Abstract: Background: To improve the delivery of paediatric
healthcare in low resource settings, Community Health Workers
(CHW) have been provided with a paper-based set of protocols
known as Community Case Management (CCM). Yet research has
shown that CHW adherence to CCM guidelines is poor, ultimately
impacting health service delivery. Digitising the CCM guidelines via
mobile technology is argued in extant literature to improve CHW
adherence. However, little research exist which outlines how (a) this
process can be digitised and (b) adherence could be improved as a
result. Aim: To explore how an electronic mobile version of CCM
(eCCM) can overcome issues associated with the paper-based CCM
protocol (inadequate adherence to guidelines) vis-à-vis service
blueprinting. This service blueprint will outline how (a) the CCM
process can be digitised using mobile Clinical Decision Support
Systems software to support clinical decision-making and (b)
adherence can be improved as a result. Method: Development of a
single service blueprint for a standalone application which visually
depicts the service processes (eCCM) when supporting the CHWs,
using an application known as Supporting LIFE (SL eCCM app) as
an exemplar. Results: A service blueprint is developed which
illustrates how the SL eCCM app can be utilised by CHWs to assist
with the delivery of healthcare services to children. Leveraging
smartphone technologies can (a) provide CHWs with just-in-time
data to assist with their decision making at the point-of-care and (b)
improve CHW adherence to CCM guidelines. Conclusions: The
development of the eCCM opens up opportunities for the CHWs to
leverage the inherent benefit of mobile devices to assist them with
health service delivery in rural settings. To ensure that benefits are
achieved, it is imperative to comprehend the functionality and form
of the eCCM service process. By creating such a service blueprint for
an eCCM approach, CHWs are provided with a clear picture
regarding the role of the eCCM solution, often resulting in buy-in
from the end-users.
Abstract: Presently various computational techniques are used
in modeling and analyzing environmental engineering data. In the
present study, an intra-comparison of polynomial and radial basis
kernel functions based on Support Vector Regression and, in turn, an
inter-comparison with Multi Linear Regression has been attempted in
modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ
multiple plunging jets (varying from 1 to 16 numbers). The data set
used in this study consists of four input parameters with a total of
eighty eight cases, forty four each for vertical and inclined multiple
plunging jets. For testing, tenfold cross validation was used.
Correlation coefficient values of 0.971 and 0.981 along with
corresponding root mean square error values of 0.0025 and 0.0020
were achieved by using polynomial and radial basis kernel functions
based Support Vector Regression respectively. An intra-comparison
suggests improved performance by radial basis function in
comparison to polynomial kernel based Support Vector Regression.
Further, an inter-comparison with Multi Linear Regression
(correlation coefficient = 0.973 and root mean square error = 0.0024)
reveals that radial basis kernel functions based Support Vector
Regression performs better in modeling and estimating mass transfer
by multiple plunging jets.
Abstract: Annihilations, phase shifts, scattering lengths and
elastic cross sections of low energy positrons scattering from
magnesium atoms were studied using the least-squares variational
method (LSVM). The possibility of positron binding to the
magnesium atoms is investigated. A trial wave function is suggested
to represent e+-Mg elastic scattering and scattering parameters were
derived to estimate the binding energy and annihilation rates. The
trial function is taken to depend on several adjustable parameters, and
is improved iteratively by increasing the number of terms. The
present results have the same behavior as reported semi-empirical,
theoretical and experimental results. Especially, the estimated
positive scattering length supports the possibility of positronmagnesium
bound state system that was confirmed in previous
experimental and theoretical work.
Abstract: Maintaining factory default battery endurance rate
over time in supporting huge amount of running applications on
energy-restricted mobile devices has created a new challenge for
mobile applications developer. While delivering customers’
unlimited expectations, developers are barely aware of efficient use
of energy from the application itself. Thus, developers need a set of
valid energy consumption indicators in assisting them to develop
energy saving applications. In this paper, we present a few software
product metrics that can be used as an indicator to measure energy
consumption of Android-based mobile applications in the early of
design stage. In particular, Trepn Profiler (Power profiling tool for
Qualcomm processor) has used to collect the data of mobile
application power consumption, and then analyzed for the 23
software metrics in this preliminary study. The results show that
McCabe cyclomatic complexity, number of parameters, nested block
depth, number of methods, weighted methods per class, number of
classes, total lines of code and method lines have direct relationship
with power consumption of mobile application.
