been tested to
localize the single and multi-point sound sources. We observe that
incorporating extrapolation technique increases the spatial resolution,
localization accuracy and reduces spectral leakage when small curtail
aperture with a lower number of sensors accounts.
Abstract: This paper presents the cepstral and trispectral
analysis of a speech signal produced by normal men, men with
defective audition (deaf, deep deaf) and others affected by
tracheotomy, the trispectral analysis based on parametric methods
(Autoregressive AR) using the fourth order cumulant. These
analyses are used to detect and compare the pitches and the formants
of corresponding voiced sounds (vowel \a\, \i\ and \u\). The first
results appear promising, since- it seems after several experimentsthere
is no deformation of the spectrum as one could have supposed
it at the beginning, however these pathologies influenced the two
characteristics:
The defective audition influences to the formants contrary to the
tracheotomy, which influences the fundamental frequency (pitch).
Abstract: This paper presents the H-ARQ techniques comparison for OFDM systems with a new family of non-binary LDPC codes which has been developed within the EU FP7 DAVINCI project. The punctured NB-LDPC codes have been used in a simulated model of the transmission system. The link level performance has been evaluated in terms of spectral efficiency, codeword error rate and average number of retransmissions. The NB-LDPC codes can be easily and effective implemented with different methods of the retransmission needed if correct decoding of a codeword failed. Here the Optimal Symbol Selection method is proposed as a Chase Combining technique.
Abstract: Semiconductor detector arrays are widely used in
high-temperature plasma diagnostics. They have a fast response,
which allows observation of many processes and instabilities in
tokamaks. In this paper, there are reviewed several diagnostics based
on semiconductor arrays as cameras, AXUV photodiodes (referred
often as fast “bolometers") and detectors of both soft X-rays and
visible light installed on the COMPASS tokamak recently. Fresh
results from both spring and summer campaigns in 2012 are
introduced. Examples of the utilization of the detectors are shown on
the plasma shape determination, fast calculation of the radiation
center, two-dimensional plasma radiation tomography in different
spectral ranges, observation of impurity inflow, and also on
investigation of MHD activity in the COMPASS tokamak discharges.
Abstract: This paper presents a formant-tracking linear prediction
(FTLP) model for speech processing in noise. The main focus of this
work is the detection of formant trajectory based on Hidden Markov
Models (HMM), for improved formant estimation in noise. The
approach proposed in this paper provides a systematic framework for
modelling and utilization of a time- sequence of peaks which satisfies
continuity constraints on parameter; the within peaks are modelled
by the LP parameters. The formant tracking LP model estimation
is composed of three stages: (1) a pre-cleaning multi-band spectral
subtraction stage to reduce the effect of residue noise on formants
(2) estimation stage where an initial estimate of the LP model of
speech for each frame is obtained (3) a formant classification using
probability models of formants and Viterbi-decoders. The evaluation
results for the estimation of the formant tracking LP model tested
in Gaussian white noise background, demonstrate that the proposed
combination of the initial noise reduction stage with formant tracking
and LPC variable order analysis, results in a significant reduction in
errors and distortions. The performance was evaluated with noisy
natual vowels extracted from international french and English vocabulary
speech signals at SNR value of 10dB. In each case, the
estimated formants are compared to reference formants.