Abstract: The main objective of this work is to provide a fault detection and isolation based on Markov parameters for residual generation and a neural network for fault classification. The diagnostic approach is accomplished in two steps: In step 1, the system is identified using a series of input / output variables through an identification algorithm. In step 2, the fault is diagnosed comparing the Markov parameters of faulty and non faulty systems. The Artificial Neural Network is trained using predetermined faulty conditions serves to classify the unknown fault. In step 1, the identification is done by first formulating a Hankel matrix out of Input/ output variables and then decomposing the matrix via singular value decomposition technique. For identifying the system online sliding window approach is adopted wherein an open slit slides over a subset of 'n' input/output variables. The faults are introduced at arbitrary instances and the identification is carried out in online. Fault residues are extracted making a comparison of the first five Markov parameters of faulty and non faulty systems. The proposed diagnostic approach is illustrated on benchmark problems with encouraging results.
Abstract: Investigation of sandy clay behavior is important since
urban development demands mean that sandy clay areas are
increasingly encountered, especially for transportation
infrastructures. This paper presents the results of the finite element
analysis of the direct shear test (under three vertical loading 44, 96
and 192 kPa) and discusses the effects of different parameters such as
cohesion, friction angle and Young's modulus on the shear strength of
sandy clay. The numerical model was calibrated against the
experimental results of large-scale direct shear tests. The results have
shown that the shear strength was increased with increase in friction
angle and cohesion. However, the shear strength was not influenced
by raising the friction angle at normal stress of 44 kPa. Also, the
effect of different young's modulus factors on stress-strain curve was
investigated.
Abstract: Numerical investigation of flow around a square cylinder are presented using the multi-relaxation-time lattice Boltzmann methods at different Reynolds numbers. A detail analysis are given in terms of time-trace analysis of drag and lift coefficients, power spectra analysis of lift coefficient, vorticity contours visualizations, streamlines and phase diagrams. A number of physical quantities mean drag coefficient, drag coefficient, Strouhal number and root-mean-square values of drag and lift coefficients are calculated and compared with the well resolved experimental data and numerical results available in open literature. The Reynolds numbers affected the physical quantities.
Abstract: A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.
Abstract: This paper presents findings from the evaluation study carried out to review the UAE national ID card software. The paper consults the relevant literature to explain many of the concepts and frameworks explained herein. The findings of the evaluation work that was primarily based on the ISO 9126 standard for system quality measurement highlighted many practical areas that if taken into account is argued to more likely increase the success chances of similar system implementation projects.
Abstract: Deciding the numerous parameters involved in
designing a competent artificial neural network is a complicated task.
The existence of several options for selecting an appropriate
architecture for neural network adds to this complexity, especially
when different applications of heterogeneous natures are concerned.
Two completely different applications in engineering and medical
science were selected in the present study including prediction of
workpiece's surface roughness in ultrasonic-vibration assisted turning
and papilloma viruses oncogenicity. Several neural network
architectures with different parameters were developed for each
application and the results were compared. It was illustrated in this
paper that some applications such as the first one mentioned above
are apt to be modeled by a single network with sufficient accuracy,
whereas others such as the second application can be best modeled
by different expert networks for different ranges of output.
Development of knowledge about the essentials of neural networks
for different applications is regarded as the cornerstone of
multidisciplinary network design programs to be developed as a
means of reducing inconsistencies and the burden of the user
intervention.
Abstract: Low frequency power oscillations may be triggered
by many events in the system. Most oscillations are damped by the
system, but undamped oscillations can lead to system collapse.
Oscillations develop as a result of rotor acceleration/deceleration
following a change in active power transfer from a generator. Like
the operations limits, the monitoring of power system oscillating
modes is a relevant aspect of power system operation and control.
Unprevented low-frequency power swings can be cause of cascading
outages that can rapidly extend effect on wide region. On this regard,
a Wide Area Monitoring, Protection and Control Systems
(WAMPCS) help in detecting such phenomena and assess power
system dynamics security. The monitoring of power system
electromechanical oscillations is very important in the frame of
modern power system management and control. In first part, this
paper compares the different technique for identification of power
system oscillations. Second part analyzes possible identification
some power system dynamics behaviors Using Wide Area
Monitoring Systems (WAMS) based on Phasor Measurement Units
(PMUs) and wavelet technique.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: In this study, a classification-based video
super-resolution method using artificial neural network (ANN) is
proposed to enhance low-resolution (LR) to high-resolution (HR)
frames. The proposed method consists of four main steps:
classification, motion-trace volume collection, temporal adjustment,
and ANN prediction. A classifier is designed based on the edge
properties of a pixel in the LR frame to identify the spatial information.
