Abstract: In this study, a 3D combustion chamber was simulated
using FLUENT 6.32. Aims to obtain accurate information about the
profile of the combustion in the furnace and also check the effect of
oxygen enrichment on the combustion process. Oxygen enrichment is
an effective way to reduce combustion pollutant. The flow rate of air
to fuel ratio is varied as 1.3, 3.2 and 5.1 and the oxygen enriched
flow rates are 28, 54 and 68 lit/min. Combustion simulations
typically involve the solution of the turbulent flows with heat
transfer, species transport and chemical reactions. It is common to
use the Reynolds-averaged form of the governing equation in
conjunction with a suitable turbulence model. The 3D Reynolds
Averaged Navier Stokes (RANS) equations with standard k-ε
turbulence model are solved together by Fluent 6.3 software. First
order upwind scheme is used to model governing equations and the
SIMPLE algorithm is used as pressure velocity coupling. Species
mass fractions at the wall are assumed to have zero normal
gradients.Results show that minimum mole fraction of CO2 happens
when the flow rate ratio of air to fuel is 5.1. Additionally, in a fixed
oxygen enrichment condition, increasing the air to fuel ratio will
increase the temperature peak. As a result, oxygen-enrichment can
reduce the CO2 emission at this kind of furnace in high air to fuel
rates.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: In this paper, a new algorithm for generating codebook is proposed for vector quantization (VQ) in image coding. The significant features of the training image vectors are extracted by using the proposed Orthogonal Polynomials based transformation. We propose to generate the codebook by partitioning these feature vectors into a binary tree. Each feature vector at a non-terminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. The binary tree codebook is used for encoding and decoding the feature vectors. In the decoding process the feature vectors are subjected to inverse transformation with the help of basis functions of the proposed Orthogonal Polynomials based transformation to get back the approximated input image training vectors. The results of the proposed coding are compared with the VQ using Discrete Cosine Transform (DCT) and Pairwise Nearest Neighbor (PNN) algorithm. The new algorithm results in a considerable reduction in computation time and provides better reconstructed picture quality.
Abstract: Three-dimensional reconstruction of small objects has
been one of the most challenging problems over the last decade.
Computer graphics researchers and photography professionals have
been working on improving 3D reconstruction algorithms to fit the
high demands of various real life applications. Medical sciences,
animation industry, virtual reality, pattern recognition, tourism
industry, and reverse engineering are common fields where 3D
reconstruction of objects plays a vital role. Both lack of accuracy and
high computational cost are the major challenges facing successful
3D reconstruction. Fringe projection has emerged as a promising 3D
reconstruction direction that combines low computational cost to both
high precision and high resolution. It employs digital projection,
structured light systems and phase analysis on fringed pictures.
Research studies have shown that the system has acceptable
performance, and moreover it is insensitive to ambient light.
This paper presents an overview of fringe projection approaches. It
also presents an experimental study and implementation of a simple
fringe projection system. We tested our system using two objects
with different materials and levels of details. Experimental results
have shown that, while our system is simple, it produces acceptable
results.
Abstract: Linear approximation of point spread function (PSF) is a new method for determining subpixel translations between images. The problem with the actual algorithm is the inability of determining translations larger than 1 pixel. In this paper a multiresolution technique is proposed to deal with the problem. Its performance is evaluated by comparison with two other well known registration method. In the proposed technique the images are downsampled in order to have a wider view. Progressively decreasing the downsampling rate up to the initial resolution and using linear approximation technique at each step, the algorithm is able to determine translations of several pixels in subpixel levels.
Abstract: In this paper, the performance of three types of serial
concatenated convolutional codes (SCCC) is compared and analyzed
in additive white Gaussian noise (AWGN) channel. In Type I, only the
parity bits of outer encoder are passed to inner encoder. In Type II and
Type III, both the information bits and the parity bits of outer encoder
are transferred to inner encoder. As results of simulation, Type I shows
the best bit error rate (BER) performance at low signal-to-noise ratio
(SNR). On the other hand, Type III shows the best BER performance
at high SNR in AWGN channel. The simulation results are analyzed
using the distance spectrum.
