Abstract: The electromagnetic spectrum is a natural resource
and hence well-organized usage of the limited natural resources is the
necessities for better communication. The present static frequency
allocation schemes cannot accommodate demands of the rapidly
increasing number of higher data rate services. Therefore, dynamic
usage of the spectrum must be distinguished from the static usage to
increase the availability of frequency spectrum. Cognitive radio is not
a single piece of apparatus but it is a technology that can incorporate
components spread across a network. It offers great promise for
improving system efficiency, spectrum utilization, more effective
applications, reduction in interference and reduced complexity of
usage for users. Cognitive radio is aware of its environmental,
internal state, and location, and autonomously adjusts its operations
to achieve designed objectives. It first senses its spectral environment
over a wide frequency band, and then adapts the parameters to
maximize spectrum efficiency with high performance. This paper
only focuses on the analysis of Bit-Error-Rate in cognitive radio by
using Particle Swarm Optimization Algorithm. It is theoretically as
well as practically analyzed and interpreted in the sense of
advantages and drawbacks and how BER affects the efficiency and
performance of the communication system.
Abstract: Fractional Fourier Transform is a generalization of the
classical Fourier Transform. The Fractional Fourier span in general
depends on the amplitude and phase functions of the signal and varies
with the transform order. However, with the development of the
Fractional Fourier filter banks, it is advantageous in some cases to
have different transform orders for different filter banks to achieve
better decorrelation of the windowed and overlapped time signal. We
present an expression that is useful for finding the perturbation in the
Fractional Fourier span due to the erroneous transform order and the
possible variation in the window shape and length. The expression is
based on the dependency of the time-Fractional Fourier span
Uncertainty on the amplitude and phase function of the signal. We
also show with the help of the developed expression that the
perturbation of span has a varying degree of sensitivity for varying
degree of transform order and the window coefficients.
Abstract: This project relates to a two-wheeled self balancing
robot for transferring loads on different locations along a path. This
robot specifically functions as a dual mode navigation to navigate
efficiently along a desired path. First, as a plurality of distance
sensors mounted at both sides of the body for collecting information
on tilt angle of the body and second, as a plurality of speed sensors
mounted at the bottom of the body for collecting information of the
velocity of the body in relative to the ground. A microcontroller for
processing information collected from the sensors and configured to
set the path and to balance the body automatically while a processor
operatively coupled to the microcontroller and configured to compute
change of the tilt and velocity of the body. A direct current motor
operatively coupled to the microcontroller for controlling the wheels
and characterized in that a remote control is operatively coupled to
the microcontroller to operate the robot in dual navigation modes.
Abstract: An information procuring and processing emerging technology wireless sensor network (WSN) Consists of autonomous nodes with versatile devices underpinned by applications. Nodes are equipped with different capabilities such as sensing, computing, actuation and wireless communications etc. based on application requirements. A WSN application ranges from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. The nodes are deployed independently to cooperatively monitor the physical and environmental conditions. The architecture of WSN differs based on the application requirements and focus on low cost, flexibility, fault tolerance capability, deployment process as well as conserve energy. In this paper we have present the characteristics, architecture design objective and architecture of WSN
Abstract: The sensitivity of UAVs to the atmospheric effects are
apparent. All the same the meteorological support for the UAVs
missions is often non-adequate or partly missing.
In our paper we show a new complex meteorological support
system for different types of UAVs pilots, specialists and decision
makers, too. The mentioned system has two important parts with
different forecasts approach such as the statistical and dynamical
ones.
The statistical prediction approach is based on a large
climatological data base and the special analog method which is able
to select similar weather situations from the mentioned data base to
apply them during the forecasting procedure.
The applied dynamic approach uses the specific WRF model runs
twice a day and produces 96 hours, high resolution weather forecast
for the UAV users over the Hungary. An easy to use web-based
system can give important weather information over the Carpathian
basin in Central-Europe. The mentioned products can be reached via
internet connection.
