Abstract: The use of amine mixtures employing
methyldiethanolamine (MDEA), monoethanolamine (MEA), and diethanolamine (DEA) have been investigated for a variety of cases
using a process simulation program called HYSYS. The results show that, at high pressures, amine mixtures have little or no advantage in the cases studied. As the pressure is lowered, it becomes more difficult for MDEA to meet residual gas requirements and mixtures can usually improve plant performance. Since the CO2 reaction rate
with the primary and secondary amines is much faster than with
MDEA, the addition of small amounts of primary or secondary amines to an MDEA based solution should greatly improve the overall reaction rate of CO2 with the amine solution. The addition of MEA caused the CO2 to be absorbed more strongly in the upper portion of the column than for MDEA along. On the other hand,
raising the concentration for MEA to 11%wt, CO2 is almost
completely absorbed in the lower portion of the column. The addition of MEA would be most advantageous.
Thus, in areas where MDEA cannot meet the residual gas
requirements, the use of amine mixtures can usually improve the plant
performance.
Abstract: The third generation (3G) of cellular system adopted
the spread spectrum as solution for the transmission of the data in the
physical layer. Contrary to systems IS-95 or CDMAOne (systems
with spread spectrum of the preceding generation), the new standard,
called Universal Mobil Telecommunications System (UMTS), uses
long codes in the down link. The system is conceived for the vocal
communication and the transmission of the data. In particular, the
down link is very important, because of the asymmetrical request of
the data, i.e., more remote loading towards the mobiles than towards
the basic station. Moreover, the UMTS uses for the down link an
orthogonal spreading out with a variable factor of spreading out
(OVSF for Orthogonal Variable Spreading Factor). This
characteristic makes it possible to increase the flow of data of one or
more users by reducing their factor of spreading out without
changing the factor of spreading out of other users. In the current
standard of the UMTS, two techniques to increase the performances
of the down link were proposed, the diversity of sending antenna and
the codes space-time. These two techniques fight only fainding. The
receiver proposed for the mobil station is the RAKE, but one can
imagine a receiver more sophisticated, able to reduce the interference
between users and the impact of the coloured noise and interferences
to narrow band. In this context, where the users have long codes
synchronized with variable factor of spreading out and ignorance by
the mobile of the other active codes/users, the use of the sequences of
code pseudo-noises different lengths is presented in the form of one
of the most appropriate solutions.
Abstract: The structure of retinal vessels is a prominent feature,
that reveals information on the state of disease that are reflected in
the form of measurable abnormalities in thickness and colour.
Vascular structures of retina, for implementation of clinical diabetic
retinopathy decision making system is presented in this paper.
Retinal Vascular structure is with thin blood vessel, whose accuracy
is highly dependent upon the vessel segmentation. In this paper the
blood vessel thickness is automatically detected using preprocessing
techniques and vessel segmentation algorithm. First the capture
image is binarized to get the blood vessel structure clearly, then it is
skeletonised to get the overall structure of all the terminal and
branching nodes of the blood vessels. By identifying the terminal
node and the branching points automatically, the main and branching
blood vessel thickness is estimated. Results are presented and
compared with those provided by clinical classification on 50 vessels
collected from Bejan Singh Eye hospital..
Abstract: In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroom) with a teacher and additionally at home at a convenient time; student himself sets the optimal speed and intensity of the learning process; this method helps student to discipline himself and learn to work independently.
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: Different problems may causes distortion of the rotor,
and hence vibration, which is the most severe damage of the turbine
rotors. In many years different techniques have been developed for
the straightening of bent rotors. The method for straightening can be
selected according to initial information from preliminary inspections
and tests such as nondestructive tests, chemical analysis, run out tests
and also a knowledge of the shaft material. This article covers the
various causes of excessive bends and then some applicable common
straightening methods are reviewed. Finally, hot spotting is opted for
a particular bent rotor. A 325 MW steam turbine rotor is modeled and
finite element analyses are arranged to investigate this straightening
process. Results of experimental data show that performing the exact
hot spot straightening process reduced the bending of the rotor
significantly.
