Abstract: In more complex systems, such as automotive
gearbox, a rigorous treatment of the data is necessary because there
are several moving parts (gears, bearings, shafts, etc.), and in this
way, there are several possible sources of errors and also noise. The
basic objective of this work is the detection of damage in automotive
gearbox. The detection methods used are the wavelet method, the
bispectrum; advanced filtering techniques (selective filtering) of
vibrational signals and mathematical morphology. Gearbox vibration
tests were performed (gearboxes in good condition and with defects)
of a production line of a large vehicle assembler. The vibration
signals are obtained using five accelerometers in different positions
of the sample. The results obtained using the kurtosis, bispectrum,
wavelet and mathematical morphology showed that it is possible to
identify the existence of defects in automotive gearboxes.
Abstract: Fiber Bragg optic sensor is embedded in composite
material to detect and monitor the damage that occurs in composite
structures. In this paper, we deal with the mode-Ι delamination to
determine the material strength to crack propagation, using the
coupling mode theory and T-matrix method to simulate the FBGs
spectrum for both uniform and non-uniform strain distribution. The
double cantilever beam test is modeled in FEM to determine the
longitudinal strain. Two models are implemented, the first is the
global half model, and the second is the sub-model to represent the
FBGs with higher refined mesh. This method can simulate damage in
composite structures and converting strain to a wavelength shifting in
the FBG spectrum.
Abstract: The emerging Cognitive Radio is combo of both the
technologies i.e. Radio dynamics and software technology. It involve
wireless system with efficient coding, designing, and making them
artificial intelligent to take the decision according to the surrounding
environment and adopt themselves accordingly, so as to deliver the
best QoS. This is the breakthrough from fixed hardware and fixed
utilization of the spectrum. This software-defined approach of
research is centralized at user-definition and application driven
model, various software method are used for the optimization of the
wireless communication. This paper focused on the Spectrum
allocation technique using genetic algorithm GA to evolve radio,
represented by chromosomes. The chromosomes gene represents the
adjustable parameters in given radio and by using GA, evolving over
the generations, the optimized set of parameters are evolved, as per
the requirement of user and availability of the spectrum, in our
prototype the gene consist of 6 different parameters, and the best set
of parameters are evolved according to the application need and
availability of the spectrum holes and thus maintaining best QoS for
user, simultaneously maintaining licensed user rights. The analyzing
tool Matlab is used for the performance of the prototype.
Abstract: Spectrum sensing is the main feature of cognitive
radio technology. Spectrum sensing gives an idea of detecting the
presence of the primary users in a licensed spectrum. In this paper we
compare the theoretical results of detection probability of different
fading environments like Rayleigh, Rician, Nakagami-m fading
channels with the simulation results using energy detection based
spectrum sensing. The numerical results are plotted as Pf Vs Pd for
different SNR values, fading parameters. It is observed that
Nakagami fading channel performance is better than other fading
channels by using energy detection in spectrum sensing. A MATLAB
simulation test bench has been implemented to know the performance
of energy detection in different fading channel environment.
Abstract: Cognitive Radio is a turning out technology that
empowers viable usage of the spectrum. Energy Detector-based
Sensing is the most broadly utilized spectrum sensing strategy.
Besides, it's a lot of generic as receivers doesn't would like any
information on the primary user's signals, channel data, of even the
sort of modulation. This paper puts forth the execution of energy
detection sensing for AM (Amplitude Modulated) signal at 710 KHz,
FM (Frequency Modulated) signal at 103.45 MHz (local station
frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz.
The OFDM/OFDMA based WiMAX physical layer with
convolutional channel coding is actualized utilizing USRP N210
(Universal Software Radio Peripheral) and GNU Radio based
Software Defined Radio (SDR). Test outcomes demonstrated the
BER (Bit Error Rate) augmentation with channel noise and BER
execution is dissected for different Eb/N0 (the energy per bit to noise
power spectral density ratio) values.
Abstract: Natural dye extracted from Caesalpinia sappan Linn. was applied to a cotton fabric and silk yarn by dyeing process. The dyestuff component of Caesalpinia sappan Linn. was extracted using water and ethanol. Analytical studies such as UV–VIS spectrophotometry and gravimetric analysis were performed on the extracts. Brazilein, the major dyestuff component of Caesalpinia sappan Linn. was confirmed in both aqueous and ethanolic extracts by UV–VIS spectrum. The color of each dyed material was investigated in terms of the CIELAB (L*, a* and b*) and K/S values. Cotton fabric dyed without mordant had a shade of reddish-brown, while those post-mordanted with aluminum potassium sulfate, ferrous sulfate and copper sulfate produced a variety of wine red to dark purple color shades. Cotton fabric and silk yarn dyeing was studied using aluminum potassium sulfate as a mordant. The observed color strength was enhanced with increase in mordant concentration.
