Abstract: One main drawback of intrusion detection system is the
inability of detecting new attacks which do not have known
signatures. In this paper we discuss an intrusion detection method
that proposes independent component analysis (ICA) based feature
selection heuristics and using rough fuzzy for clustering data. ICA is
to separate these independent components (ICs) from the monitored
variables. Rough set has to decrease the amount of data and get rid of
redundancy and Fuzzy methods allow objects to belong to several
clusters simultaneously, with different degrees of membership. Our
approach allows us to recognize not only known attacks but also to
detect activity that may be the result of a new, unknown attack. The
experimental results on Knowledge Discovery and Data Mining-
(KDDCup 1999) dataset.
Abstract: Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.
Abstract: This paper presents a solution for the behavioural
animation of autonomous virtual agent navigation in virtual environments.
We focus on using Dempster-Shafer-s Theory of Evidence
in developing visual sensor for virtual agent. The role of the visual
sensor is to capture the information about the virtual environment
or identifie which part of an obstacle can be seen from the position
of the virtual agent. This information is require for vitual agent to
coordinate navigation in virtual environment. The virual agent uses
fuzzy controller as a navigation system and Fuzzy α - level for
the action selection method. The result clearly demonstrates the path
produced is reasonably smooth even though there is some sharp turn
and also still not diverted too far from the potential shortest path.
This had indicated the benefit of our method, where more reliable
and accurate paths produced during navigation task.
Abstract: This paper presents the effectiveness of artificial
intelligent technique to apply for pattern recognition and
classification of Partial Discharge (PD). Characteristics of PD signal
for pattern recognition and classification are computed from the
relation of the voltage phase angle, the discharge magnitude and the
repeated existing of partial discharges by using statistical and fractal
methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern
recognition and classification as artificial intelligent technique. PDs
quantities, 13 parameters from statistical method and fractal method
results, are inputted to Simplified Fuzzy ARTMAP to train system
for pattern recognition and classification. The results confirm the
effectiveness of purpose technique.
Abstract: Conventional WBL is effective for meaningful student, because rote student learn by repeating without thinking or trying to understand. It is impossible to have full benefit from conventional WBL. Understanding of rote student-s intention and what influences it becomes important. Poorly designed user interface will discourage rote student-s cultivation and intention to use WBL. Thus, user interface design is an important factor especially when WBL is used as comprehensive replacement of conventional teaching. This research proposes the influencing factors that can enhance student-s intention to use the system. The enhanced TAM is used for evaluating the proposed factors. The research result points out that factors influencing rote student-s intention are Perceived Usefulness of Homepage Content Structure, Perceived User Friendly Interface, Perceived Hedonic Component, and Perceived (homepage) Visual Attractiveness.
Abstract: In this paper, an automatic detecting algorithm for
QRS complex detecting was applied for analyzing ECG recordings
and five criteria for dangerous arrhythmia diagnosing are applied for a
protocol type of automatic arrhythmia diagnosing system. The
automatic detecting algorithm applied in this paper detected the
distribution of QRS complexes in ECG recordings and related
information, such as heart rate and RR interval. In this investigation,
twenty sampled ECG recordings of patients with different pathologic
conditions were collected for off-line analysis. A combinative
application of four digital filters for bettering ECG signals and
promoting detecting rate for QRS complex was proposed as
pre-processing. Both of hardware filters and digital filters were
applied to eliminate different types of noises mixed with ECG
recordings. Then, an automatic detecting algorithm of QRS complex
was applied for verifying the distribution of QRS complex. Finally,
the quantitative clinic criteria for diagnosing arrhythmia were
programmed in a practical application for automatic arrhythmia
diagnosing as a post-processor. The results of diagnoses by automatic
dangerous arrhythmia diagnosing were compared with the results of
off-line diagnoses by experienced clinic physicians. The results of
comparison showed the application of automatic dangerous
arrhythmia diagnosis performed a matching rate of 95% compared
with an experienced physician-s diagnoses.
Abstract: This paper deals with the effect of a power transformer’s vector group on the basic voltage sag characteristics during unbalanced faults at a meshed or radial power network. Specifically, the propagation of voltage sags through a power transformer is studied with advanced short-circuit analysis. A smart method to incorporate this effect on analytical mathematical expressions is proposed. Based on this methodology, the positive effect of transformers of certain vector groups on the mitigation of the expected number of voltage sags per year (sag frequency) at the terminals of critical industrial customers can be estimated.
