SISME, estuarine monitoring system based on IOT and machine learning for the detection of salt wedge in aquifers: case study of the Magdalena river estuary

This article contains methods, results, and analysis agreed for the development of an application based on the internet of things and making use of machine learning techniques that serves as a support for the identification of the saline wedge in the Magdalena River estuary, Colombia. As a result of this investigation, the process of identifying the most suitable telecommunications architecture to be installed in the estuary is shown, as well as the characteristics of the software developed called SISME (Estuary Monitoring System), and the results obtained after the implementation of prediction techniques based on time series. This implementation supports the maritime security of the port of Barranquilla since it can support decision-making related to the estuary. This research is the result of the project “Implementation of a Wireless System of Temperature, Conductivity and Pressure Sensors to support the identification of the saline wedge and its impact on the maritime safety of the Magdalena River estuary”

GA-IRACE: Genetic Algorithm-Based Improved Resource Aware Cost-Efficient Scheduler for Cloud Fog Computing Environment

The ever-growing number of Internet of Things (IoT) devices increases the amount of data produced on daily basis. To handle such a massive amount of data, cloud computing provides storage, processing, and analytical services. Besides this, real-time applications, i.e., online gaming, smart traffic management, and smart healthcare, cannot tolerate the high latency and bandwidth consumption. The fog computing paradigm brings the cloud services closer to the network edge to provide quality of service (QoS) to such applications. However, efficient task scheduling becomes critical for improving the performance due to the heterogeneous nature, resource-constrained, and distributed environment of fog resources. With an efficient task scheduling algorithm, the response time to application requests can be reduced along with bandwidth and cloud resource costs. This paper presents a genetic algorithm-based solution to find an efficient scheduling approach for mapping application modules in a cloud fog computing environment. Our proposed solution is based on the execution time as a fitness function to determine an efficient module scheduling on the available fog devices. The proposed approach has been evaluated and compared against baseline algorithms in terms of execution time, monetary cost, and bandwidth. Comprehensive simulation results show that the proposed approach offers a better scheduling strategy than the existing scheduler

Exploring medical and nursing students\u27 perceptions about a patient safety course: A qualitative study

Background: Educating health professionals on patient safety can potentially reduce healthcare-associated harm. Patient safety courses have been incorporated into medical and nursing curricula in many high-income countries and their impact has been demonstrated in the literature through objective assessments. This study aimed to explore student perceptions about a patient safety course to assess its influence on aspiring health professionals at a personal level as well as to explore differences in areas of focus between medical and nursing students.Methods: A dedicated patient safety course was introduced for year III medical and year II and IV nursing students at the Aga Khan University (2021-2022). As part of a post-course assessment, 577 participating students (184 medical and 393 nursing) wrote reflections on the course, detailing its influence on them. These free-text responses were thematically analyzed using NVivo.Results: The findings revealed five major themes: acquired skills (clinical, interpersonal), understanding of medical errors (increased awareness, prevention and reduction, responding to errors), personal experiences with patient safety issues, impact of course (changed perceptions, professional integrity, need for similar sessions, importance of the topic) and course feedback (format, preparation for clinical years, suggestions). Students reported a lack of baseline awareness regarding the frequency and consequences of medical errors. After the course, medical students reported a perceptional shift in favor of systems thinking regarding error causality, and nursing students focused on human factors and error prevention. The interactive course format involving scenario-based learning was deemed beneficial in terms of increasing awareness, imparting relevant clinical and interpersonal skills, and changing perspectives on patient safety.Conclusions: Student perspectives illustrate the benefits of an early introduction of dedicated courses in imparting patient safety education to aspiring health professionals. Students reported a lack of baseline awareness of essential patient safety concepts, highlighting gaps in the existing curricula. This study can help provide an impetus for incorporating patient safety as a core component in medical and nursing curricula nationally and across the region. Additionally, patient safety courses can be tailored to emphasize areas identified as gaps among each professional group, and interprofessional education can be employed for shared learning. The authors further recommend conducting longitudinal studies to assess the long-term impact of such courses