Abstract: Absorption and fluorescence spectra of quinine
sulphate (QSD) have been recorded at room temperature in wide
range of solvents of different polarities. The ground-state dipole
moment of QSD was obtained from quantum mechanical calculations
and the excited state dipole moment of QSD was estimated from
Bakhshiev-s and Kawski-Chamma-Viallet-s equations by means of
solvatochromic shift method. Higher value of dipole moment is
observed for excited state as compared to the corresponding ground
state value and this is attributed to the more polar excited state of
QSD.
Abstract: Active Power Filters (APFs) are today the most
widely used systems to eliminate harmonics compensate power
factor and correct unbalanced problems in industrial power plants.
We propose to improve the performances of conventional APFs by
using artificial neural networks (ANNs) for harmonics estimation.
This new method combines both the strategies for extracting the
three-phase reference currents for active power filters and DC link
voltage control method. The ANNs learning capabilities to
adaptively choose the power system parameters for both to compute
the reference currents and to recharge the capacitor value requested
by VDC voltage in order to ensure suitable transit of powers to
supply the inverter. To investigate the performance of this
identification method, the study has been accomplished using
simulation with the MATLAB Simulink Power System Toolbox. The
simulation study results of the new (SAPF) identification technique
compared to other similar methods are found quite satisfactory by
assuring good filtering characteristics and high system stability.
Abstract: Existing methods in which the animation data of all frames are stored and reproduced as with vertex animation cannot be used in mobile device environments because these methods use large amounts of the memory. So 3D animation data reduction methods aimed at solving this problem have been extensively studied thus far and we propose a new method as follows. First, we find and remove frames in which motion changes are small out of all animation frames and store only the animation data of remaining frames (involving large motion changes). When playing the animation, the removed frame areas are reconstructed using the interpolation of the remaining frames. Our key contribution is to calculate the accelerations of the joints of individual frames and the standard deviations of the accelerations using the information of joint locations in the relevant 3D model in order to find and delete frames in which motion changes are small. Our methods can reduce data sizes by approximately 50% or more while providing quality which is not much lower compared to original animations. Therefore, our method is expected to be usefully used in mobile device environments or other environments in which memory sizes are limited.
Abstract: Steel surface defect detection is essentially one of
pattern recognition problems. Support Vector Machines (SVMs) are
known as one of the most proper classifiers in this application. In this
paper, we introduce a more accurate classification method by using
SVMs as our final classifier of the inspection system. In this scheme,
multiclass classification task is performed based on the "one-againstone"
method and different kernels are utilized for each pair of the
classes in multiclass classification of the different defects.
In the proposed system, a decision tree is employed in the first
stage for two-class classification of the steel surfaces to "defect" and
"non-defect", in order to decrease the time complexity. Based on
the experimental results, generated from over one thousand images,
the proposed multiclass classification scheme is more accurate than
the conventional methods and the overall system yields a sufficient
performance which can meet the requirements in steel manufacturing.
Abstract: This paper focuses on a novel method for semantic
searching and retrieval of information about learning materials.
Metametadata encapsulate metadata instances by using the properties
and attributes provided by ontologies rather than describing learning
objects. A novel metametadata taxonomy has been developed which
provides the basis for a semantic search engine to extract, match and
map queries to retrieve relevant results. The use of ontological views
is a foundation for viewing the pedagogical content of metadata
extracted from learning objects by using the pedagogical attributes
from the metametadata taxonomy. Using the ontological approach
and metametadata (based on the metametadata taxonomy) we present
a novel semantic searching mechanism.These three strands – the
taxonomy, the ontological views, and the search algorithm – are
incorporated into a novel architecture (OMESCOD) which has been
implemented.
