Abstract: This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.
Abstract: An on chip low drop out voltage regulator that
employs elegant compensation scheme is presented in this paper. The
novelty in this design is that the device parasitic capacitances are
exploited for compensation at different loads. The proposed LDO is
designed to provide a constant voltage of 1.2V and is implemented in
UMC 180 nano meter CMOS technology. The voltage regulator
presented improves stability even at lighter loads and enhances line
and load regulation.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: Using the quantum hydrodynamic (QHD) model for quantum plasma at finite temperature the modulational instability of electron plasma waves is investigated by deriving a nonlinear Schrodinger equation. It was found that the electron degeneracy parameter significantly affects the linear and nonlinear properties of electron plasma waves in quantum plasma.
Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: Collision is considered as a time-depended nonlinear
dynamic phenomenon. The majority of researchers have focused on
deriving the resultant damage of the ship collisions via analytical,
experimental, and finite element methods.In this paper, first, the
force-penetration curve of a head collision on a container ship with
rigid barrier based on Yang and Pedersen-s methods for internal
mechanic section is studied. Next, the obtained results from different
analytical methods are compared with each others. Then, through a
simulation of the container ship collision in Ansys Ls-Dyna, results
from finite element approach are compared with analytical methods
and the source of errors is discussed. Finally, the effects of
parameters such as velocity, and angle of collision on the forcepenetration
curve are investigated.
Abstract: the elastic scattering of protons, deuterons and 3He on 6Li at different incident energies have been analyzed in the framework of the optical model using ECIS88 as well as SPI GENOA codes. The potential parameters were extracted in the phenomenological treatment of measured by us angular distributions and literature data. A good agreement between theoretical and experimental differential cross sections was obtained in whole angular range. Parameters for real part of potential have been also calculated microscopically with singleand double-folding model for the p and d, 3He scattering, respectively, using DFPOT code. For best agreement with experiment the normalization factor N for the potential depth is obtained in the range of 0.7-0.9.
Abstract: This paper proposes a novel multi-format stream grid
architecture for real-time image monitoring system. The system, based
on a three-tier architecture, includes stream receiving unit, stream
processor unit, and presentation unit. It is a distributed computing and
a loose coupling architecture. The benefit is the amount of required
servers can be adjusted depending on the loading of the image
monitoring system. The stream receive unit supports multi capture
source devices and multi-format stream compress encoder. Stream
processor unit includes three modules; they are stream clipping
module, image processing module and image management module.
Presentation unit can display image data on several different platforms.
We verified the proposed grid architecture with an actual test of image
monitoring. We used a fast image matching method with the
adjustable parameters for different monitoring situations. Background
subtraction method is also implemented in the system. Experimental
results showed that the proposed architecture is robust, adaptive, and
powerful in the image monitoring system.
Abstract: Near-infrared (NIR) spectroscopy is a widely used
method for material identification for laboratory and industrial applications.
While standard spectrometers only allow measurements at
one sampling point at a time, NIR Spectral Imaging techniques can
measure, in real-time, both the size and shape of an object as well as
identify the material the object is made of. The online classification
and sorting of recovered paper with NIR Spectral Imaging (SI)
is used with success in the paper recycling industry throughout
Europe. Recently, the globalisation of the recycling material streams
caused that water-based flexographic-printed newspapers mainly from
UK and Italy appear also in central Europe. These flexo-printed
newspapers are not sufficiently de-inkable with the standard de-inking
process originally developed for offset-printed paper. This de-inking
process removes the ink from recovered paper and is the fundamental
processing step to produce high-quality paper from recovered paper.
Thus, the flexo-printed newspapers are a growing problem for the
recycling industry as they reduce the quality of the produced paper
if their amount exceeds a certain limit within the recovered paper
material.
This paper presents the results of a research project for the
development of an automated entry inspection system for recovered
paper that was jointly conducted by CTR AG (Austria) and PTS
Papiertechnische Stiftung (Germany). Within the project an NIR
SI prototype for the identification of flexo-printed newspaper has
been developed. The prototype can identify and sort out flexoprinted
newspapers in real-time and achieves a detection accuracy
for flexo-printed newspaper of over 95%. NIR SI, the technology the
prototype is based on, allows the development of inspection systems
for incoming goods in a paper production facility as well as industrial
sorting systems for recovered paper in the recycling industry in the
near future.
Abstract: Short message integrated distributed monitoring systems (SM-DMS) are growing rapidly in wireless communication applications in various areas, such as electromagnetic field (EMF) management, wastewater monitoring, and air pollution supervision, etc. However, delay in short messages often makes the data embedded in SM-DMS transmit unreliably. Moreover, there are few regulations dealing with this problem in SMS transmission protocols. In this study, based on the analysis of the command and data requirements in the SM-DMS, we developed a processing model for the control center to solve the delay problem in data transmission. Three components of the model: the data transmission protocol, the receiving buffer pool method, and the timer mechanism were described in detail. Discussions on adjusting the threshold parameter in the timer mechanism were presented for the adaptive performance during the runtime of the SM-DMS. This model optimized the data transmission reliability in SM-DMS, and provided a supplement to the data transmission reliability protocols at the application level.
Abstract: To investigate the applicability of the EDR-2 film for
clinical radiation dosimetry, percentage depth-doses, profiles and
distributions in open and dynamically wedged fields were measured
using film and compared with data from a Treatment Planning
system.The validity of the EDR2 film to measure dose in a plane
parallel to the beam was tested by irradiating 10 cm×10 cm and 4
cm×4 cm fields from a Siemens, primus linac with a 6MV beam and
a source-to-surface distance of 100 cm. The film was placed
Horizontally between solid water phantom blocks and marked
with pin holes at a depth of 10 cm from the incident beam surface.
