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: In this paper, the effect of receive and/or transmit
antenna spacing on the performance (BER vs. SNR) of multipleantenna
systems is determined by using an RCS (Radar Cross
Section) channel model. In this physical model, the scatterers
existing in the propagation environment are modeled by their RCS so
that the correlation of the receive signal complex amplitudes, i.e.,
both magnitude and phase, can be estimated. The proposed RCS
channel model is then compared with classical models.
Abstract: Adapting wireless devices to communicate within grid
networks empowers us by providing range of possibilities.. These
devices create a mechanism for consumers and publishers to create
modern networks with or without peer device utilization. Emerging
mobile networks creates new challenges in the areas of reliability,
security, and adaptability. In this paper, we propose a system
encompassing mobility management using AAA context transfer for
mobile grid networks. This system ultimately results in seamless task
processing and reduced packet loss, communication delays,
bandwidth, and errors.
Abstract: In this paper, Wavelet based ANFIS for finding inter
turn fault of generator is proposed. The detector uniquely responds to
the winding inter turn fault with remarkably high sensitivity.
Discrimination of different percentage of winding affected by inter
turn fault is provided via ANFIS having an Eight dimensional input
vector. This input vector is obtained from features extracted from
DWT of inter turn faulty current leaving the generator phase
winding. Training data for ANFIS are generated via a simulation of
generator with inter turn fault using MATLAB. The proposed
algorithm using ANFIS is giving satisfied performance than ANN
with selected statistical data of decomposed levels of faulty current.
Abstract: The back-propagation algorithm calculates the weight
changes of an artificial neural network, and a two-term algorithm
with a dynamically optimal learning rate and a momentum factor
is commonly used. Recently the addition of an extra term, called a
proportional factor (PF), to the two-term BP algorithm was proposed.
The third term increases the speed of the BP algorithm. However,
the PF term also reduces the convergence of the BP algorithm, and
optimization approaches for evaluating the learning parameters are
required to facilitate the application of the three terms BP algorithm.
This paper considers the optimization of the new back-propagation
algorithm by using derivative information. A family of approaches
exploiting the derivatives with respect to the learning rate, momentum
factor and proportional factor is presented. These autonomously
compute the derivatives in the weight space, by using information
gathered from the forward and backward procedures. The three-term
BP algorithm and the optimization approaches are evaluated using
the benchmark XOR problem.
Abstract: This paper describes the application of a model
predictive controller to the problem of batch reactor temperature
control. Although a great deal of work has been done to improve
reactor throughput using batch sequence control, the control of the
actual reactor temperature remains a difficult problem for many
operators of these processes. Temperature control is important as
many chemical reactions are sensitive to temperature for formation of
desired products. This controller consist of two part (1) a nonlinear
control method GLC (Global Linearizing Control) to create a linear
model of system and (2) a Model predictive controller used to obtain
optimal input control sequence. The temperature of reactor is tuned
to track a predetermined temperature trajectory that applied to the
batch reactor. To do so two input signals, electrical powers and the
flow of coolant in the coil are used. Simulation results show that the
proposed controller has a remarkable performance for tracking
reference trajectory while at the same time it is robust against noise
imposed to system output.
Abstract: Image compression is one of the most important
applications Digital Image Processing. Advanced medical imaging
requires storage of large quantities of digitized clinical data. Due to
the constrained bandwidth and storage capacity, however, a medical
image must be compressed before transmission and storage. There
are two types of compression methods, lossless and lossy. In Lossless
compression method the original image is retrieved without any
distortion. In lossy compression method, the reconstructed images
contain some distortion. Direct Cosine Transform (DCT) and Fractal
Image Compression (FIC) are types of lossy compression methods.
This work shows that lossy compression methods can be chosen for
medical image compression without significant degradation of the
image quality. In this work DCT and Fractal Compression using
Partitioned Iterated Function Systems (PIFS) are applied on different
modalities of images like CT Scan, Ultrasound, Angiogram, X-ray
and mammogram. Approximately 20 images are considered in each
modality and the average values of compression ratio and Peak
Signal to Noise Ratio (PSNR) are computed and studied. The quality
of the reconstructed image is arrived by the PSNR values. Based on
the results it can be concluded that the DCT has higher PSNR values
and FIC has higher compression ratio. Hence in medical image
compression, DCT can be used wherever picture quality is preferred
and FIC is used wherever compression of images for storage and
transmission is the priority, without loosing picture quality
diagnostically.
Abstract: In this paper we are to find the optimum
multiwavelet for compression of electrocardiogram (ECG)
signals. 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 MITBIH
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 cardbal2 by the
means of identity (Id) prefiltering method to be the best
effective transformation.
Abstract: In this paper presents a technique for developing the
computational efficiency in simulating double output induction
generators (DOIG) with two rotor circuits where stator transients are
to be included. Iterative decomposition is used to separate the flux–
Linkage equations into decoupled fast and slow subsystems, after
which the model order of the fast subsystems is reduced by
neglecting the heavily damped fast transients caused by the second
rotor circuit using integral manifolds theory. The two decoupled
subsystems along with the equation for the very slowly changing slip
constitute a three time-scale model for the machine which resulted in
increasing computational speed. Finally, the proposed method of
reduced order in this paper is compared with the other conventional
methods in linear and nonlinear modes and it is shown that this
method is better than the other methods regarding simulation
accuracy and speed.
Abstract: Asynchronous Transfer Mode (ATM) is widely used
in telecommunications systems to send data, video and voice at a
very high speed. In ATM network optimizing the bandwidth through
dynamic routing is an important consideration. Previous research
work shows that traditional optimization heuristics result in suboptimal
solution. In this paper we have explored non-traditional
optimization technique. We propose comparison of two such
algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on
non-traditional Optimization approach, for solving the dynamic
routing problem in ATM networks which in return will optimize the
bandwidth. The optimized bandwidth could mean that some
attractive business applications would become feasible such as high
speed LAN interconnection, teleconferencing etc. We have also
performed a comparative study of the selection mechanisms in GA
and listed the best selection mechanism and a new initialization
technique which improves the efficiency of the GA.
