Abstract: This paper presents the convergence analysis
of a prediction based blind equalizer for IIR channels.
Predictor parameters are estimated by using the recursive
least squares algorithm. It is shown that the prediction
error converges almost surely (a.s.) toward a scalar
multiple of the unknown input symbol sequence. It is
also proved that the convergence rate of the parameter
estimation error is of the same order as that in the iterated
logarithm law.
Abstract: Novel acrylated epoxidized hemp oil (AEHO) based
bioresins were successfully synthesised, characterized and applied to
biocomposites reinforced with woven jute fibre. Characterisation of
the synthesised AEHO consisted of acid number titrations and FTIR
spectroscopy to assess the success of the acrylation reaction. Three
different matrices were produced (vinylester (VE), 50/50 blend of
AEHO/VE and 100% AEHO) and reinforced with jute fibre to form
three different types of biocomposite samples. Mechanical properties
in the form of flexural and interlaminar shear strength (ILSS) were
investigated and compared for the different samples. Results from the
mechanical tests showed that AEHO and 50/50 based neat bioresins
displayed lower flexural properties compared with the VE samples.
However when applied to biocomposites and compared with VE
based samples, AEHO biocomposites demonstrated comparable
flexural performance and improved ILSS. These results are attributed
to improved fibre-matrix interfacial adhesion due to surface-chemical
compatibility between the natural fibres and bioresin.
Abstract: The purpose of this study was to evaluate the tissue
composition and carcass muscularity of 32 legs of Ile de France
lambs fed with diets containing sunflower seeds and vitamin E, with
mean body weight of 15 kg, lodged in individual pens at 15 kg and
slaughtered at 32 kg of body weight. The treatments influenced
(P0,05) by the treatments. The
interaction of the sunflower and vitamin E was positive for bone total
weights and intermuscular fat.
Abstract: This paper present a MATLAB-SIMULINK model of a single phase 2.5 KVA, 240V RMS controlled PV VSI (Photovoltaic Voltage Source Inverter) inverter using IGBTs (Insulated Gate Bipolar Transistor). The behavior of output voltage, output current, and the total harmonic distortion (THD), with the variation in input dc blocking capacitor (Cdc), for linear and non-linear load has been analyzed. The values of Cdc as suggested by the other authors in their papers are not clearly defined and it poses difficulty in selecting the proper value. As the dc power stored in Cdc, (generally placed parallel with battery) is used as input to the VSI inverter. The simulation results shows the variation in the output voltage and current with different values of Cdc for linear and non-linear load connected at the output side of PV VSI inverter and suggest the selection of suitable value of Cdc.
Abstract: This paper presents the comparison ageing deterioration of silicone rubber housing material for outdoor polymer insulators by using salt fog ageing test based on IEC 61109 and outdoor exposure test.Four types of high temperature silicone vulcanized silicone rubber sheet with different amount of ATH were used as testing specimen. For salt fog ageing test, the specimens were tested continuously 1000 hours with energized in test chamber. For outdoor exposure test, the specimens were hung continuously 18 months without energized. Physical and chemical analyses were conducted to evaluate degree of ageing deterioration of tested specimens. Slightly surface erosion was observed on specimen surface after salt fog ageing test and no erosion was observed on surface of outdoor exposure specimen. However, comparable degree of ageing deterioration can be seen from surface analysis results.
Abstract: This paper presents kinematic and dynamic analysis of a novel 8-DOF hybrid robot manipulator. The hybrid robot manipulator under consideration consists of a parallel robot which
is followed by a serial mechanism. The parallel mechanism has three translational DOF, and the serial mechanism has five DOF so that the overall degree of freedom is eight. The introduced
manipulator has a wide workspace and a high capability to reduce
the actuating energy. The inverse and forward kinematic solutions are described in closed form. The theoretical results are verified by
a numerical example. Inverse dynamic analysis of the robot is presented by utilizing the Iterative Newton-Euler and Lagrange dynamic formulation methods. Finally, for performing a multi-step
arc welding process, results have indicated that the introduced manipulator is highly capable of reducing the actuating energy.
Abstract: Algae-based fuel are considered a promising sources
of clean energy, and because it has many advantages over traditional
biofuel, research and business ventures have driven into developing
and producing Algal-biofuel. But its production stages create a cost
structure that it is not competitive with traditional fuels. Therefore,
cost becomes the main obstacle in commercial production purpose.
However, the present research which aims at using cost structure
model, and designed MS-Dose program, to investigate the a mount of
production cost and determined the parameter had great effect on it,
second to measured the amount of contribution rate of algae in
process the pollution by capturing Co2 from air . The result generated
from the model shows that the production cost of biomass is between
$0.137 /kg for 100 ha and $0.132 /kg for 500 ha which was less than
cost of other studies, while gallon costs between $3.4 - 3.5, more
than traditional sources of oil about $1 ,which regarded as a rate of
contribution of algal in capturing CO2 from air.
