scholarly journals Just-in-Time Simulation Using Artificial Intelligence

Author(s):  
S. Manivannan
Author(s):  
Gunjan Kamdar ◽  
David O. Kessler ◽  
Lindsey Tilt ◽  
Geetanjali Srivastava ◽  
Kajal Khanna ◽  
...  

Author(s):  
Lina Montuori ◽  
Manuel Alcázar-Ortega ◽  
Paula Bastida-Molina ◽  
Carlos Vargas-Salgado

In the so-called society 4.0, Artificial Intelligence (AI) is being widely used in many areas of life. Machine learning uses mathematical algorithms based on "training data", which are able to make predictions or take decisions with the ability to change their behavior through a self-training approach. Furthermore, thanks to AI, a large volume of data can be now processed with the overall goal to extract patterns and transform the information into a comprehensible structure for further utilization, which manually done by humans would easily take several years. In this framework, this article explores the potential of AI and machine learning to empower flipped classroom with just-in-time teaching (JiTT). JiTT is a pedagogical method that can be easily combined with the reverse teaching. It allows professors to receive feedback from students before class, so they may be able to adapt the lesson flow, as well as preparing strategies and activities focused on the student deficiencies. This research explores the application of AI in high education as a tool to analyze the key variables involved in the learning process of students and to integrate JiTT within the flipped classroom. Finally, a case of application of this methodology is presented, applied to the course of Industrial Refrigeration taught at the Polytechnic University of Valencia.


1991 ◽  
Vol 20 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Hsiang-Kuan Kung ◽  
Chaweng Changchit

Author(s):  
José Luís Cacho ◽  
Adalberto Tokarski ◽  
Elizabete Thomas ◽  
Valentina Chkoniya

The maritime supply chain is growing in complexity. Ports are at the crossroads of many activities, modes, and stakeholders, and are actively becoming digital hubs. Today, digital and physical connectivity go hand in hand. The port could benefit from taping the opportunities arising from digitalization and data integration since it helps to leverage external knowledge, engage stakeholders, create new decision-making anchors, lower the risk of certain investments, boost productivity and cut costs, and accelerate greening and digital transition, generating possibilities for just-in-time operations and optimizations. The chapter aims to apprehend the use of data science in the port sector. The state of the art in Brazil and Portugal are different. Even inside Brazil, there is no homogeneity of ports in the usage of digital infrastructure, cloud computing, or artificial intelligence. The existing inequalities hinder general cooperation between nations but, at the same time, reveal opportunities to approach specific nodes in the international supply chain.


Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Akira Nishisaki ◽  
Shawn Colborn ◽  
Christine Watson ◽  
Dana Niles ◽  
Susan Ferry ◽  
...  

Introduction : Competence in orotracheal intubation is a requirement for Pediatric residency. However, opportunities for residents are limited. We hypothesize Just-in-Time simulation-based multi-disciplinary team training for acute airway resuscitation in a pediatric ICU (PICU) would improve physician trainee intubation participation and success, and decrease undesired T racheal I ntubation A ssociated E vents ( TIAE ) such as esophageal intubation, or mainstem intubation. Methods : With IRB approval, on-call residents in a tertiary PICU received 30 minute airway resuscitation multidisciplinary simulation training before 24 hour on-call duties. Airway resuscitation performance was captured in both simulated and real airway resuscitations using a validated airway registry (NEAR-4-KIDS) tool. Resident participation, success, first attempt success, and the incidence of TIAE were compared before and after this intervention (Pre: Jan 2005–Jun11, 2007; Post: Jun12, 2007–May2008). Analysis by time series analysis, and Fisher’s exact test. Results : 150 simulation training sessions were conducted, and 123 consecutive real orotracheal intubations were evaluated. Resident participation significantly increased: Pre 23 % vs Post 36 % (p=0.016). Overall resident airway resuscitation success (58% vs. 68%, p=0.39) and first attempt success (44% vs. 56%, p= 0.30) improvement were not statistically significant. Despite the increased participation by resident trainees, there was no increase in TIAE (23% vs. 21%, p=0.78) in real airway resuscitation. Conclusion : Simulation-based “Just-in-Time” multidisciplinary training for pediatric advanced airway resuscitation improved actual resident trainee participation in real ICU intubations, but did not compromise airway resuscitation procedural success or patient safety. Supported by Agency for Healthcare Research and Quality (AHRQ), and CHOP Endowed Chair, Critical Care Medicine


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