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: 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: 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: 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: 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: 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: 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.
Abstract: Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.
Abstract: Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.
Abstract: The purpose of this paper isunavailability of the two main types of conveSwedish traction power supply (TPS) system, i.e.static converter. The number of outages and the ouused to analyze and compare the unavailability oconverters. The mean cumulative function (MCF)analyze the number of outages and the unavailabthe forced outage rate (FOR) concept has been uoutage rates. The study shows that the outagesfailure occur at a constant rate by calendar timconverter stations, while very few stations havedecreasing rate. It has also been found that the stata higher number of outages and a higher outage ratcompared to the rotary converter types. The resultsthat combining the number of outages and the fgives a better view of the converters performasupport for the maintenance decision. In fact, usingdoes not reflect reality. Comparing these two indein identifying the areas where extra resources are maintenance planning and where improvementsoutage in the TPS system.KeywordsFrequency Converter, Forced OuCumulative Function, Traction Power Supply, ESystems.
Abstract: Independent component analysis (ICA) in the
frequency domain is used for solving the problem of blind source
separation (BSS). However, this method has some problems. For
example, a general ICA algorithm cannot determine the permutation
of signals which is important in the frequency domain ICA. In this
paper, we propose an approach to the solution for a permutation
problem. The idea is to effectively combine two conventional
approaches. This approach improves the signal separation
performance by exploiting features of the conventional approaches.
We show the simulation results using artificial data.
Abstract: In this study, an ablation, mechanical and thermal properties of a rocket motor insulation from phenolic/ fiber matrix composites forming a laminate with different fiber between fiberglass and locally available synthetic fibers. The phenolic/ fiber matrix composites was mechanics and thermal properties by means of tensile strength, ablation, TGA and DSC. The design of thermal insulation involves several factors.Determined the mechanical properties according to MIL-I-24768: Density >1.3 g/cm3, Tensile strength >103 MPa and Ablation
Abstract: IP multicasting is a key technology for many existing and emerging applications on the Internet. Furthermore, with increasing popularity of wireless devices and mobile equipment, it is necessary to determine the best way to provide this service in a wireless environment. IETF Mobile IP, that provides mobility for hosts in IP networks, proposes two approaches for mobile multicasting, namely, remote subscription (MIP-RS) and bi-directional tunneling (MIP-BT). In MIP-RS, a mobile host re-subscribes to the multicast groups each time it moves to a new foreign network. MIP-RS suffers from serious packet losses while mobile host handoff occurs. In MIP-BT, mobile hosts send and receive multicast packets by way of their home agents (HAs), using Mobile IP tunnels. Therefore, it suffers from inefficient routing and wastage of system resources. In this paper, we propose a protocol called Mobile Multicast support using Old Foreign Agent (MMOFA) for Mobile Hosts. MMOFA is derived from MIP-RS and with the assistance of Mobile host's Old foreign agent, routes the missing datagrams due to handoff in adjacent network via tunneling. Also, we studied the performance of the proposed protocol by simulation under ns-2.27. The results demonstrate that MMOFA has optimal routing efficiency and low delivery cost, as compared to other approaches.
Abstract: The last decade has shown that object-oriented
concept by itself is not that powerful to cope with the rapidly
changing requirements of ongoing applications. Component-based
systems achieve flexibility by clearly separating the stable parts of
systems (i.e. the components) from the specification of their
composition. In order to realize the reuse of components effectively
in CBSD, it is required to measure the reusability of components.
However, due to the black-box nature of components where the
source code of these components are not available, it is difficult to
use conventional metrics in Component-based Development as these
metrics require analysis of source codes. In this paper, we survey
few existing component-based reusability metrics. These metrics
give a border view of component-s understandability, adaptability,
and portability. It also describes the analysis, in terms of quality
factors related to reusability, contained in an approach that aids
significantly in assessing existing components for reusability.