Abstract: This paper systematically investigates the timedependent
health outcomes for office staff during computer work
using the developed mathematical model. The model describes timedependent
health outcomes in multiple body regions associated with
computer usage. The association is explicitly presented with a doseresponse
relationship which is parametrized by body region
parameters. Using the developed model we perform extensive
investigations of the health outcomes statically and dynamically. We
compare the risk body regions and provide various severity rankings
of the discomfort rate changes with respect to computer-related
workload dynamically for the study population. Application of the
developed model reveals a wide range of findings. Such broad
spectrum of investigations in a single report literature is lacking.
Based upon the model analysis, it is discovered that the highest
average severity level of the discomfort exists in neck, shoulder, eyes,
shoulder joint/upper arm, upper back, low back and head etc. The
biggest weekly changes of discomfort rates are in eyes, neck, head,
shoulder, shoulder joint/upper arm and upper back etc. The fastest
discomfort rate is found in neck, followed by shoulder, eyes, head,
shoulder joint/upper arm and upper back etc. Most of our findings are
consistent with the literature, which demonstrates that the developed
model and results are applicable and valuable and can be utilized to
assess correlation between the amount of computer-related workload
and health risk.
Abstract: A new analytical model is developed which provides
close-formed solutions for both transient indoor and envelope
temperature changes in buildings. Time-dependent boundary
temperature is presented as Fourier series which can approximate real
weather conditions. The final close-formed solutions are simple,
concise, and comprehensive. The model was compared with
numerical results and good accuracy was obtained. The model can
be used as design and control guidelines in engineering applications
for analysing mechanical heat transfer properties for buildings.
Abstract: Sickness absence represents a major economic and
social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is
often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient
and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using
a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model
selection and a critical analysis of the temporal trends, the occurrence
and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large
sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to
select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model
applicability to complicated longitudinal data.
Abstract: As the data-driven economy is growing faster than
ever and the demand for energy is being spurred, we are facing
unprecedented challenges of improving energy efficiency in data
centers. Effectively maximizing energy efficiency or minimising the
cooling energy demand is becoming pervasive for data centers. This
paper investigates overall energy consumption and the energy
efficiency of cooling system for a data center in Finland as a case
study. The power, cooling and energy consumption characteristics
and operation condition of facilities are examined and analysed.
Potential energy and cooling saving opportunities are identified and
further suggestions for improving the performance of cooling system
are put forward. Results are presented as a comprehensive evaluation
of both the energy performance and good practices of energy
efficient cooling operations for the data center. Utilization of an
energy recovery concept for cooling system is proposed. The
conclusion we can draw is that even though the analysed data center
demonstrated relatively high energy efficiency, based on its power
usage effectiveness value, there is still a significant potential for
energy saving from its cooling systems.