Abstract: In this work, the autoregressive vectors are used to
know dynamics of the Agricultural export and import, and the real
effective exchange rate (REER). In order to analyze the interactions,
the impulse- response function is used in decomposition of variance,
causality of Granger as well as the methodology of Johansen to know
the relations co integration. The REER causes agricultural export and
import in the sense of Granger. The influence displays the
innovations of the REER on the agricultural export and import is not
very great and the duration of the effects is short. It displays that
REER has an immediate positive effect, after the tenth year it
displays smooth results on the agricultural export. Evidence of a
vector exists co integration, In short run, REER has smaller effects
on export and import, compared to the long-run effects.
Abstract: Cognitive Dissonance can be conceived both as a concept related to the tendency to avoid internal contradictions in certain situations, and as a higher order theory about information processing in the human mind. In the last decades, this last sense has been strongly surpassed by the former, as nearly all experiment on the matter discuss cognitive dissonance as an output of motivational contradictions. In that sense, the question remains: is cognitive dissonance a process intrinsically associated with the way that the mind processes information, or is it caused by such specific contradictions? Objective: To evaluate the effects of cognitive dissonance in the absence of rewards or any mechanisms to manipulate motivation. Method: To solve this question, we introduce a new task, the hypothetical social arrays paradigm, which was applied to 50 undergraduate students. Results: Our findings support the perspective that the human mind shows a tendency to avoid internal dissonance even when there are no rewards or punishment involved. Moreover, our findings also suggest that this principle works outside the conscious level.
Abstract: Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.
Abstract: For the electrical metrics that describe photovoltaic
cell performance are inherently multivariate in nature, use of a
univariate, or one variable, statistical process control chart can have
important limitations. Development of a comprehensive process
control strategy is known to be significantly beneficial to reducing
process variability that ultimately drives up the manufacturing cost
photovoltaic cells. The multivariate moving average or MMA chart,
is applied to the electrical metrics of photovoltaic cells to illustrate
the improved sensitivity on process variability this method of control
charting offers. The result show the ability of the MMA chart to
expand to as any variables as needed, suggests an application
with multiple photovoltaic electrical metrics being used in
concert to determine the processes state of control.
Abstract: Hearing impairment is the number one chronic
disability affecting many people in the world. Background noise is
particularly damaging to speech intelligibility for people with
hearing loss especially for sensorineural loss patients. Several
investigations on speech intelligibility have demonstrated
sensorineural loss patients need 5-15 dB higher SNR than the normal
hearing subjects. This paper describes Discrete Hartley Transform
Power Normalized Least Mean Square algorithm (DHT-LMS) to
improve the SNR and to reduce the convergence rate of the Least
Means Square (LMS) for sensorineural loss patients. The DHT
transforms n real numbers to n real numbers, and has the convenient
property of being its own inverse. It can be effectively used for noise
cancellation with less convergence time. The simulated result shows
the superior characteristics by improving the SNR at least 9 dB for
input SNR with zero dB and faster convergence rate (eigenvalue ratio
12) compare to time domain method and DFT-LMS.
Abstract: Organizations are supposed to be systems and
consequently require defining the notion of equilibrium within.
However, organizations comprise people and unavoidably entail their
irrational aspects. Then, the question is what is the organizational
equilibrium and equilibrating mechanisms considering these aspects.
Hence, some arguments are provided here to conceptualize human
unconsciousness, irrationalities and consequent uncertainties within
organizations in the form of a system of psychic dynamism. The
assumption is this dynamism maintains the psychic balance of the
organization through a psychodynamic point of view. The resultant
conceptualization expected to promote the understanding of such
aspects in different organizational settings by hypothesizing
organizational equilibration from this perspective. As a result, the
main expectation is, if it is known that how the organization
equilibrates in this sense, we can explain and deal with such
irrationalities and unconsciousness by rational and, of course
conscious, planning and accomplishing.