Abstract: The performance of a sucrose-based H2 production in
a completely stirred tank reactor (CSTR) was modeled by neural
network back-propagation (BP) algorithm. The H2 production was
monitored over a period of 450 days at 35±1 ºC. The proposed model
predicts H2 production rates based on hydraulic retention time
(HRT), recycle ratio, sucrose concentration and degradation, biomass
concentrations, pH, alkalinity, oxidation-reduction potential (ORP),
acids and alcohols concentrations. Artificial neural networks (ANNs)
have an ability to capture non-linear information very efficiently. In
this study, a predictive controller was proposed for management and
operation of large scale H2-fermenting systems. The relevant control
strategies can be activated by this method. BP based ANNs modeling
results was very successful and an excellent match was obtained
between the measured and the predicted rates. The efficient H2
production and system control can be provided by predictive control
method combined with the robust BP based ANN modeling tool.
Abstract: In the present paper, we propose numerical methods for solving the Stein equation AXC - X - D = 0 where the matrix A is large and sparse. Such problems appear in discrete-time control problems, filtering and image restoration. We consider the case where the matrix D is of full rank and the case where D is factored as a product of two matrices. The proposed methods are Krylov subspace methods based on the block Arnoldi algorithm. We give theoretical results and we report some numerical experiments.
Abstract: In this paper a fast motion estimation method for
H.264/AVC named Triplet Search Motion Estimation (TS-ME) is
proposed. Similar to some of the traditional fast motion estimation
methods and their improved proposals which restrict the search points
only to some selected candidates to decrease the computation
complexity, proposed algorithm separate the motion search process to
several steps but with some new features. First, proposed algorithm try
to search the real motion area using proposed triplet patterns instead of
some selected search points to avoid dropping into the local minimum.
Then, in the localized motion area a novel 3-step motion search
algorithm is performed. Proposed search patterns are categorized into
three rings on the basis of the distance from the search center. These
three rings are adaptively selected by referencing the surrounding
motion vectors to early terminate the motion search process. On the
other hand, computation reduction for sub pixel motion search is also
discussed considering the appearance probability of the sub pixel
motion vector. From the simulation results, motion estimation speed
improved by a factor of up to 38 when using proposed algorithm than
that of the reference software of H.264/AVC with ignorable picture
quality loss.
Abstract: The optimal control problem of a linear distributed
parameter system is studied via shifted Legendre polynomials (SLPs)
in this paper. The partial differential equation, representing the
linear distributed parameter system, is decomposed into an n - set
of ordinary differential equations, the optimal control problem is
transformed into a two-point boundary value problem, and the twopoint
boundary value problem is reduced to an initial value problem
by using SLPs. A recursive algorithm for evaluating optimal control
input and output trajectory is developed. The proposed algorithm is
computationally simple. An illustrative example is given to show the
simplicity of the proposed approach.
Abstract: Prior research has not effectively investigated how the
profitability of Chinese branches affect FDIs in China [1, 2], so this
study for the first time incorporates realistic earnings information
to systematically investigate effects of innovation, imitation, and
profit factors of FDI diffusions from Taiwan to China. Our nonlinear
least square (NLS) model, which incorporates earnings factors,
forms a nonlinear ordinary differential equation (ODE) in numerical
simulation programs. The model parameters are obtained through
a genetic algorithms (GA) technique and then optimized with the
collected data for the best accuracy. Particularly, Taiwanese regulatory
FDI restrictions are also considered in our modified model to meet
the realistic conditions. To validate the model-s effectiveness, this
investigation compares the prediction accuracy of modified model
with the conventional diffusion model, which does not take account
of the profitability factors.
The results clearly demonstrate the internal influence to be positive,
as early FDI adopters- consistent praises of FDI attract potential firms
to make the same move. The former erects a behavior model for the
latter to imitate their foreign investment decision. Particularly, the
results of modified diffusion models show that the earnings from
Chinese branches are positively related to the internal influence. In
general, the imitating tendency of potential consumers is substantially
hindered by the losses in the Chinese branches, and these firms would
invest less into China. The FDI inflow extension depends on earnings
of Chinese branches, and companies will adjust their FDI strategies
based on the returns. Since this research has proved that earning is
an influential factor on FDI dynamics, our revised model explicitly
performs superior in prediction ability than conventional diffusion
model.
