Abstract: Today’s modern interconnected power system is
highly complex in nature. In this, one of the most important
requirements during the operation of the electric power system is the
reliability and security. Power and frequency oscillation damping
mechanism improve the reliability. Because of power system
stabilizer (PSS) low speed response against of major fault such as
three phase short circuit, FACTs devise that can control the network
condition in very fast time, are becoming popular. But FACTs
capability can be seen in a major fault present when nonlinear models
of FACTs devise and power system equipment are applied. To realize
this aim, the model of multi-machine power system with FACTs
controller is developed in MATLAB/SIMULINK using Sim Power
System (SPS) blockiest. Among the FACTs device, Static
synchronous series compensator (SSSC) due to high speed changes
its reactance characteristic inductive to capacitive, is effective power
flow controller. Tuning process of controller parameter can be
performed using different method. But Genetic Algorithm (GA)
ability tends to use it in controller parameter tuning process. In this
paper firstly POD controller is used to power oscillation damping.
But in this station, frequency oscillation dos not has proper damping
situation. So FOD controller that is tuned using GA is using that
cause to damp out frequency oscillation properly and power
oscillation damping has suitable situation.
Abstract: Underwater acoustic network is one of the rapidly
growing areas of research and finds different applications for
monitoring and collecting various data for environmental studies. The
communication among dynamic nodes and high error probability in
an acoustic medium forced to maximize energy consumption in
Underwater Sensor Networks (USN) than in traditional sensor
networks. Developing energy-efficient routing protocol is the
fundamental and a curb challenge because all the sensor nodes are
powered by batteries, and they cannot be easily replaced in UWSNs.
This paper surveys the various recent routing techniques that mainly
focus on energy efficiency.
Abstract: Wireless sensor network (WSN) is a network of many interconnected networked systems, they equipped with energy resources and they are used to detect other physical characteristics. On WSN, there are many researches are performed in past decades. WSN applicable in many security systems govern by military and in many civilian related applications. Thus, the security of WSN gets attention of researchers and gives an opportunity for many future aspects. Still, there are many other issues are related to deployment and overall coverage, scalability, size, energy efficiency, quality of service (QoS), computational power and many more. In this paper we discus about various applications and security related issue and requirements of WSN.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: Predicting earthquakes is an important issue in the
study of geography. Accurate prediction of earthquakes can help
people to take effective measures to minimize the loss of personal
and economic damage, such as large casualties, destruction of
buildings and broken of traffic, occurred within a few seconds.
United States Geological Survey (USGS) science organization
provides reliable scientific information about Earthquake Existed
throughout history & the Preliminary database from the National
Center Earthquake Information (NEIC) show some useful factors to
predict an earthquake in a seismic area like Aleutian Arc in the U.S.
state of Alaska. The main advantage of this prediction method that it
does not require any assumption, it makes prediction according to the
future evolution of the object's time series. The article compares
between simulation data result from trained BP and RBF neural
network versus actual output result from the system calculations.
Therefore, this article focuses on analysis of data relating to real
earthquakes. Evaluation results show better accuracy and higher
speed by using radial basis functions (RBF) neural network.
Abstract: This paper proposes the designing direct adaptive
neural controller to apply for a class of a nonlinear pendulum
dynamic system. The radial basis function (RBF) neural adaptive
controller is robust in presence of external and internal uncertainties.
Both the effectiveness of the controller and robustness against
disturbances are importance of this paper. The simulation results
show the promising performance of the proposed controller.
Abstract: The use of mobile phones is growing tremendously all
over the world. In Tanzania there are a number of operators licensed
by Tanzania Communications Regulatory Authority (TCRA) aiming
at attracting customers into their networks. So far
telecommunications market competition has been very stiff. Various
measures are being taken by mobile operators to survive in the
market. Such measure include introducing of different air time
bundles on daily, weekly and monthly at lower tariffs. Other
measures include the introduction of normal tariff, tourist package
and one network. Despite of all these strategies, there is a dynamic
competition in the market which needs to be explored. Some
influences which attract customers to choose a certain mobile
operator are of particular interest. This paper is investigating if the
network effects and Quality of Services (QoS) influence mobile
customers in selection of their mobile network operators. Seventy
seven students from high learning institutions in Dodoma
Municipality in Tanzania participated in responding to prepared
questionnaires. The data was analyzed using Statistical Package for
Social Science (SPSS) Software. The results indicate that, network
coverage does influence customers in selection of mobile operators.
In addition, this paper proposes further research in some areas
especially where the study came up with different findings from what
the theory has in place.
