Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
The authors present the design and implementation of an exploratory virtual learning environment that assists children with autism (ASD) in learning science, technology, engineering, and mathematics (STEM) skills along with improving social-emotional and communication skills. The primary contribution of this exploratory research is how educational research informs technological advances in triggering a virtual AI companion (AIC) for children in need of social-emotional and communication skills development. The AIC adapts to students’ varying levels of needed support. This project began by using puppetry control (human-in-the-loop) of the AIC, assisting students with ASD in learning basic coding, practicing their social skills with the AIC, and attaining emotional recognition and regulation skills for effective communication and learning. The student is given the challenge to program a robot, Dash™, to move in a square. Based on observed behaviors, the puppeteer controls the virtual agent’s actions to support the student in coding the robot. The virtual agent’s actions that inform the development of the AIC include speech, facial expressions, gestures, respiration, and heart color changes coded to indicate emotional state. The paper provides exploratory findings of the first 2 years of this 5-year scaling-up research study. The outcomes discussed align with a common approach of researchmore »Free, publicly-accessible full text available October 14, 2023
Environmental impact reduction as a new dimension for quality measurement of healthcare services: The case of magnetic resonance imagingPurpose The purpose of this paper is to provide a detailed accounting of energy and materials consumed during magnetic resonance imaging (MRI). Design/methodology/approach The first and second stages of ISO standard (ISO 14040:2006 and ISO 14044:2006) were followed to develop life cycle inventory (LCI). The LCI data collection took the form of observations, time studies, real-time metered power consumption, review of imaging department scheduling records and review of technical manuals and literature. Findings The carbon footprint of the entire MRI service on a per-patient basis was measured at 22.4 kg CO 2 eq. The in-hospital energy use (process energy) for performing MRI is 29 kWh per patient for the MRI machine, ancillary devices and light fixtures, while the out-of-hospital energy consumption is approximately 260 percent greater than the process energy, measured at 75 kWh per patient related to fuel for generation and transmission of electricity for the hospital, plus energy to manufacture disposable, consumable and reusable products. The actual MRI and standby energy that produces the MRI images is only about 38 percent of the total life cycle energy. Research limitations/implications The focus on methods and proof-of-concept meant that only one facility and one type of imaging device technology were used to reachmore »