Abstract: Serial Analysis of Gene Expression is a powerful
quantification technique for generating cell or tissue gene expression
data. The profile of the gene expression of cell or tissue in several
different states is difficult for biologists to analyze because of the large
number of genes typically involved. However, feature selection in
machine learning can successfully reduce this problem. The method
allows reducing the features (genes) in specific SAGE data, and
determines only relevant genes. In this study, we used a genetic
algorithm to implement feature selection, and evaluate the
classification accuracy of the selected features with the K-nearest
neighbor method. In order to validate the proposed method, we used
two SAGE data sets for testing. The results of this study conclusively
prove that the number of features of the original SAGE data set can be
significantly reduced and higher classification accuracy can be
achieved.
Abstract: Group contribution based models are widely used in
industrial applications for its convenience and flexibility. Although a
number of group contribution models have been proposed, there were
certain limitations inherent to those models. Models based on group
contribution excess Gibbs free energy are limited to low pressures and
models based on equation of state (EOS) cannot properly describe
highly nonideal mixtures including acids without introducing
additional modification such as chemical theory. In the present study
new a new approach derived from quantum chemistry have been used
to calculate necessary EOS group interaction parameters. The
COSMO-RS method, based on quantum mechanics, provides a
reliable tool for fluid phase thermodynamics. Benefits of the group
contribution EOS are the consistent extension to hydrogen-bonded
mixtures and the capability to predict polymer-solvent equilibria up to
high pressures. The authors are confident that with a sufficient
parameter matrix the performance of the lattice EOS can be improved
significantly.
Abstract: Wavelet transforms are multiresolution
decompositions that can be used to analyze signals and images.
Image compression is one of major applications of wavelet
transforms in image processing. It is considered as one of the most
powerful methods that provides a high compression ratio. However,
its implementation is very time-consuming. At the other hand,
parallel computing technologies are an efficient method for image
compression using wavelets. In this paper, we propose a parallel
wavelet compression algorithm based on quadtrees. We implement
the algorithm using MatlabMPI (a parallel, message passing version
of Matlab), and compute its isoefficiency function, and show that it is
scalable. Our experimental results confirm the efficiency of the
algorithm also.
Abstract: Among all mechanical joining processes, welding has
been employed for its advantage in design flexibility, cost saving,
reduced overall weight and enhanced structural performance.
However, for structures made of relatively thin components, welding
can introduce significant buckling distortion which causes loss of
dimensional control, structural integrity and increased fabrication
costs. Different parameters can affect buckling behavior of welded
thin structures such as, heat input, welding sequence, dimension of
structure. In this work, a 3-D thermo elastic-viscoplastic finite
element analysis technique is applied to evaluate the effect of shell
dimensions on buckling behavior and entropy generation of welded
thin shells. Also, in the present work, the approximated longitudinal
transient stresses which produced in each time step, is applied to the
3D-eigenvalue analysis to ratify predicted buckling time and
corresponding eigenmode. Besides, the possibility of buckling
prediction by entropy generation at each time is investigated and it is
found that one can predict time of buckling with drawing entropy
generation versus out of plane deformation. The results of finite
element analysis show that the length, span and thickness of welded
thin shells affect the number of local buckling, mode shape of global
buckling and post-buckling behavior of welded thin shells.
Abstract: This research work proposes a model of network security systems aiming to prevent production system in a data center from being attacked by intrusions. Conceptually, we introduce a decoy system as a part of the security system for luring intrusions, and apply network intrusion detection (NIDS), coupled with the decoy system to perform intrusion prevention. When NIDS detects an activity of intrusions, it will signal a redirection module to redirect all malicious traffics to attack the decoy system instead, and hence the production system is protected and safe. However, in a normal situation, traffic will be simply forwarded to the production system as usual. Furthermore, we assess the performance of the model with various bandwidths, packet sizes and inter-attack intervals (attacking frequencies).
Abstract: Cognitive radio devices have been considered as a key technology for next-generation of wireless communication. These devices in the context of IEEE 802.11 standards and IEEE 802.16 standards, can opportunistically utilize the wireless spectrum to achieve better user performance and improve the overall spectrumutilization efficiency, mainly in the unlicensed 5 GHz bands. However, opportunistic use of wireless spectrum creates news problems such as peaceful coexistence with other wireless technologies, such as the radiolocation systems, as well as understanding the influence of interference that each of these networks can create. In this paper, we suggest a dynamic access model that considerably reduces this interference and allows efficiency and fairness use of the wireless spectrum.
Abstract: The B'enard-Marangoni thermal instability problem for
a viscoelastic Jeffreys- fluid layer with internal heat generation is
investigated. The fluid layer is bounded above by a realistic free
deformable surface and by a plane surface below. Our analysis
shows that while the internal heat generation and the relaxation time
both destabilize the fluid layer, its stability may be enhanced by an
increased retardation time.