Abstract: The next stage of the home networking environment is
supposed to be ubiquitous, where each piece of material is equipped
with an RFID (Radio Frequency Identification) tag. To fully support
the ubiquitous environment, home networking middleware should be
able to recommend home services based on a user-s interests and
efficiently manage information on service usage profiles for the users.
Therefore, USN (Ubiquitous Sensor Network) technology, which
recognizes and manages a appliance-s state-information (location,
capabilities, and so on) by connecting RFID tags is considered. The
Intelligent Multi-Agent Middleware (IMAM) architecture was
proposed to intelligently manage the mobile RFID-based home
networking and to automatically supply information about home
services that match a user-s interests. Evaluation results for
personalization services for IMAM using Bayesian-Net and Decision
Trees are presented.
Abstract: The purpose of this research is to develop and apply the
RSCMAC to enhance the dynamic accuracy of Global Positioning
System (GPS). GPS devices provide services of accurate positioning,
speed detection and highly precise time standard for over 98% area on
the earth. The overall operation of Global Positioning System includes
24 GPS satellites in space; signal transmission that includes 2
frequency carrier waves (Link 1 and Link 2) and 2 sets random
telegraphic codes (C/A code and P code), on-earth monitoring stations
or client GPS receivers. Only 4 satellites utilization, the client position
and its elevation can be detected rapidly. The more receivable
satellites, the more accurate position can be decoded. Currently, the
standard positioning accuracy of the simplified GPS receiver is greatly
increased, but due to affected by the error of satellite clock, the
troposphere delay and the ionosphere delay, current measurement
accuracy is in the level of 5~15m. In increasing the dynamic GPS
positioning accuracy, most researchers mainly use inertial navigation
system (INS) and installation of other sensors or maps for the
assistance. This research utilizes the RSCMAC advantages of fast
learning, learning convergence assurance, solving capability of
time-related dynamic system problems with the static positioning
calibration structure to improve and increase the GPS dynamic
accuracy. The increasing of GPS dynamic positioning accuracy can be
achieved by using RSCMAC system with GPS receivers collecting
dynamic error data for the error prediction and follows by using the
predicted error to correct the GPS dynamic positioning data. The
ultimate purpose of this research is to improve the dynamic positioning
error of cheap GPS receivers and the economic benefits will be
enhanced while the accuracy is increased.
Abstract: To distinguish small retinal hemorrhages in early
diabetic retinopathy from dust artifacts, we analyzed hue, lightness,
and saturation (HLS) color spaces. The fundus of 5 patients with
diabetic retinopathy was photographed. For the initial experiment, we
placed 4 different colored papers on the ceiling of a darkroom. Using
each color, 10 fragments of house dust particles on a magnifier were
photographed. The colored papers were removed, and 3 different
colored light bulbs were suspended from the ceiling. Ten fragments of
house dust particles on the camera-s object lens were photographed.
We then constructed an experimental device that can photograph
artificial eyes. Five fragments of house dust particles under the ocher
fundus of the artificial eye were photographed. On analyzing HLS
color space of the dust artifact, lightness and saturation were found to
be highly sensitive. However, hue was not highly sensitive.
Abstract: Smart Grids employ wireless sensor networks for
their control and monitoring. Sensors are characterized by limitations
in the processing power, energy supply and memory spaces, which
require a particular attention on the design of routing and data
management algorithms.
Since most routing algorithms for sensor networks, focus on
finding energy efficient paths to prolong the lifetime of sensor
networks, the power of sensors on efficient paths depletes quickly,
and consequently sensor networks become incapable of monitoring
events from some parts of their target areas. In consequence, the
design of routing protocols should consider not only energy
efficiency paths, but also energy efficient algorithms in general.
