Abstract: Background - The TrendCare Patient Dependency
System is currently used by a large number of maternity Services
across Australia, New Zealand and Singapore. In 2012, 2013 and
2014 validation studies were initiated in all three countries to validate
the acuity tools used for women in labour, and postnatal mothers and
babies. This paper will present the findings of the validation study.
Aim - The aim of this study was to; identify if the care hours
provided by the TrendCare acuity system was an accurate reflection
of the care required by women and babies; obtain evidence of
changes required to acuity indicators and/or category timings to
ensure the TrendCare acuity system remains reliable and valid across
a range of maternity care models in three countries.
Method - A non-experimental action research methodology was
used across maternity services in four District Health Boards in New
Zealand, a large tertiary and a large secondary maternity service in
Singapore and a large public maternity service in Australia.
Standardised data collection forms and timing devices were used to
collect midwife contact times, with women and babies included in the
study. Rejection processes excluded samples when care was not
completed/rationed, and contact timing forms were incomplete. The
variances between actual timed midwife/mother/baby contact and the
TrendCare acuity category times were identified and investigated.
Results - Thirty two (88.9%) of the 36 TrendCare acuity category
timings, fell within the variance tolerance levels when compared to
the actual timings recorded for midwifery care. Four (11.1%)
TrendCare categories provided less minutes of care than the actual
timings and exceeded the variance tolerance level. These were all
night shift category timings. Nine postnatal categories were not able
to be compared as the sample size for these categories was
statistically insignificant. 100% of labour ward TrendCare categories
matched actual timings for midwifery care, all falling within the
variance tolerance levels.
The actual time provided by core midwifery staff to assist lead
maternity carer (LMC) midwives in New Zealand labour wards
showed a significant deviation to previous studies. The findings of
the study demonstrated the need for additional time allocations in
TrendCare to accommodate an increased level of assistance given to
LMC midwives.
Conclusion - The results demonstrated the importance of regularly
validating the TrendCare category timings with actual timings of the
care hours provided. It was evident from the findings that variances
to models of care and length of stay in maternity units have increased
midwifery workloads on the night shift. The level of assistance
provided by the core labour ward staff to the LMC midwife has
increased substantially.
Outcomes - As a consequence of this study, changes were made to
the night duty TrendCare maternity categories, additional acuity
indicators were developed and times for assisting LMC midwives in
labour ward increased. The updated TrendCare version was delivered
to maternity services in 2014.
Abstract: Employer branding is considered as a useful tool for
addressing the global-local problem facing complex organisations
that have operations scattered across the globe and face challenges of
dealing with the local environment alongside. Despite being an
established field of study within the Western developed world, there
is little empirical evidence concerning the relevance of employer
branding to global companies that operate in the under-developed
economies. This paper fills this gap by gaining rich insight into the
implementation of employer branding programs in a foreign
multinational operating in Pakistan dealing with the global-local
problem. The study is qualitative in nature and employs semistructured
and focus group interviews with senior/middle managers
and local frontline employees to deeply examine the phenomenon in
case organisation. Findings suggest that authenticity is required in
employer brands to enable them to respond to the local needs thereby
leading to the resolution of the global-local problem. However, the
role of signaling theory is key to the development of authentic
employer brands as it stresses on the need to establish an efficient and
effective signaling environment where in signals travel in both
directions (from signal designers to receivers and backwards) and
facilitate firms with the global-local problem. The paper also
identifies future avenues of research for the employer branding field.
Abstract: This paper presents effects of distilled water, seawater
and sustained bending strains of 30% and 50% ultimate strain at
room temperature, on the durability of unidirectional pultruded
carbon fiber reinforced polymer (CFRP) plates. In this study,
dynamic mechanical analyzer (DMA) was used to investigate the
synergic effects of the immersions and bending strains on the viscoelastic
properties of (CFRP) such as storage modulus, tan delta and
glass transition temperature. The study reveals that the storage
modulus and glass transition temperature increase while tan delta
peak decreases in the initial stage of both immersions due to the
progression of curing. The storage modulus and Tg subsequently
decrease and tan delta increases due to the matrix plasticization. The
blister induced damages in the unstrained seawater samples enhance
water uptake and cause more serious degradation of Tg and storage
modulus than in water immersion. Increasing sustained bending
decreases Tg and storage modulus in a long run for both immersions
due to resin matrix cracking and debonding. The combined effects of
immersions and strains are not clearly reflected due to the statistical
effects of DMA sample sizes and competing processes of molecular
reorientation and postcuring.
