Abstract: In this research work, neural networks were applied to
classify two types of hip joint implants based on the relative hip joint
implant side speed and three components of each ground reaction
force. The condition of walking gait at normal velocity was used and
carried out with each of the two hip joint implants assessed. Ground
reaction forces’ kinetic temporal changes were considered in the first
approach followed but discarded in the second one. Ground reaction
force components were obtained from eighteen patients under such
gait condition, half of which had a hip implant type I-II, whilst the
other half had the hip implant, defined as type III by Orthoload®.
After pre-processing raw gait kinetic data and selecting the time
frames needed for the analysis, the ground reaction force components
were used to train a MLP neural network, which learnt to distinguish
the two hip joint implants in the abovementioned condition. Further
to training, unknown hip implant side and ground reaction force
components were presented to the neural networks, which assigned
those features into the right class with a reasonably high accuracy for
the hip implant type I-II and the type III. The results suggest that
neural networks could be successfully applied in the performance
assessment of hip joint implants.
Abstract: The lactic acid bacteria (LAB) were isolated from
10 samples of fermented foods (Sa-tor-dong and Bodo) in South
locality of Thailand. The 23 isolates of lactic acid bacteria were
selected, which were exhibited a clear zone and growth on MRS
agar supplemented with CaCO3. All of lactic acid bacteria were
tested on morphological and biochemical. The result showed that
all isolates were Gram’s positive, non-spore forming but only
10 isolates displayed catalase negative. The 10 isolates including
BD1 .1, BD 1.2, BD 2.1, BD2.2, BD 2.3, BD 3.1, BD 4.1, BD 5.2,
ST 4.1 and ST 5.2 were selected for inhibition activity
determination. Only 2 strains (ST 4.1 and BD 2.3) showed
inhibition zone on agar, when using Escherichia coli sp. as target
strain. The ST 4.1 showed highest inhibition zone on agar, which
was selected for probiotic property testing. The ST4.1 isolate
could grow in MRS broth containing a high concentration of
sodium chloride 6%, bile salts 7%, pH 4-10 and vary temperature
at 15-45°C.
Abstract: In this study, a three dimensional numerical heat
transfer model has been used to simulate the laser structuring of
polymer substrate material in the Three-Dimensional Molded
Interconnect Device (3D MID) which is used in the advanced multifunctional
applications. A finite element method (FEM) transient
thermal analysis is performed using APDL (ANSYS Parametric
Design Language) provided by ANSYS. In this model, the effect of
surface heat source was modeled with Gaussian distribution, also the
effect of the mixed boundary conditions which consist of convection
and radiation heat transfers have been considered in this analysis. The
model provides a full description of the temperature distribution, as
well as calculates the depth and the width of the groove upon material
removal at different set of laser parameters such as laser power and
laser speed. This study also includes the experimental procedure to
study the effect of laser parameters on the depth and width of the
removal groove metal as verification to the modeled results. Good
agreement between the experimental and the model results is
achieved for a wide range of laser powers. It is found that the quality
of the laser structure process is affected by the laser scan speed and
laser power. For a high laser structured quality, it is suggested to use
laser with high speed and moderate to high laser power.
Abstract: With demand for primary energy continuously
growing, search for renewable and efficient energy sources has been
high on agenda of our society. One of the most promising energy
sources is biogas technology. Residues coming from dairy industry
and milk processing could be used in biogas production; however,
low efficiency and high cost impede wide application of such
technology. One of the main problems is management and conversion
of organic residues through the anaerobic digestion process which is
characterized by acidic environment due to the low whey pH (
Abstract: In this paper, we propose a multi-agent intelligent
system that is used for monitoring the health conditions of elderly
people. Monitoring the health condition of elderly people is a
complex problem that involves different medical units and requires
continuous monitoring. Such expert system is highly needed in rural
areas because of inadequate number of available specialized
physicians or nurses. Such monitoring must have autonomous
interactions between these medical units in order to be effective. A
multi-agent system is formed by a community of agents that
exchange information and proactively help one another to achieve the
goal of elderly monitoring. The agents in the developed system are
equipped with intelligent decision maker that arms them with the
rule-based reasoning capability that can assist the physicians in
making decisions regarding the medical condition of elderly people.
