Abstract: The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.
Abstract: Mobile ad hoc network is a collection of mobile
nodes communicating through wireless channels without any existing
network infrastructure or centralized administration. Because of the
limited transmission range of wireless network interfaces, multiple
"hops" may be needed to exchange data across the network. In order
to facilitate communication within the network, a routing protocol is
used to discover routes between nodes. The primary goal of such an
ad hoc network routing protocol is correct and efficient route
establishment between a pair of nodes so that messages may be
delivered in a timely manner. Route construction should be done
with a minimum of overhead and bandwidth consumption. This paper
examines two routing protocols for mobile ad hoc networks– the
Destination Sequenced Distance Vector (DSDV), the table- driven
protocol and the Ad hoc On- Demand Distance Vector routing
(AODV), an On –Demand protocol and evaluates both protocols
based on packet delivery fraction, normalized routing load, average
delay and throughput while varying number of nodes, speed and
pause time.
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: This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (Kp. Kd, KI, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system
Abstract: The hybridisation of genetic algorithm with heuristics has been shown to be one of an effective way to improve its performance. In this work, genetic algorithm hybridised with four heuristics including a new heuristic called neighbourhood improvement were investigated through the classical travelling salesman problem. The experimental results showed that the proposed heuristic outperformed other heuristics both in terms of quality of the results obtained and the computational time.
Abstract: With increasing number of wireless devices like
laptops, Wi-Fi Web Cams, network extenders, etc., a new kind of
problems appeared, mostly related to poor Wi-Fi throughput or
communication problems. In this paper an investigation on wireless
networks and it-s saturation in Vilnius City and its surrounding is
presented, covering the main problems of wireless saturation and
network load during day. Also an investigation on wireless channel
selection and noise levels were made, showing the impact of
neighbor AP to signal and noise levels and how it changes during the
day.
Abstract: In this paper, the problem of stability criteria of neural networks (NNs) with two-additive time-varying delay compenents is investigated. The relationship between the time-varying delay and its lower and upper bounds is taken into account when estimating the upper bound of the derivative of Lyapunov functional. As a result, some improved delay stability criteria for NNs with two-additive time-varying delay components are proposed. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
Abstract: A magnetohydrodynamic mixed convective flow in a
cavity was studied in this paper. The lower surface of cavity was
heated from below whereas other walls of the cavity were thermally
isolated. The governing two-dimensional flow equations have been
solved by using finite volume code. The effects of magnetic field
were studied on flow and temperature field and heat transfer
performance at a wide range of parameters, Such as Hartmann
(0≤Ha≤100) and Reynolds (1≤Re≤100) numbers. The results showed
that as Hartman number increases the Nusselt number, representing
heat transfer from the cavity decreases.
Abstract: In this paper a comprehensive model of a fossil fueled
power plant (FFPP) is developed in order to evaluate the
performance of a newly designed turbine follower controller.
Considering the drawbacks of previous works, an overall model is
developed to minimize the error between each subsystem model
output and the experimental data obtained at the actual power plant.
The developed model is organized in two main subsystems namely;
Boiler and Turbine. Considering each FFPP subsystem
characteristics, different modeling approaches are developed. For
economizer, evaporator, superheater and reheater, first order models
are determined based on principles of mass and energy conservation.
Simulations verify the accuracy of the developed models. Due to the
nonlinear characteristics of attemperator, a new model, based on a
genetic-fuzzy systems utilizing Pittsburgh approach is developed
showing a promising performance vis-à-vis those derived with other
methods like ANFIS. The optimization constraints are handled
utilizing penalty functions. The effect of increasing the number of
rules and membership functions on the performance of the proposed
model is also studied and evaluated. The turbine model is developed
based on the equation of adiabatic expansion. Parameters of all
evaluated models are tuned by means of evolutionary algorithms.
Based on the developed model a fuzzy PI controller is developed. It
is then successfully implemented in the turbine follower control
strategy of the plant. In this control strategy instead of keeping
control parameters constant, they are adjusted on-line with regard to
the error and the error rate. It is shown that the response of the
system improves significantly. It is also shown that fuel consumption
decreases considerably.
Abstract: Cooperative diversity (CD) has been adopted in many communication systems because it helps in improving performance of the wireless communication systems with the help of the relays that emulate the multiple antenna terminals. This work aims to provide the derivation of the performance analysis expressions of the multiuser diversity (MUD) in the two-hop cooperative multi-relay wireless networks (TCMRNs). Considering the work analysis, we provide analytically the derivation of a closed form expression of the two most commonly used performance metrics namely, the outage probability and the symbol error probability (SEP) for the fixed decode-and-forward (FDF) protocol with MUD.
