Abstract: CFlow is a flow chart software, it contains facilities to
draw and evaluate a flow chart. A flow chart evaluation applies a
simulation method to enable presentation of work flow in a flow
chart solution. Flow chart simulation of CFlow is executed by
manipulating the CFlow data file which is saved in a graphical vector
format. These text-based data are organised by using a data
classification technic based on a Library classification-scheme. This
paper describes the file format for flow chart simulation software of
CFlow.
Abstract: Radio frequency identification (RFID) applications have grown rapidly in many industries, especially in indoor location identification. The advantage of using received signal strength indicator (RSSI) values as an indoor location measurement method is a cost-effective approach without installing extra hardware. Because the accuracy of many positioning schemes using RSSI values is limited by interference factors and the environment, thus it is challenging to use RFID location techniques based on integrating positioning algorithm design. This study proposes the location estimation approach and analyzes a scheme relying on RSSI values to minimize location errors. In addition, this paper examines different factors that affect location accuracy by integrating the backpropagation neural network (BPN) with the LANDMARC algorithm in a training phase and an online phase. First, the training phase computes coordinates obtained from the LANDMARC algorithm, which uses RSSI values and the real coordinates of reference tags as training data for constructing an appropriate BPN architecture and training length. Second, in the online phase, the LANDMARC algorithm calculates the coordinates of tracking tags, which are then used as BPN inputs to obtain location estimates. The results show that the proposed scheme can estimate locations more accurately compared to LANDMARC without extra devices.
Abstract: The purpose of this research is to develop a security model for voice eavesdropping protection over digital networks. The proposed model provides an encryption scheme and a personal secret key exchange between communicating parties, a so-called voice data transformation system, resulting in a real-privacy conversation. The operation of this system comprises two main steps as follows: The first one is the personal secret key exchange for using the keys in the data encryption process during conversation. The key owner could freely make his/her choice in key selection, so it is recommended that one should exchange a different key for a different conversational party, and record the key for each case into the memory provided in the client device. The next step is to set and record another personal option of encryption, either taking all frames or just partial frames, so-called the figure of 1:M. Using different personal secret keys and different sets of 1:M to different parties without the intervention of the service operator, would result in posing quite a big problem for any eavesdroppers who attempt to discover the key used during the conversation, especially in a short period of time. Thus, it is quite safe and effective to protect the case of voice eavesdropping. The results of the implementation indicate that the system can perform its function accurately as designed. In this regard, the proposed system is suitable for effective use in voice eavesdropping protection over digital networks, without any requirements to change presently existing network systems, mobile phone network and VoIP, for instance.
Abstract: Optical burst switching(OBS) is considered as one of
preferable network technologies for the next generation Internet. The
Internet has two traffic classes, i.e. real-time bursts and reliable bursts.
It is an important subject for OBS to achieve cooperated operation of
real-time bursts and reliable bursts. In this paper, we proposes a new
effective traffic control method named Separate TB+LB (Token
Bucket + Leaky Bucket : TB+LB) method. The proposed method
presents a new Token Bucket scheme for real-time bursts called as
RBO-TB (Real-time Bursts Oriented Token Bucket). The method also
applies the LB method to reliable bursts for obtaining better
performance. This paper verifies the effectiveness of the Separate
TB+LB method through the performance evaluation.
Abstract: In this paper, a new reversible watermarking method is presented that reduces the size of a stereoscopic image sequence while keeping its content visible. The proposed technique embeds the residuals of the right frames to the corresponding frames of the left sequence, halving the total capacity. The residual frames may result in after a disparity compensated procedure between the two video streams or by a joint motion and disparity compensation. The residuals are usually lossy compressed before embedding because of the limited embedding capacity of the left frames. The watermarked frames are visible at a high quality and at any instant the stereoscopic video may be recovered by an inverse process. In fact, the left frames may be exactly recovered whereas the right ones are slightly distorted as the residuals are not embedded intact. The employed embedding method reorders the left frame into an array of consecutive pixel pairs and embeds a number of bits according to their intensity difference. In this way, it hides a number of bits in intensity smooth areas and most of the data in textured areas where resulting distortions are less visible. The experimental evaluation demonstrates that the proposed scheme is quite effective.