Abstract: Modelling techniques for a fluid coupling taken from
published literature have been extended to include the effects of the
filling and emptying of the coupling with oil and the variation in
losses when the coupling is partially full. In the model, the fluid flow
inside the coupling is considered to have two principal velocity
components; one circumferentially about the coupling axis
(centrifugal head) and the other representing the secondary vortex
within the coupling itself (vortex head). The calculation of liquid
mass flow rate circulating between the two halves of the coupling is
based on: the assumption of a linear velocity variation in the
circulating vortex flow; the head differential in the fluid due to the
speed difference between the two shafts; and the losses in the
circulating vortex flow as a result of the impingement of the flow
with the blades in the coupling and friction within the passages
between the blades.
Abstract: Brand name plays a vital role for in-shop buying
behavior of consumers and mutated brand name may affect the
selling of leading branded products. In Indian market, there are many
products with mutated brand names which are either orthographically
or phonologically similar. Due to presence of such products, Indian
consumers very often fall under confusion when buying some
regularly used stuff. Authors of the present paper have attempted to
demonstrate relationship between less attention and false recognition
of mutated brand names during a product selection process. To
achieve this goal, visual attention study was conducted on 15 male
college students using eye-tracker against a mutated brand name and
errors in recognition were noted using questionnaire. Statistical
analysis of the acquired data revealed that there was more false
recognition of mutated brand name when less attention was paid
during selection of favorite product. Moreover, it was perceived that
eye tracking is an effective tool for analyzing false recognition of
brand name mutation.
Abstract: The study was conducted to investigate the profile of
hepatitis in Kingdom of Saudi Arabia, and to determine which age
group hepatitis viruses most commonly infect. The epidemiology of
viral hepatitis in Saudi Arabia has undergone major changes,
concurrent with major socioeconomic developments over the last two
to three decades. This disease represents a major public health
problem in Saudi Arabia resulting in the need for considerable
healthcare resources. A retrospective cross sectional analysis of the
reported cases of viral hepatitis was conducted based on the reports
of The Ministry of Health in Saudi Arabia about Hepatitis A, B and C
infections in all regions from the period of January 2006 to December
2010. The study demonstrated that incidence of viral Hepatitis is
decreasing, except for Hepatitis B that showed minimal increase. Of
hepatitis A, B, and C, Hepatitis B virus (HBV) was the most
predominant type, accounting for (53%) of the cases, followed by
Hepatitis C virus (HCV) (30%) and HAV (17%). HAV infection
predominates in children (5–14 years) with 60% of viral hepatitis
cases, HBV in young adults (15–44 years) with 69% of viral hepatitis
cases, and HCV in older adults (>45 years) with 59% of viral
hepatitis cases. Despite significant changes in the prevalence of viral
hepatitis A, B and C, it remains a major public health problem in
Saudi Arabia; however, it showed a significant decline in the last two
decades that could be attributed to the vaccination programs and the
improved health facilities. Further researches are needed to identify
the risk factors making a specific age group or a specific region in
Saudi Arabia targeted for a specific type of hepatitis viruses.
Abstract: This paper presents the use of anti-sway angle control
approaches for a two-dimensional gantry crane with disturbances
effect in the dynamic system. Delayed feedback signal (DFS) and
proportional-derivative (PD)-type fuzzy logic controller are the
techniques used in this investigation to actively control the sway
angle of the rope of gantry crane system. A nonlinear overhead
gantry crane system is considered and the dynamic model of the
system is derived using the Euler-Lagrange formulation. A complete
analysis of simulation results for each technique is presented in time
domain and frequency domain respectively. Performances of both
controllers are examined in terms of sway angle suppression and
disturbances cancellation. Finally, a comparative assessment of the
impact of each controller on the system performance is presented and
discussed.
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.
Abstract: We present the development of a new underwater laser
cutting process in which a water-jet has been used along with the
laser beam to remove the molten material through kerf. The
conventional underwater laser cutting usually utilizes a high pressure
gas jet along with laser beam to create a dry condition in the cutting
zone and also to eject out the molten material. This causes a lot of gas
bubbles and turbulence in water, and produces aerosols and waste
gas. This may cause contamination in the surrounding atmosphere
while cutting radioactive components like burnt nuclear fuel. The
water-jet assisted underwater laser cutting process produces much
less turbulence and aerosols in the atmosphere. Some amount of
water vapor bubbles is formed at the laser-metal-water interface;
however, they tend to condense as they rise up through the
surrounding water. We present the design and development of a
water-jet assisted underwater laser cutting head and the parametric
study of the cutting of AISI 304 stainless steel sheets with a 2 kW
CW fiber laser. The cutting performance is similar to that of the gas
assist laser cutting; however, the process efficiency is reduced due to
heat convection by water-jet and laser beam scattering by vapor. This
process may be attractive for underwater cutting of nuclear reactor
components.