The film measurement results, in absolute dose, were compared with
ion chamber measurements using a Welhoffer scanning water tank
system and Treatment Planning system. Our results indicate a
maximum underestimate of calculated dose of 8 % with Treatment
Planning system.
Abstract: In a pilot plant scale of a fluidized bed reactor, a
reduction reaction of sodium sulfate by natural gas has been
investigated. Natural gas is applied in this study as a reductant. Feed
density, feed mass flow rate, natural gas and air flow rate
(independent parameters)and temperature of bed and CO
concentration in inlet and outlet of reactor (dependent parameters)
were monitored and recorded at steady state. The residence time was
adjusted close to value of traditional reaction [1]. An artificial neural
network (ANN) was established to study dependency of yield and
carbon gradient on operating parameters. Resultant 97% accuracy of
applied ANN is a good prove that natural gas can be used as a
reducing agent. Predicted ANN model for relation between other
sources carbon gradient (accuracy 74%) indicates there is not a
meaningful relation between other sources carbon variation and
reduction process which means carbon in granule does not have
significant effect on the reaction yield.
Abstract: Laboratory experiments have been performed to investigate photocatalytic detoxification by using TiO2 photocatalyst for treating dairy effluent. Various operational parameters such as catalyst concentration, initial concentration, angle of tilt of solar flat plate reactor and flow rate were investigated. Results indicated that the photocatalytic detoxification process can efficiently treat dairy effluent. Experimental runs with dairy wastewater can be used to identify the optimum operational parameters to perform wastewater degradation on large scale for recycling purpose. Also effect of two different types of reactors on degradation process was analyzed.
Abstract: Flow around a flat tube is studied numerically. Reynolds number is defined base on equivalent circular tube and it is varied in range of 100 to 300. Equations are solved by using finite volume method and results are presented in form of drag and lift coefficient. Results show that drag coefficient of flat tube is up to 66% lower than circular tube with equivalent diameter. In addition, by increasing l/D from 1 to 2, the drag coefficient of flat tube is decreased about 14-27%.
Abstract: To improve the efficiency of parametric studies or
tests planning the method is proposed, that takes into account all input parameters, but only a few simulation runs are performed to
assess the relative importance of each input parameter. For K input
parameters with N input values the total number of possible combinations of input values equals NK. To limit the number of runs,
only some (totally N) of possible combinations are taken into account. The sampling procedure Updated Latin Hypercube
Sampling is used to choose the optimal combinations. To measure the
relative importance of each input parameter, the Spearman rank
correlation coefficient is proposed. The sensitivity and the influence
of all parameters are analyzed within one procedure and the key
parameters with the largest influence are immediately identified.
Abstract: An approach of design of stable of control systems with ultimately wide ranges of uncertainly disturbed parameters is offered. The method relies on using of nonlinear structurally stable functions from catastrophe theory as controllers. Theoretical part presents an analysis of designed nonlinear second-order control systems. As more important the integrators in series, canonical controllable form and Jordan forms are considered. The analysis resumes that due to added controllers systems become stable and insensitive to any disturbance of parameters. Experimental part presents MATLAB simulation of design of control systems of epidemic spread, aircrafts angular motion and submarine depth. The results of simulation confirm the efficiency of offered method of design. KeywordsCatastrophes, robust control, simulation, uncertain parameters.
Abstract: A numerical simulation of vortex-induced vibration of
a 2-dimensional elastic circular cylinder with two degree of freedom
under the uniform flow is calculated when Reynolds is 200.
2-dimensional incompressible Navier-Stokes equations are solved
with the space-time finite element method, the equation of the cylinder
motion is solved with the new explicit integral method and the mesh
renew is achieved by the spring moving mesh technology. Considering
vortex-induced vibration with the low reduced damping parameter, the
variety trends of the lift coefficient, the drag coefficient, the
displacement of cylinder are analyzed under different oscillating
frequencies of cylinder. The phenomena of locked-in, beat and
phases-witch were captured successfully. The evolution of vortex
shedding from the cylinder with time is discussed. There are very
similar trends in characteristics between the results of the one degree
of freedom cylinder model and that of the two degree of freedom
cylinder model. The streamwise vibrations have a certain effect on the
lateral vibrations and their characteristics.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: The efficient use of available licensed spectrum is
becoming more and more critical with increasing demand and usage
of the radio spectrum. This paper shows how the use of spectrum as
well as dynamic spectrum management can be effectively managed
and spectrum allocation schemes in the wireless communication
systems be implemented and used, in future. This paper would be an
attempt towards better utilization of the spectrum. This research will
focus on the decision-making process mainly, with an
assumption that the radio environment has already been sensed and
the QoS requirements for the application have been specified either
by the sensed radio environment or by the secondary user itself. We
identify and study the characteristic parameters of Cognitive Radio
and use Genetic Algorithm for spectrum allocation. Performance
evaluation is done using MATLAB toolboxes.
Abstract: The hydrologic time series data display periodic
structure and periodic autoregressive process receives considerable
attention in modeling of such series. In this communication long
term record of monthly waste flow of Lyari river is utilized to
quantify by using PAR modeling technique. The parameters of
model are estimated by using Frances & Paap methodology. This
study shows that periodic autoregressive model of order 2 is the most
parsimonious model for assessing periodicity in waste flow of the
river. A careful statistical analysis of residuals of PAR (2) model is
used for establishing goodness of fit. The forecast by using proposed
model confirms significance and effectiveness of the model.