Abstract: In this paper, a framework for the simplification and
standardization of metaheuristic related parameter-tuning by applying
a four phase methodology, utilizing Design of Experiments and
Artificial Neural Networks, is presented. Metaheuristics are multipurpose
problem solvers that are utilized on computational optimization
problems for which no efficient problem specific algorithm
exist. Their successful application to concrete problems requires the
finding of a good initial parameter setting, which is a tedious and
time consuming task. Recent research reveals the lack of approach
when it comes to this so called parameter-tuning process. In the
majority of publications, researchers do have a weak motivation for
their respective choices, if any. Because initial parameter settings
have a significant impact on the solutions quality, this course of
action could lead to suboptimal experimental results, and thereby
a fraudulent basis for the drawing of conclusions.
Abstract: Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Abstract: Food borne illnesses have been reported to be a global
health challenge. Annual incidences of food–related diseases involve
76 million cases, of which only 14 million can be traced to known
pathogens. Poor hygienic practices have contributed greatly to this. It
has been reported that in the year 2000 about 2.1 million people died
from diarrheal diseases, hence, there is a need to ensure food safety at
all level. This study focused on the sterility examination and
inhibitory effect of honey samples on selected gram negative and
gram positive food borne pathogen from South West Nigeria. The
laboratory examinations revealed the presence of some bacterial and
fungal contaminations of honey samples and that inhibitory activity
of the honey sample was more pronounced on the gram negative
bacteria than the gram positive bacterial isolates. Antibiotic
sensitivity test conducted on the different bacterial isolates also
showed that honey was able to inhibit the proliferation of the tested
bacteria than the employed antibiotics.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
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: 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 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: In this paper we investigate the electrical
characteristics of a new structure of gate all around strained silicon
nanowire field effect transistors (FETs) with dual dielectrics by
changing the radius (RSiGe) of silicon-germanium (SiGe) wire and
gate dielectric. Indeed the effect of high-κ dielectric on Field Induced
Barrier Lowering (FIBL) has been studied. Due to the higher electron
mobility in tensile strained silicon, the n-type FETs with strained
silicon channel have better drain current compare with the pure Si
one. In this structure gate dielectric divided in two parts, we have
used high-κ dielectric near the source and low-κ dielectric near the
drain to reduce the short channel effects. By this structure short
channel effects such as FIBL will be reduced indeed by increasing
the RSiGe, ID-VD characteristics will be improved. The leakage
current and transfer characteristics, the threshold-voltage (Vt), the
drain induced barrier height lowering (DIBL), are estimated with
respect to, gate bias (VG), RSiGe and different gate dielectrics. For
short channel effects, such as DIBL, gate all around strained silicon
nanowire FET have similar characteristics with the pure Si one while
dual dielectrics can improve short channel effects in this structure.
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: 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: 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.