Abstract: In this paper we introduce an ultra low power CMOS
LC oscillator and analyze a method to design a low power low phase
noise complementary CMOS LC oscillator. A 1.8GHz oscillator is
designed based on this analysis. The circuit has power supply equal
to 1.1 V and dissipates 0.17 mW power. The oscillator is also
optimized for low phase noise behavior. The oscillator phase noise is
-126.2 dBc/Hz and -144.4 dBc/Hz at 1 MHz and 8 MHz offset
respectively.
Abstract: In this article, the flow behavior around a NACA 0012 airfoil which is oscillating with different Reynolds numbers and in various amplitudes has been investigated numerically. Numerical simulations have been performed with ANSYS software. First, the 2- D geometry has been studied in different Reynolds numbers and angles of attack with various numerical methods in its static condition. This analysis was to choose the best turbulent model and comparing the grids to have the optimum one for dynamic simulations. Because the analysis was to study the blades of wind turbines, the Reynolds numbers were not arbitrary. They were in the range of 9.71e5 to 22.65e5. The angle of attack was in the range of -41.81° to 41.81°. By choosing the forward wind speed as the independent parameter, the others like Reynolds and the amplitude of the oscillation would be known automatically. The results show that the SST turbulent model is the best choice that leads the least numerical error with respect the experimental ones. Also, a dynamic stall phenomenon is more probable at lower wind speeds in which the lift force is less.
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 study demonstrates the feasibility of joining the commercial pure copper plates by friction stir welding (FSW). Microstructure, microhardness and tensile properties in terms of the joint efficiency were found 94.03 % compare to as receive base material (BM). The average hardness at the top was higher than bottom. Hardness of weld zone was higher than the base material. Different microstructure zones were revealed by optical microscopy and scanning electron microscopy. The stirred zone (SZ) exhibited primary two phases namely, recrystallized grains and fine precipitates in matrix of copper.
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: The state and stability of hemoglobin adsorbed on the
glass surface was investigated using slab optical waveguide (SOWG)
spectroscopy. The peak position of the absorption band of hemoglobin
adsorbed on the glass surface was same as that of the hemoglobin in
solution. This result suggests that no significant denaturation occurred
by adsorption. The adsorption of hemoglobin is relatively strong that
the hemoglobin molecules even remained adsorbed after rinsing the
cell with buffer solution. The peak shift caused by the reduction of
adsorbed hemoglobin was also observed.
Abstract: Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.
Abstract: The study aimed to investigate characteristics of
vegetative tissue for taxonomic purpose and possibly trend of waste
application in industry. Stems and branches of 15 species in Solanum
found in Thailand were prepared for fiber and examined by light
microscopy. Microstructural characteristic data of fiber i.e. fiber
length and width, fiber lumen diameter and fiber cell wall thickness
were recorded. The longest average fiber cell length (>3.9 mm.) were
obtained in S. lycopersicum L. and S. tuberosum L. Fiber cells from
S. lycopersicum also revealed the widest average diameter of whole
cell and its lumen at >45.5 μm and >29 μm respectively. However
fiber cells with thickest wall of > 9.6 μm were belonged to the
ornamental tree species, S. wrightii Benth. The results showed that
the slenderness ratio, Runkel ratio, and flexibility coefficient, with
potentially suitable for feedstock in paper industry fell in 4 exotic
species, i.e. Solanumamericanum L., S. lycopersicum, S.
seaforthianum Andr., and S. tuberosum L
Abstract: Functional near infrared spectroscopy (fNIRS) is a
practical non-invasive optical technique to detect characteristic of
hemoglobin density dynamics response during functional activation of
the cerebral cortex. In this paper, fNIRS measurements were made in
the area of motor cortex from C4 position according to international
10-20 system. Three subjects, aged 23 - 30 years, were participated in
the experiment.
The aim of this paper was to evaluate the effects of different motor
activation tasks of the hemoglobin density dynamics of fNIRS signal.
The chaotic concept based on deterministic dynamics is an important
feature in biological signal analysis. This paper employs the chaotic
properties which is a novel method of nonlinear analysis, to analyze
and to quantify the chaotic property in the time series of the
hemoglobin dynamics of the various motor imagery tasks of fNIRS
signal. Usually, hemoglobin density in the human brain cortex is
found to change slowly in time. An inevitable noise caused by various
factors is to be included in a signal. So, principle component analysis
method (PCA) is utilized to remove high frequency component. The
phase pace is reconstructed and evaluated the Lyapunov spectrum, and
Lyapunov dimensions. From the experimental results, it can be
conclude that the signals measured by fNIRS are chaotic.
