Abstract: The paper presents a novel idea to control computer
mouse cursor movement with human eyes. In this paper, a working
of the product has been described as to how it helps the special
people share their knowledge with the world. Number of traditional
techniques such as Head and Eye Movement Tracking Systems etc.
exist for cursor control by making use of image processing in which
light is the primary source. Electro-oculography (EOG) is a new
technology to sense eye signals with which the mouse cursor can be
controlled. The signals captured using sensors, are first amplified,
then noise is removed and then digitized, before being transferred to
PC for software interfacing.
Abstract: The study describes chitosan membrane platform
modified with nanostructure pattern which using nanotechnology to
fabricate. The cell-substrate interaction between neuro-2a neuroblasts
cell lines and chitosan membrane (flat, nanostructure and
nanostructure pattern types) was investigated. The adhered
morphology of neuro-2a cells depends on the topography of chitosan
surface. We have found that neuro-2a showed different morphogenesis
when cells adhered on flat and nanostructure chitosan membrane. The
cell projected area of neuro-2a on flat chitosan membrane is larger
than on nanostructure chitosan membrane. In addition, neuro-2a cells
preferred to adhere on flat chitosan surface region than on
nanostructure chitosan membrane to immobilize and differentiation.
The experiment suggests surface topography can be used as a critical
mechanism to isolate group of neuro-2a to a particular rectangle area
on chitosan membrane. Our finding will provide a platform to take
patch clamp to record electrophysiological behavior about neurons in
vitro in the future.
Abstract: In this paper we introduce the notion of protein interaction
network. This is a graph whose vertices are the protein-s
amino acids and whose edges are the interactions between them.
Using a graph theory approach, we identify a number of properties of
these networks. We compare them to the general small-world network
model and we analyze their hierarchical structure.
Abstract: The spin (ms) and orbital (mo) magnetic moment of
the antiferromagnetic NiO and MnO have been studied in the local
spin density approximation (LSDA+U) within full potential linear
muffin-tin orbital (FP-LMTO method with in the coulomb interaction
U varying from 0 to 10eV, exchange interaction J, from 0 to 1.0eV,
and volume compression VC in range of 0 to 80%. Our calculated
results shown that the spin magnetic moments and the orbital
magnetic moments increase linearly with increasing U and J. While
the interesting behaviour appears when volume compression is
greater than 70% for NiO and 50% for MnO at which ms collapses.
Further increase of volume compression to be at 80% leads to the
disappearance of both magnetic moments.
Abstract: Linear stability of wake-shear layers in two-phase
shallow flows is analyzed in the present paper. Stability analysis is
based on two-dimensional shallow water equations. 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. Linear stability curves are obtained for different
values of the particle loading parameter, the velocity ratio and the
velocity deficit. It is shown that the increase in the velocity ratio
destabilizes the flow. The particle loading parameter has a stabilizing
effect on the flow. The role of the velocity deficit is also
destabilizing: the increase of the velocity deficit leads to less stable
flow.
Abstract: Interactive public displays give access as an
innovative media to promote enhanced communication between
people and information. However, digital public displays are subject
to a few constraints, such as content presentation. Content
presentation needs to be developed to be more interesting to attract
people’s attention and motivate people to interact with the display. In
this paper, we proposed idea to implement contents with interaction
elements for vision-based digital public display. Vision-based
techniques are applied as a sensor to detect passers-by and theme
contents are suggested to attract their attention for encouraging them
to interact with the announcement content. Virtual object, gesture
detection and projection installation are applied for attracting
attention from passers-by. Preliminary study showed positive
feedback of interactive content designing towards the public display.
This new trend would be a valuable innovation as delivery of
announcement content and information communication through this
media is proven to be more engaging.
Abstract: Color categorization is shared among members in a
society. This allows communication of color, especially when using
natural language such as English. Hence sociable robot, to live
coexist with human in human society, must also have the shared
color categorization. To achieve this, many works have been done
relying on modeling of human color perception and mathematical
complexities. In contrast, in this work, the computer as brain of the
robot learns color categorization through interaction with humans
without much mathematical complexities.
Abstract: The adsorption of simulated aqueous solution containing textile remazol reactive dye, namely Red 3BS by palm shell activated carbon (PSAC) as adsorbent was carried out using Response Surface Methodology (RSM). A Box-Behnken design in three most important operating variables; initial dye concentration, dosage of adsorbent and speed of impeller was employed for experimental design and optimization of results. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95% confidence limits. Model indicated that with the increasing of dosage and speed give the result of removal up to 90% with the capacity uptake more than 7 mg/g. High regression coefficient between the variables and the response (R-Sq = 93.9%) showed of good evaluation of experimental data by polynomial regression model.
