Abstract: It is well-known that in wireless local area networks,
authenticating nodes by their MAC addresses is not secure since it is
very easy for an attacker to learn one of the authorized addresses and
change his MAC address accordingly. In this paper, in order to
prevent MAC address spoofing attacks, we propose to use
dynamically changing MAC addresses and make each address usable
for only one session. The scheme we propose does not require any
change in 802.11 protocols and incurs only a small performance
overhead. One of the nice features of our new scheme is that no third
party can link different communication sessions of the same user by
monitoring MAC addresses therefore our scheme is preferable also
with respect to user privacy.
Abstract: This paper presents the voltage regulation scheme of
D-STATCOM under three-phase faults. It consists of the voltage
detection and voltage regulation schemes in the 0dq reference. The
proposed control strategy uses the proportional controller in which
the proportional gain, kp, is appropriately adjusted by using genetic
algorithms. To verify its use, a simplified 4-bus test system is situated
by assuming a three-phase fault at bus 4. As a result, the DSTATCOM
can resume the load voltage to the desired level within
1.8 ms. This confirms that the proposed voltage regulation scheme
performs well under three-phase fault events.
Abstract: RFID system, in which we give identification number to each item and detect it with radio frequency, supports more variable service than barcode system can do. For example, a refrigerator with RFID reader and internet connection will automatically notify expiration of food validity to us. But, in spite of its convenience, RFID system has some security threats, because anybody can get ID information of item easily. One of most critical threats is privacy invasion. Existing privacy protection schemes or systems have been proposed, and these schemes or systems defend normal users from attempts that any attacker tries to get information using RFID tag value. But, these systems still have weakness that attacker can get information using analogous value instead of original tag value. In this paper, we mention this type of attack more precisely and suggest 'Tag Broker Model', which can defend it. Tag broker in this model translates original tag value to random value, and user can only get random value. Attacker can not use analogous tag value, because he/she is not able to know original one from it.
Abstract: This paper proposes an adaptive sliding mode
controller which combines adaptive control and sliding
mode control to control a nonlinear robotic manipulator
with uncertain parameters. We use an adaptive algorithm
based on the concept of sliding mode control to alleviate the
chattering phenomenon of control input. Adaptive laws are
developed to obtain the gain of switching input and the
boundary layer parameters. The stability and convergence
of the robotic manipulator control system are guaranteed
by applying the Lyapunov theorem. Simulation results
demonstrate that the chattering of control input can be
alleviated effectively. The proposed controller scheme can
assure robustness against a large class of uncertainties and
achieve good trajectory tracking performance.
Abstract: A novel application of neural network approach to
fault classification and fault location of Medium voltage cables is
demonstrated in this paper. Different faults on a protected cable
should be classified and located correctly. This paper presents the use
of neural networks as a pattern classifier algorithm to perform these
tasks. The proposed scheme is insensitive to variation of different
parameters such as fault type, fault resistance, and fault inception
angle. Studies show that the proposed technique is able to offer high
accuracy in both of the fault classification and fault location tasks.
Abstract: In this paper, an magnetorheological (MR) mount with
fuzzy sliding mode controller (FSMC) is studied for vibration
suppression when the system is subject to base excitations. In recent
years, magnetorheological fluids are becoming a popular material in
the field of the semi-active control. However, the dynamic equation of
an MR mount is highly nonlinear and it is difficult to identify. FSMC
provides a simple method to achieve vibration attenuation of the
nonlinear system with uncertain disturbances. This method is capable
of handling the chattering problem of sliding mode control effectively
and the fuzzy control rules are obtained by using the Lyapunov
stability theory. The numerical simulations using one-dimension and
two-dimension FSMC show effectiveness of the proposed controller
for vibration suppression. Further, the well-known skyhook control
scheme and an adaptive sliding mode controller are also included in
the simulation for comparison with the proposed FSMC.
Abstract: Prediction of sinusoidal signals with time-varying
frequencies has been an important research topic in power electronics
systems. To solve this problem, we propose a new fuzzy
predictive filtering scheme, which is based on a Finite Impulse
Response (FIR) filter bank. Fuzzy logic is introduced here to provide
appropriate interpolation of individual filter outputs. Therefore,
instead of regular 'hard' switching, our method has the advantageous
'soft' switching among different filters. Simulation
comparisons between the fuzzy predictive filtering and conventional
filter bank-based approach are made to demonstrate that the
new scheme can achieve an enhanced prediction performance for
slowly changing sinusoidal input signals.
Abstract: In this paper we present a study of the impact of connection schemes on the performance of iterative decoding of Generalized Parallel Concatenated block (GPCB) constructed from one step majority logic decodable (OSMLD) codes and we propose a new connection scheme for decoding them. All iterative decoding connection schemes use a soft-input soft-output threshold decoding algorithm as a component decoder. Numerical result for GPCB codes transmitted over Additive White Gaussian Noise (AWGN) channel are provided. It will show that the proposed scheme is better than Hagenauer-s scheme and Lucas-s scheme [1] and slightly better than the Pyndiah-s scheme.
