Abstract: In this paper, autonomous performance of a small
manufactured unmanned helicopter is tried to be increased. For this
purpose, a small unmanned helicopter is manufactured in Erciyes
University, Faculty of Aeronautics and Astronautics. It is called as
ZANKA-Heli-I. For performance maximization, autopilot parameters
are determined via minimizing a cost function consisting of flight
performance parameters such as settling time, rise time, overshoot
during trajectory tracking. For this purpose, a stochastic optimization
method named as simultaneous perturbation stochastic approximation
is benefited. Using this approach, considerable autonomous
performance increase (around %23) is obtained.
Abstract: Model updating is an inverse eigenvalue problem which
concerns the modification of an existing but inaccurate model with
measured modal data. In this paper, an efficient gradient based
iterative method for updating the mass, damping and stiffness
matrices simultaneously using a few of complex measured modal
data is developed. Convergence analysis indicates that the iterative
solutions always converge to the unique minimum Frobenius norm
symmetric solution of the model updating problem by choosing a
special kind of initial matrices.
Abstract: The out-of-band impedance environment is considered
to be of paramount importance in engineering the in-band impedance
environment. Presenting the frequency independent and constant outof-
band impedances across the wide modulation bandwidth is
extremely important for reliable device characterization for future
wireless systems. This paper presents an out-of-band impedance
optimization scheme based on simultaneous engineering of
significant baseband components IF1 (twice the modulation
frequency) and IF2 (four times the modulation frequency) and higher
baseband components such as IF3 (six times the modulation
frequency) and IF4 (eight times the modulation frequency) to
engineer the in-band impedance environment. The investigations
were carried out on a 10W GaN HEMT device driven to deliver a
peak envelope power of approximately 40.5dBm under modulated
excitation. The presentation of frequency independent baseband
impedances to all the significant baseband components whilst
maintaining the optimum termination for fundamental tones as well
as reactive termination for 2nd harmonic under class-J mode of
operation has outlined separate optimum impedances for best
intermodulation (IM) linearity.
Abstract: This paper proposes an APPLE scheme that aims at providing absolute and proportional throughput guarantees, and maximizing system throughput simultaneously for wireless LANs with homogeneous and heterogenous traffic. We formulate our objectives as an optimization problem, present its exact and approximate solutions, and prove the existence and uniqueness of the approximate solution. Simulations validate that APPLE scheme is accurate, and the approximate solution can well achieve the desired objectives already.
Abstract: The field of instrumentation electronics is undergoing
an explosive growth, due to its wide range of applications. The
proliferation of electrical devices in a close working proximity can
negatively influence each other’s performance. The degradation in
the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic
interference originating in the General Purpose Interface Bus (GPIB)
control-network of the AC-DC transfer measurement system.
Remedial measures of reducing measurement errors and failure of
range of industrial devices due to EMI have been explored. The ACDC
transfer measurement system was analysed for the commonmode
(CM) EMI effects. Further investigation of coupling path as
well as much accurate identification of noise propagation mechanism
has been outlined. To prevent the occurrence of common-mode
(ground loops) which was identified between the GPIB system
control circuit and the measurement circuit, a microcontroller-driven
GPIB switching isolator device was designed, prototyped,
programmed and validated. This mitigation technique has been
explored to reduce EMI effectively.
Abstract: Digital images are widely used in computer
applications. To store or transmit the uncompressed images
requires considerable storage capacity and transmission bandwidth.
Image compression is a means to perform transmission or storage of
visual data in the most economical way. This paper explains about
how images can be encoded to be transmitted in a multiplexing
time-frequency domain channel. Multiplexing involves packing
signals together whose representations are compact in the working
domain. In order to optimize transmission resources each 4 × 4
pixel block of the image is transformed by a suitable polynomial
approximation, into a minimal number of coefficients. Less than
4 × 4 coefficients in one block spares a significant amount of
transmitted information, but some information is lost. Different
approximations for image transformation have been evaluated as
polynomial representation (Vandermonde matrix), least squares +
gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev
polynomials or singular value decomposition (SVD). Results have
been compared in terms of nominal compression rate (NCR),
compression ratio (CR) and peak signal-to-noise ratio (PSNR)
in order to minimize the error function defined as the difference
between the original pixel gray levels and the approximated
polynomial output. Polynomial coefficients have been later encoded
and handled for generating chirps in a target rate of about two
chirps per 4 × 4 pixel block and then submitted to a transmission
multiplexing operation in the time-frequency domain.
