Abstract: Nonspecific protein adsorption generally occurs on
any solid surfaces and usually has adverse consequences. Adsorption
of proteins onto a solid surface is believed to be the initial and
controlling step in biofouling. Surfaces modified with end-tethered
poly(ethylene glycol) (PEG) have been shown to be protein-resistant
to some degree. In this study, the adsorption of β-casein and
lysozyme was performed on 6 different types of surfaces where PEG
was tethered onto stainless steel by polyethylene imine (PEI) through
either OH or NHS end groups. Protein adsorption was also performed
on the bare stainless steel surface as a control. The adsorption was
conducted at 23 °C and pH 7.2. In situ QCM-D was used to
determine PEG adsorption kinetics, plateau PEG chain densities,
protein adsorption kinetics and plateau protein adsorbed quantities.
PEG grafting density was the highest for a NHS coupled chain,
around 0.5 chains / nm2. Interestingly, lysozyme which has smaller
size than β-casein, appeared to adsorb much less mass than that of β-
casein. Overall, the surface with high PEG grafting density exhibited
a good protein rejection.
Abstract: K-Means (KM) is considered one of the major
algorithms widely used in clustering. However, it still has some
problems, and one of them is in its initialization step where it is
normally done randomly. Another problem for KM is that it
converges to local minima. Genetic algorithms are one of the
evolutionary algorithms inspired from nature and utilized in the field
of clustering. In this paper, we propose two algorithms to solve the
initialization problem, Genetic Algorithm Initializes KM (GAIK) and
KM Initializes Genetic Algorithm (KIGA). To show the effectiveness
and efficiency of our algorithms, a comparative study was done
among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA),
and FCM [19].
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: Edge detection is usually the first step in medical
image processing. However, the difficulty increases when a
conventional kernel-based edge detector is applied to ultrasonic
images with a textural pattern and speckle noise. We designed an
adaptive diffusion filter to remove speckle noise while preserving the
initial edges detected by using a Sobel edge detector. We also propose
a genetic algorithm for edge selection to form complete boundaries of
the detected entities. We designed two fitness functions to evaluate
whether a criterion with a complex edge configuration can render a
better result than a simple criterion such as the strength of gradient.
The edges obtained by using a complex fitness function are thicker and
more fragmented than those obtained by using a simple fitness
function, suggesting that a complex edge selecting scheme is not
necessary for good edge detection in medical ultrasonic images;
instead, a proper noise-smoothing filter is the key.
Abstract: Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize
parametric actions with object context is presented. Objects are key instruments in understanding an action when there is uncertainty.
Ambiguities arising in similar actions can be resolved with objectn context. We classify actions according to the changes they make to
the object space. Actions that produce the same state change in the object movement space are classified to belong to the same class. This allow us to define several classes of actions where members of
each class are connected with a semantic interpretation.
Abstract: There have been numerous implementations of
security system using biometric, especially for identification and
verification cases. An example of pattern used in biometric is the iris
pattern in human eye. The iris pattern is considered unique for each
person. The use of iris pattern poses problems in encoding the human
iris.
In this research, an efficient iris recognition method is proposed.
In the proposed method the iris segmentation is based on the
observation that the pupil has lower intensity than the iris, and the
iris has lower intensity than the sclera. By detecting the boundary
between the pupil and the iris and the boundary between the iris and
the sclera, the iris area can be separated from pupil and sclera. A step
is taken to reduce the effect of eyelashes and specular reflection of
pupil. Then the four levels Coiflet wavelet transform is applied to the
extracted iris image. The modified Hamming distance is employed to
measure the similarity between two irises.
This research yields the identification success rate of 84.25% for
the CASIA version 1.0 database. The method gives an accuracy of
77.78% for the left eyes of MMU 1 database and 86.67% for the
right eyes. The time required for the encoding process, from the
segmentation until the iris code is generated, is 0.7096 seconds.
These results show that the accuracy and speed of the method is
better than many other methods.
