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: The aim of this paper is to introduce a parametric
distribution model in fatigue life reliability analysis dealing with
variation in material properties. Service loads in terms of responsetime
history signal of Belgian pave were replicated on a multi-axial
spindle coupled road simulator and stress-life method was used to
estimate the fatigue life of automotive stub axle. A PSN curve was
obtained by monotonic tension test and two-parameter Weibull
distribution function was used to acquire the mean life of the
component. A Pearson system was developed to evaluate the fatigue
life reliability by considering stress range intercept and slope of the
PSN curve as random variables. Considering normal distribution of
fatigue strength, it is found that the fatigue life of the stub axle to
have the highest reliability between 10000 – 15000 cycles. Taking
into account the variation of material properties associated with the
size effect, machining and manufacturing conditions, the method
described in this study can be effectively applied in determination of
probability of failure of mass-produced parts.
Abstract: Currently, many types of no-reversible compressed
sound source, represented by MP3 (MPEG Audio Layer-3) are
popular in the world and they are widely used to make the music file
size smaller. The sound data created in this way has less information as
compared to pre-compressed data. The objective of this study is by
analyzing EEG to determine if people can recognize such difference as
differences in sound. A measurement system that can measure and
analyze EEG when a subject listens to music were experimentally
developed. And ten subjects were studied with this system. In this
experiment, a WAVE formatted music data and a MP3 compressed
music data that is made from the WAVE formatted data were
prepared. Each subject was made to hear these music sources at the
same volume. From the results of this experiment, clear differences
were confirmed between two wound sources.
Abstract: Result of the study on knowledge management systems in businesses was shown that the most of these businesses provide internet accessibility for their employees in order to study new knowledge via internet, corporate website, electronic mail, and electronic learning system. These business organizations use information technology application for knowledge management because of convenience, time saving, ease of use, accuracy of information and knowledge usefulness. The result indicated prominent improvements for corporate knowledge management systems as the following; 1) administrations must support corporate knowledge management system 2) the goal of corporate knowledge management must be clear 3) corporate culture should facilitate the exchange and sharing of knowledge within the organization 4) cooperation of personnel of all levels must be obtained 5) information technology infrastructure must be provided 6) they must develop the system regularly and constantly.
Abstract: Simulations play a major role in education not only because they provide realistic models with which students can interact to acquire real world experiences, but also because they constitute safe environments in which students can repeat processes without any risk in order to perceive easier concepts and theories. Virtual reality is widely recognized as a significant technological advance that can facilitate learning process through the development of highly realistic 3D simulations supporting immersive and interactive features. The objective of this paper is to analyze the influence of virtual reality-s use in chemistry instruction as well as to present an integrated web-based learning environment for the simulation of chemical experiments. The proposed application constitutes a cost-effective solution for both schools and universities without appropriate infrastructure and a valuable tool for distance learning and life-long education in chemistry. Its educational objectives are the familiarization of students with the equipment of a real chemical laboratory and the execution of virtual volumetric analysis experiments with the active participation of students.
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: High level and high velocity flood flows are
potentially harmful to bridge piers as evidenced in many toppled
piers, and among them the single-column piers were considered as
the most vulnerable. The flood flow characteristic parameters
including drag coefficient, scouring and vortex shedding are built into
a pier-flood interaction model to investigate structural safety against
flood hazards considering the effects of local scouring, hydrodynamic
forces, and vortex induced resonance vibrations. By extracting the
pier-flood simulation results embedded in a neural networks code,
two cases of pier toppling occurred in typhoon days were reexamined:
(1) a bridge overcome by flash flood near a mountain side;
(2) a bridge washed off in flood across a wide channel near the
estuary. The modeling procedures and simulations are capable of
identifying the probable causes for the tumbled bridge piers during
heavy floods, which include the excessive pier bending moments and
resonance in structural vibrations.
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: A theoretical approach to radiation damage evolution
is developed. Stable temporal behavior taking place in solids under
irradiation are examined as phenomena of self-organization in nonequilibrium
systems.