Abstract: Voltage sags are the most common power quality
disturbance in the distribution system. It occurs due to the fault in the
electrical network or by the starting of a large induction motor and
this can be solved by using the custom power devices such as
Dynamic Voltage Restorer (DVR). In this paper DVR is proposed to
compensate voltage sags on critical loads dynamically. The DVR
consists of VSC, injection transformers, passive filters and energy
storage (lead acid battery). By injecting an appropriate voltage, the
DVR restores a voltage waveform and ensures constant load voltage.
The simulation and experimental results of a DVR using MATLAB
software shows clearly the performance of the DVR in mitigating
voltage sags.
Abstract: In development of floating photovoltaic generation
system, finding a suitable place of installation is as important as
development of economically feasible and stable structure. Especially
since floating photovoltaic system has its facility floating on water
surface, it is extremely important to review the effects of weather
conditions such as wind, water flow and floating matters, various
factors (such as fogs) that can reduce generation efficiency, possibility
of connection with power system, and legal restrictions. The method of
investigating suitable area and resource for development of
tracking-type floating photovoltaic generation system was proposed in
this paper, which can be used for development of floating and ocean
photovoltaic system in the future.
Abstract: This paper aims at finding a suitable neural network
for monitoring congestion level in electrical power systems. In this
paper, the input data has been framed properly to meet the target
objective through supervised learning mechanism by defining normal
and abnormal operating conditions for the system under study. The
congestion level, expressed as line congestion index (LCI), is
evaluated for each operating condition and is presented to the NN
along with the bus voltages to represent the input and target data.
Once, the training goes successful, the NN learns how to deal with a
set of newly presented data through validation and testing
mechanism. The crux of the results presented in this paper rests on
performance comparison of a multi-layered feed forward neural
network with eleven types of back propagation techniques so as to
evolve the best training criteria. The proposed methodology has been
tested on the standard IEEE-14 bus test system with the support of
MATLAB based NN toolbox. The results presented in this paper
signify that the Levenberg-Marquardt backpropagation algorithm
gives best training performance of all the eleven cases considered in
this paper, thus validating the proposed methodology.
Abstract: The system is designed to show images which are
related to the query image. Extracting color, texture, and shape
features from an image plays a vital role in content-based image
retrieval (CBIR). Initially RGB image is converted into HSV color
space due to its perceptual uniformity. From the HSV image, Color
features are extracted using block color histogram, texture features
using Haar transform and shape feature using Fuzzy C-means
Algorithm. Then, the characteristics of the global and local color
histogram, texture features through co-occurrence matrix and Haar
wavelet transform and shape are compared and analyzed for CBIR.
Finally, the best method of each feature is fused during similarity
measure to improve image retrieval effectiveness and accuracy.
Abstract: In healthy humans, the cortical brain rhythm shows
specific mu (~6-14 Hz) and beta (~18-24 Hz) band patterns in the
cases of both real and imaginary motor movements. As cerebellar
ataxia is associated with impairment of precise motor movement
control as well as motor imagery, ataxia is an ideal model system in
which to study the role of the cerebellocortical circuit in rhythm
control. We hypothesize that the EEG characteristics of ataxic patients
differ from those of controls during the performance of a
Brain-Computer Interface (BCI) task. Ataxia and control subjects
showed a similar distribution of mu power during cued relaxation.
During cued motor imagery, however, the ataxia group showed
significant spatial distribution of the response, while the control group
showed the expected decrease in mu-band power (localized to the
motor cortex).
Abstract: In this paper we make a temperature investigations in
two type of superposed crimped connections using experimental
determinations. All the samples use 8 copper wire 7.1 x 3 mm2
crimped by two methods: the first method uses one crimp indents and
the second is a proposed method with two crimp indents. The ferrule
is a parallel one. We study the influence of number and position of
crimp indents. The samples are heated in A.C. current at different
current values until steady state heating regime. After obtaining of
temperature values, we compare them and present the conclusion.