Abstract: India recognizes the personal laws of the various
religious communities that reside in the country. At the same time all
the institutions of the state in India are committed to the value of
secularism. This paper has been developed on the basis of a case
study that indicates the dynamics of religion in the working of the
lower judiciary in India. Majority of the commentary on religion and
the judiciary has focused on debates surrounding the existence and
application of personal laws. This paper, through a case study in the
lower judiciary, makes an attempt to examine whether the interface
between religion and the judiciary goes beyond personal laws.
The first part of this paper explains the history and application of
personal laws in social, political and legal contexts in India. The
second part examines the case study located in two courts of first
instance, following into the third part which provides an analysis of
the empirical evidence. The fourth part focuses on preliminary
observations about why there is a hesitancy to speak about religion in
relation to the working of the judicial system.
Abstract: A new interface circuit for capacitive sensor is
presented. This paper presents the design and simulation of soil
moisture capacitive sensor interface circuit based on phase
differential technique. The circuit has been designed and fabricated
using MIMOS- 0.35"m CMOS technology. Simulation and test
results show linear characteristic from 36 – 52 degree phase
difference, representing 0 – 100% in soil moisture level. Test result
shows the circuit has sensitivity of 0.79mV/0.10 phase difference,
translating into resolution of 10% soil moisture level.
Abstract: In order to meet the limits imposed on automotive
emissions, engine control systems are required to constrain air/fuel
ratio (AFR) in a narrow band around the stoichiometric value, due to
the strong decay of catalyst efficiency in case of rich or lean mixture.
This paper presents a model of a sample spark ignition engine and
demonstrates Simulink-s capabilities to model an internal combustion
engine from the throttle to the crankshaft output. We used welldefined
physical principles supplemented, where appropriate, with
empirical relationships that describe the system-s dynamic behavior
without introducing unnecessary complexity. We also presents a PID
tuning method that uses an adaptive fuzzy system to model the
relationship between the controller gains and the target output
response, with the response specification set by desired percent
overshoot and settling time. The adaptive fuzzy based input-output
model is then used to tune on-line the PID gains for different
response specifications. Experimental results demonstrate that better
performance can be achieved with adaptive fuzzy tuning relative to
similar alternative control strategies. The actual response
specifications with adaptive fuzzy matched the desired response
specifications.
Abstract: Innovation is more important in any companies.
However, it is not easy to measure the innovation performance
correctly. Patent is one of measuring index nowadays. This paper
wants to purpose an approach for valuing patents based on market
reaction to patent infringement litigations. The interesting
phenomenon is found from collection of patent infringement litigation
events. That is if any patent litigation event occurs the stock value will
follow changing. The plaintiffs- stock value raises some percentage.
According to this interesting phenomenon, the relationship between
patent litigation and stock value is tested and verified. And then, the
stock value variation is used to deduce the infringed patents- value.
The purpose of this study is providing another concept model to
evaluate the infringed patents. This study can provide a decision assist
system to help drafting patent litigation strategy and determine the
technology value
Abstract: A topologically oriented neural network is very
efficient for real-time path planning for a mobile robot in changing
environments. When using a recurrent neural network for this
purpose and with the combination of the partial differential equation
of heat transfer and the distributed potential concept of the network,
the problem of obstacle avoidance of trajectory planning for a
moving robot can be efficiently solved. The related dimensional
network represents the state variables and the topology of the robot's
working space. In this paper two approaches to problem solution are
proposed. The first approach relies on the potential distribution of
attraction distributed around the moving target, acting as a unique
local extreme in the net, with the gradient of the state variables
directing the current flow toward the source of the potential heat. The
second approach considers two attractive and repulsive potential
sources to decrease the time of potential distribution. Computer
simulations have been carried out to interrogate the performance of
the proposed approaches.
Abstract: In order to accommodate various multimedia
services, next generation wireless networks are characterized
by very high transmission bit rates. Thus, in such systems and
networks, the received signal is not only limited by noise but -
especially with increasing symbols rate often more
significantly by the intersymbol interference (ISI) caused by
the time dispersive radio channels such as those are used in
this work. This paper deals with the study of the performance
of detector for high bit rate transmission on some worst case
models of frequency selective fading channels for outdoor
mobile radio environments. This paper deals with a number of
different wireless channels with different power profiles and
different number of resolvable paths. All the radio channels
generated in this paper are for outdoor vehicular environments
with Doppler spread of 100 Hz. A carrier frequency of 1800
MHz is used and all the channels used in this work are such
that they are useful for next generation wireless systems.
Schemes for mitigation of ISI with adaptive equalizers of
different types have been investigated and their performances
have been investigated in terms of BER measured as a function
of SNR.