Abstract: An important step in studying the statistics of
fingerprint minutia features is to reliably extract minutia features from
the fingerprint images. A new reliable method of computation for
minutiae feature extraction from fingerprint images is presented. A
fingerprint image is treated as a textured image. An orientation flow
field of the ridges is computed for the fingerprint image. To
accurately locate ridges, a new ridge orientation based computation
method is proposed. After ridge segmentation a new method of
computation is proposed for smoothing the ridges. The ridge skeleton
image is obtained and then smoothed using morphological operators
to detect the features. A post processing stage eliminates a large
number of false features from the detected set of minutiae features.
The detected features are observed to be reliable and accurate.
Abstract: Background: Widespread use of chemotherapeutic
drugs in the treatment of cancer has lead to higher health hazards
among employee who handle and administer such drugs, so nurses
should know how to protect themselves, their patients and their work
environment against toxic effects of chemotherapy. Aim of this study
was carried out to examine the effect of chemotherapy safety protocol
for oncology nurses on their protective measure practices. Design: A
quasi experimental research design was utilized. Setting: The study
was carried out in oncology department of Menoufia university
hospital and Tanta oncology treatment center. Sample: A
convenience sample of forty five nurses in Tanta oncology treatment
center and eighteen nurses in Menoufiya oncology department.
Tools: 1. an interviewing questionnaire that covering sociodemographic
data, assessment of unit and nurses' knowledge about
chemotherapy. II: Obeservational check list to assess nurses' actual
practices of handling and adminestration of chemotherapy. A base
line data were assessed before implementing Chemotherapy Safety
protocol, then Chemotherapy Safety protocol was implemented, and
after 2 monthes they were assessed again. Results: reveled that 88.9%
of study group I and 55.6% of study group II improved to good total
knowledge scores after educating on the safety protocol, also 95.6%
of study group I and 88.9% of study group II had good total practice
score after educating on the safety protocol. Moreover less than half
of group I (44.4%) reported that heavy workload is the most barriers
for them, while the majority of group II (94.4%) had many barriers
for adhering to the safety protocol such as they didn’t know the
protocol, the heavy work load and inadequate equipment.
Conclusions: Safety protocol for Oncology Nurses seemed to have
positive effect on improving nurses' knowledge and practice.
Recommendation: chemotherapy safety protocol should be instituted
for all oncology nurses who are working in any oncology unit and/ or
center to enhance compliance, and this protocol should be done at
frequent intervals.
Abstract: Quality control charts are very effective in detecting
out of control signals but when a control chart signals an out of
control condition of the process mean, searching for a special cause
in the vicinity of the signal time would not always lead to prompt
identification of the source(s) of the out of control condition as the
change point in the process parameter(s) is usually different from the
signal time. It is very important to manufacturer to determine at what
point and which parameters in the past caused the signal. Early
warning of process change would expedite the search for the special
causes and enhance quality at lower cost. In this paper the quality
variables under investigation are assumed to follow a multivariate
normal distribution with known means and variance-covariance
matrix and the process means after one step change remain at the new
level until the special cause is being identified and removed, also it is
supposed that only one variable could be changed at the same time.
This research applies artificial neural network (ANN) to identify the
time the change occurred and the parameter which caused the change
or shift. The performance of the approach was assessed through a
computer simulation experiment. The results show that neural
network performs effectively and equally well for the whole shift
magnitude which has been considered.
Abstract: This paper is concerned with the delay-distributiondependent
stability criteria for bidirectional associative memory
(BAM) neural networks with time-varying delays. Based on the
Lyapunov-Krasovskii functional and stochastic analysis approach,
a delay-probability-distribution-dependent sufficient condition is derived
to achieve the globally asymptotically mean square stable of
the considered BAM neural networks. The criteria are formulated in
terms of a set of linear matrix inequalities (LMIs), which can be
checked efficiently by use of some standard numerical packages. Finally,
a numerical example and its simulation is given to demonstrate
the usefulness and effectiveness of the proposed results.