Abstract: One of the most important issues about the structural damages caused by earthquake is the evaluating of the spectral response of the site on which the construction is built. This fact has demonstrated during many earlier earthquakes and many researchers’ reports have concerned with it. According to these reports, features of the site materials and geometry of the ground surface are considered the main factors. This study concentrates on the specific form of topographies like hills. Assessing of spectral responses of different points on the hills and beside demonstrates considerable differences between 1D and 2D methods of geotechnical analyses. A general trend of amplifications on the top of the hills and de-amplifications near the toe of the hills has been appeared within the acceleration, velocity and displacement response spectrums of horizontal motion. Evaluating of spectral responses of different sizes of the hills revealed that as much as the hill-size enlarges differences between spectral responses of 1D and 2D analyses transfers to longer range of periods and becomes wider.
Abstract: Thewake flow behind two yawed side-by-sidecircular
cylinders is investigated using athree-dimensional vorticity probe.
Four yaw angles (α), namely, 0°, 15°, 30° and 45° and twocylinder
spacing ratios T*
of 1.7 and 3.0 were tested. For T*
= 3.0, there exist
two vortex streets and the cylinders behave as independent and
isolated ones. The maximum contour value of the coherent streamwise
vorticity ~* ωx
is only about 10% of that of the spanwise vorticity ~* ωz
.
With the increase of α,
~* ωx
increases whereas ~* ωz
decreases. At α =
45°, ~* ωx
is about 67% of ~* ωz
.For T* = 1.7, only a single peak is
detected in the energy spectrum. The spanwise vorticity contours have
an organized pattern only at α = 0°. The maximum coherent vorticity
contours of ~* ω x
and ~* ωz
for T*
= 1.7 are about 30% and 7% of those
for T*
= 3.0.The independence principle (IP)in terms of Strouhal
numbers is applicable in both wakes when α< 40°.
Abstract: Absorption spectra of infra-red (IR) radiation of the
disperse water medium absorbing the most important greenhouse
gases: CO2 , N2O , CH4 , C2H2 , C2H6 have been calculated by
the molecular dynamics method. Loss of the absorbing ability at the
formation of clusters due to a reduction of the number of centers
interacting with IR radiation, results in an anti-greenhouse effect.
Absorption of O3 molecules by the (H2O)50 cluster is investigated
at its interaction with Cl- ions. The splitting of ozone molecule on
atoms near to cluster surface was observed. Interaction of water
cluster with Cl- ions causes the increase of integrated intensity of
emission spectra of IR radiation, and also essential reduction of the
similar characteristic of Raman spectrum. Relative integrated
intensity of absorption of IR radiation for small water clusters was
designed. Dependences of the quantity of weight on altitude for
vapor of monomers, clusters, droplets, crystals and mass of all
moisture were determined. The anti-greenhouse effect of clusters was
defined as the difference of increases of average global temperature
of the Earth, caused by absorption of IR radiation by free water
molecules forming clusters, and absorption of clusters themselves.
The greenhouse effect caused by clusters makes 0.53 K, and the antigreenhouse
one is equal to 1.14 K. The increase of concentration of
CO2 in the atmosphere does not always correlate with the
amplification of greenhouse effect.
Abstract: Using ab initio theoretical calculations, we present
analysis of fragmentation process. The analysis is performed in two
steps. The first step is calculation of fragmentation energies by ab
initio calculations. The second step is application of the energies to
kinetic description of process. The energies of fragments are
presented in this paper. The kinetics of fragmentation process can be
described by numerical models. The method for kinetic analysis is
described in this paper. The result - composition of fragmentation
products - will be calculated in future. The results from model can be
compared to the concentrations of fragments from mass spectrum.
Abstract: In the context of spectrum surveillance, a method to
recover the code of spread spectrum signal is presented, whereas the
receiver has no knowledge of the transmitter-s spreading sequence.
The approach is based on a genetic algorithm (GA), which is forced to
model the received signal. Genetic algorithms (GAs) are well known
for their robustness in solving complex optimization problems.
Experimental results show that the method provides a good
estimation, even when the signal power is below the noise power.
Abstract: In this work we present an efficient approach for face
recognition in the infrared spectrum. In the proposed approach
physiological features are extracted from thermal images in order to
build a unique thermal faceprint. Then, a distance transform is used
to get an invariant representation for face recognition. The obtained
physiological features are related to the distribution of blood vessels
under the face skin. This blood network is unique to each individual
and can be used in infrared face recognition. The obtained results are
promising and show the effectiveness of the proposed scheme.
