Abstract: The fault detection and diagnosis of complicated
production processes is one of essential tasks needed to run the process
safely with good final product quality. Unexpected events occurred in
the process may have a serious impact on the process. In this work,
triangular representation of process measurement data obtained in an
on-line basis is evaluated using simulation process. The effect of using
linear and nonlinear reduced spaces is also tested. Their diagnosis
performance was demonstrated using multivariate fault data. It has
shown that the nonlinear technique based diagnosis method produced
more reliable results and outperforms linear method. The use of
appropriate reduced space yielded better diagnosis performance. The
presented diagnosis framework is different from existing ones in that it
attempts to extract the fault pattern in the reduced space, not in the
original process variable space. The use of reduced model space helps
to mitigate the sensitivity of the fault pattern to noise.
Abstract: Image coding based on clustering provides immediate
access to targeted features of interest in a high quality decoded
image. This approach is useful for intelligent devices, as well as for
multimedia content-based description standards. The result of image
clustering cannot be precise in some positions especially on pixels
with edge information which produce ambiguity among the clusters.
Even with a good enhancement operator based on PDE, the quality of
the decoded image will highly depend on the clustering process. In
this paper, we introduce an ambiguity cluster in image coding to
represent pixels with vagueness properties. The presence of such
cluster allows preserving some details inherent to edges as well for
uncertain pixels. It will also be very useful during the decoding phase
in which an anisotropic diffusion operator, such as Perona-Malik,
enhances the quality of the restored image. This work also offers a
comparative study to demonstrate the effectiveness of a fuzzy
clustering technique in detecting the ambiguity cluster without losing
lot of the essential image information. Several experiments have been
carried out to demonstrate the usefulness of ambiguity concept in
image compression. The coding results and the performance of the
proposed algorithms are discussed in terms of the peak signal-tonoise
ratio and the quantity of ambiguous pixels.
Abstract: This paper presents the results of enhancing images from a left and right stereo pair in order to increase the resolution of a 3D representation of a scene generated from that same pair. A new neural network structure known as a Self Delaying Dynamic Network (SDN) has been used to perform the enhancement. The advantage of SDNs over existing techniques such as bicubic interpolation is their ability to cope with motion and noise effects. SDNs are used to generate two high resolution images, one based on frames taken from the left view of the subject, and one based on the frames from the right. This new high resolution stereo pair is then processed by a disparity map generator. The disparity map generated is compared to two other disparity maps generated from the same scene. The first is a map generated from an original high resolution stereo pair and the second is a map generated using a stereo pair which has been enhanced using bicubic interpolation. The maps generated using the SDN enhanced pairs match more closely the target maps. The addition of extra noise into the input images is less problematic for the SDN system which is still able to out perform bicubic interpolation.
Abstract: The sand production problem has led researchers into making various attempts to understand the phenomenon. The generally accepted concept is that the occurrence of sanding is due to the in-situ stress conditions and the induced changes in stress that results in the failure of the reservoir sandstone during hydrocarbon production from wellbores. By using a hypothetical cased (perforated) well, an approach to the problem is presented here by using Finite Element numerical modelling techniques. In addition to the examination of the erosion problem, the influence of certain key parameters is studied in order to ascertain their effect on the failure and subsequent erosion process. The major variables investigated include: drawdown, perforation depth, and the erosion criterion. Also included is the determination of the optimal mud pressure for given operational and reservoir conditions. The improved understanding between parameters enables the choice of optimal values to minimize sanding during oil production.
Abstract: Throughout this paper, a relatively new technique, the Tabu search variable selection model, is elaborated showing how it can be efficiently applied within the financial world whenever researchers come across the selection of a subset of variables from a whole set of descriptive variables under analysis. In the field of financial prediction, researchers often have to select a subset of variables from a larger set to solve different type of problems such as corporate bankruptcy prediction, personal bankruptcy prediction, mortgage, credit scoring and the Arbitrage Pricing Model (APM). Consequently, to demonstrate how the method operates and to illustrate its usefulness as well as its superiority compared to other commonly used methods, the Tabu search algorithm for variable selection is compared to two main alternative search procedures namely, the stepwise regression and the maximum R 2 improvement method. The Tabu search is then implemented in finance; where it attempts to predict corporate bankruptcy by selecting the most appropriate financial ratios and thus creating its own prediction score equation. In comparison to other methods, mostly the Altman Z-Score model, the Tabu search model produces a higher success rate in predicting correctly the failure of firms or the continuous running of existing entities.
Abstract: In recent years, most of the regions in the world are
exposed to degradation and erosion caused by increasing
population and over use of land resources. The understanding of
the most important factors on soil erosion and sediment yield are
the main keys for decision making and planning. In this study, the
sediment yield and soil erosion were estimated and the priority of
different soil erosion factors used in the MPSIAC method of soil
erosion estimation is evaluated in AliAbad watershed in southwest
of Isfahan Province, Iran. Different information layers of the
parameters were created using a GIS technique. Then, a
multivariate procedure was applied to estimate sediment yield and
to find the most important factors of soil erosion in the model. The
results showed that land use, geology, land and soil cover are the
most important factors describing the soil erosion estimated by
MPSIAC model.
