Abstract: A robust wheel slip controller for electric vehicles is
introduced. The proposed wheel slip controller exploits the dynamics
of electric traction drives and conventional hydraulic brakes for
achieving maximum energy efficiency and driving safety. Due to
the control of single wheel traction motors in combination with a
hydraulic braking system, it can be shown, that energy recuperation
and vehicle stability control can be realized simultaneously. The
derivation of a sliding mode wheel slip controller accessing two
drivetrain actuators is outlined and a comparison to a conventionally
braked vehicle is shown by means of simulation.
Abstract: In the numerical solution of the forward dynamics of a
multibody system, the positions and velocities of the bodies in the
system are obtained first. With the information of the system state
variables at each time step, the internal and external forces acting on
the system are obtained by appropriate contact force models if the
continuous contact method is used instead of a discrete contact
method. The local deformation of the bodies in contact, represented
by penetration, is used to compute the contact force. The ability and
suitability with current cylindrical contact force models to describe
the contact between bodies with cylindrical geometries with
particular focus on internal contacting geometries involving low
clearances and high loads simultaneously is discussed in this paper.
A comparative assessment of the performance of each model under
analysis for different contact conditions, in particular for very
different penetration and clearance values, is presented. It is
demonstrated that some models represent a rough approximation to
describe the conformal contact between cylindrical geometries
because contact forces are underestimated.
Abstract: In synchronized games players make their moves simultaneously
rather than alternately. Synchronized Triomineering
and Synchronized Tridomineering are respectively the synchronized
versions of Triomineering and Tridomineering, two variants of a
classic two-player combinatorial game called Domineering. Experimental
results for small m × n boards (with m + n ≤ 12 for
Synchronized Triomineering and m + n ≤ 10 for Synchronized
Tridomineering) and some theoretical results for general k×n boards
(with k = 3, 4, 5 for Synchronized Triomineering and k = 3
for Synchronized Tridomineering) are presented. Future research is
indicated.
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: In the current study, we have conducted an experimental investigation on the utilization of electronic arc furnace (EAF) reducing slag for the absorption of CO2 via wet grinding method. It was carried out by various grinding conditions. The slag was ground in the vibrating ball mill in the presence of CO2 and pure water under ambient temperature. The reaction behavior was monitored with constant pressure method, and the changes of experimental systems volume as a function of grinding time were measured. It was found that the CO2 absorption occurred as soon as the grinding started. The CO2 absorption was significantly increased in the case of wet grinding compare to the dry grinding. Generally, the amount of CO2 absorption increased as the amount of water, weight of slag and initial pressure increased. However, it was decreased when the amount of water exceeds 200ml and when smaller balls were used. The absorption of CO2 occurred simultaneously with the start of the grinding and it stopped when the grinding was stopped. According to this research, the CO2 reacted with the CaO inside the slag, forming CaCO3.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: Voltage collapse is instability of heavily loaded electric
power systems that cause to declining voltages and blackout. Power
systems are predicated to become more heavily loaded in the future
decade as the demand for electric power rises while economic and
environmental concerns limit the construction of new transmission
and generation capacity. Heavily loaded power systems are closer to
their stability limits and voltage collapse blackouts will occur if
suitable monitoring and control measures are not taken. To control
transmission lines, it can be used from FACTS devices.
In this paper Harmony search algorithm (HSA) and Genetic
Algorithm (GA) have applied to determine optimal location of
FACTS devices in a power system to improve power system stability.
Three types of FACTS devices (TCPAT, UPFS, and SVC) have been
introduced. Bus under voltage has been solved by controlling reactive
power of shunt compensator. Also a combined series-shunt
compensators has been also used to control transmission power flow
and bus voltage simultaneously.
