Abstract: Non contact evaluation of the thickness of paint
coatings can be attempted by different destructive and nondestructive
methods such as cross-section microscopy, gravimetric mass
measurement, magnetic gauges, Eddy current, ultrasound or
terahertz. Infrared thermography is a nondestructive and non-invasive
method that can be envisaged as a useful tool to measure the surface
thickness variations by analyzing the temperature response. In this
paper, the thermal quadrupole method for two layered samples heated
up with a pulsed excitation is firstly used. By analyzing the thermal
responses as a function of thermal properties and thicknesses of both
layers, optimal parameters for the excitation source can be identified.
Simulations show that a pulsed excitation with duration of ten
milliseconds allows obtaining a substrate-independent thermal
response. Based on this result, an experimental setup consisting of a
near-infrared laser diode and an Infrared camera was next used to
evaluate the variation of paint coating thickness between 60 μm and
130 μm on two samples. Results show that the parameters extracted
for thermal images are correlated with the estimated thicknesses by
the Eddy current methods. The laser pulsed thermography is thus an
interesting alternative nondestructive method that can be moreover
used for nonconductive substrates.
Abstract: The paper presents a method for a simple and
immediate motion planning of a SCARA robot, whose end-effector
has to move along a given trajectory; the calculation procedure
requires the user to define in analytical form or by points the
trajectory to be followed and to assign the curvilinear abscissa as
function of the time. On the basis of the geometrical characteristics
of the robot, a specifically developed program determines the motion
laws of the actuators that enable the robot to generate the required
movement; this software can be used in all industrial applications for
which a SCARA robot has to be frequently reprogrammed, in order
to generate various types of trajectories with different motion times.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.
Abstract: The main objective of incorporating natural fibers such as Henequen microfibers (NF) into the High Density Polyethylene (HDPE) polymer matrix is to reduce the cost and to enhance the mechanical as well as other properties. The Henequen microfibers were chopped manually to 5-7mm in length and added into the polymer matrix at the optimized concentration of 8 wt %. In order to facilitate the link between Henequen microfibers (NF) and HDPE matrix, coupling agent such as Glycidoxy (Epoxy) Functional Methoxy Silane (GPTS) at various concentrations from 0.1%, 0.3%, 0.5%, 0.7%, 0.9% and 1% by weight to the total fibers were added. The tensile strength of the composite increased marginally while % elongation at break of the composites decreased with increase in silane loading by wt %. Tensile modulus and stiffness observed increased at 0.9 wt % GPTS loading. Flexural as well as impact strength of the composite decreased with increase in GPTS loading by weight %. Dielectric strength of the composite also found increased marginally up to 0.5wt % silane loading and thereafter remained constant.
Abstract: This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.
Abstract: The article deals with the tool in Matlab GUI form
that is designed to analyse a mechatronic system sensitivity and
tolerance. In the analysed mechatronic system, a torque is transferred
from the drive to the load through a coupling containing flexible
elements. Different methods of control system design are used. The
classic form of the feedback control is proposed using Naslin method,
modulus optimum criterion and inverse dynamics method. The
cascade form of the control is proposed based on combination of
modulus optimum criterion and symmetric optimum criterion. The
sensitivity is analysed on the basis of absolute and relative sensitivity
of system function to the change of chosen parameter value of the
mechatronic system, as well as the control subsystem. The tolerance
is analysed in the form of determining the range of allowed relative
changes of selected system parameters in the field of system stability.
The tool allows to analyse an influence of torsion stiffness, torsion
damping, inertia moments of the motor and the load and controller(s)
parameters. The sensitivity and tolerance are monitored in terms of
the impact of parameter change on the response in the form of system
step response and system frequency-response logarithmic
characteristics. The Symbolic Math Toolbox for expression of the
final shape of analysed system functions was used. The sensitivity
and tolerance are graphically represented as 2D graph of sensitivity
or tolerance of the system function and 3D/2D static/interactive graph
of step/frequency response.
Abstract: This work proposes a data-driven multiscale based
quantitative measures to reveal the underlying complexity of
electroencephalogram (EEG), applying to a rodent model of
hypoxic-ischemic brain injury and recovery. Motivated by that real
EEG recording is nonlinear and non-stationary over different
frequencies or scales, there is a need of more suitable approach over
the conventional single scale based tools for analyzing the EEG data.
Here, we present a new framework of complexity measures
considering changing dynamics over multiple oscillatory scales. The
proposed multiscale complexity is obtained by calculating entropies of
the probability distributions of the intrinsic mode functions extracted
by the empirical mode decomposition (EMD) of EEG. To quantify
EEG recording of a rat model of hypoxic-ischemic brain injury
following cardiac arrest, the multiscale version of Tsallis entropy is
examined. To validate the proposed complexity measure, actual EEG
recordings from rats (n=9) experiencing 7 min cardiac arrest followed
by resuscitation were analyzed. Experimental results demonstrate that
the use of the multiscale Tsallis entropy leads to better discrimination
of the injury levels and improved correlations with the neurological
deficit evaluation after 72 hours after cardiac arrest, thus suggesting an
effective metric as a prognostic tool.