Abstract: In this paper we propose and examine an Adaptive
Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition
Autoregressive (STAR) modeling. Because STAR models follow
fuzzy logic approach, in the non-linear part fuzzy rules can be
incorporated or other training or computational methods can be
applied as the error backpropagation algorithm instead to nonlinear
squares. Furthermore, additional fuzzy membership functions can be
examined, beside the logistic and exponential, like the triangle,
Gaussian and Generalized Bell functions among others. We examine
two macroeconomic variables of US economy, the inflation rate and
the 6-monthly treasury bills interest rates.
Abstract: BRI-STARS (BRIdge Stream Tube model for Alluvial
River Simulation) program was used to investigate the scour depth around bridge piers in some of the major river systems in Iran. Model
calibration was performed by collecting different field data. Field data are cataloged on three categories, first group of bridges that
their rivers bed are formed by fine material, second group of bridges
that their rivers bed are formed by sand material, and finally bridges that their rivers bed are formed by gravel or cobble materials.
Verification was performed with some field data in Fars Province. Results show that for wide piers, computed scour depth is more than
measured one. In gravel bed streams, computed scour depth is greater
than measured scour depth, the reason is due to formation of armor layer on bed of channel. Once this layer is eroded, the computed
scour depth is close to the measured one.
Abstract: The three-species food web model proposed and investigated by Gakkhar and Naji is known to have chaotic behaviour for a choice of parameters. An attempt has been made to synchronize the chaos in the model using bidirectional coupling. Numerical simulations are presented to demonstrate the effectiveness and feasibility of the analytical results. Numerical results show that for higher value of coupling strength, chaotic synchronization is achieved. Chaos can be controlled to achieve stable synchronization in natural systems.
Abstract: This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (Kp. Kd, KI, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system
Abstract: In this paper a comprehensive model of a fossil fueled
power plant (FFPP) is developed in order to evaluate the
performance of a newly designed turbine follower controller.
Considering the drawbacks of previous works, an overall model is
developed to minimize the error between each subsystem model
output and the experimental data obtained at the actual power plant.
The developed model is organized in two main subsystems namely;
Boiler and Turbine. Considering each FFPP subsystem
characteristics, different modeling approaches are developed. For
economizer, evaporator, superheater and reheater, first order models
are determined based on principles of mass and energy conservation.
Simulations verify the accuracy of the developed models. Due to the
nonlinear characteristics of attemperator, a new model, based on a
genetic-fuzzy systems utilizing Pittsburgh approach is developed
showing a promising performance vis-à-vis those derived with other
methods like ANFIS. The optimization constraints are handled
utilizing penalty functions. The effect of increasing the number of
rules and membership functions on the performance of the proposed
model is also studied and evaluated. The turbine model is developed
based on the equation of adiabatic expansion. Parameters of all
evaluated models are tuned by means of evolutionary algorithms.
Based on the developed model a fuzzy PI controller is developed. It
is then successfully implemented in the turbine follower control
strategy of the plant. In this control strategy instead of keeping
control parameters constant, they are adjusted on-line with regard to
the error and the error rate. It is shown that the response of the
system improves significantly. It is also shown that fuel consumption
decreases considerably.
Abstract: The separation efficiency of a hydrocyclone has
extensively been considered on the rigid particle assumption. A
collection of experimental studies have demonstrated their
discrepancies from the modeling and simulation results. These
discrepancies caused by the actual particle elasticity have generally
led to a larger amount of energy consumption in the separation
process. In this paper, the influence of particle elasticity on the
separation efficiency of a hydrocyclone system was investigated
through the Finite Element (FE) simulations using crude oil droplets
as the elastic particles. A Reitema-s design hydrocyclone with a
diameter of 8 mm was employed to investigate the separation
mechanism of the crude oil droplets from water. The cut-size
diameter eter of the crude oil was 10 - Ðçm in order to fit with the
operating range of the adopted hydrocylone model. Typical
parameters influencing the performance of hydrocyclone were varied
with the feed pressure in the range of 0.3 - 0.6 MPa and feed
concentration between 0.05 – 0.1 w%. In the simulation, the Finite
Element scheme was applied to investigate the particle-flow
interaction occurred in the crude oil system during the process. The
interaction of a single oil droplet at the size of 10 - Ðçm to the flow
field was observed. The feed concentration fell in the dilute flow
regime so the particle-particle interaction was ignored in the study.
The results exhibited the higher power requirement for the separation
of the elastic particulate system when compared with the rigid
particulate system.