Abstract: The role of entrepreneurs in generating the economy is
very important. Thus, nurturing entrepreneurship skills among
society is very crucial and should start from the early age. One of the
methods is to teach through game such as board game. Game
provides a fun and interactive platform for players to learn and play.
Besides that as today-s world is moving towards Islamic approach in
terms of finance, banking and entertainment but Islamic based game
is still hard to find in the market especially games on
entrepreneurship. Therefore, there is a gap in this segment that can be
filled by learning entrepreneurship through game. The objective of
this paper is to develop an entrepreneurship digital-based game
entitled “Catur Bistari" that is based on Islamic business approach.
Knowledge and skill of entrepreneurship and Islamic business
approach will be learned through the tasks that are incorporated
inside the game.
Abstract: In this paper, parallelism in the solution of Ordinary
Differential Equations (ODEs) to increase the computational speed is
studied. The focus is the development of parallel algorithm of the two
point Block Backward Differentiation Formulas (PBBDF) that can
take advantage of the parallel architecture in computer technology.
Parallelism is obtained by using Message Passing Interface (MPI).
Numerical results are given to validate the efficiency of the PBBDF
implementation as compared to the sequential implementation.
Abstract: A complex valued neural network is a neural network
which consists of complex valued input and/or weights and/or thresholds
and/or activation functions. Complex-valued neural networks
have been widening the scope of applications not only in electronics
and informatics, but also in social systems. One of the most important
applications of the complex valued neural network is in signal
processing. In Neural networks, generalized mean neuron model
(GMN) is often discussed and studied. The GMN includes a new
aggregation function based on the concept of generalized mean of all
the inputs to the neuron. This paper aims to present exhaustive results
of using Generalized Mean Neuron model in a complex-valued neural
network model that uses the back-propagation algorithm (called
-Complex-BP-) for learning. Our experiments results demonstrate the
effectiveness of a Generalized Mean Neuron Model in a complex
plane for signal processing over a real valued neural network. We
have studied and stated various observations like effect of learning
rates, ranges of the initial weights randomly selected, error functions
used and number of iterations for the convergence of error required on
a Generalized Mean neural network model. Some inherent properties
of this complex back propagation algorithm are also studied and
discussed.
Abstract: Overcurrent (OC) relays are the major protection
devices in a distribution system. The operating time of the OC relays
are to be coordinated properly to avoid the mal-operation of the
backup relays. The OC relay time coordination in ring fed
distribution networks is a highly constrained optimization problem
which can be stated as a linear programming problem (LPP). The
purpose is to find an optimum relay setting to minimize the time of
operation of relays and at the same time, to keep the relays properly
coordinated to avoid the mal-operation of relays.
This paper presents two phase simplex method for optimum time
coordination of OC relays. The method is based on the simplex
algorithm which is used to find optimum solution of LPP. The
method introduces artificial variables to get an initial basic feasible
solution (IBFS). Artificial variables are removed using iterative
process of first phase which minimizes the auxiliary objective
function. The second phase minimizes the original objective function
and gives the optimum time coordination of OC relays.
Abstract: Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.
Abstract: The major building block of most elliptic curve cryptosystems
are computation of multi-scalar multiplication. This paper
proposes a novel algorithm for simultaneous multi-scalar multiplication,
that is by employing addition chains. The previously known
methods utilizes double-and-add algorithm with binary representations.
In order to accomplish our purpose, an efficient empirical
method for finding addition chains for multi-exponents has been
proposed.