Abstract: One of the major cause of eye strain and other
problems caused while watching television is the relative illumination between the screen and its surrounding. This can be
overcome by adjusting the brightness of the screen with respect to the surrounding light. A controller based on fuzzy logic is proposed
in this paper. The fuzzy controller takes in the intensity of light
surrounding the screen and the present brightness of the screen as input. The output of the fuzzy controller is the grid voltage corresponding to the required brightness. This voltage is given to CRT and brightness is controller dynamically. For the given test system data, different de-fuzzifier methods have been implemented and the results are compared. In order to validate the effectiveness of
the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time system. The simulations are
performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time
applications.
Abstract: Skyline extraction in mountainous images can be used
for navigation of vehicles or UAV(unmanned air vehicles), but it is
very hard to extract skyline shape because of clutters like clouds, sea
lines and field borders in images. We developed the edge-based
skyline extraction algorithm using a proposed multistage edge filtering
(MEF) technique. In this method, characteristics of clutters in the
image are first defined and then the lines classified as clutters are
eliminated by stages using the proposed MEF technique. After this
processing, we select the last line using skyline measures among the
remained lines. This proposed algorithm is robust under severe
environments with clutters and has even good performance for
infrared sensor images with a low resolution. We tested this proposed
algorithm for images obtained in the field by an infrared camera and
confirmed that the proposed algorithm produced a better performance
and faster processing time than conventional algorithms.
Abstract: The development of the poultry industry in Albania is mainly based on the existence of intensive modern farms with huge capacities, which often are mixed with other forms. Colibacillosis is commonly displayed regardless of the type of breeding, delivering high mortality in poultry industry. The mechanisms with which pathogen enterobacters are able to cause the infection in poultry are not yet clear. The routine diagnose in the field, followed by isolation of E. coli and species of Salmonella genres in reference laboratories cannot lead in classification or full recognition of circulative strains in a territory, if it is not performed a differentiation among the present microorganisms in intensive farms and those in rural areas. In this study were isolated 1.496 strains of E. coli and 378 Salmonella spp. This study, presents distribution of poultry pathogenosity of E.coli and Salmonella spp., based on the usage of innovative diagnostic methods.
Abstract: Electric vehicle (EV) is one of the effective solutions to
control emission of greenhouses gases in the world. It is of interest
for future transportation due to its sustainability and efficiency by
automotive manufacturers. Various electrical motors have been used
for propulsion system of electric vehicles in last decades. In this
paper brushed DC motor, Induction motor (IM), switched reluctance
motor (SRM) and brushless DC motor (BLDC) are simulated and
compared. BLDC motor is recommended for high performance
electric vehicles. PWM switching technique is implemented for speed
control of BLDC motor. Behavior of different modes of PWM speed
controller of BLDC motor are simulated in MATLAB/SIMULINK.
BLDC motor characteristics are compared and discussed for various
PWM switching modes under normal and inverter fault conditions.
Comparisons and discussions are verified through simulation results.
Abstract: Electroencephalogram (EEG) recordings are often
contaminated with ocular and muscle artifacts. In this paper, the
canonical correlation analysis (CCA) is used as blind source
separation (BSS) technique (BSS-CCA) to decompose the artifact
contaminated EEG into component signals. We combine the BSSCCA
technique with wavelet filtering approach for minimizing both
ocular and muscle artifacts simultaneously, and refer the proposed
method as wavelet enhanced BSS-CCA. In this approach, after
careful visual inspection, the muscle artifact components are
discarded and ocular artifact components are subjected to wavelet
filtering to retain high frequency cerebral information, and then clean
EEG is reconstructed. The performance of the proposed wavelet
enhanced BSS-CCA method is tested on real EEG recordings
contaminated with ocular and muscle artifacts, for which power
spectral density is used as a quantitative measure. Our results suggest
that the proposed hybrid approach minimizes ocular and muscle
artifacts effectively, minimally affecting underlying cerebral activity
in EEG recordings.
Abstract: In this paper present a sensorless maximum wind power extraction for variable speed constant frequency (VSCF) wind power generation systems with a doubly-fed induction generators (DFIG), to ensure stability and to impose the ideal feedback control solution despite of model uncertainties , using the principles of an active and reactive power controller (DPC) a robust sliding mode power control has been proposed to guarantees fast response times and precise control actions for control the active and reactive power independently. The simulation results in MATLAB/Simulink platform confirmed the good dynamic performance of power control approach for DFIGbased variable speed wind turbines.
Abstract: Typical Intelligent Decision Support System is 4-based, its design composes of Data Warehouse, Online Analytical Processing, Data Mining and Decision Supporting based on models, which is called Decision Support System Based on Data Warehouse (DSSBDW). This way takes ETL,OLAP and DM as its implementing means, and integrates traditional model-driving DSS and data-driving DSS into a whole. For this kind of problem, this paper analyzes the DSSBDW architecture and DW model, and discusses the following key issues: ETL designing and Realization; metadata managing technology using XML; SQL implementing, optimizing performance, data mapping in OLAP; lastly, it illustrates the designing principle and method of DW in DSSBDW.