Abstract: The Goursat partial differential equation arises in
linear and non linear partial differential equations with mixed
derivatives. This equation is a second order hyperbolic partial
differential equation which occurs in various fields of study such as
in engineering, physics, and applied mathematics. There are many
approaches that have been suggested to approximate the solution of
the Goursat partial differential equation. However, all of the
suggested methods traditionally focused on numerical differentiation
approaches including forward and central differences in deriving the
scheme. An innovation has been done in deriving the Goursat partial
differential equation scheme which involves numerical integration
techniques. In this paper we have developed a new scheme to solve
the Goursat partial differential equation based on the Adomian
decomposition (ADM) and associated with Boole-s integration rule to
approximate the integration terms. The new scheme can easily be
applied to many linear and non linear Goursat partial differential
equations and is capable to reduce the size of computational work.
The accuracy of the results reveals the advantage of this new scheme
over existing numerical method.
Abstract: In this paper, an effective sliding mode design is
applied to chaos synchronization. The proposed controller can make
the states of two identical modified Chua-s circuits globally
asymptotically synchronized. Numerical results are provided to show
the effectiveness and robustness of the proposed method.
Abstract: This paper focuses on analyzing medical diagnostic data using classification rules in data mining and context reduction in formal concept analysis. It helps in finding redundancies among the various medical examination tests used in diagnosis of a disease. Classification rules have been derived from positive and negative association rules using the Concept lattice structure of the Formal Concept Analysis. Context reduction technique given in Formal Concept Analysis along with classification rules has been used to find redundancies among the various medical examination tests. Also it finds out whether expensive medical tests can be replaced by some cheaper tests.
Abstract: A new SUZ-4 zeolite membrane with
tetraethlyammonium hydroxide as the template was fabricated on
mullite tube via hydrothermal sol-gel synthesis in a rotating
autoclave reactor. The suitable synthesis condition was SiO2:Al2O3
ratio of 21.2 for 4 days at 155 °C crystallization under autogenous
pressure. The obtained SUZ-4 possessed a high BET surface area of
396.4 m2/g, total pore volume at 2.611 cm3/g, and narrow pore size
distribution with 97 nm mean diameter and 760 nm long of needle
crystal shape. The SUZ-4 layer obtained from seeding crystallization
was thicker than that of without seeds or in situ crystallization.
Abstract: Liver segmentation is the first significant process for
liver diagnosis of the Computed Tomography. It segments the liver
structure from other abdominal organs. Sophisticated filtering techniques
are indispensable for a proper segmentation. In this paper, we
employ a 3D anisotropic diffusion as a preprocessing step. While
removing image noise, this technique preserve the significant parts
of the image, typically edges, lines or other details that are important
for the interpretation of the image. The segmentation task is done
by using thresholding with automatic threshold values selection and
finally the false liver region is eliminated using 3D connected component.
The result shows that by employing the 3D anisotropic filtering,
better liver segmentation results could be achieved eventhough simple
segmentation technique is used.
Abstract: Accurate timing alignment and stability is important
to maximize the true counts and minimize the random counts in
positron emission tomography So signals output from detectors must
be centering with the two isotopes to pre-operation and fed signals
into four units of pulse-processing units, each unit can accept up to
eight inputs. The dual source computed tomography consist two units
on the left for 15 detector signals of Cs-137 isotope and two units on
the right are for 15 detectors signals of Co-60 isotope. The gamma
spectrum consisting of either single or multiple photo peaks. This
allows for the use of energy discrimination electronic hardware
associated with the data acquisition system to acquire photon counts
data with a specific energy, even if poor energy resolution detectors
are used. This also helps to avoid counting of the Compton scatter
counts especially if a single discrete gamma photo peak is emitted by
the source as in the case of Cs-137. In this study the polyenergetic
version of the alternating minimization algorithm is applied to the
dual energy gamma computed tomography problem.
Abstract: Dynamic models of power converters are normally
time-varying because of their switching actions. Several approaches
are applied to analyze the power converters to achieve the timeinvariant
models suitable for system analysis and design via the
classical control theory. The paper presents how to derive dynamic
models of the power system consisting of a three-phase controlled
rectifier feeding an uncontrolled buck converter by using the
combination between the well known techniques called the DQ and
the generalized state-space averaging methods. The intensive timedomain
simulations of the exact topology model are used to support
the accuracies of the reported model. The results show that the
proposed model can provide good accuracies in both transient and
steady-state responses.