Abstract: The purposes of researches - to estimate implicit ethnic attitudes by direct and indirect methods, to determine the accordance of two types measuring, to investigate influence of task type used in an experiment, on the results of measuring, as well as to determine a presence or communication between recent episodic events and chronologic correlations of ethnic attitudes. Method of the implicit measuring - an evaluative priming (EPT) carried out with the use of different SOA intervals, explicit methods of research are G.Soldatova-s types of ethnic identity, G.Soldatova-s index of tolerance, E.Bogardus scale of social distance. During five stages of researches received results open some aspects of implicit measuring, its correlation with the results of self-reports on different SOA intervals, connection of implicit measuring with emotional valence of episodic events of participants and other indexes, presenting a contribution to the decision of implicit measuring application problem for study of different social constructs
Abstract: Serial hierarchical support vector machine (SHSVM)
is proposed to discriminate three brain tissues which are white matter
(WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM
has novel classification approach by repeating the hierarchical
classification on data set iteratively. It used Radial Basis Function
(rbf) Kernel with different tuning to obtain accurate results. Also as
the second approach, segmentation performed with DAGSVM
method. In this article eight univariate features from the raw DTI data
are extracted and all the possible 2D feature sets are examined within
the segmentation process. SHSVM succeed to obtain DSI values
higher than 0.95 accuracy for all the three tissues, which are higher
than DAGSVM results.
Abstract: This paper suggests a fast and stable Target Tracking
system in collaborative control of UAV and UGV. Wi-Fi communication range is limited in collaborative control of UAV and UGV. Thus, to secure a stable communications, UAV and UGV have
to be kept within a certain distance from each other. But existing
method which uses UAV Vertical Camera to follow the motion of
UGV is likely to lose a target with a sudden movement change.
Eventually, UGV has disadvantages that it could only move at a low
speed and not make any sudden change of direction in order to keep
track of the target. Therefore, we suggest utilizing AR Drone UAV front camera to track fast-moving and Omnidirectional Mecanum
Wheel UGV.
Abstract: This paper proposes a vehicle-to-vehicle propagation
model implemented with SDL. To estimate the channel
characteristics for Inter-Vehicle communication, we first define a
predicted propagation pathloss between the moving vehicles under
three typical scenarios. A Ray-tracing method is used for the simple
gamma model performance.
Abstract: It is an important task in Korean-English machine
translation to classify the gender of names correctly. When a sentence
is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun
for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus,
in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just
a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method
yields the improvement in accuracy over the simple looking-up of the
collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed
method is more plausible for the gender classification of the Korean names.
Abstract: Magnetic and semiconductor nanomaterials exhibit
novel magnetic and optical properties owing to their unique size and
shape-dependent effects. With shrinking the size down to nanoscale
region, various anomalous properties that normally not present in bulk
start to dominate. Ability in harnessing of these anomalous properties
for the design of various advance electronic devices is strictly
dependent on synthetic strategies. Hence, current research has focused
on developing a rational synthetic control to produce high quality
nanocrystals by using organometallic approach to tune both size and
shape of the nanomaterials. In order to elucidate the growth
mechanism, transmission electron microscopy was employed as a
powerful tool in performing real time-resolved morphologies and
structural characterization of magnetic (Fe3O4) and semiconductor
(ZnO) nanocrystals. The current synthetic approach is found able to
produce nanostructures with well-defined shapes. We have found that
oleic acid is an effective capping ligand in preparing oxide-based
nanostructures without any agglomerations, even at high temperature.
The oleate-based precursors and capping ligands are fatty acid
compounds, which are respectively originated from natural palm oil
with low toxicity. In comparison with other synthetic approaches in
producing nanostructures, current synthetic method offers an effective
route to produce oxide-based nanomaterials with well-defined shapes
and good monodispersity. The nanocystals are well-separated with
each other without any stacking effect. In addition, the as-synthesized
nanopellets are stable in terms of chemically and physically if
compared to those nanomaterials that are previous reported. Further
development and extension of current synthetic strategy are being
pursued to combine both of these materials into nanocomposite form
that will be used as “smart magnetic nanophotocatalyst" for industry
waste water treatment.
