Abstract: Underwater acoustic networks have attracted great
attention in the last few years because of its numerous applications.
High data rate can be achieved by efficiently modeling the physical
layer in the network protocol stack. In Acoustic medium,
propagation speed of the acoustic waves is dependent on many
parameters such as temperature, salinity, density, and depth.
Acoustic propagation speed cannot be modeled using standard
empirical formulas such as Urick and Thorp descriptions. In this
paper, we have modeled the acoustic channel using real time data of
temperature, salinity, and speed of Bay of Bengal (Indian Coastal
Region). We have modeled the acoustic channel by using Mackenzie
speed equation and real time data obtained from National Institute of
Oceanography and Technology. It is found that acoustic propagation
speed varies between 1503 m/s to 1544 m/s as temperature and
depth differs. The simulation results show that temperature, salinity,
depth plays major role in acoustic propagation and data rate
increases with appropriate data sets substituted in the simulated
model.
Abstract: Presently various computational techniques are used
in modeling and analyzing environmental engineering data. In the
present study, an intra-comparison of polynomial and radial basis
kernel functions based on Support Vector Regression and, in turn, an
inter-comparison with Multi Linear Regression has been attempted in
modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ
multiple plunging jets (varying from 1 to 16 numbers). The data set
used in this study consists of four input parameters with a total of
eighty eight cases, forty four each for vertical and inclined multiple
plunging jets. For testing, tenfold cross validation was used.
Correlation coefficient values of 0.971 and 0.981 along with
corresponding root mean square error values of 0.0025 and 0.0020
were achieved by using polynomial and radial basis kernel functions
based Support Vector Regression respectively. An intra-comparison
suggests improved performance by radial basis function in
comparison to polynomial kernel based Support Vector Regression.
Further, an inter-comparison with Multi Linear Regression
(correlation coefficient = 0.973 and root mean square error = 0.0024)
reveals that radial basis kernel functions based Support Vector
Regression performs better in modeling and estimating mass transfer
by multiple plunging jets.
Abstract: This paper presents a comparative analysis of
continuously stirred tank reactor (CSTR) control based on adaptive
control and optimal tuning of PID control based on particle swarm
optimization. In the design of adaptive control, Model reference
adaptive control (MRAC) scheme is used, in which the adaptation
law have been developed by MIT rule & Lyapunov’s rule. In PSO
control parameters of PID controller is tuned by using the concept of
particle swarm optimization to get optimized operating point for
minimum integral square error (ISE) condition. The results show the
adjustment of PID parameters converting into the optimal operating
point and the good control response can be obtained by the PSO
technique.
Abstract: Annihilations, phase shifts, scattering lengths and
elastic cross sections of low energy positrons scattering from
magnesium atoms were studied using the least-squares variational
method (LSVM). The possibility of positron binding to the
magnesium atoms is investigated. A trial wave function is suggested
to represent e+-Mg elastic scattering and scattering parameters were
derived to estimate the binding energy and annihilation rates. The
trial function is taken to depend on several adjustable parameters, and
is improved iteratively by increasing the number of terms. The
present results have the same behavior as reported semi-empirical,
theoretical and experimental results. Especially, the estimated
positive scattering length supports the possibility of positronmagnesium
bound state system that was confirmed in previous
experimental and theoretical work.
Abstract: Adequate and reliable estimates of aquifer parameters
are of utmost importance for proper management of vital
groundwater resources. At present scenario, the ground water is
polluted because of industrial waste disposed over the land and the
contaminants are transported in the aquifer from one area to another
area, which is depending on the characteristics of the aquifer and
contaminants. To know the contaminant transport, the accurate
estimation of aquifer properties is highly needed. Conventionally,
these properties are estimated through pumping tests carried out on
water wells. The occurrence and movement of ground water in the
aquifer are characteristically defined by the aquifer parameters. The
pumping (aquifer) test is the standard technique for estimating
various hydraulic properties of aquifer systems, viz., transmissivity
(T), hydraulic conductivity (K), storage coefficient (S) etc., for which
the graphical method is widely used. The study area for conducting
pumping test is Pydibheemavaram Industrial area near the coastal
belt of Srikulam, AP, India. The main objective of the present work is
to estimate the aquifer properties for developing contaminant
transport model for the study area.
