Abstract: The most important part of modern lean low NOx combustors is a premixer where swirlers are often used for intensification of mixing processes and further formation of required flow pattern in combustor liner. Swirling flow leads to formation of complex eddy structures causing flow perturbations. It is able to cause combustion instability. Therefore, at design phase, it is necessary to pay great attention to aerodynamics of premixers. Analysis based on unsteady CFD modeling of swirling flow in production combustor swirler showed presence of large number of different eddy structures that can be conditionally divided into three types relative to its location of origin and a propagation path. Further, features of each eddy type were subsequently defined. Comparison of calculated and experimental pressure fluctuations spectrums verified correctness of computations.
Abstract: Composite materials have important assets compared
to traditional materials. They bring many functional advantages:
lightness, mechanical resistance and chemical, etc. In the present
study we examine the effect of a circular central notch and a precrack
on the tensile fracture of two woven composite materials. The tensile
tests were applied to a standardized specimen, notched and a
precarcked (orientation of the crack 0°, 45° and 90°). These tensile
tests were elaborated according to an experimental planning design of
the type 23.31 requiring 24 experiments with three repetitions. By the
analysis of regression, we obtained a mathematical model describing
the maximum load according to the influential parameters (hole
diameter, precrack length, angle of a precrack orientation). The
specimens precracked at 90° have a better behavior than those having
a precrack at 45° and still better than those having of the precracks
oriented at 0°. In addition the maximum load is inversely
proportional to the notch size.
Abstract: Color Histogram is considered as the oldest method
used by CBIR systems for indexing images. In turn, the global
histograms do not include the spatial information; this is why the
other techniques coming later have attempted to encounter this
limitation by involving the segmentation task as a preprocessing step.
The weak segmentation is employed by the local histograms while
other methods as CCV (Color Coherent Vector) are based on strong
segmentation. The indexation based on local histograms consists of
splitting the image into N overlapping blocks or sub-regions, and
then the histogram of each block is computed. The dissimilarity
between two images is reduced, as consequence, to compute the
distance between the N local histograms of the both images resulting
then in N*N values; generally, the lowest value is taken into account
to rank images, that means that the lowest value is that which helps to
designate which sub-region utilized to index images of the collection
being asked. In this paper, we make under light the local histogram
indexation method in the hope to compare the results obtained against
those given by the global histogram. We address also another
noteworthy issue when Relying on local histograms namely which
value, among N*N values, to trust on when comparing images, in
other words, which sub-region among the N*N sub-regions on which
we base to index images. Based on the results achieved here, it seems
that relying on the local histograms, which needs to pose an extra
overhead on the system by involving another preprocessing step
naming segmentation, does not necessary mean that it produces better
results. In addition to that, we have proposed here some ideas to
select the local histogram on which we rely on to encode the image
rather than relying on the local histogram having lowest distance with
the query histograms.
Abstract: Frequent pattern mining is the process of finding a
pattern (a set of items, subsequences, substructures, etc.) that occurs
frequently in a data set. It was proposed in the context of frequent
itemsets and association rule mining. Frequent pattern mining is used
to find inherent regularities in data. What products were often
purchased together? Its applications include basket data analysis,
cross-marketing, catalog design, sale campaign analysis, Web log
(click stream) analysis, and DNA sequence analysis. However, one of
the bottlenecks of frequent itemset mining is that as the data increase
the amount of time and resources required to mining the data
increases at an exponential rate. In this investigation a new algorithm
is proposed which can be uses as a pre-processor for frequent itemset
mining. FASTER (FeAture SelecTion using Entropy and Rough sets)
is a hybrid pre-processor algorithm which utilizes entropy and roughsets
to carry out record reduction and feature (attribute) selection
respectively. FASTER for frequent itemset mining can produce a
speed up of 3.1 times when compared to original algorithm while
maintaining an accuracy of 71%.
Abstract: The relationship between eigenstructure (eigenvalues
and eigenvectors) and latent structure (latent roots and latent vectors)
is established. In control theory eigenstructure is associated with
the state space description of a dynamic multi-variable system and
a latent structure is associated with its matrix fraction description.
Beginning with block controller and block observer state space forms
and moving on to any general state space form, we develop the
identities that relate eigenvectors and latent vectors in either direction.
Numerical examples illustrate this result. A brief discussion of the
potential of these identities in linear control system design follows.
