Abstract: In this paper, computational fluid dynamics (CFD) is utilized to characterize a prototype biolistic delivery system, the biomedical device based on the contoured-shock-tube design (CST), with the aim at investigating shocks induced flow instabilities within the contoured shock tube. The shock/interface interactions, the growth of perturbation at an interface between two fluids of different density are interrogated. The key features of the gas dynamics and gas-particle interaction are discussed
Abstract: In seismic survey, the information regarding the
velocity of compression wave (Vp) as well as shear wave (Vs) are
very useful especially during the seismic interpretation. Previous
studies showed that both Vp and Vs determined by above methods
are totally different with respect to each other but offered good
approximation. In this study, both Vp and Vs of consolidated granite
rock were studied by using ultrasonic testing method and seismic
refraction method. In ultrasonic testing, two different condition of
rock are used which is dry and wet. The differences between Vp and
Vs getting by using ultrasonic testing and seismic refraction were
investigated and studied. The effect of water content in granite rock
towards the value of Vp and Vs during ultrasonic testing are also
measured. Within this work, the tolerance of the differences between
the velocity of seismic wave getting from ultrasonic testing and the
velocity of seismic wave getting from seismic refraction are also
measured and investigated.
Abstract: Electrocardiogram (ECG) is considered to be the
backbone of cardiology. ECG is composed of P, QRS & T waves and
information related to cardiac diseases can be extracted from the
intervals and amplitudes of these waves. The first step in extracting
ECG features starts from the accurate detection of R peaks in the
QRS complex. We have developed a robust R wave detector using
wavelets. The wavelets used for detection are Daubechies and
Symmetric. The method does not require any preprocessing therefore,
only needs the ECG correct recordings while implementing the
detection. The database has been collected from MIT-BIH arrhythmia
database and the signals from Lead-II have been analyzed. MatLab
7.0 has been used to develop the algorithm. The ECG signal under
test has been decomposed to the required level using the selected
wavelet and the selection of detail coefficient d4 has been done based
on energy, frequency and cross-correlation analysis of decomposition
structure of ECG signal. The robustness of the method is apparent
from the obtained results.
Abstract: It is well known that during the developments in the
economic sector and through the financial crises occur everywhere in
the whole world, volatility measurement is the most important
concept in financial time series. Therefore in this paper we discuss
the volatility for Amman stocks market (Jordan) for certain period of
time. Since wavelet transform is one of the most famous filtering
methods and grows up very quickly in the last decade, we compare
this method with the traditional technique, Fast Fourier transform to
decide the best method for analyzing the volatility. The comparison
will be done on some of the statistical properties by using Matlab
program.
Abstract: This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.
Abstract: This paper proposed a novel model for short term load
forecast (STLF) in the electricity market. The prior electricity
demand data are treated as time series. The model is composed of
several neural networks whose data are processed using a wavelet
technique. The model is created in the form of a simulation program
written with MATLAB. The load data are treated as time series data.
They are decomposed into several wavelet coefficient series using
the wavelet transform technique known as Non-decimated Wavelet
Transform (NWT). The reason for using this technique is the belief
in the possibility of extracting hidden patterns from the time series
data. The wavelet coefficient series are used to train the neural
networks (NNs) and used as the inputs to the NNs for electricity load
prediction. The Scale Conjugate Gradient (SCG) algorithm is used as
the learning algorithm for the NNs. To get the final forecast data, the
outputs from the NNs are recombined using the same wavelet
technique. The model was evaluated with the electricity load data of
Electronic Engineering Department in Mandalay Technological
University in Myanmar. The simulation results showed that the
model was capable of producing a reasonable forecasting accuracy in
STLF.
Abstract: Performance of millimeter-wave (mm-wave) multiband
orthogonal frequency division multiplexing (MB-OFDM) ultrawideband
(UWB) signal generation using frequency quadrupling
technique and transmission over fiber is experimentally investigated.
The frequency quadrupling is achived by using only one Mach-
Zehnder modulator (MZM) that is biased at maximum transmission
(MATB) point. At the output, a frequency quadrupling signal is
obtained then sent to a second MZM. This MZM is used for MBOFDM
UWB signal modulation. In this work, we demonstrate 30-
GHz mm-wave wireless that carries three-bands OFDM UWB
signals, and error vector magnitude (EVM) is used to analyze the
transmission quality. It is found that our proposed technique leads to
an improvement of 3.5 dB in EVM at 40% of local oscillator (LO)
modulation with comparison to the technique using two cascaded
MZMs biased at minimum transmission (MITB) point.
Abstract: Refractive index control of benzocyclobutene (BCB 4024-40) is achieved by facilitating different conditions during the thermal curing of BCB film. Refractive index (RI) change of 1.49% is obtained with curing of BCB film using an oven, while the RI change is 0.1% when the BCB is cured using a hotplate. The two different curing methods exhibit a temperature dependent refractive index change of the BCB photosensitive polymer. By carefully controlling the curing conditions, multiple layers of BCB with different RI can be fabricated, which can then be applied in the fabrication of optical waveguides.
Abstract: The oil and gas industry has moved towards Load and
Resistance Factor Design through API RP2A - LRFD and the
recently published international standard, ISO-19902, for design of
fixed steel offshore structures. The ISO 19902 is intended to provide
a harmonized design practice that offers a balanced structural fitness
for the purpose, economy and safety. As part of an ongoing work, the
reliability analysis of tubular joints of the jacket structure has been
carried out to calibrate the load and resistance factors for the design
of offshore platforms in Malaysia, as proposed in the ISO.
Probabilistic models have been established for the load effects (wave,
wind and current) and the tubular joints strengths. In this study the
First Order Reliability Method (FORM), coded in MATLAB
Software has been employed to evaluate the reliability index of the
typical joints, designed using API RP2A - WSD and ISO 19902.
Abstract: Fast delay estimation methods, as opposed to
simulation techniques, are needed for incremental performance
driven layout synthesis. On-chip inductive effects are becoming
predominant in deep submicron interconnects due to increasing clock
speed and circuit complexity. Inductance causes noise in signal
waveforms, which can adversely affect the performance of the circuit
and signal integrity. Several approaches have been put forward which
consider the inductance for on-chip interconnect modelling. But for
even much higher frequency, of the order of few GHz, the shunt
dielectric lossy component has become comparable to that of other
electrical parameters for high speed VLSI design. In order to cope up
with this effect, on-chip interconnect has to be modelled as
distributed RLCG line. Elmore delay based methods, although
efficient, cannot accurately estimate the delay for RLCG interconnect
line. In this paper, an accurate analytical delay model has been
derived, based on first and second moments of RLCG
interconnection lines. The proposed model considers both the effect
of inductance and conductance matrices. We have performed the
simulation in 0.18μm technology node and an error of as low as less
as 5% has been achieved with the proposed model when compared to
SPICE. The importance of the conductance matrices in interconnect
modelling has also been discussed and it is shown that if G is
neglected for interconnect line modelling, then it will result an delay
error of as high as 6% when compared to SPICE.