Abstract: Linear induction motors are used in various industries
but they have some specific phenomena which are the causes for
some problems. The most important phenomenon is called end effect.
End effect decreases efficiency, power factor and output force and
unbalances the phase currents. This phenomenon is more important
in medium and high speeds machines. In this paper a factor, EEF , is
obtained by an accurate equivalent circuit model, to determine the
end effect intensity. In this way, all of effective design parameters on
end effect is described. Accuracy of this equivalent circuit model is
evaluated by two dimensional finite-element analysis using ANSYS.
The results show the accuracy of the equivalent circuit model.
Abstract: Logic based methods for learning from structured data
is limited w.r.t. handling large search spaces, preventing large-sized
substructures from being considered by the resulting classifiers. A
novel approach to learning from structured data is introduced that
employs a structure transformation method, called finger printing, for
addressing these limitations. The method, which generates features
corresponding to arbitrarily complex substructures, is implemented in
a system, called DIFFER. The method is demonstrated to perform
comparably to an existing state-of-art method on some benchmark
data sets without requiring restrictions on the search space.
Furthermore, learning from the union of features generated by finger
printing and the previous method outperforms learning from each
individual set of features on all benchmark data sets, demonstrating
the benefit of developing complementary, rather than competing,
methods for structure classification.
Abstract: The distillation process in the general sense is a
relatively simple technique from the standpoints of its principles.
When dedicating distillation to water treatment and specifically
producing fresh water from sea, ocean and/ briny waters it is
interesting to notice that distillation has no limitations or domains of
applicability regarding the nature or the type of the feedstock water.
This is not the case however for other techniques that are
technologically quite complex, necessitate bigger capital investments
and are limited in their usability. In a previous paper we have
explored some of the effects of temperature on yield. In this paper,
we continue building onto that knowledge base and focus on the
effects of several additional engineering and design variables on
productivity.
Abstract: In order to be able to automatically differentiate
between two modes of permanent flow of a liquid simulating blood,
it was imperative to put together a data bank. Thus, the acquisition of
the various amplitude spectra of the Doppler signal of this liquid in
laminar flow and other spectra in turbulent flow enabled us to
establish an automatic difference between the two modes. According
to the number of parameters and their nature, a comparative study
allowed us to choose the best classifier.
Abstract: The use of 3D computer-aided design (CAD) models
to support construction project planning has been increasing in the
previous year. 3D CAD models reveal more planning ideas by
visually showing the construction site environment in different stages
of the construction process. Using 3D CAD models together with
scheduling software to prepare construction plan can identify errors
in process sequence and spatial arrangement, which is vital to the
success of a construction project. A number of 4D (3D plus time)
CAD tools has been developed and utilized in different construction
projects due to the awareness of their importance. Virtual prototyping
extends the idea of 4D CAD by integrating more features for
simulating real construction process. Virtual prototyping originates
from the manufacturing industry where production of products such
as cars and airplanes are virtually simulated in computer before they
are built in the factory. Virtual prototyping integrates 3D CAD,
simulation engine, analysis tools (like structural analysis and
collision detection), and knowledgebase to streamline the whole
product design and production process. In this paper, we present the
application of a virtual prototyping software which has been used in
a few construction projects in Hong Kong to support construction
project planning. Specifically, the paper presents an implementation
of virtual prototyping in a residential building project in Hong Kong.
The applicability, difficulties and benefits of construction virtual
prototyping are examined based on this project.
Abstract: Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.
Abstract: In a metal forming process, the friction between the
material and the tools influences the process by modifying the stress
distribution of the workpiece. This frictional behaviour is often taken
into account by using a constant coefficient of friction in the finite
element simulations of sheet metal forming processes. However,
friction coefficient varies in time and space with many parameters.
The Stribeck friction model is investigated in this study to predict
springback behaviour of AA6061-T4 sheets during V-bending
process. The coefficient of friction in Stribeck curve depends on
sliding velocity and contact pressure. The plane-strain bending
process is simulated in ABAQUS/Standard. We compared the
computed punch load-stroke curves and springback related to the
constant coefficient of friction with the defined friction model. The
results clearly showed that the new friction model provides better
agreement between experiments and results of numerical simulations.