Different scenarios have been considered. First TCPAT, UPFS, and
SVC are placed solely in transmission lines and indices have been
calculated. Then two types of above controller try to improve
parameters randomly. The last scenario tries to make better voltage
stability index and losses by implementation of three types controller
simultaneously. These scenarios are executed on typical 34-bus test
system and yields efficiency in improvement of voltage profile and
reduction of power losses; it also may permit an increase in power
transfer capacity, maximum loading, and voltage stability margin.
Abstract: this scientific article considers the peculiarities of
ecology of culture and ecological outlook from cultural and
anthropological aspect of Turkic languages speaking peoples in the
Central Asia. The ecology of culture of Turkic languages speaking
peoples in the Central Asia, formed under the influence of climatic,
geographical, economic, religious, ethno cultural and political factors
and defining the originality of traditions which have laid down in its
basis and functioned, as its components, causes an interest and
urgency simultaneously, representing the sample of life of the Person
in the World by which it is necessary to be guided today.
Abstract: Abstract–Indoor air (VOCs) samples were collected
simultaneously from variety of indoors (e.g. living rooms, baby-s
rooms) and outdoor environments which were voluntarily selected
from the houses in which pregnant residents live throughout Ankara.
This is the first comprehensive study done in Turkey starting from
prenatal period and continued till the babies had one year old. VOCs
levels were measured over 76 homes. Air samples were collected in
Tenax TA sorbent filled tubes with active sampling method and
analyzed with Thermal Desorber and Gas Chromatography/Mass
spectrometry (TD-GC/MS). At the first sampling period in the baby-s
rooms maximum concentration of toluene was measured about
240.77μg.m-3 and in the living rooms maximum concentration of
naphthalene was 180.24μg.m-3. At the second sampling period in the
baby-s rooms maximum concentration of toluene was measured
about 144.97μg.m-3 and in the living rooms maximum concentration
of naphthalene was 247.89μg.m-3. Concentration of TVOCs in the
first period was generally higher than the second period.
Abstract: Environmental pollution problems have been globally
main concern in all fields including economy, society and culture into
the 21st century. Beginning with the Kyoto Protocol, the reduction on
the emissions of greenhouse gas such as CO2 and SOX has been a
principal challenge of our day. As most buildings unlike durable goods
in other industries have a characteristic and long life cycle, they
consume energy in quantity and emit much CO2. Thus, for green
building construction, more research is needed to reduce the CO2
emissions at each stage in the life cycle. However, recent studies are
focused on the use and maintenance phase. Also, there is a lack of
research on the initial design stage, especially the structure design.
Therefore, in this study, we propose an optimal design plan
considering CO2 emissions and cost in composite buildings
simultaneously by applying to the structural design of actual building.
Abstract: A high energy dual-wavelength extracavity KTA
optical parametric oscillator (OPO) with excellent stability and beam
quality, which is pumped by a Q-switched single-longitudinal-mode
Nd:YAG laser, has been demonstrated based on a type II noncritical
phase matching (NCPM) KTA crystal. The maximum pulse energy of
10.2 mJ with the output stability of better than 4.1% rms at 3.467 μm is
obtained at the repetition rate of 10 Hz and pulse width of 2 ns, and the
11.9 mJ of 1.535 μm radiation is obtained simultaneously. This
extracavity NCPM KTA OPO is very useful when high energy, high
beam quality and smooth time domain are needed.
Abstract: We report on a high-speed quantum cryptography
system that utilizes simultaneous entanglement in polarization and in
“time-bins". With multiple degrees of freedom contributing to the
secret key, we can achieve over ten bits of random entropy per detected coincidence. In addition, we collect from multiple spots o
the downconversion cone to further amplify the data rate, allowing usto achieve over 10 Mbits of secure key per second.
Abstract: Shadow detection is still considered as one of the
potential challenges for intelligent automated video surveillance
systems. A pre requisite for reliable and accurate detection and
tracking is the correct shadow detection and classification. In such a
landscape of conditions, privacy issues add more and more
complexity and require reliable shadow detection.
