Toward an IoT based Software Defined Plumbing Network System with fault tolerance

in this paper we will see the application of computer science algorithms to the plumbing system. We propose a fault tolerant tap water system which is impossible without Internet of things and algorithms . We will show that the problem is a mutual exclusion group problem and we propose an adapted algorithm version from the literature as a solution . Coupling algorithms with the configurable plumbing network we believe that this will open new field of research on IoT we called it software defined plumbing Network where components that have been traditionally implemented in hardware (e.g. water mixers, spring faucets ,flow sensors, etc.) are instead implemented by means of software . This way we can solve other problem like instantaneous hot water,automatic cleaning of the water heater..etc since due to computer algorithms the systems can be easily smart, extensible and adaptive.

How does the effectiveness of strategies to improve healthcare provider practices in low-income and middle-income countries change after implementation? Secondary analysis of a systematic review

BackgroundA recent systematic review evaluated the effectiveness of strategies to improve healthcare provider (HCP) performance in low-income and middle-income countries. The review identified strategies with varying effects, including in-service training, supervision and group problem-solving. However, whether their effectiveness changed over time remained unclear. In particular, understanding whether effects decay over time is crucial to improve sustainability.MethodsWe conducted a secondary analysis of data from the aforementioned review to explore associations between time and effectiveness. We calculated effect sizes (defined as percentage-point (%-point) changes) for HCP practice outcomes (eg, percentage of patients correctly treated) at each follow-up time point after the strategy was implemented. We estimated the association between time and effectiveness using random-intercept linear regression models with time-specific effect sizes clustered within studies and adjusted for baseline performance.ResultsThe primary analysis included 37 studies, and a sensitivity analysis included 77 additional studies. For training, every additional month of follow-up was associated with a 0.19 %-point decrease in effectiveness (95% CI: –0.36 to –0.03). For training combined with supervision, every additional month was associated with a 0.40 %-point decrease in effectiveness (95% CI: –0.68 to –0.12). Time trend results for supervision were inconclusive. For group problem-solving alone, time was positively associated with effectiveness, with a 0.50 %-point increase in effect per month (95% CI: 0.37 to 0.64). Group problem-solving combined with training was associated with large improvements, and its effect was not associated with time.ConclusionsTime trends in the effectiveness of different strategies to improve HCP practices vary among strategies. Programmes relying solely on in-service training might need periodical refresher training or, better still, consider combining training with group problem-solving. Although more high-quality research is needed, these results, which are important for decision-makers as they choose which strategies to use, underscore the utility of studies with multiple post-implementation measurements so sustainability of the impact on HCP practices can be assessed.

Sharing of Knowledge and Problem Solving When Teammates Have Diverse Hearing Status

This study examined knowledge sharing and problem solving in teams that included teammates who were deaf or hard of hearing (DHH). Eighteen teams of four students were comprised of either all deaf or hard of hearing (DHH), all hearing, or two DHH and two hearing postsecondary students who participated in group problem-solving. Successful problem solution, recall, and recognition of knowledge shared by team members were assessed. Hearing teams shared the most team knowledge and achieved the most complete problem solutions, followed by the mixed DHH/hearing teams. DHH teams did not perform as well as the other two types of teams.