A design pattern approach to bitemporal data modeling

The importance of patterns in constructing complex systems has long been recognised in other disciplines. In software engineering, for example, well-crafted object-oriented architectures contain several design patterns. Focusing on mechanisms of constructing software during system development can yield an architecture that is simpler, clearer and more understandable than if design patterns were ignored or not properly applied. In this paper, we propose a model that uses object-oriented design patterns to develop a core bitemporal conceptual model. We define three core design patterns that form a core bitemporal conceptual model of a typical bitemporal object. Our framework is known as the Bitemporal Object, State and Event Modelling Approach (BOSEMA) and the resulting core model is known as a Bitemporal Object, State and Event (BOSE) model. Using this approach, we demonstrate that we can enrich data modelling by using well known design patterns which can help designers to build complex models of bitemporal databases.

Self-optimising data farming for web applications

Many Web applications walk the thin line between the need for dynamic data and the need to meet user performance expectations. In environments where funds are not available to constantly upgrade hardware inline with user demand, alternative approaches need to be considered. This paper introduces a ‘Data farming’ model whereby dynamic data, which is ‘grown’ in operational applications, is ‘harvested’ and ‘packaged’ for various consumer markets. Like any well managed agricultural operation, crops are harvested according to historical and perceived demand as inferred by a self-optimising process. This approach aims to make enhanced use of available resources through better utlilisation of system downtime - thereby improving application performance and increasing the availability of key business data.

An ontological characterization of time-series and state-sequences for data mining

Time-series and sequences are important patterns in data mining. Based on an ontology of time-elements, this paper presents a formal characterization of time-series and state-sequences, where a state denotes a collection of data whose validation is dependent on time. While a time-series is formalized as a vector of time-elements temporally ordered one after another, a state-sequence is denoted as a list of states correspondingly ordered by a time-series. In general, a time-series and a state-sequence can be incomplete in various ways. This leads to the distinction between complete and incomplete time-series, and between complete and incomplete state-sequences, which allows the expression of both absolute and relative temporal knowledge in data mining.

Using EMGs and kinematics data to study the take-off technique of experts and novices for a pole vaulting short run-up educational exercise

This study attempts to characterise the electromyographic activity and kinematics exhibited during the performance of take-off for a pole vaulting short run-up educational exercise, for different expertise levels. Two groups (experts and novices) participated in this study. Both groups were asked to execute their take-off technique for that specific exercise. Among the kinematics variables studied, the knee, hip and ankle angles and the hip and knee angular velocities were significantly different. There were also significant differences in the EMG variables, especially in terms of (i) biceps femoris and gastrocnemius lateralis activity at touchdown and (ii) vastus lateralis and gastrocnemius lateralis activity during take-off. During touchdown, the experts tended to increase the stiffness of the take-off leg to decrease braking. Novices exhibited less stiffness in the take-off leg due to their tendency to maintain a tighter knee angle. Novices also transferred less energy forward during take-off due to lack of contraction in the vastus lateralis, which is known to contribute to forward energy transfers. This study highlights the differences in both groups in terms of muscular and angular control according to the studied variables. Such studies of pole vaulting could be useful to help novices to learn expert's technique.

In vitro-in vivo correlations of self-emulsifying drug delivery systems combining the dynamic lipolysis model and neuro-fuzzy networks

The aim of the current study was to evaluate the potential of the dynamic lipolysis model to simulate the absorption of a poorly soluble model drug compound, probucol, from three lipid-based formulations and to predict the in vitro-in vivo correlation (IVIVC) using neuro-fuzzy networks. An oil solution and two self-micro and nano-emulsifying drug delivery systems were tested in the lipolysis model. The release of probucol to the aqueous (micellar) phase was monitored during the progress of lipolysis. These release profiles compared with plasma profiles obtained in a previous bioavailability study conducted in mini-pigs at the same conditions. The release rate and extent of release from the oil formulation were found to be significantly lower than from SMEDDS and SNEDDS. The rank order of probucol released (SMEDDS approximately SNEDDS > oil formulation) was similar to the rank order of bioavailability from the in vivo study. The employed neuro-fuzzy model (AFM-IVIVC) achieved significantly high prediction ability for different data formations (correlation greater than 0.91 and prediction error close to zero), without employing complex configurations. These preliminary results suggest that the dynamic lipolysis model combined with the AFM-IVIVC can be a useful tool in the prediction of the in vivo behavior of lipid-based formulations.

Kinematics and EMG analysis of expert pole vaulter's lower limb during take off phase (P218)

Introduction: The critical phase, in jumping events in track and field, appears to be between touchdown and take-off. Since obvious similarities exist between the take off phase in both long jump and pole vault, numerous 3D kinematics and electromyographic studies have only looked at long jump. Currently there are few detailed kinematics electromyographic data on the pole vault take-off phase. The aim of this study was therefore to characterise kinematics and electromyographic variables during the take-off phase to provide a better understanding of this phase in pole vaulting and its role in performance outcome. Material and methods: Six pole-vaulters took part in the study. Kinematics data were captured with retro reflective markers fixed on the body. Hip, knee and ankle angle were calculated. Differential bipolar surface electrodes were placed on the following muscles of the take-off leg: tibialis anterior, lateral gastrocnemius, vastus lateralis, rectus femoris, bicep femoris and gluteus maximus. EMG activity was synchronously acquired with the kinematic data. EMG data were rectified and smoothed using a second order low pass Butterworth Bidirectional filter (resulting in a 4th order filter) with a cut-off frequency of 14 Hz. Results: Evolution of hip, knee and ankle angle show no significant differences during the last step before touchdown, the take-off phase and the beginning of fly phase. Meanwhile, strong differences in EMG signal are noted inter and intra pole vaulter. However for a same subject the EMG activities seem to converge to some phase locked point. Discussion: All pole vaulters have approximately the same visible coordination This coordination reflects a different muscular control among pole vaulters but also for a considered pole vaulter. These phase locked point could be considered as invariant of motor control i.e. a prerequisite for a normal sequence of the movement and performance realization.