Abstract: Linear stability analysis of wake-shear layers in twophase
shallow flows is performed in the present paper. Twodimensional
shallow water equations are used in the analysis. It is
assumed that the fluid contains uniformly distributed solid particles.
No dynamic interaction between the carrier fluid and particles is
expected in the initial moment. The stability calculations are
performed for different values of the particle loading parameter and
two other parameters which characterize the velocity ratio and the
velocity deficit. The results show that the particle loading parameter
has a stabilizing effect on the flow while the increase in the velocity
ratio or in the velocity deficit destabilizes the flow.
Abstract: The spectral action balance equation is an equation that
used to simulate short-crested wind-generated waves in shallow water
areas such as coastal regions and inland waters. This equation consists
of two spatial dimensions, wave direction, and wave frequency which
can be solved by finite difference method. When this equation with
dominating convection term are discretized using central differences,
stability problems occur when the grid spacing is chosen too coarse.
In this paper, we introduce the splitting upwind schemes for avoiding
stability problems and prove that it is consistent to the upwind scheme
with same accuracy. The splitting upwind schemes was adopted
to split the wave spectral action balance equation into four onedimensional
problems, which for each small problem obtains the
independently tridiagonal linear systems. For each smaller system
can be solved by direct or iterative methods at the same time which
is very fast when performed by a multi-processor computer.
Abstract: In the last decade, energy based control theory has undergone a significant breakthrough in dealing with underactated mechanical systems with two successful and similar tools, controlled Lagrangians and controlled Hamiltanians (IDA-PBC). However, because of the complexity of these tools, successful case studies are lacking, in particular, MIMO cases. The seminal theoretical paper of controlled Lagrangians proposed by Bloch and his colleagues presented a benchmark example–a 4 d.o.f underactuated pendulum on a cart but a detailed and completed design is neglected. To compensate this ignorance, the note revisit their design idea by addressing explicit control functions for a similar device motivated by a vector thrust body hovering in the air. To the best of our knowledge, this system is the first MIMO, underactuated example that is stabilized by using energy based tools at the courtesy of the original design idea. Some observations are given based on computer simulation.
Abstract: Cloud Computing has recently emerged as a
compelling paradigm for managing and delivering services over the
internet. The rise of Cloud Computing is rapidly changing the
landscape of information technology, and ultimately turning the longheld
promise of utility computing into a reality. As the development
of Cloud Computing paradigm is speedily progressing, concepts, and
terminologies are becoming imprecise and ambiguous, as well as
different technologies are interfering. Thus, it becomes crucial to
clarify the key concepts and definitions. In this paper, we present the
anatomy of Cloud Computing, covering its essential concepts,
prominent characteristics, its affects, architectural design and key
technologies. We differentiate various service and deployment
models. Also, significant challenges and risks need are tackled in
order to guarantee the long-term success of Cloud Computing. The
aim of this paper is to provide a better understanding of the anatomy
of Cloud Computing and pave the way for further research in this
area.
Abstract: The line sleeves on power transmission line connects
two conductors while the transmission line is constructing. However,
the line sleeves sometimes cause transmission line break down,
because the line sleeves are deteriorated and decayed by acid rain.
When the transmission line is broken, the economical loss is huge.
Therefore the line sleeves on power transmission lines should be
inspected periodically to prevent power failure. In this paper, Korea
Electric Power Research Institute reviewed several robots to inspect
line status and proposes a robot to inspect line sleeve by measuring
magnetic field on line sleeve. The developed inspection tool can
reliable to move along transmission line and overcome several
obstacles on transmission line. The developed system is also applied
on power transmission line and verified the efficiency of the robot.
Abstract: Software-as-a-Service (SaaS) is a form of cloud
computing that relieves the user of the burden of hardware and
software installation and management. SaaS can be used at the course
level to enhance curricula and student experience. When cloud
computing and SaaS are included in educational literature, the focus
is typically on implementing administrative functions. Yet, SaaS can
make more immediate and substantial contributions to the technical
course content in educational offerings. This paper explores cloud
computing and SaaS, provides examples, reports on experiences
using SaaS to offer specialized software in courses, and analyzes the
advantages and disadvantages of using SaaS at the course level. The
paper contributes to the literature in higher education by analyzing
the major technical concepts, potential, and constraints for using
SaaS to deliver specialized software at the course level. Further it
may enable more educators and students to benefit from this
emerging technology.
Abstract: Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.
Abstract: In this paper, a two-dimensional (2D) numerical
model for the tidal currents simulation in Persian Gulf is presented.
