Abstract: This paper presents a multiband CPW-fed slot antenna
with L-slot bowtie tuning stub. The proposed antenna has been
designed for PCS 1900, UMTS, WLAN 802.11 a/b/g and bluetooth
applications, with a cost-effective FR4 substrate. The proposed
antenna still radiate as omni-directional in azimuth plane and
sufficient bandwidth for all above mentions. The proposed antenna
works as dual-wideband, bandwidth at low frequency band and high
frequency are about 45.49 % and 22.39 % respectively. The
experimental results of the constructed prototype are presented and
also compared with simulation results using a commercial software
tool.
Abstract: Biplot can be used to evaluate cultivars for their oil
percent potential and stability and to evaluate trial sites for their
discriminating ability and representativeness. Multi-environmental
trial (MET) data for oil percent of 10 open pollinating sunflower
cultivars were analyzed to investigate the genotype-environment
interactions. The genotypes were evaluated in four locations with
different climatic conditions in Iran in 2010. In each location, a
Randomized Complete Block design with four replications was used.
According to both mean and stability, Zaria, Master and R453, had
highest performances among all cultivars. The graphical analysis
identified best cultivar for each environment. Cultivars Berezans and
Record performed best in Khoy and Islamabad. Zaria and R453 were
the best genotypes in Sari and Karaj followed by Master and Favorit.
The GGE bi-plot indicated two mega-environments, group one
contained Karaj, Khoy and Islamabad and the second group
contained Sari. The best discriminating location was Karaj followed
with Khoy, Islamabad and Sari. The best representative genotypes
were Zaria, R453, Master and Favorit. Ranking of ten cultivars based
their oil percent was as Zaria > R453 ≈ Master ≈ Favorit > Record ≈
Berezans > Sor > Lakumka > Bulg3 > Bulg5.
Abstract: Utilization of waste material in asphalt pavement
would be beneficial in order to find an alternative solution to increase
service life of asphalt pavement and reduce environmental pollution
as well. One of these waste materials is Polyethylene Terephthalate
(PET) which is a type of polyester material and is produced in a large
extent. This research program is investigating the effects of adding
waste PET particles into the asphalt mixture with a maximum size of
2.36 mm. Different percentages of PET were added into the mixture
during dry process. Gap-graded mixture (SMA 14) and PG 80-100
asphalt binder have been used for this study. To evaluate PET
reinforced asphalt mixture different laboratory investigations have
been conducted on specimens. Marshall Stability test was carried
out. Besides, stiffness modulus test and indirect tensile fatigue test
were conducted on specimens at optimum asphalt content. It was
observed that in many cases PET reinforced SMA mixture had better
mechanical properties in comparison with control mixture.
Abstract: This paper describes an application of a dual satellite
geolocation (DSG) system on identifying and locating the unknown
source of uplink sweeping interference. The geolocation system
integrates the method of joint time difference of arrival (TDOA) and
frequency difference of arrival (FDOA) with ephemeris correction
technique which successfully demonstrated high accuracy in
interference source location. The factors affecting the location error
were also discussed.
Abstract: In this work a visual and reactive contour following
behaviour is learned by reinforcement. With artificial vision the
environment is perceived in 3D, and it is possible to avoid obstacles
that are invisible to other sensors that are more common in mobile
robotics. Reinforcement learning reduces the need for intervention in
behaviour design, and simplifies its adjustment to the environment,
the robot and the task. In order to facilitate its generalisation to other
behaviours and to reduce the role of the designer, we propose a
regular image-based codification of states. Even though this is much
more difficult, our implementation converges and is robust. Results
are presented with a Pioneer 2 AT on a Gazebo 3D simulator.
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: Internet Access Technologies (IAT) provide a means
through which Internet can be accessed. The choice of a suitable
Internet technology is increasingly becoming an important issue to
ISP clients. Currently, the choice of IAT is based on discretion and
intuition of the concerned managers and the reliance on ISPs. In this
paper we propose a model and designs algorithms that are used in the
Internet access technology specification. In the proposed model, three
ranking approaches are introduced; concurrent ranking, stepwise
ranking and weighted ranking. The model ranks the IAT based on
distance measures computed in ascending order while the global
ranking system assigns weights to each IAT according to the position
held in each ranking technique, determines the total weight of a
particular IAT and ranks them in descending order. The final output
is an objective ranking of IAT in descending order.
Abstract: A simple analytical model has been developed to
optimize biasing conditions for obtaining maximum linearity among
lattice-matched, pseudomorphic and metamorphic HEMT types as
well as enhancement and depletion HEMT modes. A nonlinear
current-voltage model has been simulated based on extracted data to
study and select the most appropriate type and mode of HEMT in
terms of a given gate-source biasing voltage within the device so as
to employ the circuit for the highest possible output current or
voltage linear swing. Simulation results can be used as a basis for the
selection of optimum gate-source biasing voltage for a given type
and mode of HEMT with regard to a circuit design. The
consequences can also be a criterion for choosing the optimum type
or mode of HEMT for a predetermined biasing condition.