The influence of friction models on stress distribution in the
workpiece is also studied numerically
Abstract: To create a solution for a specific problem in machine
learning, the solution is constructed from the data or by use a search
method. Genetic algorithms are a model of machine learning that can
be used to find nearest optimal solution. While the great advantage of
genetic algorithms is the fact that they find a solution through
evolution, this is also the biggest disadvantage. Evolution is inductive,
in nature life does not evolve towards a good solution but it evolves
away from bad circumstances. This can cause a species to evolve into
an evolutionary dead end. In order to reduce the effect of this
disadvantage we propose a new a learning tool (criteria) which can be
included into the genetic algorithms generations to compare the
previous population and the current population and then decide
whether is effective to continue with the previous population or the
current population, the proposed learning tool is called as Keeping
Efficient Population (KEP). We applied a GA based on KEP to the
production line layout problem, as a result KEP keep the evaluation
direction increases and stops any deviation in the evaluation.
Abstract: Khatunabad area is situated geologically in Urmieh-
Dokhtar magmatic belt in NW of Iran. In this research, studied area
has been investigated in order to recognize the potential copper and
molybdenum-bearing target areas. The survey layers include the
lithologic units, alteration, geochemical result, tectonics and copper
and molybdenum occurrence. As an accurate decision can have a
considerable effect on exploration plans, so in this efforts have been
made to make use of new combination method. For this purpose, the
analytical hierarchy process was used and revealed highly potential
copper and molybdenum mineralization areas. Based on achieved
results, geological perspective in north of studied area is appropriate
for advance stage, especially for subsurface exploration in future.
Abstract: In medical therapy, laser has been widely used to conduct cosmetic, tumor and other treatments. During the process of laser irradiation, there may be thermal damage caused by excessive laser exposure. Thus, the establishment of a complete thermal analysis model is clinically helpful to physicians in reference data. In this study, porcine liver in place of tissue was subjected to laser irradiation to set up the experimental data considering the explored impact on surface thermal field and thermal damage region under different conditions of power, laser irradiation time, and distance between laser and porcine liver. In the experimental process, the surface temperature distribution of the porcine lever was measured by the infrared thermal imager. In the part of simulation, the bio heat transfer Pennes-s equation was solved by software SYSWELD applying in welding process. The double ellipsoid function as a laser source term is firstly considered in the prediction for surface thermal field and internal tissue damage. The simulation results are compared with the experimental data to validate the mathematical model established here in.
Abstract: Address Matching is an important application of
Geographic Information System (GIS). Prior to Address Matching
working, obtaining X,Y coordinates is necessary, which process is
calling Address Geocoding. This study will illustrate the effective
address geocoding process of using household registry database, and
the check system for geocoded address.
Abstract: Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. In this paper, algorithms are introduced to compute all backward and forward static slices of a computer program by traversing the program representation graph once. The program representation graph used in this paper is called Program Dependence Graph (PDG). We have conducted an experimental comparison study using 25 software modules to show the effectiveness of the introduced algorithm for computing all backward static slices over single-point slicing approaches in computing the parallelism and functional cohesion of program modules. The effectiveness of the algorithm is measured in terms of time execution and number of traversed PDG edges. The comparison study results indicate that using the introduced algorithm considerably saves the slicing time and effort required to measure module parallelism and functional cohesion.
