Abstract: The posteroanterior manipulation technique is usually include in the procedure of the lumbar spine to evaluate the intervertebral motion according to mechanical resistance. The mechanical device with visual feedback was proposed that allows one to analysis the lumbar segments mobility “in vivo" facilitating for the therapist to take its treatment evolution. The measuring system uses load cell and displacement sensor to estimate spine stiffness. In this work, the device was tested by 2 therapists, female, applying posteroanterior force techniques to 5 volunteers, female, with frequency of approximately 1.2-1.8 Hz. A test-retest procedure was used for 2 periods of day. The visual feedback results small variation of forces and cycle time during 6 cycles rhythmic application. The stiffness values showed good agreement between test-retest procedures when used same order of maximum forces.
Abstract: Researchers investigate arious strategies to develop composite beams and maximize the structural advantages. This study
attempted to conduct experiments and analysis of changes in the
neutral axis of positive moments of a Green Beam. Strain
compatibility analysis was used, and its efficiency was demonstrated
by comparing experimental and analytical values. In the comparison of
neutral axis, the difference between experimental and analytical values
was found to range from 8.8~26.2%. It was determined that strain
compatibility analysis can be useful for predicting the behaviors of
composite beams, with the ability to predict the behavior of not only
the elastic location of the composite member, but also of the plastic
location
Abstract: Serial hierarchical support vector machine (SHSVM)
is proposed to discriminate three brain tissues which are white matter
(WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM
has novel classification approach by repeating the hierarchical
classification on data set iteratively. It used Radial Basis Function
(rbf) Kernel with different tuning to obtain accurate results. Also as
the second approach, segmentation performed with DAGSVM
method. In this article eight univariate features from the raw DTI data
are extracted and all the possible 2D feature sets are examined within
the segmentation process. SHSVM succeed to obtain DSI values
higher than 0.95 accuracy for all the three tissues, which are higher
than DAGSVM results.
Abstract: Salient points are frequently used to represent local
properties of the image in content-based image retrieval. In this paper,
we present a reduction algorithm that extracts the local most salient
points such that they not only give a satisfying representation of an
image, but also make the image retrieval process efficiently. This
algorithm recursively reduces the continuous point set by their
corresponding saliency values under a top-down approach. The
resulting salient points are evaluated with an image retrieval system
using Hausdoff distance. In this experiment, it shows that our method
is robust and the extracted salient points provide better retrieval
performance comparing with other point detectors.
Abstract: The projection methods, usually viewed as the methods
for computing eigenvalues, can also be used to estimate pseudospectra.
This paper proposes a kind of projection methods for computing
the pseudospectra of large scale matrices, including orthogonalization
projection method and oblique projection method respectively. This
possibility may be of practical importance in applications involving
large scale highly nonnormal matrices. Numerical algorithms are
given and some numerical experiments illustrate the efficiency of
the new algorithms.
Abstract: Nanocrystals (NC) alloyed composite CdSxSe1-x(x=0
to 1) have been prepared using the chemical solution deposition
technique. The energy band gap of these alloyed nanocrystals of
approximately the same size, have been determined by scanning
tunneling spectroscopy (STS) technique at room temperature. The
values of the energy band gap obtained directly using STS are
compared to those measured by optical spectroscopy. Increasing the
molar fraction ratio x from 0 to 1 causes clearly observed increase in
the band gap of the alloyed composite nanocrystal. Vegard-s law was
applied to calculate the parameters of the effective mass
approximation (EMA) model and the dimension obtained were
compared to the values measured by STM. The good agreement of
the calculated and measured values is a direct result of applying
Vegard's law in the nanocomposites.
Abstract: The importance of happiness understanding research is caused by cardinal changes experiences in system of people values in the post-Soviet countries territory. «The time of changes», which characterized with destruction of old values and not creativeness of new, stimulating experiences by the person of existential vacuum. The given research is actual not only in connection with sense formation, but also in connection with necessity creatively to adapt in integrative space. According to numerous works [1,2,3], we define happiness as the peak experience connected with satisfaction correlated system of needs, dependent on style of subject's coping behavior.