Abstract: Scrubbing by a liquid spraying is one of the most
effective processes used for removal of fine particles and soluble
gas pollutants (such as SO2, HCl, HF) from the flue gas. There are
many configurations of scrubbers designed to provide contact
between the liquid and gas stream for effectively capturing
particles or soluble gas pollutants, such as spray plates, packed bed
towers, jet scrubbers, cyclones, vortex and venturi scrubbers. The
primary function of venturi scrubber is the capture of fine particles
as well as HCl, HF or SO2 removal with effect of the flue gas
temperature decrease before input to the absorption column. In this
paper, sulfur dioxide (SO2) from flue gas was captured using new
design replacing venturi scrubber (1st degree of wet scrubbing).
The flue gas was prepared by the combustion of the carbon
disulfide solution in toluene (1:1 vol.) in the flame in the reactor.
Such prepared flue gas with temperature around 150°C was
processed in designed laboratory O-element scrubber. Water was
used as absorbent liquid. The efficiency of SO2 removal, pressure
drop and temperature drop were measured on our experimental
device. The dependence of these variables on liquid-gas ratio was
observed. The average temperature drop was in the range from
150°C to 40°C. The pressure drop was increased with increasing of
a liquid-gas ratio, but no too much as for the common venturi
scrubber designs. The efficiency of SO2 removal was up to 70 %.
The pressure drop of our new designed wet scrubber is similar to
commonly used venturi scrubbers; nevertheless the influence of
amount of the liquid on pressure drop is not so significant.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: Moving into a new era of healthcare, new tools and
devices are developed to extend and improve health services, such as
remote patient monitoring and risk prevention. In this concept,
Internet of Things (IoT) and Cloud Computing present great
advantages by providing remote and efficient services, as well as
cooperation between patients, clinicians, researchers and other health
professionals. This paper focuses on patients suffering from bipolar
disorder, a brain disorder that belongs to a group of conditions
called affective disorders, which is characterized by great mood
swings. We exploit the advantages of Semantic Web and Cloud
Technologies to develop a patient monitoring system to support
clinicians. Based on intelligently filtering of evidence-knowledge and
individual-specific information we aim to provide treatment
notifications and recommended function tests at appropriate times or
concluding into alerts for serious mood changes and patient’s nonresponse
to treatment. We propose an architecture as the back-end
part of a cloud platform for IoT, intertwining intelligence devices
with patients’ daily routine and clinicians’ support.
Abstract: We have conducted the optimal synthesis of rootmean-
squared objective filter to estimate the state vector in the case if
within the observation channel with memory the anomalous noises
with unknown mathematical expectation are complement in the
function of the regular noises. The synthesis has been carried out for
linear stochastic systems of continuous - time.
Abstract: The capability of exploiting the electronic charge and
spin properties simultaneously in a single material has made diluted
magnetic semiconductors (DMS) remarkable in the field of
spintronics. We report the designing of DMS based on zinc-blend
ZnO doped with Cr impurity. The full potential linearized augmented
plane wave plus local orbital FP-L(APW+lo) method in density
functional theory (DFT) has been adapted to carry out these
investigations. For treatment of exchange and correlation energy,
generalized gradient approximations have been used. Introducing Cr
atoms in the matrix of ZnO has induced strong magnetic moment
with ferromagnetic ordering at stable ground state. Cr:ZnO was found
to favor the short range magnetic interaction that
reflect tendency of Cr clustering. The electronic structure of ZnO is
strongly influenced in the presence of Cr impurity atoms where
impurity bands appear in the band gap.
Abstract: All the software engineering researches and best
industry practices aim at providing software products with high
degree of quality and functionality at low cost and less time. These
requirements are addressed by the Component Based Software
Engineering (CBSE) as well. CBSE, which deals with the software
construction by components’ assembly, is a revolutionary extension
of Software Engineering. CBSE must define and describe processes
to assure timely completion of high quality software systems that are
composed of a variety of pre built software components. Though
these features provide distinct and visible benefits in software design
and programming, they also raise some challenging problems. The
aim of this work is to summarize the pertinent issues and
considerations in CBSE to make an understanding in forms of
concepts and observations that may lead to development of newer
ways of dealing with the problems and challenges in CBSE.
