Abstract: In this paper we propose a Particle Swarm heuristic
optimized Multi-Antenna (MA) system. Efficient MA systems
detection is performed using a robust stochastic evolutionary
computation algorithm based on movement and intelligence of
swarms. This iterative particle swarm optimized (PSO) detector
significantly reduces the computational complexity of conventional
Maximum Likelihood (ML) detection technique. The simulation
results achieved with this proposed MA-PSO detection algorithm
show near optimal performance when compared with ML-MA
receiver. The performance of proposed detector is convincingly
better for higher order modulation schemes and large number of
antennas where conventional ML detector becomes non-practical.
Abstract: The effect of nano Co3O4 addition on the
superconducting properties of (Bi, Pb)-2223 system was studied. The
samples were prepared by the acetate coprecipitation method. The
Co3O4 with different sizes (10-30 nm and 30-50 nm) from x=0.00 to
0.05 was added to Bi1.6Pb0.4Sr2Ca2Cu3Oy(Co3O4)x. Phase analysis by
XRD method, microstructural examination by SEM and dc electrical
resistivity by four point probe method were done to characterize the
samples. The X-ray diffraction patterns of all the samples indicated
the majority Bi-2223 phase along with minor Bi-2212 and Bi-2201
phases. The volume fraction was estimated from the intensities of Bi-
2223, Bi-2212 and Bi-2201 phase. The sample with x=0.01 wt% of
the added Co3O4 (10-30 nm size) showed the highest volume fraction
of Bi-2223 phase (72%) and the highest superconducting transition
temperature, Tc (~102 K). The non-added sample showed the highest
Tc(~103 K) compared to added samples with nano Co3O4 (30-50 nm
size) added samples. Both the onset critical temperature Tc(onset)
and zero electrical resistivity temperature Tc(R=0) were in the range
of 103-115 ±1K and 91-103 ±1K respectively for samples with added
Co3O4 (10-30 nm and 30-50 nm).
Abstract: In this paper, based on steady-state models of Flexible
AC Transmission System (FACTS) devices, the sizing of static
synchronous series compensator (SSSC) controllers in transmission
network is formed as an optimization problem. The objective of this
problem is to reduce the transmission losses in the network. The
optimization problem is solved using particle swarm optimization
(PSO) technique. The Newton-Raphson load flow algorithm is
modified to consider the insertion of the SSSC devices in the
network. A numerical example, illustrating the effectiveness of the
proposed algorithm, is introduced. In addition, a novel model of a 3-
phase voltage source converter (VSC) that is suitable for series
connected FACTS a controller is introduced. The model is verified
by simulation using Power System Blockset (PSB) and Simulink
software.
Abstract: Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Abstract: Particulate reinforced metal matrix composites
(MMCs) are potential materials for various applications due to their
advantageous of physical and mechanical properties. This paper
presents a study on the performance of stir cast Al2O3 SiC reinforced
metal matrix composite materials. The results indicate that the
composite materials exhibit improved physical and mechanical
properties, such as, low coefficient of thermal expansion, high
ultimate tensile strength, high impact strength, and hardness. It has
been found that with the increase of weight percentage of
reinforcement particles in the aluminium metal matrix, the new
material exhibits lower wear rate against abrasive wearing. Being
extremely lighter than the conventional gray cast iron material, the
Al-Al2O3 and Al-SiC composites could be potential green materials
for applications in the automobile industry, for instance, in making
car disc brake rotors.
Abstract: TiO2 nanoparticles were synthesized by hydrothermal
method at 180°C from TiOSO4 aqueous solution with1m/l
concentration. The obtained products were coated with silica by
means of a seeded polymerization technique for a coating time of
1440 minutes to obtain well defined TiO2@SiO2 core-shell structure.
The uncoated and coated nanoparticles were characterized by using
X-Ray diffraction technique (XRD), Fourier Transform Infrared
Spectroscopy (FT-IR) to study their physico-chemical properties.
