Abstract: The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.
Abstract: As the information age matures, major social
infrastructures such as communication, finance, military and energy,
have become ever more dependent on information communication
systems. And since these infrastructures are connected to the Internet,
electronic intrusions such as hacking and viruses have become a new
security threat. Especially, disturbance or neutralization of a major
social infrastructure can result in extensive material damage and social
disorder. To address this issue, many nations around the world are
researching and developing various techniques and information
security policies as a government-wide effort to protect their
infrastructures from newly emerging threats. This paper proposes an
evaluation method for information security levels of CIIP (Critical
Information Infrastructure Protection), which can enhance the security
level of critical information infrastructure by checking the current
security status and establish security measures accordingly to protect
infrastructures effectively.
Abstract: The carbon based coils with the nanometer scale have
the 3 dimension helix geometry. We synthesized the carbon nano-coils
by the use of chemical vapor deposition technique with iron and tin as
the catalysts. The fabricated coils have the external diameter of
ranging few hundred nm to few thousand nm. The Scanning
Electro-Microscope (SEM) and Tunneling Electro-Microscope has
shown detail images of the coil-s structure. The fabrication of the
carbon nano-coils can be grown on the metal and non-metal substrates,
such as the stainless steel and silicon substrates. Besides growth on the
flat substrate; they also can be grown on the stainless steel wires. After
the synthesis of the coils, the mechanical and electro-mechanical
property is measured. The experimental results were reported.
Abstract: One of the essential components of much of DSP
application is noise cancellation. Changes in real time signals are
quite rapid and swift. In noise cancellation, a reference signal which
is an approximation of noise signal (that corrupts the original
information signal) is obtained and then subtracted from the noise
bearing signal to obtain a noise free signal. This approximation of
noise signal is obtained through adaptive filters which are self
adjusting. As the changes in real time signals are abrupt, this needs
adaptive algorithm that converges fast and is stable. Least mean
square (LMS) and normalized LMS (NLMS) are two widely used
algorithms because of their plainness in calculations and
implementation. But their convergence rates are small. Adaptive
averaging filters (AFA) are also used because they have high
convergence, but they are less stable. This paper provides the
comparative study of LMS and Normalized NLMS, AFA and new
enhanced average adaptive (Average NLMS-ANLMS) filters for noise
cancelling application using speech signals.
Abstract: The hidden-point bar method is useful in many
surveying applications. The method involves determining the
coordinates of a hidden point as a function of horizontal and vertical
angles measured to three fixed points on the bar. Using these
measurements, the procedure involves calculating the slant angles,
the distances from the station to the fixed points, the coordinates of
the fixed points, and then the coordinates of the hidden point. The
propagation of the measurement errors in this complex process has
not been fully investigated in the literature. This paper evaluates the
effect of the bar geometry on the position accuracy of the hidden
point which depends on the measurement errors of the horizontal and
vertical angles. The results are used to establish some guidelines
regarding the inclination angle of the bar and the location of the
observed points that provide the best accuracy.
Abstract: This study examines the use of the persuasive strategy
of deixis and personalization in advertising slogans. This rhetorical/
stylistic and linguistic strategy has been found to be widely used in
advertising slogans for over a century. A total of five hundred
advertising slogans of multinational companies in both product and
service sectors were obtained. The analysis reveals the 3 main
components of this strategy as being deictic words, absolute
uniqueness and personal pronouns. The percentage and mean of the
use of the 3 components are tabulated. The findings show that
advertisers have used this persuasive strategy in creative ways to
persuade consumers to buy their products and services.
Abstract: It is by reason of the unified measure of varieties of resources and the unified processing of the disposal of varieties of resources, that these closely related three of new basic models called the resources assembled node and the disposition integrated node as well as the intelligent organizing node are put forth in this paper; the three closely related quantities of integrative analytical mechanics including the disposal intensity and disposal- weighted intensity as well as the charge of resource charge are set; and then the resources assembled space and the disposition integrated space as well as the intelligent organizing space are put forth. The system of fundamental equations and model of complete factor synergetics is preliminarily approached for the general situation in this paper, to form the analytical base of complete factor synergetics. By the essential variables constituting this system of equations we should set twenty variables respectively with relation to the essential dynamical effect, external synergetic action and internal synergetic action of the system.