Abstract: In this work, we derive two numerical schemes for
solving a class of nonlinear partial differential equations. The first
method is of second order accuracy in space and time directions, the
scheme is unconditionally stable using Von Neumann stability
analysis, the scheme produced a nonlinear block system where
Newton-s method is used to solve it. The second method is of fourth
order accuracy in space and second order in time. The method is
unconditionally stable and Newton's method is used to solve the
nonlinear block system obtained. The exact single soliton solution
and the conserved quantities are used to assess the accuracy and to
show the robustness of the schemes. The interaction of two solitary
waves for different parameters are also discussed.
Abstract: A numerical study on the influence of electroosmotic flow on analyte preconcentration by isotachophoresis ( ITP) is made. We consider that the double layer induced electroosmotic flow ( EOF) counterbalance the electrophoretic velocity and a stationary ITP stacked zones results. We solve the Navier-Stokes equations coupled with the Nernst-Planck equations to determine the local convective velocity and the preconcentration dynamics of ions. Our numerical algorithm is based on a finite volume method along with a secondorder upwind scheme. The present numerical algorithm can capture the the sharp boundaries of step-changes ( plateau mode) or zones of steep gradients ( peak mode) accurately. The convection of ions due to EOF reduces the resolution of the ITP transition zones and produces a dispersion in analyte zones. The role of the electrokinetic parameters which induces dispersion is analyzed. A one-dimensional model for the area-averaged concentrations based on the Taylor-Aristype effective diffusivity is found to be in good agreement with the computed solutions.
Abstract: Facial expression analysis is rapidly becoming an
area of intense interest in computer science and human-computer
interaction design communities. The most expressive way humans
display emotions is through facial expressions. In this paper we
present a method to analyze facial expression from images by
applying Gabor wavelet transform (GWT) and Discrete Cosine
Transform (DCT) on face images. Radial Basis Function (RBF)
Network is used to classify the facial expressions. As a second stage,
the images are preprocessed to enhance the edge details and non
uniform down sampling is done to reduce the computational
complexity and processing time. Our method reliably works even
with faces, which carry heavy expressions.
Abstract: The effects of different parameters on the
hydrodynamics of trickle bed reactors were discussed for Newtonian
and non-Newtonian foaming systems. The varying parameters are
varying liquid velocities, gas flow velocities and surface tension. The
range for gas velocity is particularly large, thanks to the use of dense
gas to simulate very high pressure conditions. This data bank has
been used to compare the prediction accuracy of the different
trendlines and transition points from the literature. More than 240
experimental points for the trickle flow (GCF) and foaming pulsing
flow (PF/FPF) regime were obtained for present study.
Hydrodynamic characteristics involving dynamic liquid saturation
significantly influenced by gas and liquid flow rates. For 15 and 30
ppm air-aqueous surfactant solutions, dynamic liquid saturation
decreases with higher liquid and gas flow rates considerably in high
interaction regime. With decrease in surface tension i.e. for 45 and 60
ppm air-aqueous surfactant systems, effect was more pronounced
with decreases dynamic liquid saturation very sharply during regime
transition significantly at both low liquid and gas flow rates.
Abstract: Pairwise testing, which requires that every
combination of valid values of each pair of system factors be covered
by at lease one test case, plays an important role in software testing
since many faults are caused by unexpected 2-way interactions among
system factors. Although meta-heuristic strategies like simulated
annealing can generally discover smaller pairwise test suite, they may
cost more time to perform search, compared with greedy algorithms.
We propose a new method, improved Extremal Optimization (EO)
based on the Bak-Sneppen (BS) model of biological evolution, for
constructing pairwise test suites and define fitness function according
to the requirement of improved EO. Experimental results show that
improved EO gives similar size of resulting pairwise test suite and
yields an 85% reduction in solution time over SA.
Abstract: The PAX6, a transcription factor, is essential for the morphogenesis of the eyes, brain, pituitary and pancreatic islets. In rodents, the loss of Pax6 function leads to central nervous system defects, anophthalmia, and nasal hypoplasia. The haplo-insufficiency of Pax6 causes microphthalmia, aggression and other behavioral abnormalities. It is also required in brain patterning and neuronal plasticity. In human, heterozygous mutation of Pax6 causes loss of iris [aniridia], mental retardation and glucose intolerance. The 3- deletion in Pax6 leads to autism and aniridia. The phenotypes are variable in peneterance and expressivity. However, mechanism of function and interaction of PAX6 with other proteins during development and associated disease are not clear. It is intended to explore interactors of PAX6 to elucidated biology of PAX6 function in the tissues where it is expressed and also in the central regulatory pathway. This report describes In-silico approaches to explore interacting proteins of PAX6. The models show several possible proteins interacting with PAX6 like MITF, SIX3, SOX2, SOX3, IPO13, TRIM, and OGT. Since the Pax6 is a critical transcriptional regulator and master control gene of eye and brain development it might be interacting with other protein involved in morphogenesis [TGIF, TGF, Ras etc]. It is also presumed that matricelluar proteins [SPARC, thrombospondin-1 and osteonectin etc] are likely to interact during transport and processing of PAX6 and are somewhere its cascade. The proteins involved in cell survival and cell proliferation can also not be ignored.
