Abstract: The aim of this paper is to present the concept of an
agile enterprise model and to initiate discussion on the research
assumptions of the model presented. The implementation of the
research project "The agility of enterprises in the process of adapting
to the environment and its changes" began in August 2014 and is
planned to last three years. The article has the form of a work-inprogress
paper which aims to verify and initiate a debate over the
proposed research model. In the literature there are very few
publications relating to research into agility; it can be concluded that
the most controversial issue in this regard is the method of measuring
agility. In previous studies the operationalization of agility was often
fragmentary, focusing only on selected areas of agility, for example
manufacturing, or analysing only selected sectors. As a result the
measures created to date can only be treated as contributory to the
development of precise measurement tools. This research project
aims to fill a cognitive gap in the literature with regard to the
conceptualization and operationalization of an agile company. Thus,
the original contribution of the author of this project is the
construction of a theoretical model that integrates manufacturing
agility (consisting mainly in adaptation to the environment) and
strategic agility (based on proactive measures). The author of this
research project is primarily interested in the attributes of an agile
enterprise which indicate that the company is able to rapidly adapt to
changing circumstances and behave pro-actively.
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: A game using electro-oculography (EOG) as control signal was introduced in this study. Various EOG signals are generated by eye movements. Even though EOG is a quite complex type of signal, distinct and separable EOG signals could be classified from horizontal and vertical, left and right eye movements. Proper signal processing was incorporated since EOG signal has very small amplitude in the order of micro volts and contains noises influenced by external conditions. Locations of the electrodes were set to be above and below as well as left and right positions of the eyes. Four control signals of up, down, left and right were generated. A microcontroller processed signals in order to simulate a DDR game. A LCD display showed arrows falling down with four different head directions. This game may be used as eye exercise for visual concentration and acuity. Our proposed EOG control signal can be utilized in many other applications of human machine interfaces such as wheelchair, computer keyboard and home automation.
Abstract: The Emergency Department of a medical center in
Taiwan cooperated to conduct the research. A predictive model of
triage system is contracted from the contract procedure, selection of
parameters to sample screening. 2,000 pieces of data needed for the
patients is chosen randomly by the computer. After three
categorizations of data mining (Multi-group Discriminant Analysis,
Multinomial Logistic Regression, Back-propagation Neural
Networks), it is found that Back-propagation Neural Networks can
best distinguish the patients- extent of emergency, and the accuracy
rate can reach to as high as 95.1%. The Back-propagation Neural
Networks that has the highest accuracy rate is simulated into the triage
acuity expert system in this research. Data mining applied to the
predictive model of the triage acuity expert system can be updated
regularly for both the improvement of the system and for education
training, and will not be affected by subjective factors.