Abstract: The objective of this study is to design an adaptive
neuro-fuzzy inference system (ANFIS) for estimation of surface
roughness in grinding process. The Used data have been generated
from experimental observations when the wheel has been dressed
using a rotary diamond disc dresser. The input parameters of model
are dressing speed ratio, dressing depth and dresser cross-feed rate
and output parameter is surface roughness. In the experimental
procedure the grinding conditions are constant and only the dressing
conditions are varied. The comparison of the predicted values and the
experimental data indicates that the ANFIS model has a better
performance with respect to back-propagation neural network
(BPNN) model which has been presented by the authors in previous
work for estimation of the surface roughness.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: Eukaryotic protein-coding genes are interrupted by spliceosomal introns, which are removed from the RNA transcripts before translation into a protein. The exon-intron structures of different eukaryotic species are quite different from each other, and the evolution of such structures raises many questions. We try to address some of these questions using statistical analysis of whole genomes. We go through all the protein-coding genes in a genome and study correlations between the net length of all the exons in a gene, the number of the exons, and the average length of an exon. We also take average values of these features for each chromosome and study correlations between those averages on the chromosomal level. Our data show universal features of exon-intron structures common to animals, plants, and protists (specifically, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Cryptococcus neoformans, Homo sapiens, Mus musculus, Oryza sativa, and Plasmodium falciparum). We have verified linear correlation between the number of exons in a gene and the length of a protein coded by the gene, while the protein length increases in proportion to the number of exons. On the other hand, the average length of an exon always decreases with the number of exons. Finally, chromosome clustering based on average chromosome properties and parameters of linear regression between the number of exons in a gene and the net length of those exons demonstrates that these average chromosome properties are genome-specific features.
Abstract: In the recent works related with mixture discriminant
analysis (MDA), expectation and maximization (EM) algorithm is
used to estimate parameters of Gaussian mixtures. But, initial values
of EM algorithm affect the final parameters- estimates. Also, when
EM algorithm is applied two times, for the same data set, it can be
give different results for the estimate of parameters and this affect the
classification accuracy of MDA. Forthcoming this problem, we use
Self Organizing Mixture Network (SOMN) algorithm to estimate
parameters of Gaussians mixtures in MDA that SOMN is more robust
when random the initial values of the parameters are used [5]. We
show effectiveness of this method on popular simulated waveform
datasets and real glass data set.
Abstract: Prior to the use of detectors, characteristics
comparison study was performed and baseline established. In patient
specific QA, the portal dosimetry mean values of area gamma,
average gamma and maximum gamma were 1.02, 0.31 and 1.31 with
standard deviation of 0.33, 0.03 and 0.14 for IMRT and the
corresponding values were 1.58, 0.48 and 1.73 with standard
deviation of 0.31, 0.06 and 0.66 for VMAT. With ImatriXX 2-D
array system, on an average 99.35% of the pixels passed the criteria
of 3%-3 mm gamma with standard deviation of 0.24 for dynamic
IMRT. For VMAT, the average value was 98.16% with a standard
deviation of 0.86. The results showed that both the systems can be
used in patient specific QA measurements for IMRT and VMAT.
The values obtained with the portal dosimetry system were found to
be relatively more consistent compared to those obtained with
ImatriXX 2-D array system.
Abstract: This study comprehensively simulate the use of k-ε
model for predicting flow and heat transfer with measured flow field
data in a stationary duct with elucidates on the detailed physics
encountered in the fully developed flow region, and the sharp 180°
bend region. Among the major flow features predicted with accuracy
are flow transition at the entrance of the duct, the distribution of
mean and turbulent quantities in the developing, fully developed, and
sharp 180° bend, the development of secondary flows in the duct
cross-section and the sharp 180° bend, and heat transfer
augmentation. Turbulence intensities in the sharp 180° bend are
found to reach high values and local heat transfer comparisons show
that the heat transfer augmentation shifts towards the wall and along
the duct. Therefore, understanding of the unsteady heat transfer in
sharp 180° bends is important. The design and simulation are related
to concept of fluid mechanics, heat transfer and thermodynamics.
Simulation study has been conducted on the response of turbulent
flow in a rectangular duct in order to evaluate the heat transfer rate
along the small scale multiple rectangular duct
Abstract: In this paper we introduce an efficient solution
method for the Eigen-decomposition of bisymmetric and per
symmetric matrices of symmetric structures. Here we decompose
adjacency and Laplacian matrices of symmetric structures to submatrices
with low dimension for fast and easy calculation of
eigenvalues and eigenvectors. Examples are included to show the
efficiency of the method.
Abstract: Lake Nasser is one of the largest reservoirs in the
world. Over 120 million metric tons of sediments are deposited in its
dead storage zone every year. The main objective of the present work
was to determine the physical and chemical characteristics of Lake
Nasser sediments. The sample had a relatively low surface area of 2.9
m2/g which increased more than 3-fold upon chemical activation. The
main chemical elements of the raw sediments were C, O and Si with
some traces of Al, Fe and Ca. The organic functional groups for the
tested sample included O-H, C=C, C-H and C-O, with indications of
Si-O and other metal-C and/or metal-O bonds normally associated
with clayey materials. Potentiometric titration of the sample in
different ionic strength backgrounds revealed an alkaline material with
very strong positive surface charge at pH values just a little less than
the pH of zero charge which is ~9. Surface interactions of the
sediments with the background electrolyte were significant. An
advanced surface complexation model was able to capture these
effects, employing a single-site approach to represent protolysis
reactions in aqueous solution, and to determine the significant surface
species in the pH range of environmental interest.