Abstract: The aim of this paper is to introduce a parametric
distribution model in fatigue life reliability analysis dealing with
variation in material properties. Service loads in terms of responsetime
history signal of Belgian pave were replicated on a multi-axial
spindle coupled road simulator and stress-life method was used to
estimate the fatigue life of automotive stub axle. A PSN curve was
obtained by monotonic tension test and two-parameter Weibull
distribution function was used to acquire the mean life of the
component. A Pearson system was developed to evaluate the fatigue
life reliability by considering stress range intercept and slope of the
PSN curve as random variables. Considering normal distribution of
fatigue strength, it is found that the fatigue life of the stub axle to
have the highest reliability between 10000 – 15000 cycles. Taking
into account the variation of material properties associated with the
size effect, machining and manufacturing conditions, the method
described in this study can be effectively applied in determination of
probability of failure of mass-produced parts.
Abstract: Currently, many types of no-reversible compressed
sound source, represented by MP3 (MPEG Audio Layer-3) are
popular in the world and they are widely used to make the music file
size smaller. The sound data created in this way has less information as
compared to pre-compressed data. The objective of this study is by
analyzing EEG to determine if people can recognize such difference as
differences in sound. A measurement system that can measure and
analyze EEG when a subject listens to music were experimentally
developed. And ten subjects were studied with this system. In this
experiment, a WAVE formatted music data and a MP3 compressed
music data that is made from the WAVE formatted data were
prepared. Each subject was made to hear these music sources at the
same volume. From the results of this experiment, clear differences
were confirmed between two wound sources.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: In this paper, the potential use of an exponential
hidden Markov model to model a hidden pavement deterioration
process, i.e. one that is not directly measurable, is investigated. It is
assumed that the evolution of the physical condition, which is the
hidden process, and the evolution of the values of pavement distress
indicators, can be adequately described using discrete condition states
and modeled as a Markov processes. It is also assumed that condition
data can be collected by visual inspections over time and represented
continuously using an exponential distribution. The advantage of
using such a model in decision making process is illustrated through
an empirical study using real world data.
Abstract: In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.
Abstract: Applying a rigorous process to optimize the elements
of a supply-chain network resulted in reduction of the waiting time
for a service provider and customer. Different sources of downtime
of hydraulic pressure controller/calibrator (HPC) were causing
interruptions in the operations. The process examined all the issues to
drive greater efficiencies. The issues included inherent design issues
with HPC pump, contamination of the HPC with impurities, and the
lead time required for annual calibration in the USA.
HPC is used for mandatory testing/verification of formation
tester/pressure measurement/logging-while drilling tools by oilfield
service providers, including Halliburton.
After market study andanalysis, it was concluded that the current
HPC model is best suited in the oilfield industry. To use theexisting
HPC model effectively, design andcontamination issues were
addressed through design and process improvements. An optimum
network is proposed after comparing different supply-chain models
for calibration lead-time reduction.
Abstract: The ideal sinc filter, ignoring the noise statistics, is often
applied for generating an arbitrary sample of a bandlimited signal by
using the uniformly sampled data. In this article, an optimal interpolator is proposed; it reaches a minimum mean square error (MMSE)
at its output in the presence of noise. The resulting interpolator is
thus a Wiener filter, and both the optimal infinite impulse response
(IIR) and finite impulse response (FIR) filters are presented. The
mean square errors (MSE-s) for the interpolator of different length
impulse responses are obtained by computer simulations; it shows that
the MSE-s of the proposed interpolators with a reasonable length are
improved about 0.4 dB under flat power spectra in noisy environment with signal-to-noise power ratio (SNR) equal 10 dB. As expected,
the results also demonstrate the improvements for the MSE-s with various fractional delays of the optimal interpolator against the ideal
sinc filter under a fixed length impulse response.
