Abstract: In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.
Abstract: The paper describes a knowledge based system for
analysis of microscopic wear particles. Wear particles contained in
lubricating oil carry important information concerning machine
condition, in particular the state of wear. Experts (Tribologists) in the
field extract this information to monitor the operation of the machine
and ensure safety, efficiency, quality, productivity, and economy of
operation. This procedure is not always objective and it can also be
expensive. The aim is to classify these particles according to their
morphological attributes of size, shape, edge detail, thickness ratio,
color, and texture, and by using this classification thereby predict
wear failure modes in engines and other machinery. The attribute
knowledge links human expertise to the devised Knowledge Based
Wear Particle Analysis System (KBWPAS). The system provides an
automated and systematic approach to wear particle identification
which is linked directly to wear processes and modes that occur in
machinery. This brings consistency in wear judgment prediction
which leads to standardization and also less dependence on
Tribologists.
Abstract: This paper presents the novel Rao-Blackwellised
particle filter (RBPF) for mobile robot simultaneous localization and
mapping (SLAM) using monocular vision. The particle filter is
combined with unscented Kalman filter (UKF) to extending the path
posterior by sampling new poses that integrate the current observation
which drastically reduces the uncertainty about the robot pose. The
landmark position estimation and update is also implemented through
UKF. Furthermore, the number of resampling steps is determined
adaptively, which seriously reduces the particle depletion problem,
and introducing the evolution strategies (ES) for avoiding particle
impoverishment. The 3D natural point landmarks are structured with
matching Scale Invariant Feature Transform (SIFT) feature pairs. The
matching for multi-dimension SIFT features is implemented with a
KD-Tree in the time cost of O(log2
N). Experiment results on real robot
in our indoor environment show the advantages of our methods over
previous approaches.
Abstract: This paper presents the prediction of air flow,
humidity and temperature patterns in a co-current pilot plant spray
dryer fitted with a pressure nozzle using a three dimensional model.
The modelling was done with a Computational Fluid Dynamic
package (Fluent 6.3), in which the gas phase is modelled as
continuum using the Euler approach and the droplet/ particle phase is
modelled by the Discrete Phase model (Lagrange approach).Good
agreement was obtained with published experimental data where the
CFD simulation correctly predicts a fast downward central flowing
core and slow recirculation zones near the walls. In this work, the
effects of the air flow pattern on droplets trajectories, residence time
distribution of droplets and deposition of the droplets on the wall also
were investigated where atomizing of maltodextrin solution was
used.
Abstract: Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.
Abstract: In this paper, we propose a fast and efficient method for drawing very large-scale graph data. The conventional force-directed method proposed by Fruchterman and Rheingold (FR method) is well-known. It defines repulsive forces between every pair of nodes and attractive forces between connected nodes on a edge and calculates corresponding potential energy. An optimal layout is obtained by iteratively updating node positions to minimize the potential energy. Here, the positions of the nodes are updated every global timestep at the same time. In the proposed method, each node has its own individual time and time step, and nodes are updated at different frequencies depending on the local situation. The proposed method is inspired by the hierarchical individual time step method used for the high accuracy calculations for dense particle fields such as star clusters in astrophysical dynamics. Experiments show that the proposed method outperforms the original FR method in both speed and accuracy. We implement the proposed method on the MDGRAPE-3 PCI-X special purpose parallel computer and realize a speed enhancement of several hundred times.
Abstract: This paper aims to scale up Dye-sensitized Solar Cell
(DSSC) production using a commonly available industrial material –
stainless steel - and industrial plasma equipment. A working DSSC
electrode formed by (1) coating titania nanotube (TiO2 NT) film on
304 stainless steel substrate using a plasma spray technique; then, (2)
filling the nano-pores of the TiO2 NT film using a TiF4 sol-gel method.
A DSSC device consists of an anode absorbed photosensitive dye
(N3), a transparent conductive cathode with platinum (Pt)
nano-catalytic particles adhered to its surface, and an electrolytic
solution sealed between the anode and the transparent conductive
cathode. The photo-current conversion efficiency of the DSSC sample
was tested under an AM 1.5 Solar Simulator. The sample has a short
current (Isc) of 0.83 mA cm-2, open voltage (Voc) of 0.81V, filling
factor (FF) of 0.52, and conversion efficiency (η) of 2.18% on a 0.16
cm2 DSSC work-piece.
