678 research outputs found
The Stars, The Stripes and You
https://digitalcommons.library.umaine.edu/mmb-vp/6187/thumbnail.jp
A simulation-based design paradigm for complex cast components
This paper describes and exercises a new design paradigm for cast components. The methodology integrates foundry process simulation, non-destructive evaluation (NDE), stress analysis and damage tolerance simulations into the design process. Foundry process simulation is used to predict an array of porosity-related anomalies. The probability of detection of these anomalies is investigated with a radiographic inspection simulation tool (XRSIM). The likelihood that the predicted array of anomalies will lead to a failure is determined by a fatigue crack growth simulation based on the extended finite element method and therefore does not require meshing nor remeshing as the cracks grow. With this approach, the casting modeling provides initial anomaly information, the stress analysis provides a value for the critical size of an anomaly and the NDE assessment provides a detectability measure. The combination of these tools allows for accept/reject criteria to be determined at the early design stage and enables damage tolerant design philosophies. The methodology is applied to the design of a cast monolithic door used on the Boeing 757 aircraf
Toward Sensor-Based Random Number Generation for Mobile and IoT Devices
The importance of random number generators (RNGs) to various computing applications is well understood. To ensure a quality level of output, high-entropy sources should be utilized as input. However, the algorithms used have not yet fully evolved to utilize newer technology. Even the Android pseudo RNG (APRNG) merely builds atop the Linux RNG to produce random numbers. This paper presents an exploratory study into methods of generating random numbers on sensor-equipped mobile and Internet of Things devices. We first perform a data collection study across 37 Android devices to determine two things-how much random data is consumed by modern devices, and which sensors are capable of producing sufficiently random data. We use the results of our analysis to create an experimental framework called SensoRNG, which serves as a prototype to test the efficacy of a sensor-based RNG. SensoRNG employs collection of data from on-board sensors and combines them via a lightweight mixing algorithm to produce random numbers. We evaluate SensoRNG with the National Institute of Standards and Technology statistical testing suite and demonstrate that a sensor-based RNG can provide high quality random numbers with only little additional overhead
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Faculty members' perceptions of undergraduate students with autism spectrum disorder at a four-year public university
This study explored faculty members’ perceptions of students diagnosed with autism spectrum disorder at a public four-year institution of higher education. As previous researchers suggest, the number of children aged six to seventeen identified with autism spectrum disorder in public schools increased by approximately 90% between 1994 and 2006 (Zager et al., 2013). As a result, the number of students on the autism spectrum who are entering college has grown exponentially over the past few decades. Therefore, it is imperative to continue to expand our knowledge of how faculty members ensure that students with autism spectrum disorder engage in their learning, interact with the course material, and connect with fellow classmates. Although previous studies have addressed various aspects of the learning needs of students with invisible disabilities (Gunn & Delafield-Butt, 2016; Schindler & Kientz, 2013; Hewitt, 2011; Scott & Gregg, 2000; Rush, 2011; Morrison, Sansosti, & Hadley, 2009), there is a need for additional research with a specific focus on students on autism spectrum disorder. Key findings from this study examine how faculty members’ personal experiences with disability can influence their classroom environments, as well as how they overcome challenges brought about by a lack of specificity in student accommodation letters. This study lends itself to future research in understanding how disability is perceived locally (in the classroom) as well as globally (within society).Educational Leadership and Polic
Aerosol emission from the respiratory tract:an analysis of aerosol generation from oxygen delivery systems
INTRODUCTION: continuous positive airway pressure (CPAP) and high-flow nasal oxygen (HFNO) provide enhanced oxygen delivery and respiratory support for patients with severe COVID-19. CPAP and HFNO are currently designated as aerosol-generating procedures despite limited high-quality experimental data. We aimed to characterise aerosol emission from HFNO and CPAP and compare with breathing, speaking and coughing. MATERIALS AND METHODS: Healthy volunteers were recruited to breathe, speak and cough in ultra-clean, laminar flow theatres followed by using CPAP and HFNO. Aerosol emission was measured using two discrete methodologies, simultaneously. Hospitalised patients with COVID-19 had cough recorded using the same methodology on the infectious diseases ward. RESULTS: In healthy volunteers (n=25 subjects; 531 measures), CPAP (with exhalation port filter) produced less aerosol than breathing, speaking and coughing (even with large >50 L/min face mask leaks). Coughing was associated with the highest aerosol emissions of any recorded activity. HFNO was associated with aerosol emission, however, this was from the machine. Generated particles were small (<1 µm), passing from the machine through the patient and to the detector without coalescence with respiratory aerosol, thereby unlikely to carry viral particles. More aerosol was generated in cough from patients with COVID-19 (n=8) than volunteers. CONCLUSIONS: In healthy volunteers, standard non-humidified CPAP is associated with less aerosol emission than breathing, speaking or coughing. Aerosol emission from the respiratory tract does not appear to be increased by HFNO. Although direct comparisons are complex, cough appears to be the main aerosol-generating risk out of all measured activities
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