Additionally, we present a consequent result: a quick and easy
method to solve the polynomial eigenvalue problem for regular matrix
polynomials.
Abstract: Frequent, continuous speech training has proven to be
a necessary part of a successful speech therapy process, but
constraints of traveling time and employment dispensation become
key obstacles especially for individuals living in remote areas or for
dependent children who have working parents. In order to ameliorate
speech difficulties with ample guidance from speech therapists, a
website has been developed that supports speech therapy and training
for people with articulation disorders in the standard Thai language.
This web-based program has the ability to record speech training
exercises for each speech trainee. The records will be stored in a
database for the speech therapist to investigate, evaluate, compare
and keep track of all trainees’ progress in detail. Speech trainees can
request live discussions via video conference call when needed.
Communication through this web-based program facilitates and
reduces training time in comparison to walk-in training or
appointments. This type of training also allows people with
articulation disorders to practice speech lessons whenever or
wherever is convenient for them, which can lead to a more regular
training processes.
Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: This paper clarifies the role of ICT capital in economic
growth. Albeit ICT remarkably contributes to economic growth, there
are few studies on ICT capital in ICT sector from theoretical point of
view. In this paper, production function of ICT which is used as input
of intermediate good in final good and ICT sectors is incorporated
into our model. In this setting, we analyze the role of ICT on balance
growth path and show the possibility of general equilibrium solutions
for this model. Through the simulation of the equilibrium solutions,
we find that when ICT impacts on economy and economic growth
increases, it is necessary that increases of efficiency at ICT sector and
of accumulation of non-ICT and ICT capitals occur simultaneously.
Abstract: From an organizational perspective, leaders are a
variation of the same talent pool in that they all score a larger than
average value on the bell curve that maps leadership behaviors and
characteristics, namely competence, vision, communication,
confidence, cultural sensibility, stewardship, empowerment,
authenticity, reinforcement, and creativity. The question that remains
unanswered and essentially unresolved is how to explain the irony
that leaders are so much alike yet their organizations diverge so
noticeably in their ability to innovate. Leadership intersects with
innovation at the point where human interactions get exceedingly
complex and where certain paradoxical forces cohabit: conflict with
conciliation, sovereignty with interdependence, and imagination with
realism. Rather than accepting that leadership is without context, we
argue that leaders are specialists of their domain and that those
effective at leading for innovation are distinct within the broader pool
of leaders. Keeping in view the extensive literature on leadership and
innovation, we carried out a quantitative study with data collected
over a five-year period involving 240 participants from across five
dissimilar companies based in the United States. We found that while
innovation and leadership are, in general, strongly interrelated (r =
.89, p = 0.0), there are five qualities that set leaders apart on
innovation. These qualities include a large radius of trust, a restless
curiosity with a low need for acceptance, an honest sense of self and
other, a sense for knowledge and creativity as the yin and yang of
innovation, and an ability to use multiple senses in the engagement
with followers. When these particular behaviors and characteristics
are present in leaders, organizations out-innovate their rivals by a
margin of 29.3 per cent to gain an unassailable edge in a business
environment that is regularly disruptive. A strategic outcome of this
study is a psychometric scale named iLeadership, proposed with the
underlying evidence, limitations, and potential for leadership and
innovation in organizations.c
Abstract: One of the major goals of Spoken Dialog Systems
(SDS) is to understand what the user utters.
In the SDS domain, the Spoken Language Understanding (SLU)
Module classifies user utterances by means of a pre-definite
conceptual knowledge. The SLU module is able to recognize only the
meaning previously included in its knowledge base. Due the vastity
of that knowledge, the information storing is a very expensive
process.
Updating and managing the knowledge base are time-consuming
and error-prone processes because of the rapidly growing number of
entities like proper nouns and domain-specific nouns. This paper
proposes a solution to the problem of Name Entity Recognition
(NER) applied to a SDS domain. The proposed solution attempts to
automatically recognize the meaning associated with an utterance by
using the PANKOW (Pattern based Annotation through Knowledge
On the Web) method at runtime.
The method being proposed extracts information from the Web to
increase the SLU knowledge module and reduces the development
effort. In particular, the Google Search Engine is used to extract
information from the Facebook social network.
Abstract: This paper presents a new meta-heuristic bio-inspired
optimization algorithm which is called Cuttlefish Algorithm (CFA).