Abstract: For today-s and future wireless communications applications,
more and more data traffic has to be transmitted with
growing speed and quality demands. The analog front-end of any
mobile device has to cope with very hard specifications regardless
which transmission standard has to be supported. State-of-the-art
analog front-end implementations are reaching the limit of technical
feasibility. For that reason, alternative front-end architectures could
support a continuing development of mobile communications e.g.,
six-port-based front-ends [1], [2].
In this article we propose an analog front-end with high intermediate
frequency and which utilizes additive mixing instead
of multiplicative mixing. The system architecture is presented and
several spurious effects as well as their influence on the system
dimensioning are discussed. Furthermore, several issues concerning
the technical feasibility are provided and some simulation results
are discussed which show the principle functionality of the proposed
superposition heterodyne receiver.
Abstract: In this paper, a simple heuristic genetic algorithm is
used for Multistage Multiuser detection in fast fading environments.
Multipath channels, multiple access interference (MAI) and near far
effect cause the performance of the conventional detector to degrade.
Heuristic Genetic algorithms, a rapidly growing area of artificial
intelligence, uses evolutionary programming for initial search, which
not only helps to converge the solution towards near optimal
performance efficiently but also at a very low complexity as
compared with optimal detector. This holds true for Additive White
Gaussian Noise (AWGN) and multipath fading channels.
Experimental results are presented to show the superior performance
of the proposed techque over the existing methods.
Abstract: we propose a new normalized LMS (NLMS) algorithm, which gives satisfactory performance in certain applications in comaprison with con-ventional NLMS recursion. This new algorithm can be treated as a block based simplification of NLMS algorithm with significantly reduced number of multi¬ply and accumulate as well as division operations. It is also shown that such a recursion can be easily implemented in block floating point (BFP) arithmetic, treating the implementational issues much efficiently. In particular, the core challenges of a BFP realization to such adaptive filters are mainly considered in this regard. A global upper bound on the step size control parameter of the new algorithm due to BFP implementation is also proposed to prevent overflow in filtering as well as weight updating operations jointly.
Abstract: In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.
Abstract: Short message integrated distributed monitoring systems (SM-DMS) are growing rapidly in wireless communication applications in various areas, such as electromagnetic field (EMF) management, wastewater monitoring, and air pollution supervision, etc. However, delay in short messages often makes the data embedded in SM-DMS transmit unreliably. Moreover, there are few regulations dealing with this problem in SMS transmission protocols. In this study, based on the analysis of the command and data requirements in the SM-DMS, we developed a processing model for the control center to solve the delay problem in data transmission. Three components of the model: the data transmission protocol, the receiving buffer pool method, and the timer mechanism were described in detail. Discussions on adjusting the threshold parameter in the timer mechanism were presented for the adaptive performance during the runtime of the SM-DMS. This model optimized the data transmission reliability in SM-DMS, and provided a supplement to the data transmission reliability protocols at the application level.
Abstract: Since 1992, year where Hugo de Garis has published
the first paper on Evolvable Hardware (EHW), a period of intense
creativity has followed. It has been actively researched, developed
and applied to various problems. Different approaches have been
proposed that created three main classifications: extrinsic, mixtrinsic
and intrinsic EHW. Each of these solutions has a real interest.
Nevertheless, although the extrinsic evolution generates some
excellent results, the intrinsic systems are not so advanced. This
paper suggests 3 possible solutions to implement the run-time
configuration intrinsic EHW system: FPGA-based Run-Time
Configuration system, JBits-based Run-Time Configuration system
and Multi-board functional-level Run-Time Configuration system.
The main characteristic of the proposed architectures is that they are
implemented on Field Programmable Gate Array. A comparison of
proposed solutions demonstrates that multi-board functional-level
run-time configuration is superior in terms of scalability, flexibility
and the implementation easiness.
Abstract: The evolutionary design of electronic circuits, or
evolvable hardware, is a discipline that allows the user to
automatically obtain the desired circuit design. The circuit
configuration is under the control of evolutionary algorithms. Several
researchers have used evolvable hardware to design electrical
circuits. Every time that one particular algorithm is selected to carry
out the evolution, it is necessary that all its parameters, such as
mutation rate, population size, selection mechanisms etc. are tuned in
order to achieve the best results during the evolution process. This
paper investigates the abilities of evolution strategy to evolve digital
logic circuits based on programmable logic array structures when
different mutation rates are used. Several mutation rates (fixed and
variable) are analyzed and compared with each other to outline the
most appropriate choice to be used during the evolution of
combinational logic circuits. The experimental results outlined in this
paper are important as they could be used by every researcher who
might need to use the evolutionary algorithm to design digital logic
circuits.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.
Abstract: Based on the component approach, three kinds of
dynamic load models, including a single –motor model, a two-motor
model and composite load model have been developed for the
stability studies of Khuzestan power system. The study results are
presented in this paper. Voltage instability is a dynamic phenomenon
and therefore requires dynamic representation of the power system
components. Industrial loads contain a large fraction of induction
machines. Several models of different complexity are available for
the description investigations. This study evaluates the dynamic
performances of several dynamic load models in combination with
the dynamics of a load changing transformer. Case study is steel
industrial substation in Khuzestan power systems.
Abstract: This paper indicate the importance of
telecommunications supervision systems (TSS), integrating
heterogeneous TSS into single system thru umbrella systems,
introduces the structure, features, requirements of TSS and TSS
related intelligent solutions.