Evidence from XRD and FTIR results show that SiO2 is
homogenously coated on the surface of titania particles. FTIR spectra
show that there exists an interaction between TiO2 and SiO2 and
results in the formation of Ti-O-Si chemical bonds at the interface of
TiO2 particles and SiO2 coating layer. The non linear optical limiting
properties of TiO2 and TiO2@SiO2 nanoparticles dispersed in
ethylene glycol were studied at 532nm using 5ns Nd:YAG laser
pulses. Three-photon absorption is responsible for optical limiting
characteristics in these nanoparticles and it is seen that the optical
nonlinearity is enhanced in core-shell structures when compared with
single counterparts. This effective three-photon type absorption at
this wavelength, is of potential application in fabricating optical
limiting devices.
Abstract: The purpose of this study is to investigate the capacity
of natural Turkish zeolite for NH4-N removal from landfill leachate.
The effects of modification and initial concentration on the removal
of NH4-N from leachate were also investigated. The kinetics of
adsorption of NH4-N has been discussed using three kinetic models,
i.e., the pseudo-second order model, the Elovich equation, the
intraparticle diffuion model. Kinetic parameters and correlation
coefficients were determined. Equilibrium isotherms for the
adsorption of NH4-N were analyzed by Langmuir, Freundlich and
Tempkin isotherm models. Langmuir isotherm model was found to
best represent the data for NH4-N.
Abstract: This study describes the methodology for the development of a validated in-vitro in-vivo correlation (IVIVC) for metoprolol tartrate modified release dosage forms with distinctive release rate characteristics. Modified release dosage forms were formulated by microencapsulation of metoprolol tartrate into different amounts of ethylcellulose by non-solvent addition technique. Then in-vitro and in-vivo studies were conducted to develop and validate level A IVIVC for metoprolol tartrate. The values of regression co-efficient (R2-values) for IVIVC of T2 and T3 formulations were not significantly (p
Abstract: This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral-derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.
Abstract: Utilization of waste material in asphalt pavement
would be beneficial in order to find an alternative solution to increase
service life of asphalt pavement and reduce environmental pollution
as well. One of these waste materials is Polyethylene Terephthalate
(PET) which is a type of polyester material and is produced in a large
extent. This research program is investigating the effects of adding
waste PET particles into the asphalt mixture with a maximum size of
2.36 mm. Different percentages of PET were added into the mixture
during dry process. Gap-graded mixture (SMA 14) and PG 80-100
asphalt binder have been used for this study. To evaluate PET
reinforced asphalt mixture different laboratory investigations have
been conducted on specimens. Marshall Stability test was carried
out. Besides, stiffness modulus test and indirect tensile fatigue test
were conducted on specimens at optimum asphalt content. It was
observed that in many cases PET reinforced SMA mixture had better
mechanical properties in comparison with control mixture.
Abstract: The objective of this paper is the introduction to a
unified optimization framework for research and education. The
OPTILIB framework implements different general purpose algorithms
for combinatorial optimization and minimum search on standard continuous
test functions. The preferences of this library are the straightforward
integration of new optimization algorithms and problems
as well as the visualization of the optimization process of different
methods exploring the search space exclusively or for the real time
visualization of different methods in parallel. Further the usage of
several implemented methods is presented on the basis of two use
cases, where the focus is especially on the algorithm visualization.
First it is demonstrated how different methods can be compared
conveniently using OPTILIB on the example of different iterative
improvement schemes for the TRAVELING SALESMAN PROBLEM.
A second study emphasizes how the framework can be used to find
global minima in the continuous domain.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: Inspired by the recent experiments [1]-[3] indicating
unusual doubly magic nucleus 24O which lies just at the neutron
drip-line and encouraged by the success of our relativistic mean-field
(RMF) plus state dependent BCS approach for the description of
the ground state properties of the drip-line nuclei [23]-[27], we have
further employed this approach, across the entire periodic table, to
explore the unusual shell closures in exotic nuclei. In our RMF+BCS
approach the single particle continuum corresponding to the RMF is
replaced by a set of discrete positive energy states for the calculations
of pairing energy. Detailed analysis of the single particle spectrum,
pairing energies and densities of the nuclei predict the unusual proton
shell closures at Z = 6, 14, 16, 34, and unusual neutron shell closures
at N = 6, 14, 16, 34, 40, 70, 112.