Abstract: The nutritional composition and hypoglycaemic effect
of crackers produced from blend of sprouted pigeon pea, unripe
plantain and brewers’ spent grain and fed to Alloxan induced diabetic
rat was investigated. Crackers were produced from different blends of
sprouted pigeon pea, unripe plantain and brewers’ spent grain. The
crackers were evaluated for proximate composition, amino acid
profile and antinutritional factors. Blood glucose levels of normal and
diabetic rats fed with the control sample and different formulations of
cracker were measured. The protein content of the samples were
significantly different (p
Abstract: The paper presents a method in which the expert
knowledge is applied to fuzzy inference model. Even a less
experienced person could benefit from the use of such a system, e.g.
urban planners, officials. The analysis result is obtained in a very
short time, so a large number of the proposed locations can also be
verified in a short time. The proposed method is intended for testing
of locations of car parks in a city. The paper shows selected examples
of locations of the P&R facilities in cities planning to introduce the
P&R. The analyses of existing objects are also shown in the paper
and they are confronted with the opinions of the system users, with
particular emphasis on unpopular locations. The results of the
analyses are compared to expert analysis of the P&R facilities
location that was outsourced by the city and the opinions about
existing facilities users that were expressed on social networking
sites. The obtained results are consistent with actual users’ feedback.
The proposed method proves to be good, but does not require the
involvement of a large experts team and large financial contributions
for complicated research. The method also provides an opportunity to
show the alternative location of P&R facilities. Although the results
of the method are approximate, they are not worse than results of
analysis of employed experts. The advantage of this method is ease of
use, which simplifies the professional expert analysis. The ability of
analyzing a large number of alternative locations gives a broader
view on the problem. It is valuable that the arduous analysis of the
team of people can be replaced by the model's calculation. According
to the authors, the proposed method is also suitable for
implementation on a GIS platform.
Abstract: The aim of this work is to study the numerical
implementation of the Hilbert Uniqueness Method for the exact
boundary controllability of Euler-Bernoulli beam equation. This study
may be difficult. This will depend on the problem under consideration
(geometry, control and dimension) and the numerical method used.
Knowledge of the asymptotic behaviour of the control governing the
system at time T may be useful for its calculation. This idea will
be developed in this study. We have characterized as a first step, the
solution by a minimization principle and proposed secondly a method
for its resolution to approximate the control steering the considered
system to rest at time T.
Abstract: By using a fixed point theorem of a sum operator, the
existence and uniqueness of positive solution for a class of
boundary value problem of nonlinear fractional differential equation
is studied. An iterative scheme is constructed to approximate it.
Finally, an example is given to illustrate the main result.
Abstract: This study investigated the effects of thermal
treatment on Tualang honey sample in terms of honey colour and
heat-induced small metabolites. The heating process was carried out
in a temperature controlled water batch at 90oC for 4 hours. The
honey samples were put in cylinder tubes with the dimension of 1 cm
diameter and 10 cm length for homogenous heat transfer. The results
found that the thermal treatment produced not only
hydroxylmethylfurfural, but also other harmful substances such as
phthalic anhydride and radiolytic byproducts. The degradation of
honey protein was due to the detection of free amino acids such as
cysteine and phenylalanine in heat-treated honey samples. Sugar
dehydration was also occurred because fragmented di-galactose was
identified based on the presence of characteristic ions in the mass
fragmentation pattern. The honey colour was found getting darker as
the heating duration was increased up to 4 hours. Approximately, 60
mm PFund of increment was noticed for the honey colour with the
colour change rate of 14.8 mm PFund per hour. Based on the
principal component analysis, the score plot clearly shows that the
chemical profile of Tualang honey was significantly altered after 2
hours of heating at 90oC.
Abstract: Bezier curves have useful properties for path
generation problem, for instance, it can generate the reference
trajectory for vehicles to satisfy the path constraints. Both algorithms
join cubic Bezier curve segment smoothly to generate the path. Some
of the useful properties of Bezier are curvature. In mathematics,
curvature is the amount by which a geometric object deviates from
being flat, or straight in the case of a line. Another extrinsic example
of curvature is a circle, where the curvature is equal to the reciprocal
of its radius at any point on the circle. The smaller the radius, the
higher the curvature thus the vehicle needs to bend sharply. In this
study, we use Bezier curve to fit highway-like curve. We use
different approach to find the best approximation for the curve so that
it will resembles highway-like curve. We compute curvature value by
analytical differentiation of the Bezier Curve. We will then compute
the maximum speed for driving using the curvature information
obtained. Our research works on some assumptions; first, the Bezier
curve estimates the real shape of the curve which can be verified
visually. Even though, fitting process of Bezier curve does not
interpolate exactly on the curve of interest, we believe that the
estimation of speed are acceptable. We verified our result with the
manual calculation of the curvature from the map.
Abstract: In order to utilize results from global climate models,
dynamical and statistical downscaling techniques have been
developed. For dynamical downscaling, usually a limited area
numerical model is used, with associated high computational cost.
This research proposes dynamic equation for specific space-time
regional climate downscaling from the Educational Global Climate
Model (EdGCM) for Southeast Asia. The equation is for surface air
temperature. This equation provides downscaling values of surface
air temperature at any specific location and time without running a
regional climate model. In the proposed equations, surface air
temperature is approximated from ground temperature, sensible heat
flux and 2m wind speed. Results from the application of the equation
show that the errors from the proposed equations are less than the
errors for direct interpolation from EdGCM.