Abstract: In this study, oxidative steam reforming of methanol (OSRM) over a Au/CeO2–Fe2O3 catalyst prepared by a depositionprecipitation (DP) method was studied to produce hydrogen in order to feed a Proton Exchange Membrane Fuel Cell (PEMFC). The support (CeO2, Fe2O3, and CeO2–Fe2O3) were prepared by precipitation and co-precipitation methods. The impact of the support composition on the catalytic performance was studied by varying the Ce/(Ce+Fe) atomic ratio, it was found that the 1%Au/CF(0.25) calcined at 300 °C exhibited the highest catalytic activity in the whole temperature studied. In addition, the effect of Au content was investigated and 3%Au/CF(0.25) exhibited the highest activity under the optimum condition in the temperature range of 200 °C to 400 °C. The catalysts were characterized by various techniques: XRD, TPR, XRF, and UV-vis.
Abstract: Lossless compression schemes with secure
transmission play a key role in telemedicine applications that helps in
accurate diagnosis and research. Traditional cryptographic algorithms
for data security are not fast enough to process vast amount of data.
Hence a novel Secured lossless compression approach proposed in
this paper is based on reversible integer wavelet transform, EZW
algorithm, new modified runlength coding for character
representation and selective bit scrambling. The use of the lifting
scheme allows generating truly lossless integer-to-integer wavelet
transforms. Images are compressed/decompressed by well-known
EZW algorithm. The proposed modified runlength coding greatly
improves the compression performance and also increases the
security level. This work employs scrambling method which is fast,
simple to implement and it provides security. Lossless compression
ratios and distortion performance of this proposed method are found
to be better than other lossless techniques.
Abstract: An array of piezoelectric micro actuators can be used
for radiation of an ultrasonic carrier signal modulated in amplitude
with an acoustic signal, which yields audio frequency applications as
the air acts as a self-demodulating medium. This application is
known as the parametric array. We propose a parametric array with
array elements based on existing piezoelectric micro ultrasonic
transducer (pMUT) design techniques. In order to reach enough
acoustic output power at a desired operating frequency, a proper ratio
between number of array elements and array size needs to be used,
with an array total area of the order of one cm square. The
transducers presented are characterized via impedance, admittance,
noise figure, transducer gain and frequency responses.
Abstract: The exhaustive quality control is becoming more and
more important when commercializing competitive products in the
world's globalized market. Taken this affirmation as an undeniable
truth, it becomes critical in certain sector markets that need to offer
the highest restrictions in quality terms. One of these examples is the
percussion cap mass production, a critical element assembled in
firearm ammunition. These elements, built in great quantities at a
very high speed, must achieve a minimum tolerance deviation in
their fabrication, due to their vital importance in firing the piece of
ammunition where they are built in. This paper outlines a machine
vision development for the 100% inspection of percussion caps
obtaining data from 2D and 3D simultaneous images. The acquisition
speed and precision of these images from a metallic reflective piece
as a percussion cap, the accuracy of the measures taken from these
images and the multiple fabrication errors detected make the main
findings of this work.
Abstract: Set covering problem is a classical problem in
computer science and complexity theory. It has many applications,
such as airline crew scheduling problem, facilities location problem,
vehicle routing, assignment problem, etc. In this paper, three
different techniques are applied to solve set covering problem.
Firstly, a mathematical model of set covering problem is introduced
and solved by using optimization solver, LINGO. Secondly, the
Genetic Algorithm Toolbox available in MATLAB is used to solve
set covering problem. And lastly, an ant colony optimization method
is programmed in MATLAB programming language. Results
obtained from these methods are presented in tables. In order to
assess the performance of the techniques used in this project, the
benchmark problems available in open literature are used.
Abstract: Existing image-based virtual reality applications
allow users to view image-based 3D virtual environment in a more
interactive manner. User could “walkthrough"; looks left, right, up
and down and even zoom into objects in these virtual worlds of
images. However what the user sees during a “zoom in" is just a
close-up view of the same image which was taken from a distant.
Thus, this does not give the user an accurate view of the object from
the actual distance. In this paper, a simple technique for zooming in
an object in a virtual scene is presented. The technique is based on
the 'hotspot' concept in existing application. Instead of navigation
between two different locations, the hotspots are used to focus into
an object in the scene. For each object, several hotspots are created.
A different picture is taken for each hotspot. Each consecutive
hotspot created will take the user closer to the object. This will
provide the user with a correct of view of the object based on his
proximity to the object. Implementation issues and the relevance of
this technique in potential application areas are highlighted.
Abstract: This paper presents the application of discrete-time
variable structure control with sliding mode based on the 'reaching
law' method for robust control of a 'simple inverted pendulum on
moving cart' - a standard nonlinear benchmark system. The
controllers designed using the above techniques are completely
insensitive to parametric uncertainty and external disturbance. The
controller design is carried out using pole placement technique to find
state feedback gain matrix , which decides the dynamic behavior
of the system during sliding mode. This is followed by feedback gain
realization using the control law which is synthesized from 'Gao-s
reaching law'. The model of a single inverted pendulum and the
discrete variable structure control controller are developed, simulated
in MATLAB-SIMULINK and results are presented. The response of
this simulation is compared with that of the discrete linear quadratic
regulator (DLQR) and the advantages of sliding mode controller over
DLQR are also presented