Abstract: Drought is one of the most damaging climate-related
hazards, it is generally considered as a prolonged absence of
precipitation. This normal and recurring climate phenomenon had
plagued civilization throughout history because of the negative
impacts on economical, environmental and social sectors. Drought
characteristics are thus recognized as important factors in water
resources planning and management. The purpose of this study is to
detect the changes in drought frequency, persistence and severity
in the Ruhr river basin. The frequency of drought events was
calculated using the Standardized Precipitation Index (SPI). Used
data are daily precipitation records from seven meteorological
stations covering the period 1961-2007. The main benefit of the
application of this index is its versatility, only rainfall data is required
to deliver five major dimensions of a drought : duration, intensity,
severity, magnitude, and frequency. Furthermore, drought can be
calculated in different time steps. In this study SPI was calculated for
1, 3, 6, 9, 12, and 24 months. Several drought events were detected
in the covered period, these events contain mild, moderate and severe
droughts. Also positive and negative trends in the SPI values were
observed.
Abstract: This paper presents an on-going research work on the
implementation of feature-based machining via macro programming.
Repetitive machining features such as holes, slots, pockets etc can
readily be encapsulated in macros. Each macro consists of methods
on how to machine the shape as defined by the feature. The macro
programming technique comprises of a main program and
subprograms. The main program allows user to select several
subprograms that contain features and define their important
parameters. With macros, complex machining routines can be
implemented easily and no post processor is required. A case study
on machining of a part that comprised of planar face, hole and pocket
features using the macro programming technique was carried out. It
is envisaged that the macro programming technique can be extended
to other feature-based machining fields such as the newly developed
STEP-NC domain.
Abstract: In the present study, the oleaginous fungus
Mortierella alpina CBS 754.68 was screened for arachidonic
acidproduction using inexpensive agricultural by-products as
substrate. Four oilcakes were analysed to choose the best substrate
among them. Sunflower oilcake was the most effective substrate for
ARA production followed by soybean, colza and olive oilcakes. In
the next step, seven variables including substrate particle size,
moisture content, time, temperature, yeast extract supply, glucose
supply and glutamate supply were surveyed and effective variables
for ARA production were determined using a Plackett-Burman
screening design. Analysis results showed that time (12 days),
substrate particle size (1-1.4 mm) and temperature (20ºC) were the
most effective variables for the highest level of ARA production
respectively.
Abstract: This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..
Abstract: In this work, effects of catalysts (TiO2, and Nb2O5) were investigated on the hydrogen desorption of Mg(BH4)2. LiBH4 and MgCl2 with 2:1 molar ratio were mixed by using ball milling to prepare Mg(BH4)2. The desorption behaviors were measured by thermo-volumetric apparatus. The hydrogen desorption capacity of the mixed sample milled for 2 h was 4.78 wt% with a 2-step released. The first step occurred at 214 °C and the second step appeared at 374 °C. The addition of 16 wt% Nb2O5 decreased the desorption temperature in the second step about 66 °C and increased the hydrogen desorption capacity to 4.86 wt% hydrogen. The addition of TiO2 also improved the desorption temperature in the second step and the hydrogen desorption capacity. It decreased the desorption temperature about 71°C and showed a high amount of hydrogen, 5.27 wt%, released from the mixed sample. The hydrogen absorption after desorption of Mg(BH4)2 was also studied under 9.5 MPa and 350 °C for 12 h.
Abstract: Candida spp. are common and aggressive pathogens. Because of the growing resistance of Candida spp. to current antifungals, novel targets, found in Candida spp. but not in humans or other flora, have to be identified. The alternative oxidase (AOX) is one such possibility. This enzyme is insensitive to cyanide, but is sensitive to compounds such as salicylhydroxamic acid (SHAM), disulfiram and n-alkyl gallates. The growth each of six Candida spp. was inhibited significantly by ~13 mM SHAM or 2 mM cyanide, albeit to differing extents. In C. dubliniensis, C. krusei and C. tropicalis the rate of O2 uptake was inhibited by 18-36% by 25 mM SHAM, but this had little or no effect on C. glabrata, C. guilliermondii or C. parapsilosis. Although SHAM substantially inhibited the growth of Candida spp., it is unlikely that the inhibition of AOX was the cause. Salicylhydroxamic acid is used therapeutically in the treatment of urinary tract infections and urolithiasis, but it also has some potential in the treatment of Candida spp. infection.
