Abstract: This paper examined the influence of matching
students- learning preferences with the teaching methodology
adopted, on their academic performance in an accounting course in
two types of learning environment in one university in Lebanon:
classes with PowerPoint (PPT) vs. conventional classes. Learning
preferences were either for PPT or for Conventional methodology. A
statistically significant increase in academic achievement is found in
the conventionally instructed group as compared to the group taught
with PPT. This low effectiveness of PPT might be attributed to the
learning preferences of Lebanese students. In the PPT group, better
academic performance was found among students with
learning/teaching match as compared with students with
learning/teaching mismatch. Since the majority of students display a
preference for the conventional methodology, the result might
suggest that Lebanese students- performance is not optimized by PPT
in the accounting classrooms, not because of PPT itself, but because
it is not matching the Lebanese students- learning preferences in such
a quantitative course.
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: This paper presents a Particle Swarm Optimization
(PSO) method for determining the optimal parameters of a first-order
controller for TCP/AQM system. The model TCP/AQM is described
by a second-order system with time delay. First, the analytical
approach, based on the D-decomposition method and Lemma of
Kharitonov, is used to determine the stabilizing regions of a firstorder
controller. Second, the optimal parameters of the controller are
obtained by the PSO algorithm. Finally, the proposed method is
implemented in the Network Simulator NS-2 and compared with the
PI controller.
Abstract: In this paper an algorithm is used to detect the color defects of ceramic tiles. First the image of a normal tile is clustered using GCMA; Genetic C-means Clustering Algorithm; those results in best cluster centers. C-means is a common clustering algorithm which optimizes an objective function, based on a measure between data points and the cluster centers in the data space. Here the objective function describes the mean square error. After finding the best centers, each pixel of the image is assigned to the cluster with closest cluster center. Then, the maximum errors of clusters are computed. For each cluster, max error is the maximum distance between its center and all the pixels which belong to it. After computing errors all the pixels of defected tile image are clustered based on the centers obtained from normal tile image in previous stage. Pixels which their distance from their cluster center is more than the maximum error of that cluster are considered as defected pixels.
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: A structural study of an aqueous electrolyte whose
experimental results are available. It is a solution of LiCl-6H2O type
at glassy state (120K) contrasted with pure water at room temperature
by means of Partial Distribution Functions (PDF) issue from neutron
scattering technique. Based on these partial functions, the Reverse
Monte Carlo method (RMC) computes radial and angular correlation
functions which allow exploring a number of structural features of
the system. The obtained curves include some artifacts. To remedy
this, we propose to introduce a screened potential as an additional
constraint. Obtained results show a good matching between
experimental and computed functions and a significant improvement
in PDFs curves with potential constraint. It suggests an efficient fit of
pair distribution functions curves.
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: Clean air in subway station is important to passengers. The Platform Screen Doors (PSDs) can improve indoor air quality in the subway station; however the air quality in the subway tunnel is degraded. The subway tunnel has high CO2 concentration and indoor particulate matter (PM) value. The Indoor Air Quality (IAQ) level in subway environment degrades by increasing the frequency of the train operation and the number of the train. The ventilation systems of the subway tunnel need improvements to have better air-quality. Numerical analyses might be effective tools to analyze the performance of subway twin-track tunnel ventilation systems. An existing subway twin-track tunnel in the metropolitan Seoul subway system is chosen for the numerical simulations. The ANSYS CFX software is used for unsteady computations of the airflow inside the twin-track tunnel when the train moves. The airflow inside the tunnel is simulated when one train runs and two trains run at the same time in the tunnel. The piston-effect inside the tunnel is analyzed when all shafts function as the natural ventilation shaft. The supplied air through the shafts is mixed with the pollutant air in the tunnel. The pollutant air is exhausted by the mechanical ventilation shafts. The supplied and discharged airs are balanced when only one train runs in the twin-track tunnel. The pollutant air in the tunnel is high when two trains run simultaneously in opposite direction and all shafts functioned as the natural shaft cases when there are no electrical power supplies in the shafts. The remained pollutant air inside the tunnel enters into the station platform when the doors are opened.
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: Airport capacity has always been perceived in the
traditional sense as the number of aircraft operations during a
specified time corresponding to a tolerable level of average delay and
it mostly depends on the airside characteristics, on the fleet mix
variability and on the ATM. The adoption of the Directive
2002/30/EC in the EU countries drives the stakeholders to conceive
airport capacity in a different way though. Airport capacity in this
sense is fundamentally driven by environmental criteria, and since
acoustical externalities represent the most important factors, those are
the ones that could pose a serious threat to the growth of airports and
to aviation market itself in the short-medium term. The importance of
the regional airports in the deregulated market grew fast during the
last decade since they represent spokes for network carriers and a
preferential destination for low-fares carriers. Not only regional
airports have witnessed a fast and unexpected growth in traffic but
also a fast growth in the complaints for the nuisance by the people
living near those airports. In this paper the results of a study
conducted in cooperation with the airport of Bologna G. Marconi are
presented in order to investigate airport acoustical capacity as a defacto
constraint of airport growth.
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: The reduction in vehicle exhaust emissions achieved
in the last two decades is offset by the growth in traffic, as well as by
changes in the composition of emitted pollutants. The present
investigation illustrates the emissions of in-use gasoline and diesel
passenger cars using the official European driving cycle and the
ARTEMIS real-world driving cycle. It was observed that some of the
vehicles do not comply with the corresponding regulations.
Significant differences in emissions were observed between driving
cycles. Not all pollutants showed a tendency to decrease from Euro 3
to Euro 5.
Abstract: Recently global concerns for the energy security have
steadily been on the increase and are expected to become a major
issue over the next few decades. Energy security refers to a resilient
energy system. This resilient system would be capable of
withstanding threats through a combination of active, direct security
measures and passive or more indirect measures such as redundancy,
duplication of critical equipment, diversity in fuel, other sources of
energy, and reliance on less vulnerable infrastructure. Threats and
disruptions (disturbances) to one part of the energy system affect
another. The paper presents methodology in theoretical background
about energy system as an interconnected network and energy supply
disturbances impact to the network. The proposed methodology uses
a network flow approach to develop mathematical model of the
energy system network as the system of nodes and arcs with energy
flowing from node to node along paths in the network.
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.