Abstract: The main objective of this paper is to provide a new
methodology for road safety assessment in Oman through the
development of suitable accident prediction models. GLM technique
with Poisson or NBR using SAS package was carried out to develop
these models. The paper utilized the accidents data of 31 un-signalized
T-intersections during three years. Five goodness-of-fit
measures were used to assess the overall quality of the developed
models. Two types of models were developed separately; the flow-based
models including only traffic exposure functions, and the full
models containing both exposure functions and other significant
geometry and traffic variables.
The results show that, traffic exposure functions produced much
better fit to the accident data. The most effective geometric variables
were major-road mean speed, minor-road 85th percentile speed,
major-road lane width, distance to the nearest junction, and right-turn
curb radius.
The developed models can be used for intersection treatment or
upgrading and specify the appropriate design parameters of T-intersections.
Finally, the models presented in this thesis reflect the intersection
conditions in Oman and could represent the typical conditions in
several countries in the middle east area, especially gulf countries.
Abstract: The mechanisms underlying the association between
obesity and asthma may be related to a decreased immunological
tolerance induced by a defective function of regulatory T cells
(Tregs). The aim of this study is to establish the potential link
between these diseases and CD4+, CD25+ FoxP3+ Tregs as well as T
helper cells (Ths) in children. This is a prospective case control
study. Obese (n:40), asthmatic (n:40), asthmatic obese (n:40) and
healthy children (n:40), who don't have any acute or chronic diseases,
were included in this study. Obese children were evaluated according
to WHO criteria. Asthmatic patients were chosen based on GINA
criteria. Parents were asked to fill up the questionnaire. Informed
consent forms were taken. Blood samples were marked with CD4+,
CD25+ and FoxP3+ in order to determine Tregs and Ths by flow
cytometric method. Statistical analyses were performed. p≤0.05 was
chosen as meaningful threshold. Tregs exhibiting anti-inflammatory
nature were significantly lower in obese (0,16%; p≤0,001), asthmatic
(0,25%; p≤0,01) and asthmatic obese (0,29%; p≤0,05) groups than
the control group (0,38%). Ths were counted higher in asthma group
than the control (p≤0,01) and obese (p≤0,001) groups. T cell
immunity plays important roles in obesity and asthma pathogeneses.
Decreased numbers of Tregs found in obese, asthmatic and asthmatic
obese children may help to elucidate some questions in
pathophysiology of these diseases. For HOMA-IR levels, any
significant difference was not noted between control and obese
groups, but statistically higher values were found for obese
asthmatics. The values obtained in all groups were found to be below
the critical cut off points. This finding has made the statistically
significant difference observed between Tregs of obese, asthmatic,
obese asthmatic and control groups much more valuable. These
findings will be useful in diagnosis and treatment of these disorders
and future studies are needed. The production and propagation of
Tregs may be promising in alternative asthma and obesity treatments.
Abstract: This paper describes the issues relating to the role of
the flash flood early warning system provided by the Malaysian
Government to the communities in Malaysia, specifically during the
flash flood disaster in the Cameron Highlands, Malaysia. Normally,
flash flood disasters can occur as a result of heavy rainfall in an area,
and that water may possibly cause flooding via streams or narrow
channels. The focus of this study is the flash flood disaster which
occurred on 23 October 2013 in the Cameron Highlands, and as a
result the Sungai Bertam overflowed after the release of water from
the Sultan Abu Bakar Dam. This release of water from the dam
caused flash flooding which led to damage to properties and also the
death of residents and livestock in the area. Therefore, the effort of
this study is to identify the perceptions of the flash flood victims on
the role of the flash flood early warning system. For the purposes of
this study, data were gathered through face-to-face interviews from
those flood victims who were willing to participate in this study. This
approach helped the researcher to glean in-depth information about
their feelings and perceptions of the role of the flash flood early
warning system offered by the government. The data were analysed
descriptively and the findings show that the respondents of 22 flood
victims believe strongly that the flash flood early warning system was
confusing and dysfunctional, and communities had failed to response
positively to it. Therefore, most of the communities were not well
prepared for the releasing of water from the dam which caused
property damage, and 3 people were killed in the Cameron Highland
flash flood disaster.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: In this paper, the problem of steady laminar boundary
layer flow and heat transfer over a permeable exponentially
stretching/shrinking sheet with generalized slip velocity is
considered. The similarity transformations are used to transform the
governing nonlinear partial differential equations to a system of
nonlinear ordinary differential equations. The transformed equations
are then solved numerically using the bvp4c function in MATLAB.
Dual solutions are found for a certain range of the suction and
stretching/shrinking parameters. The effects of the suction parameter,
stretching/shrinking parameter, velocity slip parameter, critical shear
rate and Prandtl number on the skin friction and heat transfer
coefficients as well as the velocity and temperature profiles are
presented and discussed.
Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.