Abstract: The biodegradable family of polymers
polyhydroxyalkanoates is an interesting substitute for convectional
fossil-based plastics. However, the manufacturing and environmental
impacts associated with their production via intracellular bacterial
fermentation are strongly dependent on the raw material used and on
energy consumption during the extraction process, limiting their
potential for commercialization. Industrial wastewater is studied in
this paper as a promising alternative feedstock for waste valorization.
Based on results from laboratory and pilot-scale experiments, a
conceptual process design, techno-economic analysis and life cycle
assessment are developed for the large-scale production of the most
common type of polyhydroxyalkanoate, polyhydroxbutyrate.
Intracellular polyhydroxybutyrate is obtained via fermentation of
microbial community present in industrial wastewater and the
downstream processing is based on chemical digestion with
surfactant and hypochlorite. The economic potential and
environmental performance results help identifying bottlenecks and
best opportunities to scale-up the process prior to industrial
implementation. The outcome of this research indicates that the
fermentation of wastewater towards PHB presents advantages
compared to traditional PHAs production from sugars because the
null environmental burdens and financial costs of the raw material in
the bioplastic production process. Nevertheless, process optimization
is still required to compete with the petrochemicals counterparts.
Abstract: The paper discusses mineral water consumer market
and development policy in Georgia, the tools and measures, which
will contribute to production of mineral waters and increase its
export.
The paper studies and analyses current situation in mineral water
production sector as well as the factors affecting increase and
reduction of its export. It’s noted that in order to gain and maintain
competitive advantage, it’s necessary to provide continuous supply of
high quality goods with modern design, open new distribution
channels to enter new markets, carry out broad promotional activities,
organize e-commerce. Economic policy plays an important role in
protecting markets from counterfeit goods. The state also plays an
important role in attracting foreign direct investments. Stable
business environment and export oriented strategy is the basis for the
country’s economic growth.
Based on the research, the paper suggests the strategy for
improving competitiveness of Georgian mineral waters; relevant
conclusions and recommendations are provided.
Abstract: The objective of this work is to study the effect of two
key factors - external magnetic field and applied current density
during template-based electrodeposition of nickel nanowires using an
electrode distance of 20 mm. Morphology, length, crystallite size and
crystallographic characterization of the grown nickel nanowires at an
electrode distance of 20mm are presented. For this electrode distance
of 20 mm, these two key electrodeposition factors when coupled was
found to reduce crystallite size with a higher growth length and
preferred orientation of Ni crystals. These observed changes can be
inferred to be due to coupled interaction forces induced by the
intensity of applied electric field (current density) and external
magnetic field known as magnetohydrodynamic (MHD) effect during
the electrodeposition process.
Abstract: The introduction of degradable plastic materials into
agricultural sectors has represented a promising alternative to
promote green agriculture and environmental friendly of modern
farming practices. Major challenges of developing degradable
agricultural films are to identify the most feasible types of
degradation mechanisms, composition of degradable polymers and
related processing techniques. The incorrect choice of degradable
mechanisms to be applied during the degradation process will cause
premature losses of mechanical performance and strength. In order to
achieve controlled process of agricultural film degradation, the
compositions of degradable agricultural film also important in order
to stimulate degradation reaction at required interval of time and to
achieve sustainability of the modern agricultural practices. A set of
photodegradable polyethylene based agricultural film was developed
and produced, following the selective optimization of processing
parameters of the agricultural film manufacturing system. Example of
agricultural films application for oil palm seedlings cultivation is
presented.
