Abstract: This paper proposes a novel solution for optimizing
the size and communication overhead of a distributed multiagent
system without compromising the performance. The proposed approach
addresses the challenges of scalability especially when the
multiagent system is large. A modified spectral clustering technique
is used to partition a large network into logically related clusters.
Agents are assigned to monitor dedicated clusters rather than monitor
each device or node. The proposed scalable multiagent system is
implemented using JADE (Java Agent Development Environment)
for a large power system. The performance of the proposed topologyindependent
decentralized multiagent system and the scalable multiagent
system is compared by comprehensively simulating different
fault scenarios. The time taken for reconfiguration, the overall computational
complexity, and the communication overhead incurred are
computed. The results of these simulations show that the proposed
scalable multiagent system uses fewer agents efficiently, makes faster
decisions to reconfigure when a fault occurs, and incurs significantly
less communication overhead.
Abstract: In this paper, based on the coupled-mode and carrier rate equations, derivation of a dynamic model and numerically analysis of a MQW chirped DFB-SOA all-optical flip-flop is done precisely. We have analyzed the effects of strains of QW and MQW and cross phase modulation (XPM) on the dynamic response, and rise and fall times of the DFB-SOA all optical flip flop. We have shown that strained MQW active region in under an optimized condition into a DFB-SOA with chirped grating can improve the switching ON speed limitation in such a of the device, significantly while the fall time is increased. The values of the rise times for such an all optical flip-flop, are obtained in an optimized condition, areas tr=255ps.
Abstract: Electrical resistivity is a fundamental parameter of metals or electrical conductors. Since resistivity is a function of temperature, in order to completely understand the behavior of metals, a temperature dependent theoretical model is needed. A model based on physics principles has recently been developed to obtain an equation that relates electrical resistivity to temperature. This equation is dependent upon a parameter associated with the electron travel time before being scattered, and a parameter that relates the energy of the atoms and their separation distance. Analysis of the energy parameter reveals that the equation is optimized if the proportionality term in the equation is not constant but varies over the temperature range. Additional analysis reveals that the theoretical equation can be used to determine the mean free path of conduction electrons, the number of defects in the atomic lattice, and the ‘equivalent’ charge associated with the metallic bonding of the atoms. All of this analysis provides validation for the theoretical model and provides insight into the behavior of metals where performance is affected by temperatures (e.g., integrated circuits and temperature sensors).
Abstract: In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: Permanent magnet synchronous machines are known
as a good candidate for hybrid electric vehicles due to their unique
merits. However they have two major drawbacks i.e. high cost and
small speed range. In this paper an optimal design of a permanent
magnet machine is presented. A reduction of permanent magnet
material for a constant torque and an extension in speed and torque
ranges are chosen as the optimization aims. For this purpose the
analytical model of the permanent magnet synchronous machine is
derived and the appropriate design algorithm is devised. The genetic
algorithm is then employed to optimize some machine specifications.
Finally the finite element method is used to validate the designed
machine.
Abstract: The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.
Abstract: In this work, grinding or microcutting tools in the form of pellets were manufactured using a bounded alumina abrasive grains. The bound used is a vitreous material containing quartz feldspars, kaolinite and a quantity of hematite. The pellets were used in glass grinding process to replace the free abrasive grains lapping process. The study of the elaborated pellets were done to define their effectiveness in the grinding process and to optimize the influence of the pellets elaboration parameters. The obtained results show the existence of an optimal combination of the pellets elaboration parameters for each glass grinding phase (coarse to fine grinding). The final roughness (rms) reached by the elaborated pellets on a BK7 glass surface was about 0.392 μm.
Abstract: This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.
Abstract: The present paper discusses the selection of process
parameters for obtaining optimal nanocrystallites size in the CuOZrO2
catalyst. There are some parameters changing the inorganic
structure which have an influence on the role of hydrolysis and
condensation reaction. A statistical design test method is
implemented in order to optimize the experimental conditions of
CuO-ZrO2 nanoparticles preparation. This method is applied for the
experiments and L16 orthogonal array standard. The crystallites size
is considered as an index. This index will be used for the analysis in
the condition where the parameters vary. The effect of pH, H2O/
precursor molar ratio (R), time and temperature of calcination,
chelating agent and alcohol volume are particularity investigated
among all other parameters. In accordance with the results of
Taguchi, it is found that temperature has the greatest impact on the
particle size. The pH and H2O/ precursor molar ratio have low
influences as compared with temperature. The alcohol volume as
well as the time has almost no effect as compared with all other
parameters. Temperature also has an influence on the morphology
and amorphous structure of zirconia. The optimal conditions are
determined by using Taguchi method. The nanocatalyst is studied by
DTA-TG, XRD, EDS, SEM and TEM. The results of this research
indicate that it is possible to vary the structure, morphology and
properties of the sol-gel by controlling the above-mentioned
parameters.
