Abstract: This paper proposes a bi-objective model for the
facility location problem under a congestion system. The idea of the
model is motivated by applications of locating servers in bank
automated teller machines (ATMS), communication networks, and so
on. This model can be specifically considered for situations in which
fixed service facilities are congested by stochastic demand within
queueing framework. We formulate this model with two perspectives
simultaneously: (i) customers and (ii) service provider. The
objectives of the model are to minimize (i) the total expected
travelling and waiting time and (ii) the average facility idle-time.
This model represents a mixed-integer nonlinear programming
problem which belongs to the class of NP-hard problems. In addition,
to solve the model, two metaheuristic algorithms including nondominated
sorting genetic algorithms (NSGA-II) and non-dominated
ranking genetic algorithms (NRGA) are proposed. Besides, to
evaluate the performance of the two algorithms some numerical
examples are produced and analyzed with some metrics to determine
which algorithm works better.
Abstract: Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.
Abstract: In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Abstract: Music Information Retrieval (MIR) and modern data mining techniques are applied to identify style markers in midi music for stylometric analysis and author attribution. Over 100 attributes are extracted from a library of 2830 songs then mined using supervised learning data mining techniques. Two attributes are identified that provide high informational gain. These attributes are then used as style markers to predict authorship. Using these style markers the authors are able to correctly distinguish songs written by the Beatles from those that were not with a precision and accuracy of over 98 per cent. The identification of these style markers as well as the architecture for this research provides a foundation for future research in musical stylometry.
Abstract: The conventional GA combined with a local search
algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA)
for the traveling salesman problem (TSP). However, the geometric
properties which are problem specific knowledge can be used to
improve the search process of the HGA. Some tour segments (edges)
of TSPs are fine while some maybe too long to appear in a short tour.
This knowledge could constrain GAs to work out with fine tour
segments without considering long tour segments as often.
Consequently, a new algorithm is proposed, called intelligent-OPT
hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT
algorithm in order to reduce the search time for the optimal solution.
Based on the geometric properties, all the tour segments are assigned
2-level priorities to distinguish between good and bad genes. A
simulation study was conducted to evaluate the performance of the
IOHGA. The experimental results indicate that in general the IOHGA
could obtain near-optimal solutions with less time and better accuracy
than the hybrid genetic algorithm with simulated annealing algorithm
(HGA(SA)).
Abstract: Fossil fuels are the major source to meet the world
energy requirements but its rapidly diminishing rate and adverse
effects on our ecological system are of major concern. Renewable
energy utilization is the need of time to meet the future challenges.
Ocean energy is the one of these promising energy resources. Threefourths
of the earth-s surface is covered by the oceans. This enormous
energy resource is contained in the oceans- waters, the air above the
oceans, and the land beneath them. The renewable energy source of
ocean mainly is contained in waves, ocean current and offshore solar
energy. Very fewer efforts have been made to harness this reliable
and predictable resource. Harnessing of ocean energy needs detail
knowledge of underlying mathematical governing equation and their
analysis. With the advent of extra ordinary computational resources
it is now possible to predict the wave climatology in lab simulation.
Several techniques have been developed mostly stem from numerical
analysis of Navier Stokes equations. This paper presents a brief over
view of such mathematical model and tools to understand and
analyze the wave climatology. Models of 1st, 2nd and 3rd generations
have been developed to estimate the wave characteristics to assess the
power potential. A brief overview of available wave energy
technologies is also given. A novel concept of on-shore wave energy
extraction method is also presented at the end. The concept is based
upon total energy conservation, where energy of wave is transferred
to the flexible converter to increase its kinetic energy. Squeezing
action by the external pressure on the converter body results in
increase velocities at discharge section. High velocity head then can
be used for energy storage or for direct utility of power generation.