Abstract: Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.
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: Single crystals of Magnesium alloys such as pure Mg,
Mg-1Zn-0.5Y, Mg-0.1Y, and Mg-0.1Ce alloys were successfully
fabricated in this study by employing the modified Bridgman method.
To determine the exact orientation of crystals, pole figure
measurement using X-ray diffraction were carried out on each single
crystal. Hardness and compression tests were conducted followed by
subsequent recrysatllization annealing. Recrystallization kinetics of
Mg alloy single crystals has been investigated. Fabricated single
crystals were cut into rectangular shaped specimen and solution
treated at 400oC for 24 hrs, and then deformed in compression mode
by 30% reduction. Annealing treatment for recrystallization has been
conducted on these cold-rolled plates at temperatures of 300oC for
various times from 1 to 20 mins. The microstructure observation and
hardness measurement conducted on the recrystallized specimens
revealed that static recrystallization of ternary alloy single crystal was
very slow, while recrystallization behavior of binary alloy single
crystals appeared to be very fast.
Abstract: Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to analog circuit design automation. These researches show a better performance due to the nature of Genetic Algorithm. In this paper a modified Genetic Algorithm is applied for analog circuit design automation. The modifications are made to the topology of the circuit. These modifications will lead to a more computationally efficient algorithm.
Abstract: Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs from magnetic resonance images. Materials and methods: Thirty obese women were scanned on a Siemens Impact Expert 1T resonance machine. 1500 images were finally used in the tests. The developed segmentation method is a recursive and multilevel process that makes use of several concepts such as shaped histograms, adaptative thresholding and connectivity. The segmentation process was implemented in Matlab and operates without the need of any user interaction. The whole set of images were segmented with the developed method. An expert radiologist segmented the same set of images following a manual procedure with the aid of the SliceOmatic software (Tomovision). These constituted our 'goal standard'. Results: The number of coincidental pixels of the automatic and manual segmentation procedures was measured. The average results were above 90 % of success in most of the images. Conclusions: The proposed approach allows effective automatic segmentation of MRIs from thighs, comparable to expert manual performance.
Abstract: The aim of this study was to test whether the Attention
Networks Test (ANT) showed temporal decrements in performance.
Vigilance tasks typically show such decrements, which may reflect
impairments in executive control resulting from cognitive fatigue.
The ANT assesses executive control, as well as alerting and
orienting. Thus, it was hypothesized that ANT executive control
would deteriorate over time. Manipulations including task condition
(trial composition) and masking were included in the experimental
design in an attempt to increase performance decrements. However,
results showed that there is no temporal decrement on the ANT. The
roles of task demands, cognitive fatigue and participant motivation in
producing this result are discussed. The ANT may not be an effective
tool for investigating temporal decrement in attention.
Abstract: Agropyron cristatum L. Gaertn. is a native grass of
semiarid region in Iran which is quit resistant to cool and drought
climate and withstand heavy grazing. This species has close
phylogenetic relationship with Triticum and Hordeum. In this
research, the effect of seven different concentrations of growth
regulator 2,4-D on callus production and somatic embryogenesis of
A. cristatum was investigated on Murashige and Skoog medium. The
results showed that the rate of callus, embryo and neomorph were
highest in 1 mg L-1 2,4-D. Callus production was increased in 1 mg
L-1 2,4-D but dramatically decreased at 5.5 and 9 mg L-1 2,4-D. The
somatic embryos were observed at 1 and 4 mg L-1 2,4-D but matured
embryos and plantlet were only occurred at 1 mg L-1 2,4-D. There
were significant differences between 1 mg L-1 2,4-D and other
treatments for producing globular and torpedo embryos, plantlet,
rooted callus and number of roots (p
Abstract: Adapting wireless devices to communicate within grid
networks empowers us by providing range of possibilities.. These
devices create a mechanism for consumers and publishers to create
modern networks with or without peer device utilization. Emerging
mobile networks creates new challenges in the areas of reliability,
security, and adaptability. In this paper, we propose a system
encompassing mobility management using AAA context transfer for
mobile grid networks. This system ultimately results in seamless task
processing and reduced packet loss, communication delays,
bandwidth, and errors.
Abstract: We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.