Abstract: One of the biggest drawbacks of the wireless
environment is the limited bandwidth. However, the users sharing
this limited bandwidth have been increasing considerably. SDMA
technique which entails using directional antennas allows to increase
the capacity of a wireless network by separating users in the medium.
In this paper, it has been presented how the capacity can be enhanced
while the mean delay is reduced by using directional antennas in
wireless networks employing TDMA/FDD MAC. Computer
modeling and simulation of the wireless system studied are realized
using OPNET Modeler. Preliminary simulation results are presented
and the performance of the model using directional antennas is
evaluated and compared consistently with the one using
omnidirectional antennas.
Abstract: In this paper, based on the past project cost and time
performance, a model for forecasting project cost performance is
developed. This study presents a probabilistic project control concept
to assure an acceptable forecast of project cost performance. In this
concept project activities are classified into sub-groups entitled
control accounts. Then obtain the Stochastic S-Curve (SS-Curve), for
each sub-group and the project SS-Curve is obtained by summing
sub-groups- SS-Curves. In this model, project cost uncertainties are
considered through Beta distribution functions of the project
activities costs required to complete the project at every selected time
sections through project accomplishment, which are extracted from a
variety of sources. Based on this model, after a percentage of the
project progress, the project performance is measured via Earned
Value Management to adjust the primary cost probability distribution
functions. Then, accordingly the future project cost performance is
predicted by using the Monte-Carlo simulation method.
Abstract: Improving performance measures in the construction
processes has been a major concern for managers and decision
makers in the industry. They seek for ways to recognize the key
factors which have the largest effect on the process. Identifying such
factors can guide them to focus on the right parts of the process in
order to gain the best possible result. In the present study design of
experiment (DOE) has been applied to a computer simulation model
of brick laying process to determine significant factors while
productivity has been chosen as the response of the experiment. To
this end, four controllable factors and their interaction have been
experimented and the best factor level has been calculated for each
one. The results indicate that three factors, namely, labor of brick,
labor of mortar and inter arrival time of mortar along with interaction
of labor of brick and labor of mortar are significant.
Abstract: Radio propagation from point-to-point is affected by
the physical channel in many ways. A signal arriving at a destination
travels through a number of different paths which are referred to as
multi-paths. Research in this area of wireless communications has
progressed well over the years with the research taking different
angles of focus. By this is meant that some researchers focus on
ways of reducing or eluding Multipath effects whilst others focus on
ways of mitigating the effects of Multipath through compensation
schemes. Baseband processing is seen as one field of signal
processing that is cardinal to the advancement of software defined
radio technology. This has led to wide research into the carrying out
certain algorithms at baseband. This paper considers compensating
for Multipath for Frequency Modulated signals. The compensation
process is carried out at Radio frequency (RF) and at Quadrature
baseband (QBB) and the results are compared. Simulations are
carried out using MatLab so as to show the benefits of working at
lower QBB frequencies than at RF.
Abstract: The paper presents an optimization study based on
genetic algorithms (GA-s) for a radio-frequency applicator used in
heating dielectric band products. The weakly coupled electro-thermal
problem is analyzed using 2D-FEM. The design variables in the
optimization process are: the voltage of a supplementary “guard"
electrode and six geometric parameters of the applicator. Two
objective functions are used: temperature uniformity and total active
power absorbed by the dielectric. Both mono-objective and multiobjective
formulations are implemented in GA optimization.
Abstract: Rotation or tilt present in an image capture by digital
means can be detected and corrected using Artificial Neural Network
(ANN) for application with a Face Recognition System (FRS). Principal
Component Analysis (PCA) features of faces at different angles
are used to train an ANN which detects the rotation for an input image
and corrected using a set of operations implemented using another
system based on ANN. The work also deals with the recognition
of human faces with features from the foreheads, eyes, nose and
mouths as decision support entities of the system configured using
a Generalized Feed Forward Artificial Neural Network (GFFANN).
These features are combined to provide a reinforced decision for
verification of a person-s identity despite illumination variations. The
complete system performing facial image rotation detection, correction
and recognition using re-enforced decision support provides a
success rate in the higher 90s.