The model is based on the depth averaged equations of shallow water
which consider hydrostatic pressure distribution. The continuity
equation and two momentum equations including the effects of bed
friction, the Coriolis effects and wind stress have been solved. To
integrate the 2D equations, the Alternative Direction Implicit (ADI)
technique has been used. The base of equations discritization was
finite volume method applied on rectangular mesh. To evaluate the
model validation, a dam break case study including analytical
solution is selected and the comparison is done. After that, the
capability of the model in simulation of tidal current in a real field is
represented by modeling the current behavior in Persian Gulf. The
tidal fluctuations in Hormuz Strait have caused the tidal currents in
the area of study. Therefore, the water surface oscillations data at
Hengam Island on Hormoz Strait are used as the model input data.
The check point of the model is measured water surface elevations at
Assaluye port. The comparison between the results and the
acceptable agreement of them showed the model ability for modeling
marine hydrodynamic.
Abstract: This paper deals with heterogeneous autoregressive
models of realized volatility (HAR-RV models) on high-frequency
data of stock indices in the USA. Its aim is to capture the behavior of
three groups of market participants trading on a daily, weekly and
monthly basis and assess their role in predicting the daily realized
volatility. The benefits of this work lies mainly in the application of
heterogeneous autoregressive models of realized volatility on stock
indices in the USA with a special aim to analyze an impact of the
global financial crisis on applied models forecasting performance.
We use three data sets, the first one from the period before the global
financial crisis occurred in the years 2006-2007, the second one from
the period when the global financial crisis fully hit the U.S. financial
market in 2008-2009 years, and the last period was defined over
2010-2011 years. The model output indicates that estimated realized
volatility in the market is very much determined by daily traders and
in some cases excludes the impact of those market participants who
trade on monthly basis.
Abstract: As a part of evaluation system for R&D program, the
Korean government has applied feasibility analysis since 2008.
Various professionals put forth a great effort in order to catch up the
high degree of freedom of R&D programs, and make contributions to
evolving the feasibility analysis. We analyze diverse R&D programs
from various viewpoints, such as technology, policy, and Economics,
integrate the separate analysis, and finally arrive at a definite result;
whether a program is feasible or unfeasible. This paper describes the
concept and method of the feasibility analysis as a decision making
tool. The analysis unit and content of each criterion, which are key
elements in a comprehensive decision making structure, are examined
Abstract: Data mining, which is the exploration of
knowledge from the large set of data, generated as a result of
the various data processing activities. Frequent Pattern Mining
is a very important task in data mining. The previous
approaches applied to generate frequent set generally adopt
candidate generation and pruning techniques for the
satisfaction of the desired objective. This paper shows how
the different approaches achieve the objective of frequent
mining along with the complexities required to perform the
job. This paper will also look for hardware approach of cache
coherence to improve efficiency of the above process. The
process of data mining is helpful in generation of support
systems that can help in Management, Bioinformatics,
Biotechnology, Medical Science, Statistics, Mathematics,
Banking, Networking and other Computer related
applications. This paper proposes the use of both upward and
downward closure property for the extraction of frequent item
sets which reduces the total number of scans required for the
generation of Candidate Sets.
Abstract: We propose a method for discrimination and
classification of ovarian with benign, malignant and normal tissue
using independent component analysis and neural networks. The
method was tested for a proteomic patters set from A database, and
radial basis functions neural networks. The best performance was
obtained with probabilistic neural networks, resulting I 99% success
rate, with 98% of specificity e 100% of sensitivity.
Abstract: In this paper, we propose an effective relay
communication for layered video transmission as an alternative to
make the most of limited resources in a wireless communication
network where loss often occurs. Relaying brings stable multimedia
services to end clients, compared to multiple description coding
(MDC). Also, retransmission of only parity data about one or more
video layer using channel coder to the end client of the relay device is
paramount to the robustness of the loss situation. Using these
methods in resource-constrained environments, such as real-time user
created content (UCC) with layered video transmission, can provide
high-quality services even in a poor communication environment.
Minimal services are also possible. The mathematical analysis shows
that the proposed method reduced the probability of GOP loss rate
compared to MDC and raptor code without relay. The GOP loss rate
is about zero, while MDC and raptor code without relay have a GOP
loss rate of 36% and 70% in case of 10% frame loss rate.
Abstract: Microarrays technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.
Abstract: In this era of globalization, the role of the State in all aspects of development is widely debated. Some scholars contend the 'demise' and diminishing role of the State whilst others claim that the State is still “de facto developmental". Clearly, it is vital to ascertain which of these two contentions are reflective of the role of the State as nations ascend their development trajectories. Based on the findings of this paper, the perception that the Malaysian State plays an active and committed role towards distributing equitable educational opportunities and enhancing employability of Malaysian PWDs is actually a myth and not reality. Thus, in order to fulfill the promise of Vision 2020 to transform Malaysia into a caring and socially-inclusive society; this paper calls for a more interventionist and committed role by the Malaysian State to translate the universal rights of education and employment opportunities for PWDs from mere policy rhetoric into inclusive realities.