Abstract: Color Histogram is considered as the oldest method
used by CBIR systems for indexing images. In turn, the global
histograms do not include the spatial information; this is why the
other techniques coming later have attempted to encounter this
limitation by involving the segmentation task as a preprocessing step.
The weak segmentation is employed by the local histograms while
other methods as CCV (Color Coherent Vector) are based on strong
segmentation. The indexation based on local histograms consists of
splitting the image into N overlapping blocks or sub-regions, and
then the histogram of each block is computed. The dissimilarity
between two images is reduced, as consequence, to compute the
distance between the N local histograms of the both images resulting
then in N*N values; generally, the lowest value is taken into account
to rank images, that means that the lowest value is that which helps to
designate which sub-region utilized to index images of the collection
being asked. In this paper, we make under light the local histogram
indexation method in the hope to compare the results obtained against
those given by the global histogram. We address also another
noteworthy issue when Relying on local histograms namely which
value, among N*N values, to trust on when comparing images, in
other words, which sub-region among the N*N sub-regions on which
we base to index images. Based on the results achieved here, it seems
that relying on the local histograms, which needs to pose an extra
overhead on the system by involving another preprocessing step
naming segmentation, does not necessary mean that it produces better
results. In addition to that, we have proposed here some ideas to
select the local histogram on which we rely on to encode the image
rather than relying on the local histogram having lowest distance with
the query histograms.
Abstract: Frequent pattern mining is the process of finding a
pattern (a set of items, subsequences, substructures, etc.) that occurs
frequently in a data set. It was proposed in the context of frequent
itemsets and association rule mining. Frequent pattern mining is used
to find inherent regularities in data. What products were often
purchased together? Its applications include basket data analysis,
cross-marketing, catalog design, sale campaign analysis, Web log
(click stream) analysis, and DNA sequence analysis. However, one of
the bottlenecks of frequent itemset mining is that as the data increase
the amount of time and resources required to mining the data
increases at an exponential rate. In this investigation a new algorithm
is proposed which can be uses as a pre-processor for frequent itemset
mining. FASTER (FeAture SelecTion using Entropy and Rough sets)
is a hybrid pre-processor algorithm which utilizes entropy and roughsets
to carry out record reduction and feature (attribute) selection
respectively. FASTER for frequent itemset mining can produce a
speed up of 3.1 times when compared to original algorithm while
maintaining an accuracy of 71%.
Abstract: This paper presents a 3D guidance scheme for
Unmanned Aerial Vehicles (UAVs). The proposed guidance scheme
is based on the sliding mode approach using nonlinear sliding
manifolds. Generalized 3D kinematic equations are considered
here during the design process to cater for the coupling between
longitudinal and lateral motions. Sliding mode based guidance
scheme is then derived for the multiple-input multiple-output
(MIMO) system using the proposed nonlinear manifolds. Instead of
traditional sliding surfaces, nonlinear sliding surfaces are proposed
here for performance and stability in all flight conditions. In the
reaching phase control inputs, the bang-bang terms with signum
functions are accompanied with proportional terms in order to reduce
the chattering amplitudes. The Proposed 3D guidance scheme is
implemented on a 6-degrees-of-freedom (6-dof) simulation of a UAV
and simulation results are presented here for different 3D trajectories
with and without disturbances.
Abstract: The relationship between eigenstructure (eigenvalues
and eigenvectors) and latent structure (latent roots and latent vectors)
is established. In control theory eigenstructure is associated with
the state space description of a dynamic multi-variable system and
a latent structure is associated with its matrix fraction description.
Beginning with block controller and block observer state space forms
and moving on to any general state space form, we develop the
identities that relate eigenvectors and latent vectors in either direction.
Numerical examples illustrate this result. A brief discussion of the
potential of these identities in linear control system design follows.
Additionally, we present a consequent result: a quick and easy
method to solve the polynomial eigenvalue problem for regular matrix
polynomials.