To exploit the spatio-temporal information, a motion-trace volume is
collected using motion estimation, which can eliminate unfathomable
object motion in the LR frames. In addition, temporal lateral process is
employed for volume adjustment to reduce unnecessary temporal
features. Finally, ANN is applied to each class to learn the complicated
spatio-temporal relationship between LR and HR frames. Simulation
results show that the proposed method successfully improves both
peak signal-to-noise ratio and perceptual quality.
Abstract: Direct Torque Control is a control technique in AC
drive systems to obtain high performance torque control. The
conventional DTC drive contains a pair of hysteresis comparators.
DTC drives utilizing hysteresis comparators suffer from high torque
ripple and variable switching frequency. The most common solution
to those problems is to use the space vector depends on the reference
torque and flux. In this Paper The space vector modulation technique
(SVPWM) is applied to 2 level inverter control in the proposed
DTC-based induction motor drive system, thereby dramatically
reducing the torque ripple. Then the controller based on space vector
modulation is designed to be applied in the control of Induction
Motor (IM) with a three-level Inverter. This type of Inverter has
several advantages over the standard two-level VSI, such as a greater
number of levels in the output voltage waveforms, Lower dV/dt, less
harmonic distortion in voltage and current waveforms and lower
switching frequencies. This paper proposes a general SVPWM
algorithm for three-level based on standard two-level SVPWM. The
proposed scheme is described clearly and simulation results are
reported to demonstrate its effectiveness. The entire control scheme is
implemented with Matlab/Simulink.
Abstract: The aim of this study was to investigate whether
magnetite nanoparticles affect the viability of Bradyrhizobium
japanicum cells residing on the surface of soybean seeds during
desiccation. Different concentrations of nanoparticles suspended in
liquid medium, mixed with and adhering to Bradyrhizobium
japanicum, were investigated at two temperatures, using both
soybean seeds and glass beads as surrogates. Statistical design was a
complete randomized block (CRB) in a factorial 6×2×2×6
experimental arrangement with four replications. The most important
variable was the viability of Bradyrhizobium on the surface of the
seeds. The nanoparticles increased Bradyrhizobium viability and
inoculated seeds stored at low temperature had greater viability when
nanoparticles had been added. At the optimum nanoparticle
concentration, 50% bacterium viability on the seeds was retained
after 5 days at 4ºC. Possible explanations for the observed effects are
proposed.
Abstract: A fault detection and identification (FDI) technique is
presented to create a fault tolerant control system (FTC). The fault
detection is achieved by monitoring the position of the light source
using an array of light sensors. When a decision is made about the
presence of a fault an identification process is initiated to locate the
faulty component and reconfigure the controller signals. The signals
provided by the sensors are predictable; therefore the existence of a
fault is easily identified. Identification of the faulty sensor is based on
the dynamics of the frame. The technique is not restricted to a
particular type of controllers and the results show consistency.
Abstract: In this paper, a framework is presented trying to make
the most secure web system out of the available generic and web
security technology which can be used as a guideline for
organizations building their web sites. The framework is designed to
provide necessary security services, to address the known security
threats, and to provide some cover to other security problems
especially unknown threats. The requirements for the design are
discussed which guided us to the design of secure web system. The
designed security framework is then simulated and various quality of
service (QoS) metrics are calculated to measure the performance of
this system.
Abstract: Reverse Engineering is a very important process in
Software Engineering. It can be performed backwards from system
development life cycle (SDLC) in order to get back the source data
or representations of a system through analysis of its structure,
function and operation. We use reverse engineering to introduce an
automatic tool to generate system requirements from its program
source codes. The tool is able to accept the Cµ programming source
codes, scan the source codes line by line and parse the codes to
parser. Then, the engine of the tool will be able to generate system
requirements for that specific program to facilitate reuse and
enhancement of the program. The purpose of producing the tool is to
help recovering the system requirements of any system when the
system requirements document (SRD) does not exist due to
undocumented support of the system.