Abstract: We study the problem of decision making with Dempster-Shafer belief structure. We analyze the previous work developed by Yager about using the ordered weighted averaging (OWA) operator in the aggregation of the Dempster-Shafer decision process. We discuss the possibility of aggregating with an ascending order in the OWA operator for the cases where the smallest value is the best result. We suggest the introduction of the ordered weighted geometric (OWG) operator in the Dempster-Shafer framework. In this case, we also discuss the possibility of aggregating with an ascending order and we find that it is completely necessary as the OWG operator cannot aggregate negative numbers. Finally, we give an illustrative example where we can see the different results obtained by using the OWA, the Ascending OWA (AOWA), the OWG and the Ascending OWG (AOWG) operator.
Abstract: A simple approach is demonstrated for growing large
scale, nearly vertically aligned ZnO nanowire arrays by thermal
oxidation method. To reveal effect of temperature on growth and
physical properties of the ZnO nanowires, gold coated zinc substrates
were annealed at 300 °C and 400 °C for 4 hours duration in air. Xray
diffraction patterns of annealed samples indicated a set of well
defined diffraction peaks, indexed to the wurtzite hexagonal phase of
ZnO. The scanning electron microscopy studies show formation of
ZnO nanowires having length of several microns and average of
diameter less than 500 nm. It is found that the areal density of wires
is relatively higher, when the annealing is carried out at higher
temperature i.e. at 400°C. From the field emission studies, the values
of the turn-on and threshold field, required to draw emission current
density of 10 μA/cm2 and 100 μA/cm2 are observed to be 1.2 V/μm
and 1.7 V/μm for the samples annealed at 300 °C and 2.9 V/μm and
3.7 V/μm for that annealed at 400 °C, respectively. The field
emission current stability, investigated over duration of more than 2
hours at the preset value of 1 μA, is found to be fairly good in both
cases. The simplicity of the synthesis route coupled with the
promising field emission properties offer unprecedented advantage
for the use of ZnO field emitters for high current density
applications.
Abstract: This paper considers inference under progressive type II censoring with a compound Rayleigh failure time distribution. The maximum likelihood (ML), and Bayes methods are used for estimating the unknown parameters as well as some lifetime parameters, namely reliability and hazard functions. We obtained Bayes estimators using the conjugate priors for two shape and scale parameters. When the two parameters are unknown, the closed-form expressions of the Bayes estimators cannot be obtained. We use Lindley.s approximation to compute the Bayes estimates. Another Bayes estimator has been obtained based on continuous-discrete joint prior for the unknown parameters. An example with the real data is discussed to illustrate the proposed method. Finally, we made comparisons between these estimators and the maximum likelihood estimators using a Monte Carlo simulation study.
Abstract: Medical applications are among the most impactful
areas of microrobotics. The ultimate goal of medical microrobots is
to reach currently inaccessible areas of the human body and carry out
a host of complex operations such as minimally invasive surgery
(MIS), highly localized drug delivery, and screening for diseases at
their very early stages. Miniature, safe and efficient propulsion
systems hold the key to maturing this technology but they pose
significant challenges. A new type of propulsion developed recently,
uses multi-flagella architecture inspired by the motility mechanism of
prokaryotic microorganisms. There is a lack of efficient methods for
designing this type of propulsion system. The goal of this paper is to
overcome the lack and this way, a numerical strategy is proposed to
design multi-flagella propulsion systems. The strategy is based on the
implementation of the regularized stokeslet and rotlet theory, RFT
theory and new approach of “local corrected velocity". The effects of
shape parameters and angular velocities of each flagellum on overall
flow field and on the robot net forces and moments are considered.
Then a multi-layer perceptron artificial neural network is designed
and employed to adjust the angular velocities of the motors for
propulsion control. The proposed method applied successfully on a
sample configuration and useful demonstrative results is obtained.
Abstract: In this study, we examined gender differences in: (1) a
flexible remembering task, that asked for episodic memory decisions
at an item-specific versus category-based level, and (2) the retrieval
specificity of autobiographical memory during free recall.
Differences favouring women were found on both measures.
Furthermore, a significant association was observed, across gender
groups, between level of specificity in the autobiographical memory
interview and sensitivity to gist on the flexible remembering task.
These results suggest that similar cognitive processes may partially
contribute to both the ability for specific autobiographical recall and
the capacity for inhibition of gist-information on the flexible
remembering task.