The algorithm mimics the mechanism of color changing behavior of
the cuttlefish to solve numerical global optimization problems. The
colors and patterns of the cuttlefish are produced by reflected light
from three different layers of cells. The proposed algorithm considers
mainly two processes: reflection and visibility. Reflection process
simulates light reflection mechanism used by these layers, while
visibility process simulates visibility of matching patterns of the
cuttlefish. To show the effectiveness of the algorithm, it is tested with
some other popular bio-inspired optimization algorithms such as
Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and
Bees Algorithm (BA) that have been previously proposed in the
literature. Simulations and obtained results indicate that the proposed
CFA is superior when compared with these algorithms.
Abstract: Web search engines are designed to retrieve and
extract the information in the web databases and to return dynamic
web pages. The Semantic Web is an extension of the current web in
which it includes semantic content in web pages. The main goal of
semantic web is to promote the quality of the current web by
changing its contents into machine understandable form. Therefore,
the milestone of semantic web is to have semantic level information
in the web. Nowadays, people use different keyword- based search
engines to find the relevant information they need from the web.
But many of the words are polysemous. When these words are
used to query a search engine, it displays the Search Result Records
(SRRs) with different meanings. The SRRs with similar meanings are
grouped together based on Word Sense Disambiguation (WSD). In
addition to that semantic annotation is also performed to improve the
efficiency of search result records. Semantic Annotation is the
process of adding the semantic metadata to web resources. Thus the
grouped SRRs are annotated and generate a summary which
describes the information in SRRs. But the automatic semantic
annotation is a significant challenge in the semantic web. Here
ontology and knowledge based representation are used to annotate
the web pages.
Abstract: Male factor infertility due to endocrine disturbances
such as abnormalities in prolactin levels are encountered in a
significant proportion. This case control study was carried out to
determine the effects of prolactin on the male reproductive tract,
using 200 male white rats. The rats were maintained as the control
group (G1), hypoprolactinaemic group (G2), 3 hyperprolactinaemic
groups induced using oral largactil (G3), low dose fluphenazine (G4)
and high dose fluphenazine (G5). After 100 days, rats were subjected
to serum prolactin (PRL) level measurements and for basic seminal
fluid analysis (BSA). The difference between serum PRL
concentrations of rats in G2, G3, G4 and G5 as compared to the
control group were highly significant by Student’s t-test (p
Abstract: Concerns on corrosion and effective coating
protection of double hull tankers and bulk carriers in service have
been raised especially in water ballast tanks (WBTs). Test
protocols/methodologies specifically that which is incorporated in the
International Maritime Organisation (IMO), Performance Standard
for Protective Coatings for Dedicated Sea Water ballast tanks (PSPC)
are being used to assess and evaluate the performance of the coatings
for type approval prior to their application in WBTs. However, some
of the type approved coatings may be applied as very thick films to
less than ideally prepared steel substrates in the WBT. As such films
experience hygrothermal cycling from operating and environmental
conditions, they become embrittled which may ultimately result in
cracking. This embrittlement of the coatings is identified as an
undesirable feature in the PSPC but is not mentioned in the test
protocols within it. There is therefore renewed industrial research
aimed at understanding this issue in order to eliminate cracking and
achieve the intended coating lifespan of 15 years in good condition.
This paper will critically review test protocols currently used for
assessing and evaluating coating performance, particularly the IMO
PSPC.
Abstract: Lightning protection systems (LPS) for wind power
generation is becoming an important public issue. A serious damage
of blades, accidents where low-voltage and control circuit
breakdowns are frequently occur in many wind farms. A grounding
system is one of the most important components required for
appropriate LPSs in wind turbines WTs. Proper design of a wind
turbine grounding system is demanding and several factors for the
proper and effective implementation must taken into account. In this
paper proposed procedure of proper design of grounding systems for
a wind turbine was introduced. This procedure depends on measuring
of ground current of simulated wind farm under lightning taking into
consideration the soil ionization. The procedure also includes the
Ground Potential Rise (GPR) and the voltage distributions at ground
surface level and Touch potential. In particular, the contribution of
mitigating techniques, such as rings, rods and the proposed design
were investigated.
Abstract: The growth of wireless devices affects the availability
of limited frequencies or spectrum bands as it has been known that
spectrum bands are a natural resource that cannot be added.
Meanwhile, the licensed frequencies are idle most of the time.
Cognitive radio is one of the solutions to solve those problems.