Abstract: Wind catchers are traditional natural ventilation
systems attached to buildings in order to ventilate the indoor air. The
most common type of wind catcher is four sided one which is
capable to catch wind in all directions. CFD simulation is the perfect
way to evaluate the wind catcher performance. The accuracy of CFD
results is the issue of concern, so sensitivity analyses is crucial to
find out the effect of different settings of CFD on results. This paper
presents a series of 3D steady RANS simulations for a generic
isolated four-sided wind catcher attached to a room subjected to wind
direction ranging from 0º to 180º with an interval of 45º. The CFD
simulations are validated with detailed wind tunnel experiments. The
influence of an extensive range of computational parameters is
explored in this paper, including the resolution of the computational
grid, the size of the computational domain and the turbulence model.
This study found that CFD simulation is a reliable method for wind
catcher study, but it is less accurate in prediction of models with non
perpendicular wind directions.
Abstract: Seasonal variability of nutrients concentration in the Baltic Sea using the 3D ecosystem numerical model 3D-CEMBS has been investigated. Additionally this study shows horizontal and vertical distribution of nutrients in the Baltic Sea. Model domain is an extended Baltic Sea area divided into 600x640 horizontal grid cells. Aside from standard hydrodynamic parameters 3D-CEMBS produces modeled ecological variables such as: three types of phytoplankton, two detrital classes, dissolved oxygen and the nutrients (nitrate, ammonium, phosphate and silicate). The presented model allows prediction of parameters that describe distribution of nutrients concentration and phytoplankton biomass. 3D-CEMBS can be used to study the effect of different hydrodynamic and biogeochemical processes on distributions of these variables in a larger scale.
Abstract: Membrane distillation (MD) is a rising technology for
seawater or brine desalination process. In this work, an air gap
membrane distillation (AGMD) performance was investigated for
aqueous NaCl solution along with natural ground water and seawater.
In order to enhance the performance of the AGMD process in
desalination, that is, to get more flux, it is necessary to study the
effect of operating parameters on the yield of distillate water. The
influence of operational parameters such as feed flow rate, feed
temperature, feed salt concentration, coolant temperature and air gap
thickness on the membrane distillation (MD) permeation flux have
been investigated for low and high salt solution. the natural
application of ground water and seawater over 90 h continuous
operation, scale deposits observed on the membrane surface and
reduction in flux represents 23% for ground water and 60% for
seawater, in 90 h. This reduction was eliminated (less than 14 %) by
acidification of feed water. Hence, promote the research attention in
apply of AGMD for the ground water as well as seawater
desalination over today-s conventional RO operation.
Abstract: Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal
non-equilibrium model is studied in this paper. The left vertical wall is
maintained at a constant hot temperature Th and the right vertical wall
is maintained at a constant cold temperature Tc, while the horizontal
walls are adiabatic. The governing equations are obtained by applying
the Darcy model and Boussinesq approximation. COMSOL’s finite
element method is used to solve the non-dimensional governing
equations together with specified boundary conditions. The governing
parameters of this study are the Rayleigh number (Ra = 10^5, and Ra = 10^6 ), Darcy namber (Da = 10^−2, and Da = 10^−3),
the modified thermal conductivity ratio (10^−1 ≤ γ ≤ 10^4), the inter-phase heat transfer coefficien (10^−1 ≤ H ≤ 10^3) and the
time dependent (0.001 ≤ τ ≤ 0.2). The results presented for
values of the governing parameters in terms of streamlines in both
fluid/porous-layer, isotherms of fluid in fluid/porous-layer, isotherms
of solid in porous layer, and average Nusselt number.
Abstract: A new approach to determine the machine layout in flexible manufacturing cell, and to find the feasible robot configuration of the robot to achieve minimum cycle time is presented in this paper. The location of the input/output location and the optimal robot configuration is obtained for all sequences of work tasks of the robot within a specified period of time. A more realistic approach has been presented to model the problem using the robot joint space. The problem is formulated as a nonlinear optimization problem and solved using Sequential Quadratic Programming algorithm.
Abstract: The world wide web coupled with the ever-increasing
sophistication of online technologies and software applications puts
greater emphasis on the need of even more sophisticated and
consistent quality requirements modeling than traditional software
applications. Web sites and Web applications (WebApps) are
becoming more information driven and content-oriented raising the
concern about their information quality (InQ). The consistent and
consolidated modeling of InQ requirements for WebApps at different
stages of the life cycle still poses a challenge. This paper proposes an
approach to specify InQ requirements for WebApps by reusing and
extending the ISO 25012:2008(E) data quality model. We also
discuss learnability aspect of information quality for the WebApps.
The proposed ISO 25012 based InQ framework is a step towards a
standardized approach to evaluate WebApps InQ.