Abstract: Salient points are frequently used to represent local
properties of the image in content-based image retrieval. In this paper,
we present a reduction algorithm that extracts the local most salient
points such that they not only give a satisfying representation of an
image, but also make the image retrieval process efficiently. This
algorithm recursively reduces the continuous point set by their
corresponding saliency values under a top-down approach. The
resulting salient points are evaluated with an image retrieval system
using Hausdoff distance. In this experiment, it shows that our method
is robust and the extracted salient points provide better retrieval
performance comparing with other point detectors.
Abstract: Novel Coconut oil nanofluids of various concentrations have been prepared through ultrasonically assisted sol-gel method. The structural and morphological properties of the copper oxide nanoparticle have been analyzed with respectively and it revealed the monoclinic end-centered structure of crystallite and shuttle like flake morphology of agglomerates. Ultrasonic studies have been made for the nanofluids at different temperatures. The molecular interactions responsible for the changes in acoustical parameter with respect to concentration and temperature are discussed.
Abstract: This paper presents a novel control method based on radial basis function networks (RBFNs) for chaotic dynamical systems. The proposed method first identifies the nonlinear part of the chaotic system off-line and then constructs a model-following controller using only the estimated system parameters. Simulation results show the effectiveness of the proposed control scheme.
Abstract: Presents a concept for a multidisciplinary process
supporting effective task transitions between different technical
domains during the architectural design stage.
A system configuration challenge is the multifunctional driven
increased solution space. As a consequence, more iteration is needed
to find a global optimum, i.e. a compromise between involved
disciplines without negative impact on development time. Since state
of the art standards like ISO 15288 and VDI 2206 do not provide a
detailed methodology on multidisciplinary design process, higher
uncertainties regarding final specifications arise. This leads to the
need of more detailed and standardized concepts or processes which
could mitigate risks.
The performed work is based on analysis of multidisciplinary
interaction, of modeling and simulation techniques. To demonstrate
and prove the applicability of the presented concept, it is applied to
the design of aircraft high lift systems, in the context of the
engineering disciplines kinematics, actuation, monitoring, installation
and structure design.
Abstract: The projection methods, usually viewed as the methods
for computing eigenvalues, can also be used to estimate pseudospectra.
This paper proposes a kind of projection methods for computing
the pseudospectra of large scale matrices, including orthogonalization
projection method and oblique projection method respectively. This
possibility may be of practical importance in applications involving
large scale highly nonnormal matrices. Numerical algorithms are
given and some numerical experiments illustrate the efficiency of
the new algorithms.
Abstract: This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.
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 paper addresses parameter and state estimation problem in the presence of the perturbation of observer gain bounded input disturbances for the Lipschitz systems that are linear in unknown parameters and nonlinear in states. A new nonlinear adaptive resilient observer is designed, and its stability conditions based on Lyapunov technique are derived. The gain for this observer is derived systematically using linear matrix inequality approach. A numerical example is provided in which the nonlinear terms depend on unmeasured states. The simulation results are presented to show the effectiveness of the proposed method.
Abstract: This paper proposes an Interactive Chinese Character
Learning System (ICCLS) based on pictorial evolution as an
edutainment concept in computer-based learning of language. The
advantage of the language origination itself is taken as a learning
platform due to the complexity in Chinese language as compared to
other types of languages. Users especially children enjoy more by
utilize this learning system because they are able to memories the
Chinese Character easily and understand more of the origin of the
Chinese character under pleasurable learning environment, compares
to traditional approach which children need to rote learning Chinese
Character under un-pleasurable environment. Skeletonization is used
as the representation of Chinese character and object with an animated
pictograph evolution to facilitate the learning of the language. Shortest
skeleton path matching technique is employed for fast and accurate
matching in our implementation. User is required to either write a
word or draw a simple 2D object in the input panel and the matched
word and object will be displayed as well as the pictograph evolution
to instill learning. The target of computer-based learning system is for
pre-school children between 4 to 6 years old to learn Chinese
characters in a flexible and entertaining manner besides utilizing
visual and mind mapping strategy as learning methodology.