A comparison of real‐time and delayed visual performance feedback on teacher praise

2020 ◽  
Author(s):  
Elizabeth L. Lown ◽  
Keith C. Radley ◽  
Evan H. Dart ◽  
Brad A. Dufrene ◽  
Daniel H. Tingstrom ◽  
...  
Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4594
Author(s):  
Hayati Havlucu ◽  
Aykut Coşkun ◽  
Oğuzhan Özcan

Sports technology enhances athletes’ performance by providing feedback. However, interaction techniques of current devices may overwhelm athletes with excessive information or distract them from their performance. Despite previous research, design knowledge on how to interact with these devices to prevent such occasions are scarce. To address this gap, we introduce subtle displays as real-time sports performance feedback output devices that unobtrusively present low-resolution information. In this paper, we conceptualize and apply subtle displays to tennis by designing Tactowel, a texture changing sports towel. We evaluate Tactowel through a remote user study with 8 professional tennis players, in which they experience, compare and discuss Tactowel. Our results suggest subtle displays could prevent overwhelming and distracting athletes through three distinct design strategies: (1) Restricting the use excluding duration of performance, (2) using the available routines and interactions, and (3) giving an overall abstraction through tangible interaction. We discuss these results to present design implications and future considerations for designing subtle displays.


Author(s):  
Frederico Dinis

Aiming to explore the diverse nature of sound and image, thereby establishing a bridge with the symbiotic creation of sensations and emotions, this chapter intends to present the development and the construction of a proposal for the confluence between materiality and immateriality in site-specific sound and visual performances. Using as a focal point sound and visual narratives, the author tries to look beyond space and time and create a representative atmosphere of sense of place, attempting to understand the past and sketching new configurations for the (re)presentation of identity, guiding the audience through a journey of perceptual experiences, using field recordings, ambient electronic music, and videos. This chapter also presents the development of an experimental approach, based on a real-time sound and visual performance, and some critical forms of expression and communication that relate or incorporate sound and image, articulating concerns about their aesthetic experience and communicative functionality.


2020 ◽  
pp. 1-12
Author(s):  
Kyle J. Jaquess ◽  
Yingzhi Lu ◽  
Andrew Ginsberg ◽  
Steven Kahl ◽  
Calvin Lu ◽  
...  

2021 ◽  
pp. 1-40
Author(s):  
Eric DeShong ◽  
Benjamin Peters ◽  
Reid A. Berdanier ◽  
Karen A. Thole ◽  
Kamran Paynabar ◽  
...  

Abstract Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, the present study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modelling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within three percent of measured values.


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