In this paper we propose an energy efficient routing protocol for
wireless sensor networks without the support of any location
information system. The reliability and the efficiency of this protocol
have been demonstrated by simulation studies where we compare
them to the legacy protocols. Our simulation results show that these
algorithms scale well with network size and density.
Abstract: Symbolic Circuit Analysis (SCA) is a technique used
to generate the symbolic expression of a network. It has become a
well-established technique in circuit analysis and design. The
symbolic expression of networks offers excellent way to perform
frequency response analysis, sensitivity computation, stability
measurements, performance optimization, and fault diagnosis. Many
approaches have been proposed in the area of SCA offering different
features and capabilities. Numerical Interpolation methods are very
common in this context, especially by using the Fast Fourier
Transform (FFT). The aim of this paper is to present a method for
SCA that depends on the use of Wavelet Transform (WT) as a
mathematical tool to generate the symbolic expression for large
circuits with minimizing the analysis time by reducing the number of
computations.
Abstract: Radio wave propagation on the road surface is a major
problem on wireless sensor network for traffic monitoring. In this
paper, we compare receiving signal strength on two scenarios 1) an
empty road and 2) a road with a vehicle. We investigate the effect of
antenna polarization and antenna height to the receiving signal
strength. The transmitting antenna is installed on the road surface.
The receiving signal is measured 360 degrees around the transmitting
antenna with the radius of 2.5 meters. Measurement results show the
receiving signal fluctuation around the transmitting antenna in both
scenarios. Receiving signal with vertical polarization antenna results
in higher signal strength than horizontal polarization antenna. The
optimum antenna elevation is 1 meter for both horizon and vertical
polarizations with the vehicle on the road. In the empty road, the
receiving signal level is unvarying with the elevation when the
elevation is greater than 1.5 meters.
Abstract: Nanocrystalline thin film of Na0.1V2O5.nH2O xerogel
obtained by sol gel synthesis was used as gas sensor. Gas sensing
properties of different gases such as hydrogen, petroleum and
humidity were investigated. Applying XRD and TEM the size of the
nanocrystals is found to be 7.5 nm. SEM shows a highly porous
structure with submicron meter-sized voids present throughout the
sample. FTIR measurement shows different chemical groups
identifying the obtained series of gels. The sample was n-type
semiconductor according to the thermoelectric power and electrical
conductivity. It can be seen that the sensor response curves from
130oC to 150oC show a rapid increase in sensitivity for all types of
gas injection, low response values for heating period and the rapid
high response values for cooling period. This result may suggest that
this material is able to act as gas sensor during the heating and
cooling process.
Abstract: 16-Mercaptohexadecanoic acid (MHDA) and tripeptide glutathione conjugated with gold nanoparticles (Au-NPs) are characterized by Fourier Transform InfaRared (FTIR) spectroscopy combined with Surface-enhanced Raman scattering (SERS) spectroscopy. Surface Plasmon Resonance (SPR) technique based on FTIR spectroscopy has become an important tool in biophysics, which is perspective for the study of organic compounds. FTIR-spectra of MHDA shows the line at 2500 cm-1 attributed to thiol group which is modified by presence of Au-NPs, suggesting the formation of bond between thiol group and gold. We also can observe the peaks originate from characteristic chemical group. A Raman spectrum of the same sample is also promising. Our preliminary experiments confirm that SERS-effect takes place for MHDA connected with Au-NPs and enable us to detected small number (less than 106 cm-2) of MHDA molecules. Combination of spectroscopy methods: FTIR and SERS – enable to study optical properties of Au- NPs and immobilized bio-molecules in context of a bio-nano-sensors.
Abstract: In this paper we present a novel design of a wearable
electronic textile. After defining a special application, we used the
specifications of some low power, tiny elements including sensors,
microcontrollers, transceivers, and a fault tolerant special topology to
have the most reliability as well as low power consumption and
longer lifetime. We have considered two different conditions as
normal and bodily critical conditions and set priorities for using
different sensors in various conditions to have a longer effective
lifetime.