Abstract: TiO2/Ag composite films were prepared by
incorporating Ag in the pores of mesoporous TiO2 films using a
photoreduction method. The Ag nanoparticle sizes were in a range of
3.66-38.56 nm. The TiO2/Ag composite films were characterized by
X-ray diffraction (XRD), scanning electron microscopy (SEM) and
transmission electron microscropy (TEM). The TiO2 films and
TiO2/Ag composite films were immersed in a 0.3 mM N719 dye
solution and characterized by UV-Vis spectrophotometer. The
TiO2/Ag/N719 composite film showed that an optimal size of Ag
nanoparticles was 19.12 nm and, hence, gave the maximum optical
absorption spectra. The improved absorption was due to surface
plasmon resonance induced by the Ag nanoparticles to enhance the
absorption coefficient of the dye.
Abstract: This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.
Abstract: This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.
Abstract: Preparation of size controlled nano-particles of silver catalyst on carbon substrate from e-waste has been investigated. Chemical route was developed by extraction of the metals available in nitric acid followed by treatment with hydrofluoric acid. Silver metal particles deposited with an average size 4-10 nm. A stabilizer concentration of 10- 40 g/l was used. The average size of the prepared silver decreased with increase of the anode current density. Size uniformity of the silver nano-particles was improved distinctly at higher current density no more than 20mA... Grain size increased with EK time whereby aggregation of particles was observed after 6 h of reaction.. The chemical method involves adsorption of silver nitrate on the carbon substrate. Adsorbed silver ions were directly reduced to metal particles using hydrazine hydrate. Another alternative method is by treatment with ammonia followed by heating the carbon loaded-silver hydroxide at 980°C. The product was characterized with the help of XRD, XRF, ICP, SEM and TEM techniques.
Abstract: The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: Discretization of spatial derivatives is an important
issue in meshfree methods especially when the derivative terms
contain non-linear coefficients. In this paper, various methods used
for discretization of second-order spatial derivatives are investigated
in the context of Smoothed Particle Hydrodynamics. Three popular
forms (i.e. "double summation", "second-order kernel derivation",
and "difference scheme") are studied using one-dimensional unsteady
heat conduction equation. To assess these schemes, transient response
to a step function initial condition is considered. Due to parabolic
nature of the heat equation, one can expect smooth and monotone
solutions. It is shown, however in this paper, that regardless of
the type of kernel function used and the size of smoothing radius,
the double summation discretization form leads to non-physical
oscillations which persist in the solution. Also, results show that when
a second-order kernel derivative is used, a high-order kernel function
shall be employed in such a way that the distance of inflection
point from origin in the kernel function be less than the nearest
particle distance. Otherwise, solutions may exhibit oscillations near
discontinuities unlike the "difference scheme" which unconditionally
produces monotone results.
Abstract: The hydrothermal behavior of a bed consisting of
magnetic and shale oil particle admixtures under the effect of a
transverse magnetic field is investigated. The phase diagram, bed
void fraction are studied under wide range of the operating
conditions i.e., gas velocity, magnetic field intensity and fraction of
the magnetic particles. It is found that the range of the stabilized
regime is reduced as the magnetic fraction decreases. In addition, the
bed voidage at the onset of fluidization decreases as the magnetic
fraction decreases. On the other hand, Nusselt number and
consequently the heat transfer coefficient is found to increase as the
magnetic fraction decreases. An empirical equation is investigated to
relate the effect of the gas velocity, magnetic field intensity and
fraction of the magnetic particles on the heat transfer behavior in the
bed.
Abstract: Two optimized strategies were successfully established
to develop biomolecule-based magnetic nanoassemblies.
Streptavidin-coated and amine-coated magnetic nanoparticles were
chosen as model scaffolds onto which double-stranded DNA and
human immunoglobulin G were specifically conjugated in succession,
using biotin-streptavidin interaction or covalent cross-linkers. The
success of this study opens the prospect of developing selective and
sensitive nanoparticle-based structures for diagnostics or drug
delivery.