Experimental effects of temporal self-organization in solids under
irradiation are reviewed. Their essential common properties and
features are highlighted and analyzed.
Dynamical model to describe development of self-oscillation of
density of point defects under stationary irradiation is proposed. The
emphasis is the nonlinear couplings between rate of annealing and
density of defects that determine the kind and parameters of an
arising self-oscillation.
The field of parameters (defect generation rate and environment
temperature) at which self-oscillations develop is found. Bifurcation
curve and self-oscillation period near it is obtained.
Abstract: The paper presents the results of theoretical and
numerical modeling of propagation of shock waves in bubbly liquids
related to nonlinear effects (realistic equation of state, chemical
reactions, two-dimensional effects). On the basis on the Rankine-
Hugoniot equations the problem of determination of parameters of
passing and reflected shock waves in gas-liquid medium for
isothermal, adiabatic and shock compression of the gas component is
solved by using the wide-range equation of state of water in the
analitic form. The phenomenon of shock wave intensification is
investigated in the channel of variable cross section for the
propagation of a shock wave in the liquid filled with bubbles
containing chemically active gases. The results of modeling of the
wave impulse impact on the solid wall covered with bubble layer are
presented.
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: In order to meet environmental norms, Indian fuel
policy aims at producing ultra low sulphur diesel (ULSD) in near
future. A catalyst for meeting such requirements has been developed
and kinetics of this catalytic process is being looked into. In the
present investigations, effect of mass transfer on kinetics of ultra deep
hydrodesulphurization (UDHDS) to produce ULSD has been studied
to determine intrinsic kinetics over a pre-sulphided catalyst.
Experiments have been carried out in a continuous flow micro reactor
operated in the temperature range of 330 to 3600C, whsv of 1 hr-1 at a
pressure of 35 bar, and its parameters estimated. Based on the derived
rate expression and estimated parameters optimum operation range
has been determined for this UDHDS catalyst to obtain ULSD
product.
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: Iran is one of the greatest producers of date in the
world. However due to lack of information about its viscoelastic
properties, much of the production downgraded during harvesting
and postharvesting processes. In this study the effect of temperature
and moisture content of product were investigated on stress
relaxation characteristics. Therefore, the freshly harvested date
(kabkab) at tamar stage were put in controlled environment chamber
to obtain different temperature levels (25, 35, 45, and 55 0C) and
moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture
analyzer TAXT2 (Stable Microsystems, UK) was used to apply
uniaxial compression tests. A chamber capable to control temperature
was designed and fabricated around the plunger of texture analyzer to
control the temperature during the experiment. As a new approach a
CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass
probe to scan and record contact area between date and disk.
Afterwards, pictures were analyzed using image processing toolbox
of Matlab software. Individual date fruit was uniaxially compressed
at speed of 1 mm/s. The constant strain of 30% of thickness of date
was applied to the horizontally oriented fruit. To select a suitable
model for describing stress relaxation of date, experimental data were
fitted with three famous stress relaxation models including the
generalized Maxwell, Nussinovitch, and Pelege. The constant in
mentioned model were determined and correlated with temperature
and moisture content of product using non-linear regression analysis.
It was found that Generalized Maxwell and Nussinovitch models
appropriately describe viscoelastic characteristics of date fruits as
compared to Peleg mode.
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: Lean production (or lean management respectively)
gained popularity in several waves. The last three decades have been
filled with numerous attempts to apply these concepts in companies.
However, this has only been partially successful. The roots of lean
production can be traced back to Toyota-s just-in-time production.
This concept, which according to Womack-s, Jones- and Roos-
research at MIT was employed by Japanese car manufacturers,
became popular under its international names “lean production",
“lean-manufacturing" and was termed “Schlanke Produktion" in
Germany. This contribution shows a review about lean production in
Germany over the last thirty years: development, trial & error and
implementation as well.
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.
Abstract: In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.