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Primary data is an important source ofinformation for Competitive Intelligence. Traditionally, it has been collected from interviews with stakeholders, talks at conferences and other means of direct interpersonal communication. The role of the Internet in the data collection – if it was used at all – was that of a provider of supplementary secondary data. Here, this approach is challenged and, using three examples of Social Media, it is shown that the Internet can and does provide valuable primary information to the Competitive Intelligence professional. Accordingly, a case is made for a shift of focus in the data collection process.
The speed control system for a concept for cost effective drives with high precision is presented. The drive concept consists of two parallel working drives. The concept is an alternative to direct drives. One big advantage is the use of standard gear boxes with economical components. This paper deals with the control of the drive system consisting of two parts: one drive produces the power for the machine, another drive makes the motion precice and dynamic. Both drives are combined to one double drive by a control system. The drive system is usefull for printing machines and other machines with high power consumption at a nearly constant speed and high accuracy requirements. The calculation for a drive system with 37 kW shows, that the control drive has to supply only about 20 % of the total torque and power needed to compensate the errors of the power drive. The stability of the system is shown by a simulation of the double drive.
Background
Maternal postpartum depression has an impact on mother-infant interaction. Mothers with depression display less positive affect and sensitivity in interaction with their infants compared to non-depressed mothers. Depressed women also show more signs of distress and difficulties adjusting to their role as mothers than non-depressed women. In addition, depressive mothers are reported to be affectively more negative with their sons than with daughters.
Methods
A non-clinical sample of 106 mother-infant dyads at psychosocial risk (poverty, alcohol or drug abuse, lack of social support, teenage mothers and maternal psychic disorder) was investigated with EPDS (maternal postpartum depressive symptoms), the CARE-Index (maternal sensitivity in a dyadic context) and PSI-SF (maternal distress). The baseline data were collected when the babies had reached 19 weeks of age.
Results
A hierarchical regression analysis yielded a highly significant relation between the PSI-SF subscale "parental distress" and the EPDS total score, accounting for 55% of the variance in the EPDS. The other variables did not significantly predict the severity of depressive symptoms. A two-way ANOVA with "infant gender" and "maternal postpartum depressive symptoms" showed no interaction effect on maternal sensitivity.
Conclusions
Depressive symptoms and maternal sensitivity were not linked. It is likely that we could not find any relation between both variables due to different measuring methods (self-reporting and observation). Maternal distress was strongly related to maternal depressive symptoms, probably due to the generally increased burden in the sample, and contributed to 55% of the variance of postpartum depressive symptoms.
Background: Fall events contribute significantly to mortality, morbidity and costs in our ageing population. In order to identify persons at risk and to target preventive measures, many scores and assessment tools have been developed. These often require expertise and are costly to implement. Recent research investigates the use of wearable inertial sensors to provide objective data on motion features which can be used to assess individual fall risk automatically. So far it is unknown how well this new method performs in comparison with conventional fall risk assessment tools. The aim of our research is to compare the predictive performance of our new sensor-based method with conventional and established methods, based on prospective data.
Methods: In a first study phase, 119 inpatients of a geriatric clinic took part in motion measurements using a wireless triaxial accelerometer during a Timed Up&Go (TUG) test and a 20 m walk. Furthermore, the St. Thomas Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) was performed, and the multidisciplinary geriatric care team estimated the patients’ fall risk. In a second follow-up phase of the study, 46 of the participants were interviewed after one year, including a fall and activity assessment. The predictive performances of the TUG, the STRATIFY and team scores are compared. Furthermore, two automatically induced logistic regression models based on conventional clinical and assessment data (CONV) as well as sensor data (SENSOR) are matched.
Results: Among the risk assessment scores, the geriatric team score (sensitivity 56%, specificity 80%) outperforms STRATIFY and TUG. The induced logistic regression models CONV and SENSOR achieve similar performance values (sensitivity 68%/58%, specificity 74%/78%, AUC 0.74/0.72, +LR 2.64/2.61). Both models are able to identify more persons at risk than the simple scores.
Conclusions: Sensor-based objective measurements of motion parameters in geriatric patients can be used to assess individual fall risk, and our prediction model’s performance matches that of a model based on conventional clinical and assessment data. Sensor-based measurements using a small wearable device may contribute significant information to conventional methods and are feasible in an unsupervised setting. More prospective research is needed to assess the cost-benefit relation of our approach.
The automated transfer of flight logbook information from aircrafts into aircraft maintenance systems leads to reduced ground and maintenance time and is thus desirable from an economical point of view. Until recently, flight logbooks have not been managed electronically in aircrafts or at least the data transfer from aircraft to ground maintenance system has been executed manually. Latest aircraft types such as the Airbus A380 or the Boeing 787 do support an electronic logbook and thus make an automated transfer possible. A generic flight logbook transfer system must deal with different data formats on the input side – due to different aircraft makes and models – as well as different, distributed aircraft maintenance systems for different airlines as aircraft operators. This article contributes the concept and top level distributed system architecture of such a generic system for automated flight log data transfer. It has been developed within a joint industry and applied research project. The architecture has already been successfully evaluated in a prototypical implementation.
Decision support systems for traffic management systems have to cope with a high volume of events continuously generated by sensors. Conventional software architectures do not explicitly target the efficient processing of continuous event streams. Recently, event-driven architectures (EDA) have been proposed as a new paradigm for event-based applications. In this paper we propose a reference architecture for event-driven traffic management systems, which enables the analysis and processing of complex event streams in real-time and is therefore well-suited for decision support in sensor-based traffic control sys- tems. We will illustrate our approach in the domain of road traffic management. In particular, we will report on the redesign of an intelligent transportation management system (ITMS) prototype for the high-capacity road network in Bilbao, Spain.