Abstract: This work proposes a novel market-based air traffic flow control model considering competitive airlines in air traffic network. In the flow model, an agent based framework for resources (link/time pair) pricing is described. Resource agent and auctioneer for groups of resources are also introduced to simulate the flow management in Air Traffic Control (ATC). Secondly, the distributed group pricing algorithm is introduced, which efficiently reflect the competitive nature of the airline industry. Resources in the system are grouped according to the degree of interaction, and each auctioneer adjust s the price of one group of resources respectively until the excess demand of resources becomes zero when the demand and supply of resources of the system changes. Numerical simulation results show the feasibility of solving the air traffic flow control problem using market mechanism and pricing algorithms on the air traffic network.
Abstract: This paper presents an exact analytical model for
optimizing stability of thin-walled, composite, functionally graded
pipes conveying fluid. The critical flow velocity at which divergence
occurs is maximized for a specified total structural mass in order to
ensure the economic feasibility of the attained optimum designs. The
composition of the material of construction is optimized by defining
the spatial distribution of volume fractions of the material
constituents using piecewise variations along the pipe length. The
major aim is to tailor the material distribution in the axial direction so
as to avoid the occurrence of divergence instability without the
penalty of increasing structural mass. Three types of boundary
conditions have been examined; namely, Hinged-Hinged, Clamped-
Hinged and Clamped-Clamped pipelines. The resulting optimization
problem has been formulated as a nonlinear mathematical
programming problem solved by invoking the MatLab optimization
toolbox routines, which implement constrained function
minimization routine named “fmincon" interacting with the
associated eigenvalue problem routines. In fact, the proposed
mathematical models have succeeded in maximizing the critical flow
velocity without mass penalty and producing efficient and economic
designs having enhanced stability characteristics as compared with
the baseline designs.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: In this paper, a new time-delay estimation
technique based on the cross IB-energy operator [5] is
introduced. This quadratic energy detector measures how
much a signal is present in another one. The location of the
peak of the energy operator, corresponding to the maximum of
interaction between the two signals, is the estimate of the
delay. The method is a fully data-driven approach. The
discrete version of the continuous-time form of the cross IBenergy
operator, for its implementation, is presented. The
effectiveness of the proposed method is demonstrated on real
underwater acoustic signals arriving from targets and the
results compared to the cross-correlation method.
Abstract: High quality requirements analysis is one of the most
crucial activities to ensure the success of a software project, so that
requirements verification for software system becomes more and more
important in Requirements Engineering (RE) and it is one of the most
helpful strategies for improving the quality of software system.
Related works show that requirement elicitation and analysis can be
facilitated by ontological approaches and semantic web technologies.
In this paper, we proposed a hybrid method which aims to verify
requirements with structural and formal semantics to detect
interactions. The proposed method is twofold: one is for modeling
requirements with the semantic web language OWL, to construct a
semantic context; the other is a set of interaction detection rules which
are derived from scenario-based analysis and represented with
semantic web rule language (SWRL). SWRL based rules are working
with rule engines like Jess to reason in semantic context for
requirements thus to detect interactions. The benefits of the proposed
method lie in three aspects: the method (i) provides systematic steps
for modeling requirements with an ontological approach, (ii) offers
synergy of requirements elicitation and domain engineering for
knowledge sharing, and (3)the proposed rules can systematically assist
in requirements interaction detection.
Abstract: In this study we investigate silica nanoparticle (SiO2- NP) effects on the structure and phase properties of supported lipid monolayers and bilayers, coupling surface pressure measurements, fluorescence microscopy and atomic force microscopy. SiO2-NPs typically in size range of 10nm to 100 nm in diameter are tested. Our results suggest first that lipid molecules organization depends to their nature. Secondly, lipid molecules in the vinicity of big aggregates nanoparticles organize in liquid condensed phase whereas small aggregates are localized in both fluid liquid-expanded (LE) and liquid-condenced (LC). We demonstrated also by atomic force microscopy that by measuring friction forces it is possible to get information as if nanoparticle aggregates are recovered or not by lipid monolayers and bilayers.