Abstract: The characteristics of fluid flow and phase separation
in an oil-water separator were numerically analysed as part of the
work presented herein. Simulations were performed for different
velocities and droplet diameters, and the way this parameters can
influence the separator geometry was studied.
The simulations were carried out using the software package
Fluent 6.2, which is designed for numerical simulation of fluid flow
and mass transfer. The model consisted of a cylindrical horizontal
separator. A tetrahedral mesh was employed in the computational
domain. The condition of two-phase flow was simulated with the
two-fluid model, taking into consideration turbulence effects using
the k-ε model.
The results showed that there is a strong dependency of phase
separation on mixture velocity and droplet diameter. An increase in
mixture velocity will bring about a slow down in phase separation
and as a consequence will require a weir of greater height. An
increase in droplet diameter will produce a better phase separation.
The simulations are in agreement with results reported in literature
and show that CFD can be a useful tool in studying a horizontal oilwater
separator.
Abstract: In this paper fatigue crack growth behavior of
aeronautical aluminum alloy 2024 T351 was studied. Effects of
various loading and geometrical parameters are studied such as stress
ratio, amplitude loading, etc. The fatigue crack growth with constant
amplitude is studied using the AFGROW code when NASGRO
model is used. The effect of the stress ratio is highlighted, where one
notices a shift of the curves of crack growth. The comparative study
between two orientations L-T and T-L on fatigue behavior are
presented and shows the variation on the fatigue life. L-T orientation
presents a good fatigue crack growth resistance. Effects of crack
closure are shown in Paris domain and that no crack closure
phenomenons are present at high stress intensity factor.
Abstract: In this paper, an image adaptive, invisible digital
watermarking algorithm with Orthogonal Polynomials based
Transformation (OPT) is proposed, for copyright protection of digital
images. The proposed algorithm utilizes a visual model to determine
the watermarking strength necessary to invisibly embed the
watermark in the mid frequency AC coefficients of the cover image,
chosen with a secret key. The visual model is designed to generate a
Just Noticeable Distortion mask (JND) by analyzing the low level
image characteristics such as textures, edges and luminance of the
cover image in the orthogonal polynomials based transformation
domain. Since the secret key is required for both embedding and
extraction of watermark, it is not possible for an unauthorized user to
extract the embedded watermark. The proposed scheme is robust to
common image processing distortions like filtering, JPEG
compression and additive noise. Experimental results show that the
quality of OPT domain watermarked images is better than its DCT
counterpart.
Abstract: In this paper a hybrid technique of Genetic Algorithm
and Simulated Annealing (HGASA) is applied for Fractal Image
Compression (FIC). With the help of this hybrid evolutionary
algorithm effort is made to reduce the search complexity of matching
between range block and domain block. The concept of Simulated
Annealing (SA) is incorporated into Genetic Algorithm (GA) in order
to avoid pre-mature convergence of the strings. One of the image
compression techniques in the spatial domain is Fractal Image
Compression but the main drawback of FIC is that it involves more
computational time due to global search. In order to improve the
computational time along with acceptable quality of the decoded
image, HGASA technique has been proposed. Experimental results
show that the proposed HGASA is a better method than GA in terms
of PSNR for Fractal image Compression.
Abstract: The theoretical prediction of the acoustical
polarization effects in the heterogeneous composites, made of thick
elastic solids with thin nematic films, is presented. The numericalanalytical
solution to the problem of the different wave propagation
exhibits some new physical effects in the low frequency domain: the
appearance of the critical frequency and the existence of the narrow
transition zone where the wave rapidly changes its speed. The
associated wave attenuation is highly perturbed in this zone. We also
show the possible appearance of the critical frequencies where the
attenuation changes the sign. The numerical results of parametrical
analysis are presented and discussed.
Abstract: Wrist pulse analysis for identification of health status
is found in Ancient Indian as well as Chinese literature. The preprocessing
of wrist pulse is necessary to remove outlier pulses and
fluctuations prior to the analysis of pulse pressure signal. This paper
discusses the identification of irregular pulses present in the pulse
series and intricacies associated with the extraction of time domain
pulse features. An approach of Dynamic Time Warping (DTW) has
been utilized for the identification of outlier pulses in the wrist pulse
series. The ambiguity present in the identification of pulse features is
resolved with the help of first derivative of Ensemble Average of
wrist pulse series. An algorithm for detecting tidal and dicrotic notch
in individual wrist pulse segment is proposed.