Abstract: In this work, a new approach is proposed to control
the manipulators for Humanoid robot. The kinematics of the
manipulators in terms of joint positions, velocity, acceleration and
torque of each joint is computed using the Denavit Hardenberg (D-H)
notations. These variables are used to design the manipulator control
system, which has been proposed in this work. In view of supporting
the development of a controller, a simulation of the manipulator is
designed for Humanoid robot. This simulation is developed through
the use of the Virtual Reality Toolbox and Simulink in Matlab. The
Virtual Reality Toolbox in Matlab provides the interfacing and
controls to an environment which is developed based on the Virtual
Reality Modeling Language (VRML). Chains of bones were used to
represent the robot.
Abstract: Cooperative diversity (CD) has been adopted in many communication systems because it helps in improving performance of the wireless communication systems with the help of the relays that emulate the multiple antenna terminals. This work aims to provide the derivation of the performance analysis expressions of the multiuser diversity (MUD) in the two-hop cooperative multi-relay wireless networks (TCMRNs). Considering the work analysis, we provide analytically the derivation of a closed form expression of the two most commonly used performance metrics namely, the outage probability and the symbol error probability (SEP) for the fixed decode-and-forward (FDF) protocol with MUD.
Abstract: Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.
Abstract: Nowadays pharmaceutical care departments located in
hospitals are amongst the important pillars of the healthcare system.
The aim of this study was to evaluate quality of hospital drugstores
affiliated with Kermanshah University of Medical Sciences.
In this cross-sectional study a validated questionnaire was used.
The questionnaire was filled in by the one of the researchers in all
seventeen hospital drugstores located in the teaching and nonteaching
hospitals affiliated with Kermanshah University of Medical
Sciences. The results shows that in observed hospitals,24% of
pharmacy environments, 25% of pharmacy store and storage
conditions, 49% of storage procedure, 25% of ordering drugs and
supplies, 73% of receiving supplies (proper procedure are fallowed
for receiving supplies), 35% of receiving supplies (prompt action
taken if deterioration of drugs received is suspected), 23.35% of
drugs delivery to patients and finally 0% of stock cards are used for
proper inventory control have full compliance with standards.
Abstract: Prior research evidenced that unimodal biometric
systems have several tradeoffs like noisy data, intra-class variations,
restricted degrees of freedom, non-universality, spoof attacks, and
unacceptable error rates. In order for the biometric system to be more
secure and to provide high performance accuracy, more than one
form of biometrics are required. Hence, the need arise for multimodal
biometrics using combinations of different biometric modalities. This
paper introduces a multimodal biometric system (MMBS) based on
fusion of whole dorsal hand geometry and fingerprints that acquires
right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG)
shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100
volunteers were acquired using the designed prototype. The acquired
images were found to have good quality for all features and patterns
extraction to all modalities. HG features based on the hand shape
anatomical landmarks were extracted. Robust and fast algorithms for
FP minutia points feature extraction and matching were used. Feature
vectors that belong to similar biometric traits were fused using
feature fusion methodologies. Scores obtained from different
biometric trait matchers were fused using the Min-Max
transformation-based score fusion technique. Final normalized scores
were merged using the sum of scores method to obtain a single
decision about the personal identity based on multiple independent
sources. High individuality of the fused traits and user acceptability
of the designed system along with its experimental high performance
biometric measures showed that this MMBS can be considered for
med-high security levels biometric identification purposes.
Abstract: Flash memory has become an important storage device
in many embedded systems because of its high performance, low
power consumption and shock resistance. Multi-level cell (MLC) is
developed as an effective solution for reducing the cost and increasing
the storage density in recent years. However, most of flash file system
cannot handle the error correction sufficiently. To correct more errors
for MLC, we implement Reed-Solomon (RS) code to YAFFS, what is
widely used for flash-based file system. RS code has longer computing
time but the correcting ability is much higher than that of Hamming
code.
Abstract: As data to be stored in storage subsystems
tremendously increases, data protection techniques have become more
important than ever, to provide data availability and reliability. In this
paper, we present the file system-based data protection (WOWSnap)
that has been implemented using WORM (Write-Once-Read-Many)
scheme. In the WOWSnap, once WORM files have been created, only
the privileged read requests to them are allowed to protect data against
any intentional/accidental intrusions. Furthermore, all WORM files
are related to their protection cycle that is a time period during which
WORM files should securely be protected. Once their protection cycle
is expired, the WORM files are automatically moved to the
general-purpose data section without any user interference. This
prevents the WORM data section from being consumed by
unnecessary files. We evaluated the performance of WOWSnap on
Linux cluster.