Abstract: The purposes of this research were 1) to study
consumer-based equity of luxury brands, 2) to study consumers-
purchase intention for luxury brands, 3) to study direct factors
affecting purchase intention towards luxury brands, and 4) to study
indirect factors affecting purchase intention towards luxury brands
through brand consciousness and brand equity to analyze information
by descriptive statistic and hierarchical stepwise regression analysis.
The findings revealed that the eight variables of the framework which
were: need for uniqueness, normative susceptibility, status
consumption, brand consciousness, brand awareness, perceived
quality, brand association, and brand loyalty affected the purchase
intention of the luxury brands (at the significance of 0.05). Brand
Loyalty had the strongest direct effect while status consumption had
the strongest indirect effect affecting the purchase intention towards
luxury brands. Brand consciousness and brand equity had the
mediators through the purchase intention of the luxury brands (at the
significance of 0.05).
Abstract: The purpose of this paper primarily intends to develop GIS interface for estimating sequences of stream-flows at ungauged stations based on known flows at gauged stations. The integrated GIS interface is composed of three major steps. The first, precipitation characteristics using statistical analysis is the procedure for making multiple linear regression equation to get the long term mean daily flow at ungauged stations. The independent variables in regression equation are mean daily flow and drainage area. Traditionally, mean flow data are generated by using Thissen polygon method. However, method for obtaining mean flow data can be selected by user such as Kriging, IDW (Inverse Distance Weighted), Spline methods as well as other traditional methods. At the second, flow duration curve (FDC) is computing at unguaged station by FDCs in gauged stations. Finally, the mean annual daily flow is computed by spatial interpolation algorithm. The third step is to obtain watershed/topographic characteristics. They are the most important factors which govern stream-flows. In summary, the simulated daily flow time series are compared with observed times series. The results using integrated GIS interface are closely similar and are well fitted each other. Also, the relationship between the topographic/watershed characteristics and stream flow time series is highly correlated.
Abstract: In order to study seed yield and seed yield
components in bean under reduced irrigation condition and
assessment drought tolerance of genotypes, 15 lines of White beans
were evaluated in two separate RCB design with 3 replications under
stress and non stress conditions. Analysis of variance showed that
there were significant differences among varieties in terms of traits
under study, indicating the existence of genetic variation among
varieties. The results indicate that drought stress reduced seed yield,
number of seed per plant, biological yield and number of pod in
White been. In non stress condition, yield was highly correlated with
the biological yield, whereas in stress condition it was highly
correlated with harvest index. Results of stepwise regression showed
that, selection can we done based on, biological yield, harvest index,
number of seed per pod, seed length, 100 seed weight. Result of path
analysis showed that the highest direct effect, being positive, was
related to biological yield in non stress and to harvest index in stress
conditions. Factor analysis were accomplished in stress and nonstress
condition a, there were 4 factors that explained more than 76
percent of total variations. We used several selection indices such as
Stress Susceptibility Index ( SSI ), Geometric Mean Productivity (
GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and
Tolerance Index ( TOL ) to study drought tolerance of genotypes, we
found that the best Stress Index for selection tolerance genotypes
were STI, GMP and MP were the greatest correlations between these
Indices and seed yield under stress and non stress conditions. In
classification of genotypes base on phenotypic characteristics, using
cluster analysis ( UPGMA ), all allels classified in 5 separate groups
in stress and non stress conditions.