Abstract: A cross sectional survey design was used to collect
data from 370 diabetic patients. Two instruments were used in
obtaining data; in-depth interview guide and researchers- developed
questionnaire. Fisher's exact test was used to investigate association
between the identified factors and nonadherence. Factors identified
were: socio-demographic factors such as: gender, age, marital status,
educational level and occupation; psychosocial obstacles such as:
non-affordability of prescribed diet, frustration due to the restriction,
limited spousal support, feelings of deprivation, feeling that
temptation is inevitable, difficulty in adhering in social gatherings
and difficulty in revealing to host that one is diabetic; health care
providers obstacles were: poor attitude of health workers, irregular
diabetes education in clinics , limited number of nutrition education
sessions/ inability of the patients to estimate the desired quantity of
food, no reminder post cards or phone calls about upcoming patient
appointments and delayed start of appointment / time wasting in
clinics.
Abstract: Economically transformers constitute one of the largest investments in a Power system. For this reason, transformer condition assessment and management is a high priority task. If a transformer fails, it would have a significant negative impact on revenue and service reliability. Monitoring the state of health of power transformers has traditionally been carried out using laboratory Dissolved Gas Analysis (DGA) tests performed at periodic intervals on the oil sample, collected from the transformers. DGA of transformer oil is the single best indicator of a transformer-s overall condition and is a universal practice today, which started somewhere in the 1960s. Failure can occur in a transformer due to different reasons. Some failures can be limited or prevented by maintenance. Oil filtration is one of the methods to remove the dissolve gases and prevent the deterioration of the oil. In this paper we analysis the DGA data by regression method and predict the gas concentration in the oil in the future. We bring about a comparative study of different traditional methods of regression and the errors generated out of their predictions. With the help of these data we can deduce the health of the transformer by finding the type of fault if it has occurred or will occur in future. Additional in this paper effect of filtration on the transformer health is highlight by calculating the probability of failure of a transformer with and without oil filtrating.
Abstract: Appropriate description of business processes through
standard notations has become one of the most important assets for
organizations. Organizations must therefore deal with quality faults
in business process models such as the lack of understandability and
modifiability. These quality faults may be exacerbated if business
process models are mined by reverse engineering, e.g., from existing
information systems that support those business processes. Hence,
business process refactoring is often used, which change the internal
structure of business processes whilst its external behavior is
preserved. This paper aims to choose the most appropriate set of
refactoring operators through the quality assessment concerning
understandability and modifiability. These quality features are
assessed through well-proven measures proposed in the literature.
Additionally, a set of measure thresholds are heuristically established
for applying the most promising refactoring operators, i.e., those that
achieve the highest quality improvement according to the selected
measures in each case.
Abstract: The paper presents a simple and an accurate formula
that has been developed for the conduction angle (δ) of a single
phase half-wave or full-wave controlled rectifier with RL load. This
formula can be also used for calculating the conduction angle (δ) in
case of A.C. voltage regulator with inductive load under
discontinuous current mode. The simulation results shows that the
conduction angle calculated from the developed formula agree very
well with that obtained from the exact solution arrived from the
iterative method. Applying the developed formula can reduce the
computational time and reduce the time for manual classroom
calculation. In addition, the proposed formula is attractive for real
time implementations.
Abstract: Group-III nitride material as particularly AlxGa1-xN is
one of promising optoelectronic materials to require for shortwavelength
devices. To achieve the high-quality AlxGa1-xN films for
a high performance of such devices, AlN-nucleation layers are the
important factor. To improve the AlN-nucleation layers with a
variation of Ga-addition, XRD measurements were conducted to
analyze the crystalline quality of the subsequent Al0.1Ga0.9N with the
minimum ω-FWHMs of (0002) and (10-10) reflections of 425 arcsec
and 750 arcsec, respectively. SEM and AFM measurements were
performed to observe the surface morphology and TEM
measurements to identify the microstructures and orientations.
Results showed that the optimized Ga-atoms in the Al(Ga)Nnucleation
layers improved the surface diffusion to form moreuniform
crystallites in structure and size, better alignment of each
crystallite, and better homogeneity of island distribution. This, hence,
improves the orientation of epilayers on the Si-surface and finally
improves the crystalline quality and reduces the residual strain of
subsequent Al0.1Ga0.9N layers.
Abstract: The back propagation algorithm calculates the weight
changes of artificial neural networks, and a common approach is to
use a training algorithm consisting of a learning rate and a
momentum factor. The major drawbacks of above learning algorithm
are the problems of local minima and slow convergence speeds. The
addition of an extra term, called a proportional factor reduces the
convergence of the back propagation algorithm. We have applied the
three term back propagation to multiplicative neural network
learning. The algorithm is tested on XOR and parity problem and
compared with the standard back propagation training algorithm.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.