Abstract: In this research, effect of combustion reaction
mechanism on direct initiation of detonation has been studied
numerically. For this purpose, reaction mechanism has been
simulated by using a three-step chemical kinetics model. The reaction
scheme consists sequentially of a chain-initiation and chainbranching
step, followed by a temperature -independent chaintermination.
In a previous research, the effect of chain-branching on
the direct initiation of detonation is studied. In this research effect of
chain-initiation on direct initiation of detonation is investigated. For
the investigation, first a characteristic time (τ) for each step of
mechanism, which includes effect of different kinetics parameters, is
defined. Then the effect of characteristic time of chain-initiation (τI)
on critical initiation energy is studied. It is seen that increasing τI,
causes critical initiation energy to be increased. Drawing detonation's
shock pressure diagrams for different cases, shows that in small value
of τI , kinetics has more important effect on the behavior of the wave.
Abstract: A number of automated shot-change detection
methods for indexing a video sequence to facilitate browsing and
retrieval have been proposed in recent years. This paper emphasizes
on the simulation of video shot boundary detection using one of the
methods of the color histogram wherein scaling of the histogram
metrics is an added feature. The difference between the histograms of
two consecutive frames is evaluated resulting in the metrics. Further
scaling of the metrics is performed to avoid ambiguity and to enable
the choice of apt threshold for any type of videos which involves
minor error due to flashlight, camera motion, etc. Two sample videos
are used here with resolution of 352 X 240 pixels using color
histogram approach in the uncompressed media. An attempt is made
for the retrieval of color video. The simulation is performed for the
abrupt change in video which yields 90% recall and precision value.
Abstract: One of the approaches enabling people with amputated
limbs to establish some sort of interface with the real world includes
the utilization of the myoelectric signal (MES) from the remaining
muscles of those limbs. The MES can be used as a control input to a
multifunction prosthetic device. In this control scheme, known as the
myoelectric control, a pattern recognition approach is usually utilized
to discriminate between the MES signals that belong to different
classes of the forearm movements. Since the MES is recorded using
multiple channels, the feature vector size can become very large. In
order to reduce the computational cost and enhance the generalization
capability of the classifier, a dimensionality reduction method is
needed to identify an informative yet moderate size feature set. This
paper proposes a new fuzzy version of the well known Fisher-s
Linear Discriminant Analysis (LDA) feature projection technique.
Furthermore, based on the fact that certain muscles might contribute
more to the discrimination process, a novel feature weighting scheme
is also presented by employing Particle Swarm Optimization (PSO)
for estimating the weight of each feature. The new method, called
PSOFLDA, is tested on real MES datasets and compared with other
techniques to prove its superiority.
Abstract: This paper introduces a measure of similarity between
two clusterings of the same dataset produced by two different
algorithms, or even the same algorithm (K-means, for instance, with
different initializations usually produce different results in clustering
the same dataset). We then apply the measure to calculate the
similarity between pairs of clusterings, with special interest directed
at comparing the similarity between various machine clusterings and
human clustering of datasets. The similarity measure thus can be used
to identify the best (in terms of most similar to human) clustering
algorithm for a specific problem at hand. Experimental results
pertaining to the text categorization problem of a Portuguese corpus
(wherein a translation-into-English approach is used) are presented, as well as results on the well-known benchmark IRIS dataset. The
significance and other potential applications of the proposed measure
are discussed.
Abstract: The aim of this qualitative case study is to examine how school principals perform their new roles and responsibilities defined in accordance with the new curriculum. Of ten primary schools that the new curriculum was piloted in Istanbul in school year of 2004-2005, one school was randomly selected as the sample of the study. The participants of the study were comprised of randomly-selected 26 teachers working in the case school. To collect data, an interview schedule was developed based on the new role definitions for school principals by the National Ministry of Education. Participants were interviewed on one-to-one basis in February and March 2007. Overall results showed that the school principal was perceived to be successful in terms of the application of the new curriculum in school. According to the majority of teachers, the principal has done his best to establish the infrastructure that is necessary for successful application of the new program. In addition to these, the principal was reported to adopt a collegial and participatory leadership style by creating a positive school atmosphere that enables the school community (teachers, parents and students) to involve school more than before. Keywordscase study, curriculum implementation, school principals and curriculum
Abstract: An emotional speech recognition system for the
applications on smart phones was proposed in this study to combine
with 3G mobile communications and social networks to provide users
and their groups with more interaction and care. This study developed
a mechanism using the support vector machines (SVM) to recognize
the emotions of speech such as happiness, anger, sadness and normal.