Abstract: This communication is intended to provide some issues for thought on the importance of implementation of Blended Learning in traditional universities, particularly in the Spanish university system. In this respect, we believe that virtual environments are likely to meet some of the needs raised by the Bologna agreement, trying to maintain the quality of teaching and at the same time taking advantage of the functionalities that virtual learning platforms offer. We are aware that an approach of learning from an open and constructivist nature in universities is a complex process that faces significant technological, administrative and human barriers. Therefore, in order to put plans in our universities, it is necessary to analyze the state of the art of some indicators relating to the use of ICT, with special attention to virtual teaching and learning, so that we can identify the main obstacles and design adaptive strategies for their full integration in the education system. Finally, we present major initiatives launched in the European and state framework for the effective implementation of new virtual environments in the area of higher education.
Abstract: This paper presents a method of reducing the feedback
delay time of DWA(Data Weighted Averaging) used in sigma-delta
modulators. The delay time reduction results from the elimination of
the latch at the quantizer output and also from the falling edge
operation. The designed sigma-delta modulator improves the timing
margin about 16%. The sub-circuits of sigma-delta modulator such as
SC(Switched Capacitor) integrator, 9-level quantizer, comparator, and
DWA are designed with the non-ideal characteristics taken into
account. The sigma-delta modulator has a maximum SNR (Signal to
Noise Ratio) of 84 dB or 13 bit resolution.
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: We investigate nonfactorizable contributions to
D → ¤Ç¤Ç decay modes. We perform isospin analysis of the
nonfactorizable contributions to these decays. Obtaining the
factorizable contributions from spectator-quark diagrams using
= 3 C N , we determine nonfactorizable amplitudes for these decays
and predict their branching ratios.
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: Accurate demand forecasting is one of the most key
issues in inventory management of spare parts. The problem of
modeling future consumption becomes especially difficult for lumpy
patterns, which characterized by intervals in which there is no
demand and, periods with actual demand occurrences with large
variation in demand levels. However, many of the forecasting
methods may perform poorly when demand for an item is lumpy.
In this study based on the characteristic of lumpy demand patterns
of spare parts a hybrid forecasting approach has been developed,
which use a multi-layered perceptron neural network and a
traditional recursive method for forecasting future demands. In the
described approach the multi-layered perceptron are adapted to
forecast occurrences of non-zero demands, and then a conventional
recursive method is used to estimate the quantity of non-zero
demands. In order to evaluate the performance of the proposed
approach, their forecasts were compared to those obtained by using
Syntetos & Boylan approximation, recently employed multi-layered
perceptron neural network, generalized regression neural network
and elman recurrent neural network in this area. The models were
applied to forecast future demand of spare parts of Arak
Petrochemical Company in Iran, using 30 types of real data sets. The
results indicate that the forecasts obtained by using our proposed
mode are superior to those obtained by using other methods.
Abstract: This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.
Abstract: Binary Decision Diagrams (BDDs) are useful data
structures for symbolic Boolean manipulations. BDDs are used in
many tasks in VLSI/CAD, such as equivalence checking, property
checking, logic synthesis, and false paths. In this paper we describe a
new approach for the realization of a BDD package. To perform
manipulations of Boolean functions, the proposed approach does not
depend on the recursive synthesis operation of the IF-Then-Else
(ITE). Instead of using the ITE operation, the basic synthesis
algorithm is done using Boolean NOR operation.
Abstract: In this paper comparison of Reflector Antenna
analyzing techniques based on wave and ray nature of optics is
presented for an offset reflector antenna using GRASP (General
Reflector antenna Analysis Software Package) software. The results
obtained using PO (Physical Optics), PTD (Physical theory of
Diffraction), and GTD (Geometrical Theory of Diffraction) are
compared. The validity of PO and GTD techniques in regions around
the antenna, caustic behavior of GTD in main beam, and deviation of
GTD in case of near-in sidelobes of radiation pattern are discussed.
The comparison for far-out sidelobes predicted by PO, PO + PTD
and GTD is described. The effect of Direct Radiations from feed
which results in feed selection for the system is addressed.
Abstract: The purpose of this paper is to analyze determinants of
information security affecting adoption of the Web-based integrated
information systems (IIS). We introduced Web-based information
systems which are designed to formulate strategic plans for Peruvian
government. Theoretical model is proposed to test impact of
organizational factors (deterrent efforts and severity; preventive
efforts) and individual factors (information security threat; security
awareness) on intentions to proactively use the Web-based IIS .Our
empirical study results highlight that deterrent efforts and deterrent
severity have no significant influence on the proactive use intentions
of IIS, whereas, preventive efforts play an important role in proactive
use intentions of IIS. Thus, we suggest that organizations need to do
preventive efforts by introducing various information security
solutions, and try to improve information security awareness while
reducing the perceived information security threats.
Abstract: One of the most attractive and important field of chaos theory is control of chaos. In this paper, we try to present a simple framework for chaotic motion control using the feedback linearization method. Using this approach, we derive a strategy, which can be easily applied to the other chaotic systems. This task presents two novel results: the desired periodic orbit need not be a solution of the original dynamics and the other is the robustness of response against parameter variations. The illustrated simulations show the ability of these. In addition, by a comparison between a conventional state feedback and our proposed method it is demonstrated that the introduced technique is more efficient.