Abstract: Wireless capsule Endoscopy (WCE) has rapidly
shown its wide applications in medical domain last ten years
thanks to its noninvasiveness for patients and support for thorough
inspection through a patient-s entire digestive system including
small intestine. However, one of the main barriers to efficient
clinical inspection procedure is that it requires large amount of
effort for clinicians to inspect huge data collected during the
examination, i.e., over 55,000 frames in video. In this paper, we
propose a method to compute meaningful motion changes of
WCE by analyzing the obtained video frames based on regional
optical flow estimations. The computed motion vectors are used to
remove duplicate video frames caused by WCE-s imaging nature,
such as repetitive forward-backward motions from peristaltic
movements. The motion vectors are derived by calculating
directional component vectors in four local regions. Our
experiments are performed on small intestine area, which is of
main interest to clinical experts when using WCEs, and our
experimental results show significant frame reductions comparing
with a simple frame-to-frame similarity-based image reduction
method.
Abstract: An original Direct Numerical Simulation (DNS) method to tackle the problem of particulate flows at moderate to high concentration and finite Reynolds number is presented. Our method is built on the framework established by Glowinski and his coworkers [1] in the sense that we use their Distributed Lagrange Multiplier/Fictitious Domain (DLM/FD) formulation and their operator-splitting idea but differs in the treatment of particle collisions. The novelty of our contribution relies on replacing the simple artificial repulsive force based collision model usually employed in the literature by an efficient Discrete Element Method (DEM) granular solver. The use of our DEM solver enables us to consider particles of arbitrary shape (at least convex) and to account for actual contacts, in the sense that particles actually touch each other, in contrast with the simple repulsive force based collision model. We recently upgraded our serial code, GRIFF 1 [2], to full MPI capabilities. Our new code, PeliGRIFF 2, is developed under the framework of the full MPI open source platform PELICANS [3]. The new MPI capabilities of PeliGRIFF open new perspectives in the study of particulate flows and significantly increase the number of particles that can be considered in a full DNS approach: O(100000) in 2D and O(10000) in 3D. Results on the 2D/3D sedimentation/fluidization of isometric polygonal/polyedral particles with collisions are presented.
Abstract: X-ray mammography is the most effective method for
the early detection of breast diseases. However, the typical diagnostic
signs such as microcalcifications and masses are difficult to detect
because mammograms are of low-contrast and noisy. In this paper, a
new algorithm for image denoising and enhancement in Orthogonal
Polynomials Transformation (OPT) is proposed for radiologists to
screen mammograms. In this method, a set of OPT edge coefficients
are scaled to a new set by a scale factor called OPT scale factor. The
new set of coefficients is then inverse transformed resulting in
contrast improved image. Applications of the proposed method to
mammograms with subtle lesions are shown. To validate the
effectiveness of the proposed method, we compare the results to
those obtained by the Histogram Equalization (HE) and the Unsharp
Masking (UM) methods. Our preliminary results strongly suggest
that the proposed method offers considerably improved enhancement
capability over the HE and UM methods.
Abstract: Over the years, many implementations have been
proposed for solving IA networks. These implementations are
concerned with finding a solution efficiently. The primary goal of
our implementation is simplicity and ease of use.
We present an IA network implementation based on finite domain
non-binary CSPs, and constraint logic programming. The
implementation has a GUI which permits the drawing of arbitrary IA
networks. We then show how the implementation can be extended to
find all the solutions to an IA network. One application of finding all
the solutions, is solving probabilistic IA networks.
Abstract: In recent years, sustainable supply chain management
(SSCM) has been widely researched in academic domain. However,
due to the traditional operational role and the complexity of supply
chain management in the cement industry, a relatively small amount
of research has been conducted on cement supply chain simulation
integrated with sustainability criteria. This paper analyses the cement
supply chain operations using the Push-Pull supply chain
frameworks, the Life Cycle Assessment (LCA) methodology; and
proposal integration approach, proposes three supply chain scenarios
based on Make-To-Stock (MTS), Pack-To-Order (PTO) and Grind-
To-Order (GTO) strategies. A Discrete-Event Simulation (DES)
model of SSCM is constructed using Arena software to implement
the three-target scenarios. We conclude with the simulation results
that (GTO) is the optimal supply chain strategy that demonstrates the
best economic, ecological and social performance in the cement
industry.