Abstract: Enzymatic hydrolysis of starch from natural sources
finds potential application in commercial production of alcoholic
beverage and bioethanol. In this study the effect of starch
concentration, temperature, time and enzyme concentration were
studied and optimized for hydrolysis of cassava (Manihot esculenta)
starch powder (of mesh 80/120) into glucose syrup by immobilized
(using Polyacrylamide gel) a-amylase using central composite
design. The experimental result on enzymatic hydrolysis of cassava
starch was subjected to multiple linear regression analysis using
MINITAB 14 software. Positive linear effect of starch concentration,
enzyme concentration and time was observed on hydrolysis of
cassava starch by a-amylase. The statistical significance of the model
was validated by F-test for analysis of variance (p < 0.01). The
optimum value of starch concentration temperature, time and enzyme
concentration were found to be 4.5% (w/v), 45oC, 150 min, and 1%
(w/v) enzyme. The maximum glucose yield at optimum condition
was 5.17 mg/mL.
Abstract: In large Internet backbones, Service Providers
typically have to explicitly manage the traffic flows in order to
optimize the use of network resources. This process is often referred
to as Traffic Engineering (TE). Common objectives of traffic
engineering include balance traffic distribution across the network
and avoiding congestion hot spots. Raj P H and SVK Raja designed
the Bayesian network approach to identify congestion hors pots in
MPLS. In this approach for every node in the network the
Conditional Probability Distribution (CPD) is specified. Based on
the CPD the congestion hot spots are identified. Then the traffic can
be distributed so that no link in the network is either over utilized or
under utilized. Although the Bayesian network approach has been
implemented in operational networks, it has a number of well known
scaling issues.
This paper proposes a new approach, which we call the Pragati
(means Progress) Node Popularity (PNP) approach to identify the
congestion hot spots with the network topology alone. In the new
Pragati Node Popularity approach, IP routing runs natively over the
physical topology rather than depending on the CPD of each node as
in Bayesian network. We first illustrate our approach with a simple
network, then present a formal analysis of the Pragati Node
Popularity approach. Our PNP approach shows that for any given
network of Bayesian approach, it exactly identifies the same result
with minimum efforts. We further extend the result to a more
generic one: for any network topology and even though the network
is loopy. A theoretical insight of our result is that the optimal routing
is always shortest path routing with respect to some considerations of
hot spots in the networks.
Abstract: In the present study, a procedure was developed to
determine the optimum reaction rate constants in generalized
Arrhenius form and optimized through the Nelder-Mead method. For
this purpose, a comprehensive mathematical model of a fixed bed
reactor for dehydrogenation of heavy paraffins over Pt–Sn/Al2O3
catalyst was developed. Utilizing appropriate kinetic rate expressions
for the main dehydrogenation reaction as well as side reactions and
catalyst deactivation, a detailed model for the radial flow reactor was
obtained. The reactor model composed of a set of partial differential
equations (PDE), ordinary differential equations (ODE) as well as
algebraic equations all of which were solved numerically to
determine variations in components- concentrations in term of mole
percents as a function of time and reactor radius. It was demonstrated
that most significant variations observed at the entrance of the bed
and the initial olefin production obtained was rather high. The
aforementioned method utilized a direct-search optimization
algorithm along with the numerical solution of the governing
differential equations. The usefulness and validity of the method was
demonstrated by comparing the predicted values of the kinetic
constants using the proposed method with a series of experimental
values reported in the literature for different systems.
Abstract: In this research, we propose a weighted class based
queuing (WCBQ) mechanism to provide class differentiation and to
reduce the load for the IMS (IP Multimedia Subsystem) presence
server (PS). The tasks of admission controller for the PS are
demonstrated. Analysis and simulation models are developed to
quantify the performance of WCBQ scheme. An optimized dropping
time frame has been developed based on which some of the preexisting
messages are dropped from the PS-buffer. Cost functions are
developed and simulation comparison has been performed with FCFS
(First Come First Served) scheme. The results show that the PS
benefits significantly from the proposed queuing and dropping
algorithm (WCBQ) during heavy traffic.