Abstract: Face detection and recognition has many applications
in a variety of fields such as security system, videoconferencing and
identification. Face classification is currently implemented in
software. A hardware implementation allows real-time processing,
but has higher cost and time to-market.
The objective of this work is to implement a classifier based on
neural networks MLP (Multi-layer Perceptron) for face detection.
The MLP is used to classify face and non-face patterns. The systm is
described using C language on a P4 (2.4 Ghz) to extract weight
values. Then a Hardware implementation is achieved using VHDL
based Methodology. We target Xilinx FPGA as the implementation
support.
Abstract: Restarted GMRES methods augmented with approximate eigenvectors are widely used for solving large sparse linear systems. Recently a new scheme of augmenting with error approximations is proposed. The main aim of this paper is to develop a restarted GMRES method augmented with the combination of harmonic Ritz vectors and error approximations. We demonstrate that the resulted combination method can gain the advantages of two approaches: (i) effectively deflate the small eigenvalues in magnitude that may hamper the convergence of the method and (ii) partially recover the global optimality lost due to restarting. The effectiveness and efficiency of the new method are demonstrated through various numerical examples.
Abstract: This analysis investigates the distortion of flow
measurement and the increase of cavitation along orifice
flowmeter. The analysis using the numerical method (CFD)
validated the distortion of flow measurement through the inlet
velocity profile considering the convergence and grid
dependency. Realizable k-e model was selected and y+ was
about 50 in this numerical analysis. This analysis also estimated
the vulnerability of cavitation effect due to inlet velocity profile.
The investigation concludes that inclined inlet velocity profile
could vary the pressure which was measured at pressure tab
near pipe wall and it led to distort the pressure values ranged
from -3.8% to 5.3% near the orifice plate and to make the
increase of cavitation. The investigation recommends that the
fully developed inlet velocity flow is beneficial to accurate flow
measurement in orifice flowmeter.
Abstract: Carbon nanotubes (CNTs) possess unique structural,
mechanical, thermal and electronic properties, and have been
proposed to be used for applications in many fields. However, to
reach the full potential of the CNTs, many problems still need to be
solved, including the development of an easy and effective
purification procedure, since synthesized CNTs contain impurities,
such as amorphous carbon, carbon nanoparticles and metal particles.
Different purification methods yield different CNT characteristics
and may be suitable for the production of different types of CNTs. In
this study, the effect of different purification chemicals on carbon
nanotube quality was investigated. CNTs were firstly synthesized by
chemical vapor deposition (CVD) of acetylene (C2H2) on a
magnesium oxide (MgO) powder impregnated with an iron nitrate
(Fe(NO3)3·9H2O) solution. The synthesis parameters were selected
as: the synthesis temperature of 800°C, the iron content in the
precursor of 5% and the synthesis time of 30 min. The liquid phase
oxidation method was applied for the purification of the synthesized
CNT materials. Three different acid chemicals (HNO3, H2SO4, and
HCl) were used in the removal of the metal catalysts from the
synthesized CNT material to investigate the possible effects of each
acid solution to the purification step. Purification experiments were
carried out at two different temperatures (75 and 120 °C), two
different acid concentrations (3 and 6 M) and for three different time
intervals (6, 8 and 15 h). A 30% H2O2 : 3M HCl (1:1 v%) solution
was also used in the purification step to remove both the metal
catalysts and the amorphous carbon. The purifications using this
solution were performed at the temperature of 75°C for 8 hours.
Purification efficiencies at different conditions were evaluated by
thermogravimetric analysis. Thermal and electrical properties of
CNTs were also determined. It was found that the obtained electrical
conductivity values for the carbon nanotubes were typical for organic
semiconductor materials and thermal stabilities were changed
depending on the purification chemicals.
Abstract: Double-diffusive steady convection in a partially
porous cavity with partially permeable walls and under the combined
buoyancy effects of thermal and mass diffusion was analysed
numerically using finite volume method.
The top wall is well insulated and impermeable while the bottom
surface is partially well insulated and impermeable and partially
submitted to constant temperature T1 and concentration C1. Constant
equal temperature T2 and concentration C2 are imposed along the
vertical surfaces of the enclosure. Mass suction/injection and
injection/suction are respectively considered at the bottom of the
porous centred partition and at one of the vertical walls.
Heat and mass transfer characteristics as streamlines and average
Nusselt numbers and Sherwood numbers were discussed for different
values of buoyancy ratio, Rayleigh number, and injection/suction
coefficient.
It is especially noted that increasing the injection factor
disadvantages the exchanges in the case of the injection while the
transfer is augmented in case of suction. On the other hand, a critical
value of the buoyancy ratio was highlighted for which heat and mass
transfers are minimized.