Abstract: One of the global combinatorial optimization
problems in machine learning is feature selection. It concerned with
removing the irrelevant, noisy, and redundant data, along with
keeping the original meaning of the original data. Attribute reduction
in rough set theory is an important feature selection method. Since
attribute reduction is an NP-hard problem, it is necessary to
investigate fast and effective approximate algorithms. In this paper,
we proposed two feature selection mechanisms based on memetic
algorithms (MAs) which combine the genetic algorithm with a fuzzy
record to record travel algorithm and a fuzzy controlled great deluge
algorithm, to identify a good balance between local search and
genetic search. In order to verify the proposed approaches, numerical
experiments are carried out on thirteen datasets. The results show that
the MAs approaches are efficient in solving attribute reduction
problems when compared with other meta-heuristic approaches.
Abstract: This paper presents the results of a study on the
influence of varying percentages of rock bridges along a basal surface
defining a biplanar failure mode. A pseudo-coupled-hydromechanical
brittle fracture analysis is adopted using the state-of-the-art code
Slope Model. Model results show that rock bridge failure is strongly
influenced by the incorporation of groundwater pressures. The
models show that groundwater pressure can promote total failure of a
5% rock bridge along the basal surface. Once the percentage of the
rock bridges increases to 10 and 15%, although, the rock bridges are
broken, full interconnection of the surface defining the basal surface
of the biplanar mode does not occur. Increased damage is caused
when the rock bridge is located at the daylighting end of the basal
surface in proximity to the blast damage zone. As expected, some
cracking damage is experienced in the blast damage zone, where
properties representing a good quality controlled damage blast
technique were assumed. Model results indicate the potential increase
of permeability towards the blast damage zone.
Abstract: We present probabilistic multinomial Dirichlet
classification model for multidimensional data and Gaussian process
priors. Here, we have considered efficient computational method that
can be used to obtain the approximate posteriors for latent variables
and parameters needed to define the multiclass Gaussian process
classification model. We first investigated the process of inducing a
posterior distribution for various parameters and latent function by
using the variational Bayesian approximations and important sampling
method, and next we derived a predictive distribution of latent
function needed to classify new samples. The proposed model is
applied to classify the synthetic multivariate dataset in order to verify
the performance of our model. Experiment result shows that our model
is more accurate than the other approximation methods.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: Wireless Sensor Networks (WSNs), which sense
environmental data with battery-powered nodes, require multi-hop
communication. This power-demanding task adds an extra workload
that is unfairly distributed across the network. As a result, nodes run
out of battery at different times: this requires an impractical
individual node maintenance scheme. Therefore we investigate a new
Cooperative Sensing approach that extends the WSN operational life
and allows a more practical network maintenance scheme (where all
nodes deplete their batteries almost at the same time). We propose a
novel cooperative algorithm that derives a piecewise representation
of the sensed signal while controlling approximation accuracy.
Simulations show that our algorithm increases WSN operational life
and spreads communication workload evenly. Results convey a
counterintuitive conclusion: distributing workload fairly amongst
nodes may not decrease the network power consumption and yet
extend the WSN operational life. This is achieved as our cooperative
approach decreases the workload of the most burdened cluster in the
network.
Abstract: This research tested the performance of alternative
warehouse designs concerning the picking process. The chosen
performance measures were Travel Distance and Total Fulfilment
Time. An explanatory case study was built up around a model
implemented with SIMUL8. Hypotheses were set by selecting
outcomes from the literature survey matching popular empirical
findings. 17.4% reductions were found for Total Fulfilment Time and
Resource Utilisation. The latter was then used as a proxy for
operational efficiency. Literal replication of theoretical data-patterns
was considered as an internal validity sign. Assessing the estimated
changes benefits ahead of implementation was found to be a
contribution to practice.
Abstract: Lateral torsional buckling is a global buckling mode
which should be considered in design of slender structural members
under flexure about their strong axis. It is possible to compute the
load which causes lateral torsional buckling of a beam by finite
element analysis, however, closed form equations are needed in
engineering practice for calculation ease which can be obtained by
using energy method. In lateral torsional buckling applications of
energy method, a proper function for the critical lateral torsional
buckling mode should be chosen which can be thought as the
variation of twisting angle along the buckled beam. Accuracy of the
results depends on how close is the chosen function to the exact
mode. Since critical lateral torsional buckling mode of the cantilever
I-beams varies due to material properties, section properties and
loading case, the hardest step is to determine a proper mode function
in application of energy method. This paper presents an approximate function for critical lateral
torsional buckling mode of doubly symmetric cantilever I-beams.
Coefficient matrices are calculated for concentrated load at free end,
uniformly distributed load and constant moment along the beam
cases. Critical lateral torsional buckling modes obtained by presented
function and exact solutions are compared. It is found that the modes
obtained by presented function coincide with differential equation
solutions for considered loading cases.