Abstract: The paper deals with possibilities of interpretation of
iron ore reducibility tests. It presents a mathematical model
developed at Centre ENET, VŠB – Technical University of Ostrava,
Czech Republic for an evaluation of metallurgical material of blast
furnace feedstock such as iron ore, sinter or pellets. According to the
data from the test, the model predicts its usage in blast furnace
technology and its effects on production parameters of shaft
aggregate. At the beginning, the paper sums up the general concept
and experience in mathematical modelling of iron ore reduction. It
presents basic equation for the calculation and the main parts of the
developed model. In the experimental part, there is an example of
usage of the mathematical model. The paper describes the usage of
data for some predictive calculation. There are presented material,
method of carried test of iron ore reducibility. Then there are
graphically interpreted effects of used material on carbon
consumption, rate of direct reduction and the whole reduction
process.
Abstract: Experimental study on slicing of sapphire with fixed
abrasive diamond wire saw was conducted in this paper. The process
parameters were optimized through orthogonal experiment of three
factors and four levels. The effects of wire speed, feed speed and
tension pressure on the surface roughness were analyzed. Surface
roughness in cutting direction and feed direction were both detected.
The results show that feed speed plays the most significant role on the
surface roughness of sliced sapphire followed by wire speed and
tension pressure. The optimized process parameters are as follows:
wire speed 1.9 m/s, feed speed 0.187 mm/min and tension pressure
0.18 MPa. In the end, the results were verified by analysis of variance.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: Long Distance Truck Drivers (LDTDs) have been
found to be a high risk group in the spread of HIV/AIDS globally;
perhaps, due to their high Sexual Risk Behaviours (SRBs).
Interventions for reducing SRBs in trucking population have not been
fully exploited. A quasi-experimental control group pretest-posttest
design was used to assess the efficacy of psycho-education and
behavioural skills training in reducing SRBs among LDTDs. Sixteen
drivers rivers were randomly assigned into either experimental or
control groups using balloting technique. Questionnaire was used as
an instrument for data collection. Repeated measures t-test and
independent t-test were used to test hypotheses. Intervention had
significant effect on the SRBs among LDTDs at post-test (t{7}=
6.01, p
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.
Abstract: In this paper, a direct power control (DPC)
strategies have been investigated in order to control a high
power AC/DC converter with time variable load. This converter
is composed of a three level three phase neutral point clamped
(NPC) converter as rectifier and an H-bridge four quadrant
current control converter. In the high power application,
controller not only must adjust the desire outputs but also
decrease the level of distortions which are injected to the network
from the converter. Regarding to this reason and nonlinearity
of the power electronic converter, the conventional controllers
cannot achieve appropriate responses. In this research, the
precise mathematical analysis has been employed to design the
appropriate controller in order to control the time variable
load. A DPC controller has been proposed and simulated using
Matlab/ Simulink. In order to verify the simulation result, a real
time simulator- OPAL-RT- has been employed. In this paper,
the dynamic response and stability of the high power NPC
with variable load has been investigated and compared with
conventional types using a real time simulator. The results proved
that the DPC controller is more stable and has more precise
outputs in comparison with conventional controller.
Abstract: In this study, a computational fluid dynamics (CFD)
model has been developed for studying the effect of surface
roughness profile on the EHL problem. The cylinders contact
geometry, meshing and calculation of the conservation of mass and
momentum equations are carried out using the commercial software
packages ICEMCFD and ANSYS Fluent. The user defined functions
(UDFs) for density, viscosity and elastic deformation of the cylinders
as the functions of pressure and temperature are defined for the CFD
model. Three different surface roughness profiles are created and
incorporated into the CFD model. It is found that the developed CFD
model can predict the characteristics of fluid flow and heat transfer in
the EHL problem, including the main parameters such as pressure
distribution, minimal film thickness, viscosity, and density changes.
The results obtained show that the pressure profile at the center of the
contact area directly relates to the roughness amplitude. A rough
surface with kurtosis value of more than 3 has greater influence over
the fluctuated shape of pressure distribution than in other cases.