Abstract: This article describes the results of research focused
on quality of railway freight transport services. Improvement of these
services has a crucial importance in customer considering on the
future use of railway transport. Processes filling the customer
demands and output quality assessment were defined as a part of the
research. In this contribution is introduced the map of quality
planning and the algorithm of applied methodology. It characterizes a
model which takes into account characters of transportation with
linking a perception services quality in ordinary and extraordinary
operation. Despite the fact that rail freight transport has its solid
position in the transport market, lots of carriers worldwide have been
experiencing a stagnation for a couple of years. Therefore, specific
results of the research have a significant importance and belong to
numerous initiatives aimed to develop and support railway transport
not only by creating a single railway area or reducing noise but also
by promoting railway services. This contribution is focused also on
the application of dynamic quality models which represent an
innovative method of evaluation quality services. Through this
conception, time factor, expected, and perceived quality in each
moment of the transportation process can be taken into account.
Abstract: In this study, students’ learning has been investigated
and satisfaction in one of the course offered at Qatar University
Foundation Program. Innovative teaching has been implied
methodology that emphasizes on enhancing students’ thinking skills,
decision making, and problem solving skills. Some interesting results
were found which could be used to further improvement of the
teaching methodology. In Fall 2012 in Foundation Program Math
department at Qatar University has started implementing new ways
of teaching Math by introducing MyMathLab (MML) as an
innovative interactive tool in addition of the use Blackboard to
support standard teaching such as Discussion board in Virtual class to
engage students outside of classroom and to enhance independent,
active learning that promote students’ critical thinking skills, decision
making, and problem solving skills through the learning process.
Abstract: In this paper, we will try to demonstrate the
importance of the project approach in the urban to deal with
uncertainty, the importance of the involvement of all stakeholders in
the urban project process and that the absence of an actor can lead to
project failure but also the importance of the urban project
management. These points are handled through the following questions: Does
the urban adhere to the theory of complexity? Does the project
approach bring hope and solution to make urban planning
"sustainable"? How converging visions of actors for the same
project? Is the management of urban project the solution to support
the urban project approach?
Abstract: Modelling of building processes of a multimodal
freight transportation support information system is discussed based
on modern CASE technologies. Functional efficiencies of ports in
the eastern part of the Black Sea are analyzed taking into account
their ecological, seasonal, resource usage parameters. By resources,
we mean capacities of berths, cranes, automotive transport, as well as
work crews and neighbouring airports. For the purpose of designing
database of computer support system for Managerial (Logistics)
function, using Object-Role Modeling (ORM) tool (NORMA–Natural ORM Architecture) is proposed, after which Entity
Relationship Model (ERM) is generated in automated process.
Software is developed based on Process-Oriented and Service-Oriented architecture, in Visual Studio.NET environment.
Abstract: The aim of this study was to determine the factor
structure and psychometric properties (i.e., reliability and convergent
validity) of the Employee Trust Scale, a newly created instrument by
the researchers. The Employee Trust Scale initially contained 82
items to measure employees’ trust toward their supervisors. A sample
of 818 (343 females, 449 males) employees were selected randomly
from public and private organization sectors in Kota Kinabalu,
Sabah, Malaysia. Their ages ranged from 19 to 67 years old with a
mean of 34.55 years old. Their average tenure with their current
employer was 11.2 years (s.d. = 7.5 years). The respondents were
asked to complete the Employee Trust Scale, as well as a managerial
trust questionnaire from Mishra. The exploratory factor analysis on
employees’ trust toward their supervisor’s extracted three factors,
labeled ‘trustworthiness’ (32 items), ‘position status’ (11 items) and
‘relationship’ (6 items) which accounted for 62.49% of the total
variance. Trustworthiness factors were re-categorized into three sub
factors: competency (11 items), benevolence (8 items) and integrity
(13 items). All factors and sub factors of the scales demonstrated
clear reliability with internal consistency of Cronbach’s Alpha above
.85. The convergent validity of the Scale was supported by an
expected pattern of correlations (positive and significant correlation)
between the score of all factors and sub factors of the scale and the
score on the managerial trust questionnaire, which measured the same
construct. The convergent validity of Employee Trust Scale was
further supported by the significant and positive inter-correlation
between the factors and sub factors of the scale. The results suggest
that the Employee Trust Scale is a reliable and valid measure.
However, further studies need to be carried out in other groups of
sample as to further validate the Scale.
Abstract: The reheating furnace is used to reheat the steel slabs
before the hot-rolling process. The supported system includes the
stationary/moving beams, and the skid buttons which block some
thermal radiation transmitted to the bottom of the slabs. Therefore, it is
important to analyze the steel slab temperature distribution during the
heating period. A three-dimensional mathematical transient heat
transfer model for the prediction of temperature distribution within the
slab has been developed. The effects of different skid button height
(H=60mm, 90mm, and 120mm) and different gap distance between
two slabs (S=50mm, 75mm, and 100mm) on the slab skid mark
formation and temperature profiles are investigated. Comparison with
the in-situ experimental data from Steel Company in Taiwan shows
that the present heat transfer model works well for the prediction of
thermal behavior of the slab in the reheating furnace. It is found that
the skid mark severity decreases with an increase in the skid button
height. The effect of gap distance is important only for the slab edge
planes, while it is insignificant for the slab central planes.