Abstract: Graph decompositions are vital in the study of
combinatorial design theory. A decomposition of a graph G is a
partition of its edge set. An n-sun graph is a cycle Cn with an edge
terminating in a vertex of degree one attached to each vertex. In this
paper, we define n-sun decomposition of some even order graphs
with a perfect matching. We have proved that the complete graph
K2n, complete bipartite graph K2n, 2n and the Harary graph H4, 2n have
n-sun decompositions. A labeling scheme is used to construct the n-suns.
Abstract: Over the past few years, XML (eXtensible Mark-up
Language) has emerged as the standard for information
representation and data exchange over the Internet. This paper
provides a kick-start for new researches venturing in XML databases
field. We survey the storage representation for XML document,
review the XML query processing and optimization techniques with
respect to the particular storage instance. Various optimization
technologies have been developed to solve the query retrieval and
updating problems. Towards the later year, most researchers
proposed hybrid optimization techniques. Hybrid system opens the
possibility of covering each technology-s weakness by its strengths.
This paper reviews the advantages and limitations of optimization
techniques.
Abstract: This paper is a simple and systematic approaches to the design and analysis a pulse width modulation (PWM) based sliding mode controller for buck DC-DC Converters. Various aspects of the design, including the practical problems and the proposed solutions, are detailed. However, these control strategies can't compensate for large load current and input voltage variations. In this paper, a new control strategy by compromising both schemes advantages and avoiding their drawbacks is proposed, analyzed and simulated.
Abstract: In this paper, a method based on Non-Dominated
Sorting Genetic Algorithm (NSGA) has been presented for the Volt /
Var control in power distribution systems with dispersed generation
(DG). Genetic algorithm approach is used due to its broad
applicability, ease of use and high accuracy. The proposed method is
better suited for volt/var control problems. A multi-objective
optimization problem has been formulated for the volt/var control of
the distribution system. The non-dominated sorting genetic algorithm
based method proposed in this paper, alleviates the problem of tuning
the weighting factors required in solving the multi-objective volt/var
control optimization problems. Based on the simulation studies
carried out on the distribution system, the proposed scheme has been
found to be simple, accurate and easy to apply to solve the multiobjective
volt/var control optimization problem of the distribution
system with dispersed generation.
Abstract: The paper compares different channel models used for
modeling Broadband Power-Line Communication (BPLC) system.
The models compared are Zimmermann and Dostert, Philipps,
Anatory et al and Anatory et al generalized Transmission Line (TL)
model. The validity of each model was compared in time domain
with ATP-EMTP software which uses transmission line approach. It
is found that for a power-line network with minimum number of
branches all the models give similar signal/pulse time responses
compared with ATP-EMTP software; however, Zimmermann and
Dostert model indicates the same amplitude but different time delay.
It is observed that when the numbers of branches are increased only
generalized TL theory approach results are comparable with ATPEMTP
results. Also the Multi-Carrier Spread Spectrum (MC-SS)
system was applied to check the implication of such behavior on the
modulation schemes. It is observed that using Philipps on the
underground cable can predict the performance up to 25dB better
than other channel models which can misread the actual performance
of the system. Also modified Zimmermann and Dostert under
multipath can predict a better performance of about 5dB better than
the actual predicted by Generalized TL theory. It is therefore
suggested for a realistic BPLC system design and analyses the model
based on generalized TL theory be used.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images and set up compression-transmit schemes to distribute result to the remote doctor. To achieve this goal, we use basically a level-sets approach to delineating brain tumors in threedimensional. Then introduce a new compression and transmission plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by wireless network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: This paper reports a distributed mutual exclusion
algorithm for mobile Ad-hoc networks. The network is clustered
hierarchically. The proposed algorithm considers the clustered
network as a logical tree and develops a token passing scheme
to get the mutual exclusion. The performance analysis and
simulation results show that its message requirement is optimal,
and thus the algorithm is energy efficient.
Abstract: This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TFIDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.