The mechanism uses a hierarchical classifier to adjust the weights of
acoustic features and divides various parameters into the categories of
energy and frequency for training. In this study, 28 commonly used
acoustic features including pitch and volume were proposed for
training. In addition, a time-frequency parameter obtained by
continuous wavelet transforms was also used to identify the accent and
intonation in a sentence during the recognition process. The Berlin
Database of Emotional Speech was used by dividing the speech into
male and female data sets for training. According to the experimental
results, the accuracies of male and female test sets were increased by
4.6% and 5.2% respectively after using the time-frequency parameter
for classifying happy and angry emotions. For the classification of all
emotions, the average accuracy, including male and female data, was
63.5% for the test set and 90.9% for the whole data set.
Abstract: A pressure-based implicit procedure to solve Navier-
Stokes equations on a nonorthogonal mesh with collocated finite
volume formulation is used to simulate flow around the smart and
conventional flaps of spoiler under the ground effect. Cantilever
beam with uniformly varying load with roller support at the free end
is considered for smart flaps. The boundedness criteria for this
procedure are determined from a Normalized Variable diagram
(NVD) scheme. The procedure incorporates es the k -ε eddyviscosity
turbulence model. The method is first validated against
experimental data. Then, the algorithm is applied for turbulent
aerodynamic flows around a spoiler section with smart and
conventional flaps for different attack angle, flap angle and ground
clearance where the results of two flaps are compared.
Abstract: Wall-surface jet induced by the dielectric barrier
discharge (DBD) has been proposed as an actuator for active flow
control in aerodynamic applications. Discharge plasma evolution of
the DBD plasma actuator was simulated based on a simple fluid model,
in which the electron, one type of positive ion and negative ion were
taken into account. Two-dimensional simulation was conducted, and
the results are in agreement with the insights obtained from
experimental studies. The simulation results indicate that the discharge
mode changes depending on applied voltage slope; when the applied
voltage is positive-going with high applied voltage slope, the
corona-type discharge mode turns into the streamer-type discharge
mode and the threshold voltage slope is around 300 kV/ms in this
simulation. The characteristics of the electrohydrodynamic (EHD)
force, which is the source of the wall-surface jet, also change
depending on the discharge mode; the tentative peak value of the EHD
force during the positive-going voltage phase is saturated by the
periodical formation of the streamer-type discharge.
Abstract: As the demand and prices of various petroleum products have been on the rise in recent years, there is a growing need for alternative fuels. Biodiesel, which consists of alkyl monoesters of fatty acids from vegetable oils and animal fats, is considered as an alternative to petroleum diesel. Biodiesel has comparable performance with that of diesel and has lower brake specific fuel consumption than diesel with significant reduction in emissions of CO, hydrocarbons (HC) and smoke with however, a slight increase in NOx emissions. This paper analyzes the effect of cooled exhaust gas recirculation in the combustion characteristics of a direct injection compression ignition engine using biodiesel blended fuel as opposed to the conventional system. The combustion parameters such as cylinder pressure, heat release rate, delay period and peak pressure were analyzed at various loads. The maximum cylinder pressure reduces as the fraction of biodiesel increases in the blend the maximum rate of pressure rise was found to be higher for diesel at higher engine loads.
Abstract: Traditional parallel single string matching algorithms
are always based on PRAM computation model. Those algorithms
concentrate on the cost optimal design and the theoretical speed.
Based on the distributed string matching algorithm proposed by
CHEN, a practical distributed string matching algorithm architecture
is proposed in this paper. And also an improved single string matching
algorithm based on a variant Boyer-Moore algorithm is presented. We
implement our algorithm on the above architecture and the
experiments prove that it is really practical and efficient on distributed
memory machine. Its computation complexity is O(n/p + m), where n
is the length of the text, and m is the length of the pattern, and p is the
number of the processors.
Abstract: This work investigated the phenology of Parah tree
(Elateriospermum tapos) using the General Purpose Atmosphere
Plant Soil Simulator (GAPS model) to determine the amount of Plant
Available Water (PAW) in the soil. We found the correlation
between PAW and the timing of budburst and flower burst at Khao
Nan National Park, Nakhon Si Thammarat, Thailand. PAW from the
GAPS model can be used as an indicator of soil water stress. The low
amount of PAW may lead to leaf shedding in Parah trees.