This converter utilizes the both potential and kinetic energy of the
waves and designed for on-shore or near-shore application. Increased
wave height at the shore due to shoaling effects increases the
potential energy of the waves which is converted to renewable
energy. This approach will result in economic wave energy
converter due to near shore installation and more dense waves due to
shoaling. Method will be more efficient because of tapping both
potential and kinetic energy of the waves.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: Electronic voting (E-voting) using an internet has been
recently performed in some nations and regions. There is no spatial
restriction which a voter directly has to visit the polling place, but an
e-voting using an internet has to go together the computer in which the
internet connection is possible. Also, this voting requires an access
code for the e-voting through the beforehand report of a voter. To
minimize these disadvantages, we propose a method in which a voter,
who has the wireless certificate issued in advance, uses its own cellular
phone for an e-voting without the special registration for a vote. Our
proposal allows a voter to cast his vote in a simple and convenient way
without the limit of time and location, thereby increasing the voting
rate, and also ensuring confidentiality and anonymity.
Abstract: This paper deals with the design of a moving sliding
surface in a variable structure plant for a second order system. The
chattering phenomena is also dealt with during the switching process
for an unstable sliding surface condition. The simulation examples
considered in this paper shows the effectiveness of the sliding mode
control method used for the design of the moving sliding surfaces. A
simulink model of the continuous system was also developed in
MATLAB-SIMULINK for the design and hence demonstrated. The
phase portraits and the state plots shows the demonstration of
the powerful control technique which can be applied for second
order systems.
Abstract: Three dimensional nanostructure materials have attracted the attention of many researches because the possibility to apply them for near future devices in sensors, catalysis and energy related. Tin dioxide is the most used material for gas sensing because its three-dimensional nanostructures and properties are related to the large surface exposed to gas adsorption. We propose the use of branch SnO2 nanowhiskers in interaction with ethanol. All Sn atoms are symmetric. The total energy, potential energy and Kinetic energy calculated for interaction between SnO2 and ethanol in different distances and temperatures. The calculations achieved by methods of Langevin Dynamic and Mont Carlo simulation. The total energy increased with addition ethanol molecules and temperature so interactions between them are endothermic.
Abstract: Modularized design approach can facilitate the
modeling of complex systems and support behavior analysis and
simulation in an iterative and thus complex engineering process, by
using encapsulated submodels of components and of their interfaces.
Therefore it can improve the design efficiency and simplify the
solving complicated problem. Multi-drivers off-road vehicle is
comparatively complicated. Driving-line is an important core part to a
vehicle; it has a significant contribution to the performance of a
vehicle. Multi-driver off-road vehicles have complex driving-line, so
its performance is heavily dependent on the driving-line. A typical
off-road vehicle-s driving-line system consists of torque converter,
transmission, transfer case and driving-axles, which transfer the
power, generated by the engine and distribute it effectively to the
driving wheels according to the road condition. According to its main
function, this paper puts forward a modularized approach for
designing and evaluation of vehicle-s driving-line. It can be used to
effectively estimate the performance of driving-line during concept
design stage. Through appropriate analysis and assessment method, an
optimal design can be reached. This method has been applied to the
practical vehicle design, it can improve the design efficiency and is
convenient to assess and validate the performance of a vehicle,
especially of multi-drivers off-road vehicle.
Abstract: Chloride induced corrosion of steel reinforcement is
the main cause of deterioration of reinforced concrete marine
structures. This paper investigates the relative performance of
alternative repair options with respect to the deterioration of
reinforced concrete bridge elements in marine environments. Focus is
placed on the initiation phase of reinforcement corrosion. A
laboratory study is described which involved exposing concrete
samples to accelerated chloride-ion ingress. The study examined the
relative efficiencies of two repair methods, namely Ordinary Portland
Cement (OPC) concrete and a concrete which utilised Ground
Granulated Blastfurnace Cement (GGBS) as a partial cement
replacement. The mix designs and materials utilised were identical to
those implemented in the repair of a marine bridge on the South East
coast of Ireland in 2007. The results of this testing regime serve to
inform input variables employed in probabilistic modelling of
deterioration for subsequent reliability based analysis to compare the
relative performance of the studied repair options.