Abstract: Cortisol is essential to the regulation of the immune
system and pathological yawning is a symptom of multiple sclerosis
(MS). Electromyography activity (EMG) in the jaw muscles typically
rises when the muscles are moved – extended or flexed; and yawning
has been shown to be highly correlated with cortisol levels in healthy
people as shown in the Thompson Cortisol Hypothesis. It is likely
that these elevated cortisol levels are also seen in people with MS.
The possible link between EMG in the jaw muscles and rises in saliva
cortisol levels during yawning were investigated in a randomized
controlled trial of 60 volunteers aged 18-69 years who were exposed
to conditions that were designed to elicit the yawning response.
Saliva samples were collected at the start and after yawning, or at the
end of the presentation of yawning-provoking stimuli, in the absence
of a yawn, and EMG data was additionally collected during rest and
yawning phases. Hospital Anxiety and Depression Scale, Yawning
Susceptibility Scale, General Health Questionnaire, demographic,
and health details were collected and the following exclusion criteria
were adopted: chronic fatigue, diabetes, fibromyalgia, heart
condition, high blood pressure, hormone replacement therapy,
multiple sclerosis, and stroke. Significant differences were found
between the saliva cortisol samples for the yawners, t (23) = -4.263, p
= 0.000, as compared with the non-yawners between rest and poststimuli,
which was non-significant. There were also significant
differences between yawners and non-yawners for the EMG
potentials with the yawners having higher rest and post-yawning
potentials. Significant evidence was found to support the Thompson
Cortisol Hypothesis suggesting that rises in cortisol levels are
associated with the yawning response. Further research is underway
to explore the use of cortisol as a potential diagnostic tool as an assist
to the early diagnosis of symptoms related to neurological disorders.
Bournemouth University Research & Ethics approval granted:
JC28/1/13-KA6/9/13. Professional code of conduct, confidentiality,
and safety issues have been addressed and approved in the Ethics
submission. Trials identification number: ISRCTN61942768.
http://www.controlled-trials.com/isrctn/
Abstract: In the present study we have investigated axial
buckling characteristics of nanocomposite beams reinforced by
single-walled carbon nanotubes (SWCNTs). Various types of beam
theories including Euler-Bernoulli beam theory, Timoshenko beam
theory and Reddy beam theory were used to analyze the buckling
behavior of carbon nanotube-reinforced composite beams.
Generalized differential quadrature (GDQ) method was utilized to
discretize the governing differential equations along with four
commonly used boundary conditions. The material properties of the
nanocomposite beams were obtained using molecular dynamic (MD)
simulation corresponding to both short-(10,10) SWCNT and long-
(10,10) SWCNT composites which were embedded by amorphous
polyethylene matrix. Then the results obtained directly from MD
simulations were matched with those calculated by the mixture rule
to extract appropriate values of carbon nanotube efficiency
parameters accounting for the scale-dependent material properties.
The selected numerical results were presented to indicate the
influences of nanotube volume fractions and end supports on the
critical axial buckling loads of nanocomposite beams relevant to
long- and short-nanotube composites.
Abstract: Evaluation of the excavation-induced ground
movements is an important design aspect of support systems in urban
areas. Geological and geotechnical conditions of an excavation area
have significant effects on excavation-induced ground movements and
the related damage. This paper is aimed at studying the performance of
excavation walls supported by nails in jointed rock medium. The
performance of nailed walls is investigated based on evaluating the
excavation-induced ground movements. For this purpose, a set of
calibrated 2D finite element models are developed by taking into
account the nail-rock-structure interactions, the anisotropic properties
of jointed rock, and the staged construction process. The results of this
paper highlight effects of different parameters such as joint
inclinations, anisotropy of rocks and nail inclinations on deformation
parameters of excavation wall supported by nails.
Abstract: In this paper, we present a comparative study of three
methods of 2D face recognition system such as: Iso-Geodesic Curves
(IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram
(GIH). These approaches are based on computing of geodesic
distance between points of facial surface and between facial curves.
In this study we represented the image at gray level as a 2D surface in
a 3D space, with the third coordinate proportional to the intensity
values of pixels. In the classifying step, we use: Neural Networks
(NN), K-Nearest Neighbor (KNN) and Support Vector Machines
(SVM). The images used in our experiments are from two wellknown
databases of face images ORL and YaleB. ORL data base was
used to evaluate the performance of methods under conditions where
the pose and sample size are varied, and the database YaleB was used
to examine the performance of the systems when the facial
expressions and lighting are varied.