Abstract: Artificial Immune Systems (AIS), inspired by the
human immune system, are algorithms and mechanisms which are
self-adaptive and self-learning classifiers capable of recognizing and
classifying by learning, long-term memory and association. Unlike
other human system inspired techniques like genetic algorithms and
neural networks, AIS includes a range of algorithms modeling on
different immune mechanism of the body. In this paper, a mechanism
of a human immune system based on apoptosis is adopted to build an
Intrusion Detection System (IDS) to protect computer networks.
Features are selected from network traffic using Fisher Score. Based
on the selected features, the record/connection is classified as either
an attack or normal traffic by the proposed methodology. Simulation
results demonstrates that the proposed AIS based on apoptosis
performs better than existing AIS for intrusion detection.
Abstract: Wireless sensor network is vulnerable to a wide range
of attacks. Recover secrecy after compromise, to develop technique
that can detect intrusions and able to resilient networks that isolates
the point(s) of intrusion while maintaining network connectivity for
other legitimate users. To define new security metrics to evaluate
collaborative intrusion resilience protocol, by leveraging the sensor
mobility that allows compromised sensors to recover secure state
after compromise. This is obtained with very low overhead and in a
fully distributed fashion using extensive simulations support our
findings.
Abstract: The Quad Tree Decomposition based performance
analysis of compressed image data communication for lossy and
lossless through wireless sensor network is presented. Images have
considerably higher storage requirement than text. While transmitting
a multimedia content there is chance of the packets being dropped
due to noise and interference. At the receiver end the packets that
carry valuable information might be damaged or lost due to noise,
interference and congestion. In order to avoid the valuable
information from being dropped various retransmission schemes have
been proposed. In this proposed scheme QTD is used. QTD is an
image segmentation method that divides the image into homogeneous
areas. In this proposed scheme involves analysis of parameters such
as compression ratio, peak signal to noise ratio, mean square error,
bits per pixel in compressed image and analysis of difficulties during
data packet communication in Wireless Sensor Networks. By
considering the above, this paper is to use the QTD to improve the
compression ratio as well as visual quality and the algorithm in
MATLAB 7.1 and NS2 Simulator software tool.
Abstract: In the cloud computing hierarchy IaaS is the lowest
layer, all other layers are built over it. Thus it is the most important
layer of cloud and requisite more importance. Along with advantages
IaaS faces some serious security related issue. Mainly Security
focuses on Integrity, confidentiality and availability. Cloud
computing facilitate to share the resources inside as well as outside of
the cloud. On the other hand, cloud still not in the state to provide
surety to 100% data security. Cloud provider must ensure that end
user/client get a Quality of Service. In this report we describe
possible aspects of cloud related security.
Abstract: Botnets are one of the most serious and widespread
cyber threats. Today botnets have been facilitating many
cybercrimes, especially financial, top secret thefts. Botnets can be
available for lease in the market and are utilized by the
cybercriminals to launch massive attacks like DDoS, click fraud,
phishing attacks etc., Several large institutions, hospitals, banks,
government organizations and many social networks such as twitter,
facebook etc., became the target of the botmasters. Recently,
noteworthy researches have been carried out to detect bot, C&C
channels, botnet and botmasters. Using many sophisticated
technologies, botmasters made botnet a titan of the cyber world.
Innumerable challenges have been put forth by the botmasters to the
researchers in the detection of botnet. In this paper we present a
survey of different types of botnet C&C channels and also provide a
comparison of various botnet categories. Finally we hope that our
survey will create awareness for forthcoming botnet research
endeavors.
Abstract: Two micromechanical models for 3D smart composite
with embedded periodic or nearly periodic network of generally
orthotropic reinforcements and actuators are developed and applied to
cubic structures with unidirectional orientation of constituents.
Analytical formulas for the effective piezothermoelastic coefficients
are derived using the Asymptotic Homogenization Method (AHM).
Finite Element Analysis (FEA) is subsequently developed and used
to examine the aforementioned periodic 3D network reinforced smart
structures. The deformation responses from the FE simulations are
used to extract effective coefficients. The results from both
techniques are compared. This work considers piezoelectric materials
that respond linearly to changes in electric field, electric
displacement, mechanical stress and strain and thermal effects. This
combination of electric fields and thermo-mechanical response in
smart composite structures is characterized by piezoelectric and
thermal expansion coefficients. The problem is represented by unitcell
and the models are developed using the AHM and the FEA to
determine the effective piezoelectric and thermal expansion
coefficients. Each unit cell contains a number of orthotropic
inclusions in the form of structural reinforcements and actuators.