Abstract: A new technique of topological multi-scale analysis is
introduced. By performing a clustering recursively to build a
hierarchy, and analyzing the co-scale and intra-scale similarities, an
Iterated Function System can be extracted from any data set. The study
of fractals shows that this method is efficient to extract
self-similarities, and can find elegant solutions the inverse problem of
building fractals. The theoretical aspects and practical
implementations are discussed, together with examples of analyses of
simple fractals.
Abstract: The purpose of this research was to analyze and compare the instability of a contact surface between Copper and Nickel an alloy cathode in vacuum, the different ratio of Copper and Copper were conducted at 1%, 2% and 4% by using the cathode spot model. The transient recovery voltage is predicted. The cathode spot region is recognized as the collisionless space charge sheath connected with singly ionized collisional plasma. It was found that the transient voltage is decreased with increasing the percentage of an amount of Nickel in cathode materials.
Abstract: The aim of this paper is to investigate the
performance of the developed two point block method designed for
two processors for solving directly non stiff large systems of higher
order ordinary differential equations (ODEs). The method calculates
the numerical solution at two points simultaneously and produces
two new equally spaced solution values within a block and it is
possible to assign the computational tasks at each time step to a
single processor. The algorithm of the method was developed in C
language and the parallel computation was done on a parallel shared
memory environment. Numerical results are given to compare the
efficiency of the developed method to the sequential timing. For
large problems, the parallel implementation produced 1.95 speed-up
and 98% efficiency for the two processors.
Abstract: Minimum Quantity Lubrication (MQL) technique
obtained a significant attention in machining processes to reduce
environmental loads caused by usage of conventional cutting fluids.
Recently nanofluids are finding an extensive application in the field
of mechanical engineering because of their superior lubrication and
heat dissipation characteristics. This paper investigates the use of a
nanofluid under MQL mode to improve grinding characteristics of
Ti-6Al-4V alloy. Taguchi-s experimental design technique has been
used in the present investigation and a second order model has been
established to predict grinding forces and surface roughness.
Different concentrations of water based Al2O3 nanofluids were
applied in the grinding operation through MQL setup developed in
house and the results have been compared with those of conventional
coolant and pure water. Experimental results showed that grinding
forces reduced significantly when nano cutting fluid was used even at
low concentration of the nano particles and surface finish has been
found to improve with higher concentration of the nano particles.
Abstract: This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.
Abstract: One of the biggest drawbacks of the wireless
environment is the limited bandwidth. However, the users sharing
this limited bandwidth have been increasing considerably. SDMA
technique which entails using directional antennas allows to increase
the capacity of a wireless network by separating users in the medium.
In this paper, it has been presented how the capacity can be enhanced
while the mean delay is reduced by using directional antennas in
wireless networks employing TDMA/FDD MAC. Computer
modeling and simulation of the wireless system studied are realized
using OPNET Modeler. Preliminary simulation results are presented
and the performance of the model using directional antennas is
evaluated and compared consistently with the one using
omnidirectional antennas.
Abstract: Intercropping is one of the sustainable agricultural
factors. The SPAD meter can be used to predict nitrogen index
reliably, it may also be a useful tool for assessing the relative impact
of weeds on crops. In order to study the effect of weeds on SPAD in
corn (Zea mays L.), sweet basil (Ocimum basilicum L.) and borage
(Borago officinalis L.) in intercropping system, a factorial experiment
was conducted in three replications in 2011. Experimental factors
were included intercropping of corn with sweet basil and borage in
different ratios (100:0, 75:25, 50:50, 25:75 and 0:100 corn: borage or
sweet basil) and weed infestation (weed control and weed
interference). The results showed that intercropping of corn with
sweet basil and borage increased the SPAD value of corn compare to
monoculture in weed interference condition. Sweet basil SPAD value
in weed control treatments (43.66) was more than weed interference
treatments (40.17). Corn could increase the borage SPAD value
compare to monoculture in weed interference treatments.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.