A high performance clustering-driven MAC protocol for single-hop lightwave networks

2008 ◽  
Author(s):  
S. G. Petridou ◽  
P. G. Sarigiannidis ◽  
G. I. Papadimitriou ◽  
A. S. Pomportsis
Keyword(s):  
High Performance ◽  
Mac Protocol ◽  
Lightwave Networks

scholarly journals Theoretical and Empirical Developments of the Mindfulness-Acceptance-Commitment(MAC) Approach to Performance Enhancement

2009 ◽  
Vol 3 (4) ◽  
pp. 291-302 ◽  
Author(s):  
Zella E. Moore
Keyword(s):  
Sport Psychology ◽  
High Performance ◽  
Performance Enhancement ◽  
Mac Protocol ◽  
Skills Training ◽  
Psychological Skills ◽  
Future Directions ◽  
Psychological Skills Training ◽  
Intervention Efficacy ◽  
Theoretical Foundations

As long as athletes strive to attain optimal performance states and consistently reach high performance goals, psychological interventions will be used to assist in the development of skill and the maintenance of performance. In the pursuit of these goals, newer evidence-driven models based on mindfulness- and acceptance-based approaches have been designed to achieve these ends. Based upon questionable efficacy data for traditional psychological skills training procedures that emphasize reduction or control of internal processes, mindfulness- and acceptance-based approaches develop skills of nonjudging mindful awareness, mindful attention, and experiential acceptance to aid in the pursuit of valued goals. The most formalized and researched mindfulness- and acceptance-based approach within sport psychology is the manualized Mindfulness-Acceptance-Commitment (MAC) protocol. In the 8 years since the MAC was first developed and presented, and the 5 years since the first publication on the protocol, the MAC program has accumulated a continually growing empirical base for both its underlying theory and intervention efficacy as a performance enhancement intervention. This article reviews the empirical and theoretical foundations of the mindfulness- and acceptance-based approaches in general, and MAC in particular; reviews the accumulated empirical findings in support of the MAC approach for performance enhancement; and presents recent MAC developments and suggested future directions.

scholarly journals Wireless wearable biosensor smart physiological monitoring system for risk avoidance and rescue

2021 ◽  
Vol 19 (2) ◽  
pp. 1496-1514
Author(s):  
Kezhou Chen ◽  
◽  
Xu Lu ◽  
Rongjun Chen ◽  
Jun Liu ◽  
...  
Keyword(s):  
High Performance ◽  
Mac Protocol ◽  
Physiological Data ◽  
Physiological Monitoring ◽  
Location Tracking ◽  
Tracking Accuracy ◽  
Trajectory Prediction ◽  
Risk Avoidance ◽  
Emergency Rescue ◽  
Rescue System

<abstract> <p>Most existing physiological testing systems broadly classify monitored physiological data into three categories: normal, abnormal, and highly abnormal, but do not consider differences in the importance of data within the same category, which may result in the loss of data of higher importance. In addition, the purpose of physiological monitoring is to detect health abnormalities in patients earlier and faster, thus enabling risk avoidance and real-time rescue. Therefore, we designed a system called the adaptive physiological monitoring and rescue system (APMRS) that innovatively incorporates emergency rescue functions into traditional physiological monitoring systems using the rescue of modified-MAC (RM-MAC) protocol. The relay selection (RS) algorithm of APMRS can select the appropriate relay to forward based on the importance of the physiological data, thus ensuring priority transmission of more important monitoring data. In addition, we apply deep learning target trajectory prediction technology to the indoor rescue module (IRM) of APMRS to provide high-performance scheduling of location tracking nodes in advance by trajectory prediction. It reduces network energy consumption and ensures perceptual tracking accuracy. When APMRS monitors abnormal physiological data that may endanger a patient's life, IRM can implement effective and fast location rescue to avoid risks.</p> </abstract>

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