Accuracy Of Alerts Research Articles

Air Quality Health Index in primary care: A feasibility study

Rationale: Exposure to poor air quality is associated with increased morbidity and mortality in patients with chronic obstructive pulmonary disease (COPD), asthma and heart failure. A number of countries, including Canada, report utilization of the Air Quality Health Index (AQHI) and associated health messages tailored to different AQHI categories for the public and at-risk populations to reduce exposure, adjust physical activity and optimize clinical management. Studies indicate AQHI advisories may not adequately reach or inform at-risk populations. Objectives: The objectives of this study were to design a text alert system and evaluate the feasibility of delivering AQHI forecast alerts to participants when AQHI readings exceeded low health risk. Secondary and tertiary objectives were to determine the frequency and accuracy of the alerts. Methods: Feasibility was assessed by the following steps: recruiting older adults with asthma, COPD and heart failure from primary care practices; developing software for extracting AQHI data from the Health Canada database; registering patients on the automatic dispatch messages system; and automatically sending AQHI forecast alerts of moderate health risk or above to participants’ cell-phones the preceding night. Results: We successfully queried the Environment Canada database, detected AQHI alerts and delivered them to participants. Forecast alerts of moderate health risk were higher in summer and winter 2018-2019 in the study areas. The accuracy of AQHI forecast alerts for North Toronto versus Downtown Toronto were 81.7% (75.9 − 86.6%) and 80.7% (74.8 − 85.7%), respectively. Conclusions: Delivering AQHI alerts through text messages to patients in the primary care setting was feasible. Colder seasons should not be underestimated for moderate risk AQHI conditions.

Dynamic Aircraft Conflict Alert Based on the Markov Decision Process and Simulation of Actual Flight Data

As air traffic flow continues growing, the risk of collision between aircraft is also increasing as well. In order to ensure efficiency of airspace would not reduce due to the increase of the conflict, and thus the accuracy of alerts also has higher requirements. Traditional conflict alerts based on the static threshold method will have a great flight separation redundancy, resulting in reduced operating efficiency of airspace. So it’s necessary to study the dynamic threshold alerts approach based on actual flight scenes, which can dynamically adjust the threshold and improve operational efficiency. First in this article, Markov decision processes were introduced. And then proposed a dynamic threshold alert method based on the Markov decision process. Finally, the analysis of alert results were performed through simulation of actual flight data. The results show that this method can reduce the false alert rate and improve the performance of the alert system under the premise of ensuring flight safety.