Abstract: Antimicrobial resistant is becoming a major factor in
virtually all hospital acquired infection may soon untreatable is a
serious public health problem. These concerns have led to major
research effort to discover alternative strategies for the treatment of
bacterial infection. Nanobiotehnology is an upcoming and fast
developing field with potential application for human welfare. An
important area of nanotechnology for development of reliable and
environmental friendly process for synthesis of nanoscale particles
through biological systems In the present studies are reported on the
use of fungal strain Aspergillus species for the extracellular synthesis
of bionanoparticles from 1 mM silver nitrate (AgNO3) solution. The
report would be focused on the synthesis of metallic bionanoparticles
of silver using a reduction of aqueous Ag+ ion with the
culture supernatants of Microorganisms. The bio-reduction of the
Ag+ ions in the solution would be monitored in the aqueous
component and the spectrum of the solution would measure through
UV-visible spectrophotometer The bionanoscale particles were
further characterized by Atomic Force Microscopy (AFM), Fourier
Transform Infrared Spectroscopy (FTIR) and Thin layer
chromatography. The synthesized bionanoscale particle showed a
maximum absorption at 385 nm in the visible region. Atomic Force
Microscopy investigation of silver bionanoparticles identified that
they ranged in the size of 250 nm - 680 nm; the work analyzed the
antimicrobial efficacy of the silver bionanoparticles against various
multi drug resistant clinical isolates. The present Study would be
emphasizing on the applicability to synthesize the metallic
nanostructures and to understand the biochemical and molecular
mechanism of nanoparticles formation by the cell filtrate in order to
achieve better control over size and polydispersity of the
nanoparticles. This would help to develop nanomedicine against
various multi drug resistant human pathogens.
Abstract: Localized surface plasmon resonance (LSPR) is the
coherent oscillation of conductive electrons confined in noble
metallic nanoparticles excited by electromagnetic radiation, and
nanosphere lithography (NSL) is one of the cost-effective methods to
fabricate metal nanostructures for LSPR. NSL can be categorized
into two major groups: dispersed NSL and closely pack NSL. In
recent years, gold nanocrescents and gold nanoholes with vertical
sidewalls fabricated by dispersed NSL, and silver nanotriangles and
gold nanocaps on silica nanospheres fabricated by closely pack NSL,
have been reported for LSPR biosensing. This paper introduces
several novel gold nanostructures fabricated by NSL in LSPR
applications, including 3D nanostructures obtained by evaporating
gold obliquely on dispersed nanospheres, nanoholes with slant
sidewalls, and patchy nanoparticles on closely packed nanospheres,
all of which render satisfactory sensitivity for LSPR sensing. Since
the LSPR spectrum is very sensitive to the shape of the metal
nanostructures, formulas are derived and software is developed for
calculating the profiles of the obtainable metal nanostructures by
NSL, for different nanosphere masks with different fabrication
conditions. The simulated profiles coincide well with the profiles of
the fabricated gold nanostructures observed under scanning electron
microscope (SEM) and atomic force microscope (AFM), which
proves that the software is a useful tool for the process design of
different LSPR nanostructures.
Abstract: Palladium-catalyzed hydrodechlorination is a
promising alternative for the treatment of environmentally relevant
water bodies, such as groundwater, contaminated with chlorinated
organic compounds (COCs). In the aqueous phase
hydrodechlorination of COCs, Pd-based catalysts were found to have
a very high catalytic activity. However, the full utilization of the
catalyst-s potential is impeded by the sensitivity of the catalyst to
poisoning and deactivation induced by reduced sulfur compounds
(e.g. sulfides). Several regenerants have been tested before to recover
the performance of sulfide-fouled Pd catalyst. But these only
delivered partial success with respect to re-establishment of the
catalyst activity. In this study, the deactivation behaviour of
Pd/Al2O3 in the presence of sulfide was investigated. Subsequent to
total deactivation the catalyst was regenerated in the aqueous phase
using potassium permanganate. Under neutral pH condition,
oxidative regeneration with permanganate delivered a slow recovery
of catalyst activity. However, changing the pH of the bulk solution to
acidic resulted in the complete recovery of catalyst activity within a
regeneration time of about half an hour. These findings suggest the
superiority of permanganate as regenerant in re-activating Pd/Al2O3
by oxidizing Pd-bound sulfide.
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.