Abstract: Rural tourism is usually associated with rural
development because it has strong linkages to rural resources; but it
remains underdeveloped compared to urban tourism. This
underdevelopment of rural tourism serves as a motivation for this
study whose aim is to examine the factors affecting the perceived
satisfaction of rural tourists. The objectives of this study are: to
identify and design theories and models on rural tourism satisfaction,
and to empirically validate these models and theories through a
survey of tourists from the Malealea Lodge which is located in the
Mafeteng District, in the Mountain Kingdom of Lesotho. Data
generated by the collection of questionnaires used by this survey was
analyzed quantitatively using descriptive statistics and correlations in
SPSS after checking the validity and the reliability of the
questionnaire. The main hypothesis behind this study is the
relationship between the demographics of rural tourists, their
motivation, and their satisfaction, as supported by existing literature;
except that motivation is measured in this study according to three
dimensions: push factors, pull factors, and perceived usefulness of
ICTs in the rural tourism experience. Findings from this study
indicate that among the demographics factors, continent of origin and
marital status influence the satisfaction of rural tourists; and their
occupation affects their perceptions on the use of ICTs in rural
tourism. Moreover, only pull factors were found to influence the
satisfaction of rural tourists.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: These days customer satisfaction plays vital role in
any business. When customer searches for a product, significantly a
junk of irrelevant information is what is given, leading to customer
dissatisfaction. To provide exactly relevant information on the
searched product, we are proposing a model of KaaS (Knowledge as
a Service), which pre-processes the information using decision
making paradigm using Multi-agents.
Information obtained from various sources is taken to derive
knowledge and they are linked to Cloud to capture new idea. The
main focus of this work is to acquire relevant information
(knowledge) related to product, then convert this knowledge into a
service for customer satisfaction and deploy on cloud.
For achieving these objectives we are have opted to use multi
agents. They are communicating and interacting with each other,
manipulate information, provide knowledge, to take decisions. The
paper discusses about KaaS as an intelligent approach for Knowledge
acquisition.
Abstract: An artificial neural network is a mathematical model
inspired by biological neural networks. There are several kinds of
neural networks and they are widely used in many areas, such as:
prediction, detection, and classification. Meanwhile, in day to day life,
people always have to make many difficult decisions. For example,
the coach of a soccer club has to decide which offensive player
to be selected to play in a certain game. This work describes a
novel Neural Network using a combination of the General Regression
Neural Network and the Probabilistic Neural Networks to help a
soccer coach make an informed decision.
Abstract: Parabolic solar trough systems have seen limited
deployments in cold northern climates as they are more suitable for
electricity production in southern latitudes. A numerical dynamic
model is developed to simulate troughs installed in cold climates and
validated using a parabolic solar trough facility in Winnipeg. The
model is developed in Simulink and will be utilized to simulate a trigeneration
system for heating, cooling and electricity generation in
remote northern communities. The main objective of this simulation
is to obtain operational data of solar troughs in cold climates and use
the model to determine ways to improve the economics and address
cold weather issues.
In this paper the validated Simulink model is applied to simulate a
solar assisted absorption cooling system along with electricity
generation using Organic Rankine Cycle (ORC) and thermal storage.
A control strategy is employed to distribute the heated oil from solar
collectors among the above three systems considering the
temperature requirements. This modelling provides dynamic
performance results using measured meteorological data recorded
every minute at the solar facility location. The purpose of this
modeling approach is to accurately predict system performance at
each time step considering the solar radiation fluctuations due to
passing clouds. Optimization of the controller in cold temperatures is
another goal of the simulation to for example minimize heat losses in
winter when energy demand is high and solar resources are low.
The solar absorption cooling is modeled to use the generated heat
from the solar trough system and provide cooling in summer for a
greenhouse which is located next to the solar field.
The results of the simulation are presented for a summer day in
Winnipeg which includes comparison of performance parameters of
the absorption cooling and ORC systems at different heat transfer
fluid (HTF) temperatures.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.