Abstract: Public health surveillance system focuses on outbreak detection and data sources used. Variation or aberration in the frequency distribution of health data, compared to historical data is often used to detect outbreaks. It is important that new techniques be developed to improve the detection rate, thereby reducing wastage of resources in public health. Thus, the objective is to developed technique by applying frequent mining and outlier mining techniques in outbreak detection. 14 datasets from the UCI were tested on the proposed technique. The performance of the effectiveness for each technique was measured by t-test. The overall performance shows that DTK can be used to detect outlier within frequent dataset. In conclusion the outbreak detection technique using anomaly-based on frequent-outlier technique can be used to identify the outlier within frequent dataset.
Abstract: In this work a surgical simulator is produced which
enables a training otologist to conduct a virtual, real-time prosthetic
insertion. The simulator provides the Ear, Nose and Throat surgeon
with real-time visual and haptic responses during virtual cochlear
implantation into a 3D model of the human Scala Tympani (ST). The
parametric model is derived from measured data as published in the
literature and accounts for human morphological variance, such as
differences in cochlear shape, enabling patient-specific pre- operative
assessment. Haptic modeling techniques use real physical data and
insertion force measurements, to develop a force model which
mimics the physical behavior of an implant as it collides with the ST
walls during an insertion. Output force profiles are acquired from the
insertion studies conducted in the work, to validate the haptic model.
The simulator provides the user with real-time, quantitative insertion
force information and associated electrode position as user inserts the
virtual implant into the ST model. The information provided by this
study may also be of use to implant manufacturers for design
enhancements as well as for training specialists in optimal force
administration, using the simulator. The paper reports on the methods
for anatomical modeling and haptic algorithm development, with
focus on simulator design, development, optimization and validation.
The techniques may be transferrable to other medical applications
that involve prosthetic device insertions where user vision is
obstructed.
Abstract: Short term electricity demand forecasts are required
by power utilities for efficient operation of the power grid. In a
competitive market environment, suppliers and large consumers also
require short term forecasts in order to estimate their energy
requirements in advance. Electricity demand is influenced (among
other things) by the day of the week, the time of year and special
periods and/or days such as Ramadhan, all of which must be
identified prior to modelling. This identification, known as day-type
identification, must be included in the modelling stage either by
segmenting the data and modelling each day-type separately or by
including the day-type as an input. Day-type identification is the
main focus of this paper. A Kohonen map is employed to identify the
separate day-types in Algerian data.
Abstract: Modern organizations operate under the pressure of
dynamic and often unpredictable changes, both in external and
internal environment. Market success, in this context, requires a
particular competence in the form of flexibility, interpreted here both
on the level of individuals and on the level of organization. This
paper addresses the changes taking place in the sphere of
employment, as observed in economic entities operating on Polish
market. Based on own empirical studies, the authors focus on the
progressing trend of ‘flexibilization’ of employment, particularly in
the context of transformations in organizational structure, designed to
facilitate the transition into management by projects and
differentiation of labor forms.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear particle
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear particle. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear debris
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self-organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear debris. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: Time full of changes which is associated with globalization, tougher competition, changes in the structures of markets and economic downturn, that all force companies to think about their competitive advantages. These changes can bring the company a competitive advantage and that can help improve competitive position in the market. Policy of the European Union is focused on the fast growing innovative companies which quickly respond to market demands and consequently increase its competitiveness. To meet those objectives companies need the right conditions and support of their state.
Abstract: The NGN (Next Generation Network), which can
provide advanced multimedia services over an all-IP based network, has been the subject of much attention for years. While there have
been tremendous efforts to develop its architecture and protocols, especially for IMS, which is a key technology of the NGN, it is far
from being widely deployed. However, efforts to create an advanced
signaling infrastructure realizing many requirements have resulted in a
large number of functional components and interactions between those
components. Thus, the carriers are trying to explore effective ways to
deploy IMS while offering value-added services. As one such
approach, we have proposed a self-organizing IMS. A self-organizing
IMS enables IMS functional components and corresponding physical
nodes to adapt dynamically and automatically based on situation such
as network load and available system resources while continuing IMS
operation. To realize this, service continuity for users is an important
requirement when a reconfiguration occurs during operation. In this
paper, we propose a mechanism that will provide service continuity to
users and focus on the implementation and describe performance
evaluation in terms of number of control signaling and processing time
during reconfiguration