Abstract: The separation efficiency of a hydrocyclone has
extensively been considered on the rigid particle assumption. A
collection of experimental studies have demonstrated their
discrepancies from the modeling and simulation results. These
discrepancies caused by the actual particle elasticity have generally
led to a larger amount of energy consumption in the separation
process. In this paper, the influence of particle elasticity on the
separation efficiency of a hydrocyclone system was investigated
through the Finite Element (FE) simulations using crude oil droplets
as the elastic particles. A Reitema-s design hydrocyclone with a
diameter of 8 mm was employed to investigate the separation
mechanism of the crude oil droplets from water. The cut-size
diameter eter of the crude oil was 10 - Ðçm in order to fit with the
operating range of the adopted hydrocylone model. Typical
parameters influencing the performance of hydrocyclone were varied
with the feed pressure in the range of 0.3 - 0.6 MPa and feed
concentration between 0.05 – 0.1 w%. In the simulation, the Finite
Element scheme was applied to investigate the particle-flow
interaction occurred in the crude oil system during the process. The
interaction of a single oil droplet at the size of 10 - Ðçm to the flow
field was observed. The feed concentration fell in the dilute flow
regime so the particle-particle interaction was ignored in the study.
The results exhibited the higher power requirement for the separation
of the elastic particulate system when compared with the rigid
particulate system.
Abstract: This paper describes Nano-particle based Planar Laser
Scattering (NPLS) flow visualization of angled supersonic jets into a
supersonic cross flow based on the HYpersonic Low TEmperature
(HYLTE) nozzle which was widely used in DF chemical laser. In
order to investigate the non-reacting flowfield in the HYLTE nozzle, a
testing section with windows was designed and manufactured. The
impact of secondary fluids orifice separation on mixing was examined.
For narrow separation of orifices, the secondary fuel penetration
increased obviously compared to diluent injection, which means
smaller separation of diluent and fuel orifices would enhance the
mixing of fuel and oxidant. Secondary injections with angles of 30, 40
and 50 degrees were studied. It was found that the injectant
penetration increased as the injection angle increased, while the
interfacial surface area to entrain the freestream fluid is largest when
the injection angle is 40 degree.
Abstract: The major source of allergy in home is the house dust
mite (Dematophagoides farina, Dermatophagoides pteronyssinus)
causing allergic symptom include atopic dermatitis, asthma, perennial
rhinitis and even infant death syndrome.
Control of this mite species is dependent on the use of chemical
methods such as fumigation treatments with methylene bromide,
spraying with organophosphates such as pirimiphos-methyl, or
treatments with repellents such as DEET and benzyl benzoate.
Although effective, their repeated use for decades has sometimes
resulted in development of resistance and fostered environmental and
human health concerns. Both decomposing animal parts and the
protein that surrounds mite fecal pellets cause mite allergy. So it is
more effective to repel than to kill them because allergen is not living
house dust mite but dead body or fecal particles of house dust mite.
It is important to find out natural repellent material against house
dust mite to control them and reduce the allergic reactions. Plants may
be an alternative source for dust mite control because they contain a
range of bioactive chemicals.
The research objectives of this paper were to verify the acaricidal
and repellent effects of cinnamon essential oil and to find out it-s most
effective concentrations. We could find that cinnamon bark essential
oil was very effective material to control the house dust mite.
Furthermore, it could reduce chemical resistance and danger for
human health.
Abstract: It is well known that metallic particles reduce the
reliability of Gas-Insulated Substation (GIS) equipments by initiating
partial discharge (PDs) that can lead to breakdown and complete
failure of GIS. This paper investigates the characteristics of PDs
caused by metallic particle adhering to the solid spacer. The PD
detection and measurement were carried out by using IEC 60270
method with particles of different sizes and at different positions on
the spacer surface. The results show that a particle of certain size at
certain position possesses a unique PD characteristic as compared to
those caused by particles of different sizes and/or at different
positions. Therefore PD characteristics may be useful for the particle
size and position identification.
Abstract: This study employs the use of the fourth order
Numerov scheme to determine the eigenstates and eigenvalues of
particles, electrons in particular, in single and double delta function
potentials. For the single delta potential, it is found that the
eigenstates could only be attained by using specific potential depths.
The depth of the delta potential well has a value that varies depending
on the delta strength. These depths are used for each well on the
double delta function potential and the eigenvalues are determined.
There are two bound states found in the computation, one with a
symmetric eigenstate and another one which is antisymmetric.