Abstract: In this paper, the position control of an electronic
throttle actuator is outlined. The dynamic behavior of the actuator is
described with the help of an uncertain plant model. This motivates
the controller design based on the ideas of higher-order slidingmodes.
As a consequence anti-chattering techniques can be omitted.
It is shown that the same concept is applicable to estimate unmeasureable
signals. The control law and the observer are implemented on
an electronic control unit. Results achieved by numerical simulations
and real world experiments are presented and discussed.
Abstract: Cognitive Dissonance can be conceived both as a concept related to the tendency to avoid internal contradictions in certain situations, and as a higher order theory about information processing in the human mind. In the last decades, this last sense has been strongly surpassed by the former, as nearly all experiment on the matter discuss cognitive dissonance as an output of motivational contradictions. In that sense, the question remains: is cognitive dissonance a process intrinsically associated with the way that the mind processes information, or is it caused by such specific contradictions? Objective: To evaluate the effects of cognitive dissonance in the absence of rewards or any mechanisms to manipulate motivation. Method: To solve this question, we introduce a new task, the hypothetical social arrays paradigm, which was applied to 50 undergraduate students. Results: Our findings support the perspective that the human mind shows a tendency to avoid internal dissonance even when there are no rewards or punishment involved. Moreover, our findings also suggest that this principle works outside the conscious level.
Abstract: In this paper, we present a novel, principled approach to resolve the remained problems of substitution technique of audio steganography. Using the proposed genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.
Abstract: This paper proposes an improved approach based on
conventional particle swarm optimization (PSO) for solving an
economic dispatch(ED) problem with considering the generator
constraints. The mutation operators of the differential evolution (DE)
are used for improving diversity exploration of PSO, which called
particle swarm optimization with mutation operators (PSOM). The
mutation operators are activated if velocity values of PSO nearly to
zero or violated from the boundaries. Four scenarios of mutation
operators are implemented for PSOM. The simulation results of all
scenarios of the PSOM outperform over the PSO and other existing
approaches which appeared in literatures.
Abstract: This study investigates CO2 mitigation by methanol
synthesis from flue gas CO2 and H2 generation through water
electrolysis. Electrolytic hydrogen generation is viable provided that
the required electrical power is supplied from renewable energy
resources; whereby power generation from renewable resources is yet
commercial challenging. This approach contribute to zero-emission,
moreover it produce oxygen which could be used as feedstock for
chemical process. At ZPC, however, oxygen would be utilized
through partial oxidation of methane in autothermal reactor (ATR);
this makes ease the difficulties of O2 delivery and marketing. On the
other hand, onboard hydrogen storage and consumption; in methanol
plant; make the project economically more competitive.
Abstract: We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object (crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject (crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections.
Abstract: This paper presents a linear stability analysis of
natural convection in a horizontal layer of a viscoelastic
nanofluid. The Oldroyd B model was utilized to describe the
rheological behavior of a viscoelastic nanofluid. The model
used for the nanofluid incorporated the effects of Brownian
motion and thermophoresis. The onset criterion for stationary
and oscillatory convection was derived analytically. The effects
of the Deborah number, retardation parameters, concentration
Rayleigh number, Prandtl number, and Lewis number on the
stability of the system were investigated. Results indicated that
there was competition among the processes of thermophoresis,
Brownian diffusion, and viscoelasticity which caused
oscillatory rather than stationary convection to occur.
Oscillatory instability is possible with both bottom- and
top-heavy nanoparticle distributions. Regimes of stationary and
oscillatory convection for various parameters were derived and
are discussed in detail.
Abstract: Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.
Abstract: The detection of outliers is very essential because of
their responsibility for producing huge interpretative problem in
linear as well as in nonlinear regression analysis. Much work has
been accomplished on the identification of outlier in linear
regression, but not in nonlinear regression. In this article we propose
several outlier detection techniques for nonlinear regression. The
main idea is to use the linear approximation of a nonlinear model and
consider the gradient as the design matrix. Subsequently, the
detection techniques are formulated. Six detection measures are
developed that combined with three estimation techniques such as the
Least-Squares, M and MM-estimators. The study shows that among
the six measures, only the studentized residual and Cook Distance
which combined with the MM estimator, consistently capable of
identifying the correct outliers.