Abstract: Chua’s circuit is one of the most important electronic devices that are used for Chaos and Bifurcation studies. A central role of secure communication is devoted to it. Since the adaptive control is used vastly in the linear systems control, here we introduce a new trend of application of adaptive method in the chaos controlling field. In this paper, we try to derive a new adaptive control scheme for Chua’s circuit controlling because control of chaos is often very important in practical operations. The novelty of this approach is for sake of its robustness against the external perturbations which is simulated as an additive noise in all measured states and can be generalized to other chaotic systems. Our approach is based on Lyapunov analysis and the adaptation law is considered for the feedback gain. Because of this, we have named it NAFT (Nonlinear Adaptive Feedback Technique). At last, simulations show the capability of the presented technique for Chua’s circuit.
Abstract: Image convolution similar to the receptive fields
found in mammalian visual pathways has long been used in
conventional image processing in the form of Gabor masks.
However, no VLSI implementation of parallel, multi-layered pulsed
processing has been brought forward which would emulate this
property. We present a technical realization of such a pulsed image
processing scheme. The discussed IC also serves as a general testbed
for VLSI-based pulsed information processing, which is of interest
especially with regard to the robustness of representing an analog
signal in the phase or duration of a pulsed, quasi-digital signal, as
well as the possibility of direct digital manipulation of such an
analog signal. The network connectivity and processing properties
are reconfigurable so as to allow adaptation to various processing
tasks.
Abstract: Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.
Abstract: A fully on-chip low drop-out (LDO) voltage regulator with 100pF output load capacitor is presented. A novel frequency compensation scheme using current buffer is adopted to realize single dominant pole within the unit gain frequency of the regulation loop, the phase margin (PM) is at least 50 degree under the full range of the load current, and the power supply rejection (PSR) character is improved compared with conventional Miller compensation. Besides, the differentiator provides a high speed path during the load current transient. Implemented in 0.18μm CMOS technology, the LDO voltage regulator provides 100mA load current with a stable 1.8V output voltage consuming 80μA quiescent current.
Abstract: Bluetooth is a personal wireless communication
technology and is being applied in many scenarios. It is an emerging
standard for short range, low cost, low power wireless access
technology. Current existing MAC (Medium Access Control)
scheduling schemes only provide best-effort service for all masterslave
connections. It is very challenging to provide QoS (Quality of
Service) support for different connections due to the feature of
Master Driven TDD (Time Division Duplex). However, there is no
solution available to support both delay and bandwidth guarantees
required by real time applications. This paper addresses the issue of
how to enhance QoS support in a Bluetooth piconet. The Bluetooth
specification proposes a Round Robin scheduler as possible solution
for scheduling the transmissions in a Bluetooth Piconet. We propose
an algorithm which will reduce the bandwidth waste and enhance the
efficiency of network. We define token counters to estimate traffic of
real-time slaves. To increase bandwidth utilization, a back-off
mechanism is then presented for best-effort slaves to decrease the
frequency of polling idle slaves. Simulation results demonstrate that
our scheme achieves better performance over the Round Robin
scheduling.
Abstract: In this study, the numerical solution of unsteady flow
between two concentric rotating spheres with suction and blowing at
their boundaries is presented. The spheres are rotating about a
common axis of rotation while their angular velocities are constant.
The Navier-Stokes equations are solved by employing the finite
difference method and implicit scheme. The resulting flow patterns
are presented for various values of the flow parameters including
rotational Reynolds number Re , and a blowing/suction Reynolds
number Rew . Viscous torques at the inner and the outer spheres are
calculated, too. It is seen that increasing the amount of suction and
blowing decrease the size of eddies generated in the annulus.
Abstract: Detection of incipient abnormal events is important to
improve safety and reliability of machine operations and reduce losses
caused by failures. Improper set-ups or aligning of parts often leads to
severe problems in many machines. The construction of prediction
models for predicting faulty conditions is quite essential in making
decisions on when to perform machine maintenance. This paper
presents a multivariate calibration monitoring approach based on the
statistical analysis of machine measurement data. The calibration
model is used to predict two faulty conditions from historical reference
data. This approach utilizes genetic algorithms (GA) based variable
selection, and we evaluate the predictive performance of several
prediction methods using real data. The results shows that the
calibration model based on supervised probabilistic principal
component analysis (SPPCA) yielded best performance in this work.
By adopting a proper variable selection scheme in calibration models,
the prediction performance can be improved by excluding
non-informative variables from their model building steps.