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Sökning: WFRF:(Spieker M.) > (2019)

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1.
  • Al-Shammari, I., et al. (författare)
  • Implementation of an international standardized set of outcome indicators in pregnancy and childbirth in Kenya: Utilizing mobile technology to collect patient-reported outcomes
  • 2019
  • Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Limited data exist on health outcomes during pregnancy and childbirth in low- and middleincome countries. This is a pilot of an innovative data collection tool using mobile technology to collect patient-reported outcome measures (PROMs) selected from the International Consortium of Health Outcomes Measurement (ICHOM) Pregnancy and Childbirth Standard Set in Nairobi, Kenya. Methods Pregnant women in the third trimester were recruited at three primary care facilities in Nairobi and followed prospectively throughout delivery and until six weeks postpartum. PROMs were collected via mobile surveys at three antenatal and two postnatal time points. Outcomes included incontinence, dyspareunia, mental health, breastfeeding and satisfaction with care. Hospitals reported morbidity and mortality. Descriptive statistics on maternal and child outcomes, survey completion and follow-up rates were calculated. Results In six months, 204 women were recruited: 50% of women returned for a second ante-natal care visit, 50% delivered at referral hospitals and 51% completed the postnatal visit. The completion rates for the five PROM surveys were highest at the first antenatal care visit (92%) and lowest in the postnatal care visit (38%). Data on depression, dyspareunia, fecal and urinary incontinence were successfully collected during the antenatal and postnatal period. At six weeks postpartum, 86% of women breastfeed exclusively. Most women that completed the survey were very satisfied with antenatal care (66%), delivery care (51%), and post-natal care (60%). Conclusion We have demonstrated that it is feasible to use mobile technology to follow women throughout pregnancy, track their attendance to pre-natal and post-natal care visits and obtain data on PROM. This study demonstrates the potential of mobile technology to collect PROM in a low-resource setting. The data provide insight into the quality of maternal care services provided and will be used to identify and address gaps in access and provision of high quality care to pregnant women. © 2019 Al-Shammari et al.
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2.
  • Mossige, M., et al. (författare)
  • Time-aware test execution scheduling for cyber-physical systems
  • 2019
  • Ingår i: Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI). - : Gesellschaft fur Informatik (GI). - 9783885796862 ; , s. 121-122
  • Konferensbidrag (refereegranskat)abstract
    • The paper "Time-aware Test Execution Scheduling for Cyber-Physical Systems "first appeared in the application track of the 23rd International Conference on Principles and Practice of Constraint Programming (CP 2017). Testing cyber-physical systems involves the execution of test cases on target-machines equipped with the latest release of a software control system. When testing industrial robots, it is common that the target machines need to share some common resources, e.g., costly hardware devices, and so there is a need to schedule test case execution on the target machines, accounting for these shared resources. With a large number of such tests executed on a regular basis, this scheduling becomes difficult to manage manually. In fact, with manual test execution planning and scheduling, some robots may remain unoccupied for long periods of time and some test cases may not be executed. We introduce TC-Sched, a time-aware method for automated test case execution scheduling. TC-Sched uses Constraint Programming to schedule tests to run on multiple machines constrained by the tests' access to shared resources, such as measurement or networking devices. We will further discuss challenges and requirements encountered when automating testing for industrial robots. 
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