Abstract: Graphene, a single-atom sheet, has been considered as
the most promising material for making future nanoelectromechanical
systems as well as purely electrical switching with graphene
transistors. Graphene-based devices have advantages in scaled-up
device fabrication due to the recent progress in large area graphene
growth and lithographic patterning of graphene nanostructures. Here
we investigated its mechanical responses of circular graphene
nanoflake under the nanoindentation using classical molecular
dynamics simulations. A correlation between the load and the
indentation depth was constructed. The nanoindented force in this
work was applied to the center point of the circular graphene nanoflake
and then, the resonance frequency could be tuned by a nanoindented
depth. We found the hardening or the softening of the graphene
nanoflake during its nanoindented-deflections, and such properties
were recognized by the shift of the resonance frequency. The
calculated mechanical parameters in the force-vs-deflection plot were
in good agreement with previous experimental and theoretical works.
This proposed schematics can detect the pressure via the deflection
change or/and the resonance frequency shift, and also have great
potential for versatile applications in nanoelectromechanical systems.
Abstract: Maintaining factory default battery endurance rate
over time in supporting huge amount of running applications on
energy-restricted mobile devices has created a new challenge for
mobile applications developer. While delivering customers’
unlimited expectations, developers are barely aware of efficient use
of energy from the application itself. Thus, developers need a set of
valid energy consumption indicators in assisting them to develop
energy saving applications. In this paper, we present a few software
product metrics that can be used as an indicator to measure energy
consumption of Android-based mobile applications in the early of
design stage. In particular, Trepn Profiler (Power profiling tool for
Qualcomm processor) has used to collect the data of mobile
application power consumption, and then analyzed for the 23
software metrics in this preliminary study. The results show that
McCabe cyclomatic complexity, number of parameters, nested block
depth, number of methods, weighted methods per class, number of
classes, total lines of code and method lines have direct relationship
with power consumption of mobile application.
Abstract: Exact solution of an unsteady MHD flow of elasticoviscous
fluid through a porous media in a tube of elliptic cross
section under the influence of magnetic field and constant pressure
gradient has been obtained in this paper. Initially, the flow is
generated by a constant pressure gradient. After attaining the steady
state, the pressure gradient is suddenly withdrawn and the resulting
fluid motion in a tube of elliptical cross section by taking into
account of the porosity factor and magnetic parameter of the
bounding surface is investigated. The problem is solved in two-stages
the first stage is a steady motion in tube under the influence of a
constant pressure gradient, the second stage concern with an unsteady
motion. The problem is solved employing separation of variables
technique. The results are expressed in terms of a non-dimensional
porosity parameter, magnetic parameter and elastico-viscosity
parameter, which depends on the Non-Newtonian coefficient. The
flow parameters are found to be identical with that of Newtonian case
as elastic-viscosity parameter, magnetic parameter tends to zero, and
porosity tends to infinity. The numerical results were simulated in
MATLAB software to analyze the effect of Elastico-viscous
parameter, porosity parameter, and magnetic parameter on velocity
profile. Boundary conditions were satisfied. It is seen that the effect
of elastico-viscosity parameter, porosity parameter and magnetic
parameter of the bounding surface has significant effect on the
velocity parameter.
Abstract: In this paper, a comparative performance analysis of
mostly used four nonlinearity cancellation techniques used to realize
the passive resistor by MOS transistors, is presented. The comparison
is done by using an integrator circuit which is employing sequentially
Op-amp, OTRA and ICCII as active element. All of the circuits are
implemented by MOS-C realization and simulated by PSPICE
program using 0.35μm process TSMC MOSIS model parameters.
With MOS-C realization, the circuits became electronically tunable
and fully integrable which is very important in IC design. The output
waveforms, frequency responses, THD analysis results and features
of the nonlinearity cancellation techniques are also given.
Abstract: People, throughout the history, have made estimates
and inferences about the future by using their past experiences.
Developing information technologies and the improvements in the
database management systems make it possible to extract useful
information from knowledge in hand for the strategic decisions.