Abstract: Aggression is a behavior that cannot be approved by
the society. Vandalism which is aggression towards objects is an
action that tends to damage public or personal property. The
behaviors that are described as vandalism can often be observed in
the schools as well. According to Zwier and Vaughan (1)
previous research about the reasons of and precautionary measures
for vandalism in schools can be grouped in three tendency categories:
conservative, liberal and radical. In this context, the main aim of this
study is to discover which ideological tendency of the reasons of
school vandalism is adopted by the teachers and what are their
physical, environmental, school system and societal solutions for
vandalism. A total of 200 teachers participated in this study, and the
mean age was 34.20 years (SD = 6.54). The sample was made up of
109 females and 91 males. For the analysis of the data, SPSS 15.00,
frequency, percentage, and t-test were used. The research showed
that the teachers have tendencies in the order of conservative, liberal
and radical for the reasons of vandalism. The research also showed
that the teachers do not have any tendency for eliminating vandalism
physically and general solutions on the level of society; on the other
hand they mostly adopt a conservative tendency in terms of
precautions against vandalism in the school system. Second most,
they adopt the liberal tendency in terms of precautions against
vandalism in the school system. . It is observed that the findings of
this study are comparable to the existing literature on the subject.
Future studies should be conducted with multiple variants and
bigger sampling.
Abstract: In this paper, a solution is presented for a robotic
manipulation problem in industrial settings. The problem is sensing
objects on a conveyor belt, identifying the target, planning and
tracking an interception trajectory between end effector and the
target. Such a problem could be formulated as combining object
recognition, tracking and interception. For this purpose, we integrated
a vision system to the manipulation system and employed tracking
algorithms. The control approach is implemented on a real industrial
manipulation setting, which consists of a conveyor belt, objects
moving on it, a robotic manipulator, and a visual sensor above the
conveyor. The trjectory for robotic interception at a rendezvous point
on the conveyor belt is analytically calculated. Test results show that
tracking the raget along this trajectory results in interception and
grabbing of the target object.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: People nowadays love to travel around the world.
Regardless of their location and time, they especially Muslims still need to perform their five times prayer. Normally for travelers, they
need to bring maps, compass and for Muslim, they even have to bring Qibla pointer when they travel. It is slightly difficult to
determine the Qibla direction and to know the time for each prayer. In this paper we present a new electronic device called Universal Qibla and Prayer Time Finder to locate the Qibla direction and to determine each prayer time based on the current user-s location. This device use PIC microcontroller equipped with digital compass and
Global Positioning System (GPS) where it will display the exact Qibla direction and prayer time automatically at any place in the world. This device is reliable, user friendly and accurate in
determining the Qibla direction and prayer time.
Abstract: With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called MorfeoSMC, enabling the development of mobility applications and services according to a channel model based on Services Oriented Architecture (SOA) principles. It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation of mobile Web contents. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering, as well as to exploit these semantic annotations in a novel user profile-aware content adaptation process. Semantic Web content adaptation is a way of adding value to and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).
Abstract: Computer-mediated communication technologies which provide for virtual communities have typically evolved in a cross-dichotomous manner, such that technical constructs of the technology have evolved independently from the social environment of the community. The present paper analyses some limitations of current implementations of computer-mediated communication technology that are implied by such a dichotomy, and discusses their inhibiting effects on possible developments of virtual communities. A Socio-Technical Indicator Model is introduced that utilizes integrated feedback to describe, simulate and operationalise increasing representativeness within a variety of structurally and parametrically diverse systems. In illustration, applications of the model are briefly described for financial markets and for eco-systems. A detailed application is then provided to resolve the aforementioned technical limitations of moderation on the evolution of virtual communities. The application parameterises virtual communities to function as self-transforming social-technical systems which are sensitive to emergent and shifting community values as products of on-going communications within the collective.
Abstract: Lacking an inherent “natural" dissimilarity measure
between objects in categorical dataset presents special difficulties in
clustering analysis. However, each categorical attributes from a given
dataset provides natural probability and information in the sense of
Shannon. In this paper, we proposed a novel method which
heuristically converts categorical attributes to numerical values by
exploiting such associated information. We conduct an experimental
study with real-life categorical dataset. The experiment demonstrates
the effectiveness of our approach.
Abstract: A Novel fuzzy neural network combining with support vector learning mechanism called support-vector-based fuzzy neural networks (SVBFNN) is proposed. The SVBFNN combine the capability of minimizing the empirical risk (training error) and expected risk (testing error) of support vector learning in high dimensional data spaces and the efficient human-like reasoning of FNN.