Abstract: A plausible architecture of an ancient genetic code is derived from an extended base triplet vector space over the Galois field of the extended base alphabet {D, G, A, U, C}, where the letter D represent one or more hypothetical bases with unspecific pairing. We hypothesized that the high degeneration of a primeval genetic code with five bases and the gradual origin and improvements of a primitive DNA repair system could make possible the transition from the ancient to the modern genetic code. Our results suggest that the Watson-Crick base pairing and the non-specific base pairing of the hypothetical ancestral base D used to define the sum and product operations are enough features to determine the coding constraints of the primeval and the modern genetic code, as well as the transition from the former to the later. Geometrical and algebraic properties of this vector space reveal that the present codon assignment of the standard genetic code could be induced from a primeval codon assignment. Besides, the Fourier spectrum of the extended DNA genome sequences derived from the multiple sequence alignment suggests that the called period-3 property of the present coding DNA sequences could also exist in the ancient coding DNA sequences.
Abstract: A new fast correlation algorithm for calibrating the
wavelength of Optical Spectrum Analyzers (OSAs) was introduced
in [1]. The minima of acetylene gas spectra were measured and
correlated with saved theoretical data [2]. So it is possible to find the
correct wavelength calibration data using a noisy reference spectrum.
First tests showed good algorithmic performance for gas line spectra
with high noise. In this article extensive performance tests were made
to validate the noise resistance of this algorithm. The filter and
correlation parameters of the algorithm were optimized for improved
noise performance. With these parameters the performance of this
wavelength calibration was simulated to predict the resulting
wavelength error in real OSA systems. Long term simulations were
made to evaluate the performance of the algorithm over the lifetime
of a real OSA.
Abstract: This paper proposes method of diagnosing ball screw
preload loss through the Hilbert-Huang Transform （HHT） and
Multiscale entropy （MSE） process. The proposed method can
diagnose ball screw preload loss through vibration signals when the
machine tool is in operation. Maximum dynamic preload of 2 %, 4 %,
and 6 % ball screws were predesigned, manufactured, and tested
experimentally. Signal patterns are discussed and revealed using
Empirical Mode Decomposition（EMD）with the Hilbert Spectrum.
Different preload features are extracted and discriminated using HHT.
The irregularity development of a ball screw with preload loss is
determined and abstracted using MSE based on complexity
perception. Experiment results show that the proposed method can
predict the status of ball screw preload loss. Smart sensing for the
health of the ball screw is also possible based on a comparative
evaluation of MSE by the signal processing and pattern matching of
EMD/HHT. This diagnosis method realizes the purposes of prognostic
effectiveness on knowing the preload loss and utilizing convenience.
Abstract: Frequency domain independent component analysis has
a scaling indeterminacy and a permutation problem. The scaling
indeterminacy can be solved by use of a decomposed spectrum. For
the permutation problem, we have proposed the rules in terms of gain
ratio and phase difference derived from the decomposed spectra and
the source-s coarse directions.
The present paper experimentally clarifies that the gain ratio and
the phase difference work effectively in a real environment but their
performance depends on frequency bands, a microphone-space and
a source-microphone distance. From these facts it is seen that it is
difficult to attain a perfect solution for the permutation problem in a
real environment only by either the gain ratio or the phase difference.
For the perfect solution, this paper gives a solution to the problems
in a real environment. The proposed method is simple, the amount of
calculation is small. And the method has high correction performance
without depending on the frequency bands and distances from source
signals to microphones. Furthermore, it can be applied under the real
environment. From several experiments in a real room, it clarifies
that the proposed method has been verified.
Abstract: Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.
Abstract: The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.
Abstract: In the context of spectrum surveillance, a new method
to recover the code of spread spectrum signal is presented, while the
receiver has no knowledge of the transmitter-s spreading sequence. In
our previous paper, we used Genetic algorithm (GA), to recover
spreading code. Although genetic algorithms (GAs) are well known
for their robustness in solving complex optimization problems, but
nonetheless, by increasing the length of the code, we will often lead
to an unacceptable slow convergence speed. To solve this problem we
introduce Particle Swarm Optimization (PSO) into code estimation in
spread spectrum communication system. In searching process for
code estimation, the PSO algorithm has the merits of rapid
convergence to the global optimum, without being trapped in local
suboptimum, and good robustness to noise. In this paper we describe
how to implement PSO as a component of a searching algorithm in
code estimation. Swarm intelligence boasts a number of advantages
due to the use of mobile agents. Some of them are: Scalability, Fault
tolerance, Adaptation, Speed, Modularity, Autonomy, and
Parallelism. These properties make swarm intelligence very attractive
for spread spectrum code estimation. They also make swarm
intelligence suitable for a variety of other kinds of channels. Our
results compare between swarm-based algorithms and Genetic
algorithms, and also show PSO algorithm performance in code
estimation process.
Abstract: In this paper, a technique is proposed to implement
an artificial voltage-controlled capacitance or inductance which can
replace the well-known varactor diode in many applications. The
technique is based on injecting the current of a voltage-controlled
current source onto a fixed capacitor or inductor. Then, by controlling
the transconductance of the current source by an external bias voltage,
a voltage-controlled capacitive or inductive reactance is obtained.
The proposed voltage-controlled reactance devices can be designed
to work anywhere in the frequency spectrum. Practical circuits for the
proposed voltage-controlled reactances are suggested and simulated.