Abstract: In this paper, the phase control antenna array synthesis
is presented. The problem is formulated as a constrained optimization
problem that imposes nulls with prescribed level while maintaining
the sidelobe at a prescribed level. For efficient use of the algorithm
memory, compared to the well known Particle Swarm Optimization
(PSO), the Accelerated Particle Swarm Optimization (APSO) is used
to estimate the phase parameters of the synthesized array. The
objective function is formed using a main objective and set of
constraints with penalty factors that measure the violation of each
feasible solution in the search space to each constraint. In this case
the obtained feasible solution is guaranteed to satisfy all the
constraints. Simulation results have shown significant performance
increases and a decreased randomness in the parameter search space
compared to a single objective conventional particle swarm
optimization.
Abstract: This paper investigates vortex shedding processes
occurring at the end of a stack of parallel plates, due to an oscillating
flow induced by an acoustic standing wave within an acoustic
resonator. Here, Particle Image Velocimetry (PIV) is used to quantify
the vortex shedding processes within an acoustic cycle
phase-by-phase, in particular during the “ejection" of the fluid out of
the stack. Standard hot-wire anemometry measurement is also applied
to detect the velocity fluctuations near the end of the stack.
Combination of these two measurement techniques allowed a detailed
analysis of the vortex shedding phenomena. The results obtained show
that, as the Reynolds number varies (by varying the plate thickness
and drive ratio), different flow patterns of vortex shedding are
observed by the PIV measurement. On the other hand, the
time-dependent hot-wire measurements allow obtaining detailed
frequency spectra of the velocity signal, used for calculating
characteristic Strouhal numbers. The impact of the plate thickness and
the Reynolds number on the vortex shedding pattern has been
discussed. Furthermore, a detailed map of the relationship between the
Strouhal number and Reynolds number has been obtained and
discussed.
Abstract: This paper presents a particle swarm optimization
(PSO) based approach for multiple object tracking based on histogram
matching. To start with, gray-level histograms are calculated to
establish a feature model for each of the target object. The difference
between the gray-level histogram corresponding to each particle in the
search space and the target object is used as the fitness value. Multiple
swarms are created depending on the number of the target objects
under tracking. Because of the efficiency and simplicity of the PSO
algorithm for global optimization, target objects can be tracked as
iterations continue. Experimental results confirm that the proposed
PSO algorithm can rapidly converge, allowing real-time tracking of
each target object. When the objects being tracked move outside the
tracking range, global search capability of the PSO resumes to re-trace
the target objects.
Abstract: The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.
Abstract: In this article, using finite element analysis (FEA)
and an X-ray diffractometer (XRD), cold-sprayed titanium particles
on a steel substrate is investigated in term of cooling time and the
development of residual strains. Three cooling-down models of
sprayed particles after deposition stage are simulated and discussed:
the first model (m1) considers conduction effect to the substrate only,
the second model (m2) considers both conduction as well as
convection effect to the environment, and the third model (m3) which
is the same as the second model but with the substrate heated to a
near particle temperature before spraying. Thereafter, residual strains
developed in the third model is compared with the experimental
measurement of residual strains, which involved a Bruker D8
Advance Diffractometer using CuKa radiation (40kV, 40mA)
monochromatised with a graphite sample monochromator. For
deposition conditions of this study, a good correlation was found to
exist between the FEA results and XRD measurements of residual
strains.
Abstract: In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
Abstract: Accumulation of dust from the outdoor environment
on the panels of solar photovoltaic (PV) system is natural. There
were studies that showed that the accumulated dust can reduce the
performance of solar panels, but the results were not clearly
quantified. The objective of this research was to study the effects of
dust accumulation on the performance of solar PV panels.
Experiments were conducted using dust particles on solar panels with
a constant-power light source, to determine the resulting electrical
power generated and efficiency. It was found from the study that the
accumulated dust on the surface of photovoltaic solar panel can
reduce the system-s efficiency by up to 50%.