Abstract: Two types of commercial cylindrical lithium ion
batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah
INR-18650), were investigated experimentally. The capacities of these
samples were individually measured using constant current-constant
voltage (CC-CV) method at different ambient temperatures (-10°C,
0°C, 25°C). Their internal resistance was determined by
electrochemical impedance spectroscopy (EIS) and pulse discharge
methods. The cells with different configurations of parallel connection
NCR-NCR, INR-INR and NCR-INR were charged/discharged at the
aforementioned ambient temperatures. The results showed that the
difference of internal resistance between cells much more evident at
low temperatures. Furthermore, the parallel connection of NCR-NCR
exhibits the most uniform temperature distribution in cells at -10°C,
this feature is quite favorable for the safety of the battery pack.
Abstract: During welding, the amount of heat present in weld
zones determines the quality of weldment produced. Thus, the heat
distribution characteristics and its magnitude in weld zones with
respect to process variables such as tool pin-shoulder rotational and
traveling speed during welding is analyzed using thermal finite
element analyses method. For this purpose, transient thermal finite
element analyses are performed to model the temperatures
distribution and its quantities in weld-zones with respect to process
variables such as rotational speed and traveling speed during welding.
Commercially available software Altair HyperWork is used to model
three-dimensional tool pin-shoulder vs. workpieces and to simulate
the friction stir process. The results show that increasing tool
rotational speed, at a constant traveling speed, will increase the
amount of heat generated in weld-zones. In contrary, increasing
traveling speed, at constant tool pin-shoulder rotational speeds, will
reduce the amount of heat generated in weld zones.
Abstract: In this paper, strontium ferrite (SrO.6Fe2O3) was
synthesized by the sol-gel auto-combustion process. The thermal
behavior of powder obtained from self-propagating combustion of
initial gel was evaluated by simultaneous differential thermal analysis
(DTA) and thermo gravimetric (TG), from room temperature to
1200°C. The as-burnt powder was calcined at various temperatures
from 700-900°C to achieve the single-phase Sr-ferrite. Phase
composition, morphology and magnetic properties were investigated
using X-ray diffraction (XRD), transmission electron microscopy
(TEM) and vibrating sample magnetometry (VSM) techniques.
Results showed that the single-phase and nano-sized hexagonal
strontium ferrite particles were formed at calcination temperature of
800°C with crystallite size of 27 nm and coercivity of 6238 Oe.
Abstract: Boron-gypsum is a waste which occurs in the boric
acid production process. In this study, the boron content of this waste
is evaluated for the use in synthesis of magnesium borates and such
evaluation of this kind of waste is useful more than storage or
disposal. Magnesium borates, which are a sub-class of boron
minerals, are useful additive materials for the industries due to their
remarkable thermal and mechanical properties. Magnesium borates
were obtained hydrothermally at different temperatures. Novelty of
this study is the search of the solution density effects to magnesium
borate synthesis process for the increasing the possibility of borongypsum
usage as a raw material. After the synthesis process, products
are subjected to XRD and FT-IR to identify and characterize their
crystal structure, respectively.
Abstract: Fly ash is an important waste, produced in thermal
power plants which causes very important environmental pollutions.
For this reason the usage and evaluation the fly ash in various areas
are very important. Nearly, 15 million tons/year of fly ash is
produced in Turkey. In this study, usage of fly ash with diatomite and
molasses for heavy metal (Cd) adsorption from wastewater is
investigated. The samples of Seyitomer region fly ash were analyzed
by X-ray fluorescence (XRF) and Scanning Electron Microscope
(SEM) then diatomite (0 and 1% in terms of fly ash, w/w) and
molasses (0-0.75 mL) were pelletized under 30 MPa of pressure for
the usage of cadmium (Cd) adsorption in wastewater. After the
adsorption process, samples of Seyitomer were analyzed using
Optical Emission Spectroscopy (ICP-OES). As a result, it is seen that
the usage of Seyitomer fly ash is proper for cadmium (Cd) adsorption
and an optimum adsorption yield with 52% is found at a compound
with Seyitomer fly ash (10 g), diatomite (0.5 g) and molasses (0.75
mL) at 2.5 h of reaction time, pH:4, 20ºC of reaction temperature and
300 rpm of stirring rate.