Cognitive radio is a promising technology that allows the unlicensed
users known as secondary users (SUs) to access licensed bands
without making interference to licensed users or primary users (PUs).
As cloud computing has become popular in recent years, cognitive
radio networks (CRNs) can be integrated with cloud platform. One of
the important issues in CRNs is security. It becomes a problem since
CRNs use radio frequencies as a medium for transmitting and CRNs
share the same issues with wireless communication systems. Another
critical issue in CRNs is performance. Security has adverse effect to
performance and there are trade-offs between them. The goal of this
paper is to investigate the performance related to security trade-off in
CRNs with supporting cloud platforms. Furthermore, Queuing
Network Models with preemptive resume and preemptive repeat
identical priority are applied in this project to measure the impact of
security to performance in CRNs with or without cloud platform. The
generalized exponential (GE) type distribution is used to reflect the
bursty inter-arrival and service times at the servers. The results show
that the best performance is obtained when security is disabled and
cloud platform is enabled.
Abstract: This paper presents the design and analysis of Liquid
Crystal (LC) based tunable reflectarray antenna with different design
configurations within X-band frequency range. The effect of LC
volume used for unit cell element on frequency tunability and
reflection loss performance has been investigated. Moreover different
slot embedded patch element configurations have been proposed for
LC based tunable reflectarray antenna design with enhanced
performance. The detailed fabrication and measurement procedure
for different LC based unit cells has been presented. The waveguide
scattering parameter measured results demonstrated that by using the
circular slot embedded patch elements, the frequency tunability and
dynamic phase range can be increased from 180MHz to 200MHz and
120° to 124° respectively. Furthermore the circular slot embedded
patch element can be designed at 10GHz resonant frequency with a
patch volume of 2.71mm3 as compared to 3.47mm3 required for
rectangular patch without slot.
Abstract: Despite four years of study in the tourism industry, the
Bachelor’s graduates cannot perform their jobs as experienced tour
guides. This research aimed to develop French teaching and studying
for Tourism with two main purposes: to analyze ‘Moves’ used in oral
presentations at tourist attraction; and to study content in guiding
presentations or 'Guide Speak'. The study employed audio recording
of these presentations as an interview method in authentic situations,
having four tour guides as respondents and information providers.
The data was analyzed via moves and content analysis. The results
found that there were eight Moves used; namely, Welcoming,
Introducing oneself, Drawing someone’s attention, Giving
information, Explaining, Highlighting, Persuading and Saying
goodbye. In terms of content, the information being presented
covered the outstanding characteristics of the places and wellintegrated
with other related content. The findings were used as
guidelines for curriculum development; in particular, the core content
and the presentation forming the basis for students to meet the
standard requirements of the labor-market and professional schemes.
Abstract: This paper presents the voltage problem location
classification using performance of Least Squares Support Vector
Machine (LS-SVM) and Learning Vector Quantization (LVQ) in
electrical power system for proper voltage problem location
implemented by IEEE 39 bus New- England. The data was collected
from the time domain simulation by using Power System Analysis
Toolbox (PSAT). Outputs from simulation data such as voltage, phase
angle, real power and reactive power were taken as input to estimate
voltage stability at particular buses based on Power Transfer Stability
Index (PTSI).The simulation data was carried out on the IEEE 39 bus
test system by considering load bus increased on the system. To verify
of the proposed LS-SVM its performance was compared to Learning
Vector Quantization (LVQ). The results showed that LS-SVM is faster
and better as compared to LVQ. The results also demonstrated that the
LS-SVM was estimated by 0% misclassification whereas LVQ had
7.69% misclassification.
Abstract: In Egypt, girls have traditionally been educationally
disadvantaged. This disadvantage, however, has been focused on the
failure to enter school. Increasingly it is recognized that girls who
ever-enroll are at least as likely to complete primary and secondary
education as boys. Still the belief persists that girls, especially those
from poor families, will be disadvantaged in terms of school
expenditures and the transitions to secondary and higher education.
We examine expenditures on tutoring during the final year of
preparatory school, and the transition to specific tracks of secondary
education. Tests during the last year of preparatory largely determine
a student’s educational future. Results show that girls, even girls from
poor families, are not disadvantaged in terms of expenditures,
whether for tutoring, fees or general expenses. Moreover, girls are
more likely than boys to advance to general secondary education, the
track that leads to higher education.