Abstract: Rotor Flux based Model Reference Adaptive System
(RF-MRAS) is the most popularly used conventional speed
estimation scheme for sensor-less IM drives. In this scheme, the
voltage model equations are used for the reference model. This
encounters major drawbacks at low frequencies/speed which leads to
the poor performance of RF-MRAS. Replacing the reference model
using Neural Network (NN) based flux estimator provides an
alternate solution and addresses such drawbacks. This paper
identifies an NN based flux estimator using Single Neuron Cascaded
(SNC) Architecture. The proposed SNC-NN model replaces the
conventional voltage model in RF-MRAS to form a novel MRAS
scheme named as SNC-NN-MRAS. Through simulation the proposed
SNC-NN-MRAS is shown to be promising in terms of all major
issues and robustness to parameter variation. The suitability of the
proposed SNC-NN-MRAS based speed estimator and its advantages
over RF-MRAS for sensor-less induction motor drives is
comprehensively presented through extensive simulations.
Abstract: Generalization is one of the most challenging issues
of Learning Classifier Systems. This feature depends on the
representation method which the system used. Considering the
proposed representation schemes for Learning Classifier System, it
can be concluded that many of them are designed to describe the
shape of the region which the environmental states belong and the
other relations of the environmental state with that region was
ignored. In this paper, we propose a new representation scheme
which is designed to show various relationships between the
environmental state and the region that is specified with a particular
classifier.
Abstract: An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.
Abstract: A block backward differentiation formula of uniform
order eight is proposed for solving first order stiff initial value
problems (IVPs). The conventional 8-step Backward Differentiation
Formula (BDF) and additional methods are obtained from the same
continuous scheme and assembled into a block matrix equation which
is applied to provide the solutions of IVPs on non-overlapping
intervals. The stability analysis of the method indicates that the
method is L0-stable. Numerical results obtained using the proposed
new block form show that it is attractive for solutions of stiff problems
and compares favourably with existing ones.
Abstract: This paper discusses a new heavy tailed distribution based data hiding into discrete cosine transform (DCT) coefficients of image, which provides statistical security as well as robustness against steganalysis attacks. Unlike other data hiding algorithms, the proposed technique does not introduce much effect in the stegoimage-s DCT coefficient probability plots, thus making the presence of hidden data statistically undetectable. In addition the proposed method does not compromise on hiding capacity. When compared to the generic block DCT based data-hiding scheme, our method found more robust against a variety of image manipulating attacks such as filtering, blurring, JPEG compression etc.
Abstract: In this paper, self-starting block hybrid method of
order (5,5,5,5)T is proposed for the solution of the special second
order ordinary differential equations with associated initial or
boundary conditions. The continuous hybrid formulations enable us
to differentiate and evaluate at some grids and off – grid points to
obtain four discrete schemes, which were used in block form for
parallel or sequential solutions of the problems. The computational
burden and computer time wastage involved in the usual reduction of
second order problem into system of first order equations are avoided
by this approach. Furthermore, a stability analysis and efficiency of
the block method are tested on stiff ordinary differential equations,
and the results obtained compared favorably with the exact solution.
Abstract: The performance of ground to deep space optical
communication systems is degraded by distortion of the beam as it
propagates through the turbulent atmosphere. Turbulence causes
fluctuations in the intensity of the received signal which ultimately
affects the acquisition time required to acquire and locate the spaceborne
target using narrow laser beam. In this paper, performance of
free-space optical (FSO) communication system in atmospheric
turbulence has been analyzed in terms of acquisition time for
coherent and non-coherent modulation schemes. Numerical results
presented in graphical and tabular forms show that the acquisition
time increases with the increase in turbulence level. This is true for
both schemes. The BPSK has lowest acquisition time among all
schemes. In non-coherent schemes, M-PPM performs better than the
other schemes. With the increase in M, acquisition time becomes
lower, but at the cost of increase in system complexity.
Abstract: Finding suitable non-supersingular elliptic curves for
pairing-based cryptosystems becomes an important issue for the
modern public-key cryptography after the proposition of id-based
encryption scheme and short signature scheme. In previous work
different algorithms have been proposed for finding such elliptic
curves when embedding degree k ∈ {3, 4, 6} and cofactor h ∈ {1, 2, 3,
4, 5}. In this paper a new method is presented to find more
non-supersingular elliptic curves for pairing-based cryptosystems with
general embedding degree k and large values of cofactor h. In
addition, some effective parameters of these non-supersingular elliptic
curves are provided in this paper.