Therefore, different methods have been developed. Data mining by
association rules learning is one of such methods. Apriori algorithm,
one of the well-known association rules learning algorithms, is not
commonly used in spatio-temporal data sets. However, it is possible
to embed time and space features into the data sets and make Apriori
algorithm a suitable data mining technique for learning spatiotemporal
association rules. Lake Van, the largest lake of Turkey, is a
closed basin. This feature causes the volume of the lake to increase or
decrease as a result of change in water amount it holds. In this study,
evaporation, humidity, lake altitude, amount of rainfall and
temperature parameters recorded in Lake Van region throughout the
years are used by the Apriori algorithm and a spatio-temporal data
mining application is developed to identify overflows and newlyformed
soil regions (underflows) occurring in the coastal parts of
Lake Van. Identifying possible reasons of overflows and underflows
may be used to alert the experts to take precautions and make the
necessary investments.
Abstract: In this study, the commercial finite element software
ABAQUS was used to develop a three-dimensional nonlinear finite
element model capable of simulating the pull-out test of reinforcing
bars from underwater concrete. The results of thirty-two pull-out tests
that have different parameters were implemented in the software to
study the effect of the concrete cover, the bar size, the use of stirrups,
and the compressive strength of concrete. The interaction properties used in the model provided accurate
results in comparison with the experimental bond-slip results, thus
the model has successfully simulated the pull-out test. The results of
the finite element model are used to better understand and visualize
the distribution of stresses in each component of the model, and to
study the effect of the various parameters used in this study including
the role of the stirrups in preventing the stress from reaching to the
sides of the specimens.
Abstract: During machining process, chatter is an unavoidable
phenomenon. Boring bars possess the cantilever shape and due to
this, it is subjected to chatter. The adverse effect of chatter includes
the increase in temperature which will leads to excess tool wear. To
overcome these problems, in this investigation, Cartridge brass (Cu –
70% and Zn – 30%) is passively fixed on the boring bar and also
clearance is provided in order to reduce the displacement, tool wear
and cutting temperature. A conventional all geared lathe is attached
with vibrometer and pyrometer is used to measure the displacement
and temperature. The influence of input parameters such as cutting
speed, depth of cut and clearance on temperature, tool wear and
displacement are investigated for various cutting conditions. From
the result, the optimum conditions to obtain better damping in boring
process for chatter reduction is identified.
Abstract: This study, tries to suggest a design method based on
displacement using finite difference numerical modeling in
reinforcing soil retaining wall with steel strip. In this case, dynamic
loading characteristics such as duration, frequency, peak ground
acceleration, geometrical characteristics of reinforced soil structure
and type of the site are considered to correct the pseudo static method
and finally introduce the pseudo static coefficient as a function of
seismic performance level and peak ground acceleration. For this
purpose, the influence of dynamic loading characteristics,
reinforcement length, height of reinforced system and type of the site
are investigated on seismic behavior of reinforcing soil retaining wall
with steel strip. Numerical results illustrate that the seismic response
of this type of wall is highly dependent to cumulative absolute
velocity, maximum acceleration, and height and reinforcement length
so that the reinforcement length can be introduced as the main factor
in shape of failure. Considering the loading parameters, geometric parameters of the
wall and type of the site showed that the used method in this study
leads to efficient designs in comparison with other methods, which
are usually based on limit-equilibrium concept. The outputs show the
over-estimation of equilibrium design methods in comparison with
proposed displacement based methods here.
Abstract: This study focuses on the hydro-geology and chemical
constituents analysis of Ikogosi Warm Spring waters in South West
Nigeria. Ikogosi warm spring is a global tourist attraction because it
has both warm and cold spring sources. Water samples from the cold
spring, warm spring and the meeting point were collected, analyzed
and the result shows close similarity in temperature, hydrogen iron
concentration (pH), alkalinity, hardness, Calcium, Magnesium,
Sodium, Iron, total dissolved solid and heavy metals. The measured
parameters in the water samples are within World Health
Organisation standards for fresh water. The study of the geology of
the warm spring reveals that the study area is underlain by a group of
slightly migmatised to non-migmatised paraschists and meta-igneous
rocks. Also, concentration levels of selected heavy metals, (Copper,
Cadmium, Zinc, Arsenic and Cromium) were determined in the water
(ppm) samples. Chromium had the highest concentration value of
1.52ppm (an average of 49.67%) and Cadmium had the lowest
concentration with value of 0.15ppm (an average of 4.89%).