In this work the intertwining between security, accuracy,
reliability and privacy is analyzed and, accordingly, a novel
architecture for Privacy Enhancing Video Surveillance (PEVS) is
introduced. Shadow detection and masking are dealt with through the
combination of two different approaches simultaneously. This results
in a unique privacy enhancement, without affecting security.
Subsequently, the methodology was employed successfully in a
large-scale wireless video surveillance system; privacy relevant
information was stored and encrypted on the unit, without
transferring it over an un-trusted network.
Abstract: As a part of the development of a numerical method of
close capture exhausts systems for machining devices, a test rig
recreating a situation similar to a grinding operation, but in a
perfectly controlled environment, is used. The properties of the
obtained spray of solid particles are initially characterized using
particle tracking velocimetry (PTV), in order to obtain input and
validation parameters for numerical simulations. The dispersion of a
tracer gas (SF6) emitted simultaneously with the particle jet is then
studied experimentally, as the dispersion of such a gas is
representative of that of finer particles, whose aerodynamic response
time is negligible. Finally, complete modeling of the test rig is
achieved to allow comparison with experimental results and thus to
progress towards validation of the models used to describe a twophase
flow generated by machining operation.
Abstract: Optimization plays an important role in most real
world applications that support decision makers to take the right
decision regarding the strategic directions and operations of the
system they manage. Solutions for traffic management and traffic
congestion problems are considered major problems that most
decision making authorities for cities around the world are looking
for. This review paper gives a full description of the traffic problem
as part of the transportation planning process and present a view as a
framework of urban transportation system analysis where the core of
the system is a transportation network equilibrium model that is
based on optimization techniques and that can also be used for
evaluating an alternative solution or a combination of alternative
solutions for the traffic congestion. Different transportation network
equilibrium models are reviewed from the sequential approach to the
multiclass combining trip generation, trip distribution, modal split,
trip assignment and departure time model. A GIS-Based intelligent
decision support system framework for urban transportation system
analysis is suggested for implementation where the selection of
optimized alternative solutions, single or packages, will be based on
an intelligent agent rather than human being which would lead to
reduction in time, cost and the elimination of the difficulty, by
human being, for finding the best solution to the traffic congestion
problem.
Abstract: In this paper, we propose the pre-processor based on
the Evidence Supporting Measure of Similarity (ESMS) filter and also
propose the unified fusion approach (UFA) based on the general
fusion machine coupled with ESMS filter, which improve the
correctness and precision of information fusion in any fields of
application. Here we mainly apply the new approach to Simultaneous
Localization And Mapping (SLAM) of Pioneer II mobile robots. A
simulation experiment was performed, where an autonomous virtual
mobile robot with sonar sensors evolves in a virtual world map with
obstacles. By comparing the result of building map according to the
general fusion machine (here DSmT-based fusing machine and
PCR5-based conflict redistributor considereded) coupling with ESMS
filter and without ESMS filter, it shows the benefit of the selection of
the sources as a prerequisite for improvement of the information
fusion, and also testifies the superiority of the UFA in dealing with
SLAM.
Abstract: Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.
Abstract: In this paper a combined feature selection method is
proposed which takes advantages of sample domain filtering,
resampling and feature subset evaluation methods to reduce
dimensions of huge datasets and select reliable features. This method
utilizes both feature space and sample domain to improve the process
of feature selection and uses a combination of Chi squared with
Consistency attribute evaluation methods to seek reliable features.
This method consists of two phases. The first phase filters and
resamples the sample domain and the second phase adopts a hybrid
procedure to find the optimal feature space by applying Chi squared,
Consistency subset evaluation methods and genetic search.
Experiments on various sized datasets from UCI Repository of
Machine Learning databases show that the performance of five
classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First
Decision Tree and JRIP) improves simultaneously and the
classification error for these classifiers decreases considerably. The
experiments also show that this method outperforms other feature
selection methods.