Abstract: In this paper, an approach to reduce the computation steps required by fast neural networksfor the searching process is presented. The principle ofdivide and conquer strategy is applied through imagedecomposition. Each image is divided into small in sizesub-images and then each one is tested separately usinga fast neural network. The operation of fast neuralnetworks based on applying cross correlation in thefrequency domain between the input image and theweights of the hidden neurons. Compared toconventional and fast neural networks, experimentalresults show that a speed up ratio is achieved whenapplying this technique to locate human facesautomatically in cluttered scenes. Furthermore, fasterface detection is obtained by using parallel processingtechniques to test the resulting sub-images at the sametime using the same number of fast neural networks. Incontrast to using only fast neural networks, the speed upratio is increased with the size of the input image whenusing fast neural networks and image decomposition.
Abstract: Cast metal inlays can be used on molars requiring a
class II restoration instead amalgam and offer a durable alternative.
Because it is known that class II inlays may increase the
susceptibility to fracture, it is important to ensure optimal
performance in selection of the adequate preparation design to reduce
stresses in teeth structures and also in the restorations. The aim of the
study was to investigate the influence of preparation design on stress
distribution in molars with different class II preparations and in cast
metal inlays. The first step of the study was to achieve 3D models in
order to analyze teeth and cast metal class II inlays. The geometry of
the intact tooth was obtained by 3D scanning using a manufactured
device. With a NURBS modeling program the preparations and the
appropriately inlays were designed. 3D models of first upper molars
of the same shape and size were created. Inlay cavities designs were
created using literature data. The geometrical model was exported
and the mesh structure of the solid 3D model was created for
structural simulations. Stresses were located around the occlusal
contact areas. For the studied cases, the stress values were not
significant influenced by the taper of the preparation. it was
demonstrated stresses are higher in the cast metal restorations and
therefore the strength of the teeth is not affected.
Abstract: We have applied new accelerated algorithm for linear
discriminate analysis (LDA) in face recognition with support vector
machine. The new algorithm has the advantage of optimal selection
of the step size. The gradient descent method and new algorithm has
been implemented in software and evaluated on the Yale face
database B. The eigenfaces of these approaches have been used to
training a KNN. Recognition rate with new algorithm is compared
with gradient.
Abstract: The flow field within the combustor of scramjet
engine is very complex and poses a considerable challenge in the
design and development of a supersonic combustor with an optimized
geometry. In this paper comprehensive numerical studies on flow
field characteristics of different cavity based scramjet combustors
with transverse injection of hydrogen have been carried out for both
non-reacting and reacting flows. The numerical studies have been
carried out using a validated 2D unsteady, density based 1st-order
implicit k-omega turbulence model with multi-component finite rate
reacting species. The results show a wide variety of flow features
resulting from the interactions between the injector flows, shock
waves, boundary layers, and cavity flows. We conjectured that an
optimized cavity is a good choice to stabilize the flame in the
hypersonic flow, and it generates a recirculation zone in the scramjet
combustor. We comprehended that the cavity based scramjet
combustors having a bearing on the source of disturbance for the
transverse jet oscillation, fuel/air mixing enhancement, and flameholding
improvement. We concluded that cavity shape with
backward facing step and 45o forward ramp is a good choice to get
higher temperatures at the exit compared to other four models of
scramjet combustors considered in this study.
Abstract: Bubble generation was observed using a high-speed
camera in subcooled flow boiling at low void fraction. Constant heat
flux was applied on one side of an upward rectangular channel to
make heated test channel. Water as a working fluid from high
subcooling to near saturation temperature was injected step by step to
investigate bubble behavior during void development. Experiments
were performed in two different pressures condition close to 2bar and
4bar. It was observed that in high subcooling when boiling was
commenced, bubble after nucleation departed its origin and slid
beside heated surface. In an observation window mean release
frequency of bubble fb,mean, nucleation site Ns and mean bubble
volume Vb,mean in each step of experiments were measured to
investigate wall vaporization rate. It was found that in proximity of
PNVG vaporization rate was increased significantly in compare with
condensation rate which remained in low value.