Using matrix representation of the coupled response of the unit cell,
the effective piezoelectric and thermal expansion coefficients are
calculated and compared with results of the asymptotic
homogenization method. A very good agreement is shown between
these two approaches.
Abstract: Distributed Generation (DG) can help in reducing the
cost of electricity to the costumer, relieve network congestion and
provide environmentally friendly energy close to load centers. Its
capacity is also scalable and it provides voltage support at distribution
level. Hence, DG placement and penetration level is an important
problem for both the utility and DG owner. DG allocation and capacity
determination is a nonlinear optimization problem. The objective
function of this problem is the minimization of the total loss of the
distribution system. Also high levels of penetration of DG are a new
challenge for traditional electric power systems. This paper presents a
new methodology for the optimal placement of DG and penetration
level of DG in distribution system based on General Algebraic
Modeling System (GAMS) and Genetic Algorithm (GA).
Abstract: In an urban area the location allocation of emergency
services mobile units, such as ambulances, police patrol cars must be
designed so as to achieve a prompt response to demand locations.
In this paper the partition of a given urban network into distinct
sub-networks is performed such that the vertices in each component
are close and simultaneously the sums of the corresponding
population in the sub-networks are almost uniform. The objective
here is to position appropriately in each sub-network a mobile
emergency unit in order to reduce the response time to the demands.
A mathematical model in framework of graph theory is developed.
In order to clarify the corresponding method a relevant numerical
example is presented on a small network.
Abstract: In this paper, we propose a new packing strategy to
find a free resource for run-time mapping of application tasks to
NoC-based Heterogeneous MPSoC. The proposed strategy minimizes
the task mapping time in addition to placing the communicating tasks
close to each other. To evaluate our approach, a comparative study is
carried out for a platform containing single task supported PEs.
Experiments show that our strategy provides better results when
compared to latest dynamic mapping strategies reported in the
literature.
Abstract: The handwriting is a physical demonstration of a
complex cognitive process learnt by man since his childhood. People
with disabilities or suffering from various neurological diseases are
facing so many difficulties resulting from problems located at the
muscle stimuli (EMG) or signals from the brain (EEG) and which
arise at the stage of writing. The handwriting velocity of the same
writer or different writers varies according to different criteria: age,
attitude, mood, writing surface, etc. Therefore, it is interesting to
reconstruct an experimental basis records taking, as primary
reference, the writing speed for different writers which would allow
studying the global system during handwriting process. This paper
deals with a new approach of the handwriting system modeling based
on the velocity criterion through the concepts of artificial neural
networks, precisely the Radial Basis Functions (RBF) neural
networks. The obtained simulation results show a satisfactory
agreement between responses of the developed neural model and the
experimental data for various letters and forms then the efficiency of
the proposed approaches.
Abstract: In this paper, we have proposed a parallel IDS and
honeypot based approach to detect and analyze the unknown and
known attack taxonomy for improving the IDS performance and
protecting the network from intruders. The main theme of our
approach is to record and analyze the intruder activities by using both
the low and high interaction honeypots. Our architecture aims to
achieve the required goals by combing signature based IDS,
honeypots and generate the new signatures. The paper describes the
basic component, design and implementation of this approach and
also demonstrates the effectiveness of this approach to reduce the
probability of network attacks.
Abstract: The reachable set bounding estimation for distributed
delay systems with disturbances is a new problem. In this paper,we
consider this problem subject to not only time varying delay and
polytopic uncertainties but also distributed delay systems which is
not studied fully untill now. we can obtain improved non-ellipsoidal
reachable set estimation for neural networks with time-varying delay
by the maximal Lyapunov-Krasovskii fuctional which is constructed
as the pointwise maximum of a family of Lyapunov-Krasovskii
fuctionals corresponds to vertexes of uncertain polytope.On the other
hand,matrix inequalities containing only one scalar and Matlabs
LMI Toolbox is utilized to give a non-ellipsoidal description of the
reachable set.finally,numerical examples are given to illustrate the
existing results.
Abstract: The world wide web network is a network with a
complex topology, the main properties of which are the distribution
of degrees in power law, A low clustering coefficient and a weak
average distance. Modeling the web as a graph allows locating the
information in little time and consequently offering a help in the
construction of the research engine. Here, we present a model based
on the already existing probabilistic graphs with all the aforesaid
characteristics. This work will consist in studying the web in order to
know its structuring thus it will enable us to modelize it more easily
and propose a possible algorithm for its exploration.