Comparison of these results showed that, their mean levels are within
the standard values obtained in Nigeria. It can be concluded that both
warm and spring water are safe for drinking.
Abstract: In the context of the handwriting recognition, we
propose an off line system for the recognition of the Arabic
handwritten words of the Algerian departments. The study is based
mainly on the evaluation of neural network performances, trained
with the gradient back propagation algorithm. The used parameters to
form the input vector of the neural network are extracted on the
binary images of the handwritten word by several methods. The
Distribution parameters, the centered moments of the different
projections of the different segments, the centered moments of the
word image coding according to the directions of Freeman, and the
Barr features applied binary image of the word and on its different
segments. The classification is achieved by a multi layers perceptron.
A detailed experiment is carried and satisfactory recognition results
are reported.
Abstract: The need to save time and cost of soil testing at the
planning stage of road work has necessitated developing predictive
models. This study proposes a model for predicting the dry density of
lateritic soils stabilized with corn cob ash (CCA) and blended cement
- CCA. Lateritic soil was first stabilized with CCA at 1.5, 3.0, 4.5 and
6% of the weight of soil and then stabilized with the same
proportions as replacement for cement. Dry density, specific gravity,
maximum degree of saturation and moisture content were determined
for each stabilized soil specimen, following standard procedure.
Polynomial equations containing alpha and beta parameters for CCA
and blended CCA-cement were developed. Experimental values were
correlated with the values predicted from the Matlab curve fitting
tool, and the Solver function of Microsoft Excel 2010. The correlation
coefficient (R2) of 0.86 was obtained indicating that the model could
be accepted in predicting the maximum dry density of CCA stabilized
soils to facilitate quick decision making in roadworks.
Abstract: Extreme formation is a theoretical concept of selfsustain
flight when a big airliner is followed by a small UAV glider
flying in the airliner wake vortex. The paper presents results of a
climb analysis with the goal to lift the gliding UAV to airliners cruise
altitude. Wake vortex models, the UAV drag polar and basic
parameters and airliner’s climb profile are introduced at first.
Afterwards, flight performance of the UAV in a wake vortex is
evaluated by analytical methods. Time history of optimal distance
between an airliner and the UAV during a climb is determined. The
results are encouraging. Therefore available UAV drag margin for
electricity generation is figured out for different vortex models.
Abstract: This article presents the main results of a numerical
investigation on the uncertainty of dynamic response of structures
with statistically correlated random damping Gamma distributed. A
computational method based on a Linear Statistical Model (LSM) is
implemented to predict second order statistics for the response of a
typical industrial building structure. The significance of random
damping with correlated parameters and its implications on the
sensitivity of structural peak response in the neighborhood of a
resonant frequency are discussed in light of considerable ranges of
damping uncertainties and correlation coefficients. The results are
compared to those generated using Monte Carlo simulation
techniques. The numerical results obtained show the importance of
damping uncertainty and statistical correlation of damping
coefficients when obtaining accurate probabilistic estimates of
dynamic response of structures. Furthermore, the effectiveness of the
LSM model to efficiently predict uncertainty propagation for
structural dynamic problems with correlated damping parameters is
demonstrated.
Abstract: Modelling of building processes of a multimodal
freight transportation support information system is discussed based
on modern CASE technologies. Functional efficiencies of ports in
the eastern part of the Black Sea are analyzed taking into account
their ecological, seasonal, resource usage parameters. By resources,
we mean capacities of berths, cranes, automotive transport, as well as
work crews and neighbouring airports. For the purpose of designing
database of computer support system for Managerial (Logistics)
function, using Object-Role Modeling (ORM) tool (NORMA–Natural ORM Architecture) is proposed, after which Entity
Relationship Model (ERM) is generated in automated process.
Software is developed based on Process-Oriented and Service-Oriented architecture, in Visual Studio.NET environment.
Abstract: A mixed method for model order reduction is
presented in this paper. The denominator polynomial is derived by
matching both Markov parameters and time moments, whereas
numerator polynomial derivation and error minimization is done
using Genetic Algorithm. The efficiency of the proposed method can
be investigated in terms of closeness of the response of reduced order
model with respect to that of higher order original model and a
comparison of the integral square error as well.