Abstract: In this work, we attempt to associate firm
characteristics with innovative activity. We collect microdata from
listed firms of selected Eurozone Country-members, after the
beginning of 2007 financial crisis. The following literature, several
indicators of growth and performance were selected and tested for
their ability to interpret innovative activity. The main scope is to
examine the possible differences in performance and growth between
innovative and non-innovative firms, during a severe recession.
Additionally to that, a special focus will be held on whether
macroeconomic performance and national innovation system,
determines the extent of innovators' performance. Preliminary
findings, through correlation matrices and non-parametric tests,
strongly indicate the positive relation between innovative activity and
most of the measures used (profitability, size, employment),
confirming that even during a recessionary period, innovative firms
not only survive but also seem to succeed better economic results in
almost all indexes relative to non-innovative. However, even though
innovators seem to perform better in all economies examined, the
extent of that performance seems to be strongly affected by the
supportive mechanisms (financial and structural) that their country
provides. Thus, it is clear, that the technologically intensive 'gap'
between European South and North, during the economic crisis,
became chaotic, due to the harsh austerity measures and reduced
budgets in those countries, even in sectors with high potentials in
economic activity and employment, impairing the effects of crisis and
enhancing the vicious circle of recession.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: Complex environments triggered by globalization
have necessitated new paradigms of leadership – Complexity
Leadership that encompass multiple roles that leaders need to take
upon. Success of Higher Education institutions depends on how well
leaders can provide adaptive, administrative and enabling leadership.
Complexity Leadership seems all the more relevant for institutions
that are knowledge-driven and thrive on Knowledge creation,
Knowledge storage and retrieval, Knowledge Sharing and
Knowledge applications. Discussed in this paper are the elements of
Globalization and the opportunities and challenges that are brought
forth by globalization. The Complexity leadership paradigm in a
knowledge-based economy and the need for such a paradigm shift for
higher education institutions is presented. Further, the paper also
discusses the support the leader requires in a knowledge-driven
economy through knowledge management initiatives.
Abstract: There are real needs to integrate types of Open
Educational Resources (OER) with an intelligent system to extract
information and knowledge in the semantic searching level. The
needs came because most of current learning standard adopted web
based learning and the e-learning systems do not always serve all
educational goals. Semantic Web systems provide educators,
students, and researchers with intelligent queries based on a semantic
knowledge management learning system. An ontology-based learning
system is an advanced system, where ontology plays the core of the
semantic web in a smart learning environment. The objective of this
paper is to discuss the potentials of ontologies and mapping different
kinds of ontologies; heterogeneous or homogenous to manage and
control different types of Open Educational Resources. The important
contribution of this research is that it uses logical rules and
conceptual relations to map between ontologies of different
educational resources. We expect from this methodology to establish
an intelligent educational system supporting student tutoring, self and
lifelong learning system.
Abstract: Rapid population growth, urbanization and
industrialization are known as the most important factors of
environment problems. Elimination and management of solid wastes
are also within the most important environment problems. One of the
main problems in solid waste management is the selection of the best
site for elimination of solid wastes. Lately, Geographical Information
System (GIS) has been used for easing selection of landfill area. GIS
has the ability of imitating necessary economic, environmental and
political limitations. They play an important role for the site selection
of landfill area as a decision support tool. In this study; map layers will be studied for minimum effect of
environmental, social and cultural factors and maximum effect for
engineering/economic factors for site selection of landfill areas and
using GIS for a decision support mechanism in solid waste landfill
areas site selection will be presented in Aksaray/Turkey city,
Güzelyurt district practice.
Abstract: Structural failure is caused mainly by damage that
often occurs on structures. Many researchers focus on to obtain very
efficient tools to detect the damage in structures in the early state. In
the past decades, a subject that has received considerable attention in
literature is the damage detection as determined by variations in the
dynamic characteristics or response of structures. The study presents
a new damage identification technique. The technique detects the
damage location for the incomplete structure system using output
data only. The method indicates the damage based on the free
vibration test data by using ‘Two Points Condensation (TPC)
technique’. This method creates a set of matrices by reducing the
structural system to two degrees of freedom systems. The current
stiffness matrices obtain from optimization the equation of motion
using the measured test data. The current stiffness matrices compare
with original (undamaged) stiffness matrices. The large percentage
changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply
supported steel beam model structure after inducing thickness change
in one element, where two cases consider. The method detects the
damage and determines its location accurately in both cases. In
addition, the results illustrate these changes in stiffness matrix can be
a useful tool for continuous monitoring of structural safety using
ambient vibration data. Furthermore, its efficiency proves that this
technique can be used also for big structures.