Abstract: Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller
Abstract: This paper deals with the application for contentbased
image retrieval to extract color feature from natural images
stored in the image database by segmenting the image through
clustering. We employ a class of nonparametric techniques in which
the data points are regarded as samples from an unknown probability
density. Explicit computation of the density is avoided by using the
mean shift procedure, a robust clustering technique, which does not
require prior knowledge of the number of clusters, and does not
constrain the shape of the clusters. A non-parametric technique for
the recovery of significant image features is presented and
segmentation module is developed using the mean shift algorithm to
segment each image. In these algorithms, the only user set parameter
is the resolution of the analysis and either gray level or color images
are accepted as inputs. Extensive experimental results illustrate
excellent performance.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.
Abstract: Distributed Computing Systems are usually considered the most suitable model for practical solutions of many parallel algorithms. In this paper an enhanced distributed system is presented to improve the time complexity of Binary Indexed Trees (BIT). The proposed system uses multi-uniform processors with identical architectures and a specially designed distributed memory system. The analysis of this system has shown that it has reduced the time complexity of the read query to O(Log(Log(N))), and the update query to constant complexity, while the naive solution has a time complexity of O(Log(N)) for both queries. The system was implemented and simulated using VHDL and Verilog Hardware Description Languages, with xilinx ISE 10.1, as the development environment and ModelSim 6.1c, similarly as the simulation tool. The simulation has shown that the overhead resulting by the wiring and communication between the system fragments could be fairly neglected, which makes it applicable to practically reach the maximum speed up offered by the proposed model.
Abstract: Very Large and/or computationally complex optimization problems sometimes require parallel or highperformance computing for achieving a reasonable time for computation. One of the most popular and most complicate problems of this family is “Traveling Salesman Problem". In this paper we have introduced a Branch & Bound based algorithm for the solution of such complicated problems. The main focus of the algorithm is to solve the “symmetric traveling salesman problem". We reviewed some of already available algorithms and felt that there is need of new algorithm which should give optimal solution or near to the optimal solution. On the basis of the use of logarithmic sampling, it was found that the proposed algorithm produced a relatively optimal solution for the problem and results excellent performance as compared with the traditional algorithms of this series.
Abstract: Character segmentation is an important preprocessing
step for text recognition. In degraded documents, existence of
touching characters decreases recognition rate drastically, for any
optical character recognition (OCR) system. In this paper we have
proposed a complete solution for segmenting touching characters in
all the three zones of printed Gurmukhi script. A study of touching
Gurmukhi characters is carried out and these characters have been
divided into various categories after a careful analysis. Structural
properties of the Gurmukhi characters are used for defining the
categories. New algorithms have been proposed to segment the
touching characters in middle zone, upper zone and lower zone.
These algorithms have shown a reasonable improvement in
segmenting the touching characters in degraded printed Gurmukhi
script. The algorithms proposed in this paper are applicable only to
machine printed text. We have also discussed a new and useful
technique to segment the horizontally overlapping lines.
Abstract: Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.
Abstract: Key management represents a major and the most
sensitive part of cryptographic systems. It includes key generation,
key distribution, key storage, and key deletion. It is also considered
the hardest part of cryptography. Designing secure cryptographic
algorithms is hard, and keeping the keys secret is much harder.
Cryptanalysts usually attack both symmetric and public key
cryptosystems through their key management. We introduce a
protocol to exchange cipher keys over insecure communication
channel. This protocol is based on public key cryptosystem,
especially elliptic curve cryptosystem. Meanwhile, it tests the cipher
keys and selects only the good keys and rejects the weak one.
Abstract: A novel low-cost impedance control structure is
proposed for monitoring the contact force between end-effector and
environment without installing an expensive force/torque sensor.
Theoretically, the end-effector contact force can be estimated from the
superposition of each joint control torque. There have a nonlinear
matrix mapping function between each joint motor control input and
end-effector actuating force/torques vector. This new force control
structure can be implemented based on this estimated mapping matrix.
First, the robot end-effector is manipulated to specified positions, then
the force controller is actuated based on the hall sensor current
feedback of each joint motor. The model-free fuzzy sliding mode
control (FSMC) strategy is employed to design the position and force
controllers, respectively. All the hardware circuits and software
control programs are designed on an Altera Nios II embedded
development kit to constitute an embedded system structure for a
retrofitted Mitsubishi 5 DOF robot. Experimental results show that PI
and FSMC force control algorithms can achieve reasonable contact
force monitoring objective based on this hardware control structure.