Abstract: In this paper, we present a matrix game-theoretic cross-layer optimization formulation to maximize the network lifetime in wireless ad hoc networks with network coding. To this end, we introduce a cross-layer formulation of general NUM (network utility maximization) that accommodates routing, scheduling, and stream control from different layers in the coded networks. Specifically, for the scheduling problem and then the objective function involved, we develop a matrix game with the strategy sets of the players corresponding to hyperlinks and transmission modes, and design the payoffs specific to the lifetime. In particular, with the inherit merit that matrix game can be solved with linear programming, our cross-layer programming formulation can benefit from both game-based and NUM-based approaches at the same time by cooperating the programming model for the matrix game with that for the other layers in a consistent framework. Finally, our numerical example demonstrates its performance results on a well-known wireless butterfly network to verify the cross-layer optimization scheme.
Abstract: In this paper, we study statistical multiplexing of VBR
video in ATM networks. ATM promises to provide high speed realtime
multi-point to central video transmission for telemedicine
applications in rural hospitals and in emergency medical services.
Video coders are known to produce variable bit rate (VBR) signals
and the effects of aggregating these VBR signals need to be
determined in order to design a telemedicine network infrastructure
capable of carrying these signals. We first model the VBR video
signal and simulate it using a generic continuous-data autoregressive
(AR) scheme. We carry out the queueing analysis by the Fluid
Approximation Model (FAM) and the Markov Modulated Poisson
Process (MMPP). The study has shown a trade off: multiplexing
VBR signals reduces burstiness and improves resource utilization,
however, the buffer size needs to be increased with an associated
economic cost. We also show that the MMPP model and the Fluid
Approximation model fit best, respectively, the cell region and the
burst region. Therefore, a hybrid MMPP and FAM completely
characterizes the overall performance of the ATM statistical
multiplexer. The ramifications of this technology are clear: speed,
reliability (lower loss rate and jitter), and increased capacity in video
transmission for telemedicine. With migration to full IP-based
networks still a long way to achieving both high speed and high
quality of service, the proposed ATM architecture will remain of
significant use for telemedicine.
Abstract: Power line channel is proposed as an alternative for broadband data transmission especially in developing countries like Tanzania [1]. However the channel is affected by stochastic attenuation and deep notches which can lead to the limitation of channel capacity and achievable data rate. Various studies have characterized the channel without giving exactly the maximum performance and limitation in data transfer rate may be this is due to complexity of channel modeling being used. In this paper the channel performance of medium voltage, low voltage and indoor power line channel is presented. In the investigations orthogonal frequency division multiplexing (OFDM) with phase shift keying (PSK) as carrier modulation schemes is considered, for indoor, medium and low voltage channels with typical ten branches and also Golay coding is applied for medium voltage channel. From channels, frequency response deep notches are observed in various frequencies which can lead to reduce the achievable data rate. However, is observed that data rate up to 240Mbps is realized for a signal to noise ratio of about 50dB for indoor and low voltage channels, however for medium voltage a typical link with ten branches is affected by strong multipath and coding is required for feasible broadband data transfer.
Abstract: The African Great Lakes Region refers to the zone
around lakes Victoria, Tanganyika, Albert, Edward, Kivu, and
Malawi. The main source of electricity in this region is hydropower
whose systems are generally characterized by relatively weak,
isolated power schemes, poor maintenance and technical deficiencies
with limited electricity infrastructures. Most of the hydro sources are
rain fed, and as such there is normally a deficiency of water during
the dry seasons and extended droughts. In such calamities fossil fuels
sources, in particular petroleum products and natural gas, are
normally used to rescue the situation but apart from them being nonrenewable,
they also release huge amount of green house gases to our
environment which in turn accelerates the global warming that has at
present reached an amazing stage. Wind power is ample, renewable,
widely distributed, clean, and free energy source that does not
consume or pollute water. Wind generated electricity is one of the
most practical and commercially viable option for grid quality and
utility scale electricity production. However, the main shortcoming
associated with electric wind power generation is fluctuation in its
output both in space and time. Before making a decision to establish
a wind park at a site, the wind speed features there should therefore
be known thoroughly as well as local demand or transmission
capacity. The main objective of this paper is to utilise monthly
average wind speed data collected from one prospective site within
the African Great Lakes Region to demonstrate that the available
wind power there is high enough to generate electricity. The mean
monthly values were calculated from records gathered on hourly
basis for a period of 5 years (2001 to 2005) from a site in Tanzania.
The documentations that were collected at a height of 2 m were
projected to a height of 50 m which is the standard hub height of
wind turbines. The overall monthly average wind speed was found to
be 12.11 m/s whereas June to November was established to be the
windy season as the wind speed during the session is above the
overall monthly wind speed. The available wind power density
corresponding to the overall mean monthly wind speed was evaluated
to be 1072 W/m2, a potential that is worthwhile harvesting for the
purpose of electric generation.