Abstract: This paper adopted the hybrid differential transform approach for studying heat transfer problems in a gold/chromium thin film with an ultra-short-pulsed laser beam projecting on the gold side. The physical system, formulated based on the hyperbolic two-step heat transfer model, covers three characteristics: (i) coupling effects between the electron/lattice systems, (ii) thermal wave propagation in metals, and (iii) radiation effects along the interface. The differential transform method is used to transfer the governing equations in the time domain into the spectrum equations, which is further discretized in the space domain by the finite difference method. The results, obtained through a recursive process, show that the electron temperature in the gold film can rise up to several thousand degrees before its electron/lattice systems reach equilibrium at only several hundred degrees. The electron and lattice temperatures in the chromium film are much lower than those in the gold film.
Abstract: In a previous work, we presented the numerical
solution of the two dimensional second order telegraph partial
differential equation discretized by the centred and rotated five-point
finite difference discretizations, namely the explicit group (EG) and
explicit decoupled group (EDG) iterative methods, respectively. In
this paper, we utilize a domain decomposition algorithm on these
group schemes to divide the tasks involved in solving the same
equation. The objective of this study is to describe the development
of the parallel group iterative schemes under OpenMP programming
environment as a way to reduce the computational costs of the
solution processes using multicore technologies. A detailed
performance analysis of the parallel implementations of points and
group iterative schemes will be reported and discussed.
Abstract: This paper provides an introduction into the evolution
of information and communication technology and illustrates its
usage in the work domain. The paper is sub-divided into two parts.
The first part gives an overview over the different phases of
information processing in the work domain. It starts by charting the
past and present usage of computers in work environments and shows
current technological trends, which are likely to influence future
business applications. The second part starts by briefly describing,
how the usage of computers changed business processes in the past,
and presents first Ambient Intelligence applications based on
identification and localization information, which are already used in
the production and retail sector. Based on current systems and
prototype applications, the paper gives an outlook of how Ambient
Intelligence technologies could change business processes in the
future.
Abstract: Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.
Abstract: The mechanical behavior of porous media is governed by the interaction between its solid skeleton and the fluid existing inside its pores. The interaction occurs through the interface of gains and fluid. The traditional analysis methods of porous media, based on the effective stress and Darcy's law, are unable to account for these interactions. For an accurate analysis, the porous media is represented in a fluid-filled porous solid on the basis of the Biot theory of wave propagation in poroelastic media. In Biot formulation, the equations of motion of the soil mixture are coupled with the global mass balance equations to describe the realistic behavior of porous media. Because of irregular geometry, the domain is generally treated as an assemblage of fmite elements. In this investigation, the numerical formulation for the field equations governing the dynamic response of fluid-saturated porous media is analyzed and employed for the study of transient wave motion. A finite element model is developed and implemented into a computer code called DYNAPM for dynamic analysis of porous media. The weighted residual method with 8-node elements is used for developing of a finite element model and the analysis is carried out in the time domain considering the dynamic excitation and gravity loading. Newmark time integration scheme is developed to solve the time-discretized equations which are an unconditionally stable implicit method Finally, some numerical examples are presented to show the accuracy and capability of developed model for a wide variety of behaviors of porous media.
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.
Abstract: This paper presents a model of case based corporate
memory named ReCaRo (REsource, CAse, ROle). The approach
suggested in ReCaRo decomposes the domain to model through a set
of components. These components represent the objects developed by
the company during its activity. They are reused, and sometimes,
while bringing adaptations. These components are enriched by
knowledge after each reuse. ReCaRo builds the corporate memory on
the basis of these components. It models two types of knowledge: 1)
Business Knowledge, which constitutes the main knowledge capital
of the company, refers to its basic skill, thus, directly to the
components and 2) the Experience Knowledge which is a specialised
knowledge and represents the experience gained during the handling
of business knowledge. ReCaRo builds corporate memories which
are made up of five communicating ones.
Abstract: The Norwegian Military Academy (Army) has
initiated a project with the main ambition to explore possible avenues
to enhancing operational effectiveness through an increased use of
simulation-based training and exercises. Within a cost/benefit
framework, we discuss opportunities and limitations of vertical and
horizontal integration of the existing tactical training system. Vertical
integration implies expanding the existing training system to span the
full range of training from tactical level (platoon, company) to
command and staff level (battalion, brigade). Horizontal integration
means including other domains than army tactics and staff
procedures in the training, such as military ethics, foreign languages,
leadership and decision making. We discuss each of the integration
options with respect to purpose and content of training, "best
practice" for organising and conducting simulation-based training,
and suggest how to evaluate training procedures and measure
learning outcomes. We conclude by giving guidelines towards further
explorative work and possible implementation.