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: The ε4 allele of the ε2, ε3 and ε4 protein isoform polymorphism in the gene encoding apolipoprotein E (Apo E) has previously been associated with increased cardiac artery disease (CAD); therefore to investigate the significance of this polymorphism in pathogenesis of CAD in Iranian patients with stenosis and control subjects. To investigate the association between
Apo E polymorphism and coronary artery disease we performed a comparative case control study of the frequency of Apo E
polymorphism in One hundred CAD patients with stenosis who underwent coronary angiography (>50% stenosis) and 100 control subjects (
Abstract: Series of experimental tests were conducted on a
section of a 660 kW wind turbine blade to measure the pressure
distribution of this model oscillating in plunging motion. In order to
minimize the amount of data required to predict aerodynamic loads
of the airfoil, a General Regression Neural Network, GRNN, was
trained using the measured experimental data. The network once
proved to be accurate enough, was used to predict the flow behavior
of the airfoil for the desired conditions.
Results showed that with using a few of the acquired data, the
trained neural network was able to predict accurate results with
minimal errors when compared with the corresponding measured
values. Therefore with employing this trained network the
aerodynamic coefficients of the plunging airfoil, are predicted
accurately at different oscillation frequencies, amplitudes, and angles
of attack; hence reducing the cost of tests while achieving acceptable
accuracy.
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: The paper discusses optimising work on a method of processing ceramic / metal composite coatings for various applications and is based on preliminary work on processing anodes for solid oxide fuel cells (SOFCs). The composite coating is manufactured by the electroless co-deposition of nickel and yttria stabilised zirconia (YSZ) simultaneously on to a ceramic substrate. The effect on coating characteristics of substrate surface treatments and electroless nickel bath parameters such as pH and agitation methods are also investigated. Characterisation of the resulting deposit by scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDXA) is also discussed.
Abstract: Zirconium diamine and triamine complexes can possess biological activities. These complexes were synthesised via the reaction of equimolar quantities of 1,10-phenanthroline {NC3H3(C6H2)NC3H3} (L1) or 4-4-amino phenazone {ONC6H5(NH)CH(NH2} (L2) or diphenyl carbizon {HNNCO(NH)2(C6H5)} (L3) with a Zirconium Salt {ZrOCl2} in a 1:1 ratio to form complexes [{NC3H3(C6H2)NC3H3}ZrOCl2}] [ZrOCl2L1], [{(O2NC6H4(NH)(NH2)}ZrOCl2] [ZrOCl2L2] and [{HNNCO(NH)2(C6H5)ZrOCl2}] [ZrOCl2L3] respectively. They were characterised using Fourier Transform Infrared (FT-IR) and UV-Visible spectroscopy. Also a variable temperature study of these complexes was completed, using UV-Visible spectroscopy to observe electronic transitions under temperature control. Also a DFT study was done on these complexes via the information from FT-IR and UV-Visible spectroscopy.
These complexes were found to show different inhibition to the growth of bacterial strains of Bacillus spp. & Klebsiella spp. & E. coli & Proteus spp. & Pseudomona spp. at different concentrations (0.001, 0.2 and 1M). For better understanding these complexes were examined by using a Density Functional Theory (DFT) calculation.
Abstract: The model of neural networks on the small-world
topology, with metric (local and random connectivity) is investigated.
The synaptic weights are random, driving the network towards a
chaotic state for the neural activity. An ordered macroscopic neuron
state is induced by a bias in the network connections. When the
connections are mainly local, the network emulates a block-like
structure. It is found that the topology and the bias compete to
influence the network to evolve into a global or a block activity
ordering, according to the initial conditions.
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: In this paper, the periodic surveillance scheme has
been proposed for any convex region using mobile wireless sensor
nodes. A sensor network typically consists of fixed number of
sensor nodes which report the measurements of sensed data such as
temperature, pressure, humidity, etc., of its immediate proximity
(the area within its sensing range). For the purpose of sensing an
area of interest, there are adequate number of fixed sensor
nodes required to cover the entire region of interest. It implies
that the number of fixed sensor nodes required to cover a given
area will depend on the sensing range of the sensor as well as
deployment strategies employed. It is assumed that the sensors to
be mobile within the region of surveillance, can be mounted on
moving bodies like robots or vehicle. Therefore, in our
scheme, the surveillance time period determines the number of
sensor nodes required to be deployed in the region of interest.
The proposed scheme comprises of three algorithms namely:
Hexagonalization, Clustering, and Scheduling, The first algorithm
partitions the coverage area into fixed sized hexagons that
approximate the sensing range (cell) of individual sensor node.
The clustering algorithm groups the cells into clusters, each of
which will be covered by a single sensor node. The later
determines a schedule for each sensor to serve its respective cluster.
Each sensor node traverses all the cells belonging to the cluster
assigned to it by oscillating between the first and the last cell for
the duration of its life time. Simulation results show that our
scheme provides full coverage within a given period of time using
few sensors with minimum movement, less power consumption,
and relatively less infrastructure cost.
Abstract: This paper deals with the effect of a power transformer’s vector group on the basic voltage sag characteristics during unbalanced faults at a meshed or radial power network. Specifically, the propagation of voltage sags through a power transformer is studied with advanced short-circuit analysis. A smart method to incorporate this effect on analytical mathematical expressions is proposed. Based on this methodology, the positive effect of transformers of certain vector groups on the mitigation of the expected number of voltage sags per year (sag frequency) at the terminals of critical industrial customers can be estimated.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.