Abstract: With the proliferation of World Wide Web,
development of web-based technologies and the growth in web
content, the structure of a website becomes more complex and web
navigation becomes a critical issue to both web designers and users.
In this paper we define the content and web pages as two important
and influential factors in website navigation and paraphrase the
enhancement in the website navigation as making some useful
changes in the link structure of the website based on the
aforementioned factors. Then we suggest a new method for
proposing the changes using fuzzy approach to optimize the website
architecture. Applying the proposed method to a real case of Iranian
Civil Aviation Organization (CAO) website, we discuss the results of
the novel approach at the final section.
Abstract: This paper proposes an efficient method for the design
of two channel quadrature mirror filter (QMF) bank. To achieve
minimum value of reconstruction error near to perfect reconstruction,
a linear optimization process has been proposed. Prototype low pass
filter has been designed using Kaiser window function. The modified
algorithm has been developed to optimize the reconstruction error
using linear objective function through iteration method. The result
obtained, show that the performance of the proposed algorithm is
better than that of the already exists methods.
Abstract: The mechanism of abiotic stress tolerance is crucial
for plants to survive in harsh condition and the knowledge of this
mechanism can be use to solve the problem of declining productivity
of plants or crops around the world. However in-depth description is
still unclear and it is argued, in particular that there is a relationship
between high salinity tolerance and the ability to tolerate high light
condition. In this study, Dunaliella salina, which can withstand high
salt was used as a model. Chlorophyll fluorometer for nonphotochemical
quenching (NPQ) measurement and high-performance
liquid chromatography for pigment determination was used. The
results show that NPQ value and the amount of pigment were
increased along with the levels of salinity. However, it establish a
clear relationship between high salt and high light but the further
study to optimized the solutions mentioned above is still required.
Abstract: To establish optical communication between any two
satellites, the transmitter satellite must track the beacon of the
receiver satellite and point the information optical beam in its
direction. Optical tracking and pointing systems for free space suffer
during tracking from high-amplitude vibration because of
background radiation from interstellar objects such as the Sun, Moon,
Earth, and stars in the tracking field of view or the mechanical
impact from satellite internal and external sources. The vibrations of
beam pointing increase the bit error rate and jam communication
between the two satellites. One way to overcome this problem is the
use of very small transmitter beam divergence angles of too narrow
divergence angle is that the transmitter beam may sometimes miss
the receiver satellite, due to pointing vibrations. In this paper we
propose the use of genetic algorithm to optimize the BER as function
of transmitter optics aperture.
Abstract: System identification is the process of creating
models of dynamic process from input- output signals. The aim of
system identification can be identified as “ to find a model with
adjustable parameters and then to adjust them so that the predicted
output matches the measured output". This paper presents a method
of modeling and simulating with system identification to achieve the
maximum fitness for transformation function. First by using
optimized KLM equivalent circuit for PVDF piezoelectric transducer
and assuming different inputs including: sinuside, step and sum of
sinusides, get the outputs, then by using system identification
toolbox in MATLAB, we estimate the transformation function from
inputs and outputs resulted in last program. Then compare the fitness
of transformation function resulted from using ARX,OE(Output-
Error) and BJ(Box-Jenkins) models in system identification toolbox
and primary transformation function form KLM equivalent circuit.
Abstract: An enhanced particle swarm optimization algorithm
(PSO) is presented in this work to solve the non-convex OPF
problem that has both discrete and continuous optimization variables.
The objective functions considered are the conventional quadratic
function and the augmented quadratic function. The latter model
presents non-differentiable and non-convex regions that challenge
most gradient-based optimization algorithms. The optimization
variables to be optimized are the generator real power outputs and
voltage magnitudes, discrete transformer tap settings, and discrete
reactive power injections due to capacitor banks. The set of equality
constraints taken into account are the power flow equations while the
inequality ones are the limits of the real and reactive power of the
generators, voltage magnitude at each bus, transformer tap settings,
and capacitor banks reactive power injections. The proposed
algorithm combines PSO with Newton-Raphson algorithm to
minimize the fuel cost function. The IEEE 30-bus system with six
generating units is used to test the proposed algorithm. Several cases
were investigated to test and validate the consistency of detecting
optimal or near optimal solution for each objective. Results are
compared to solutions obtained using sequential quadratic
programming and Genetic Algorithms.