scholarly journals Towards Probabilistic Session-Type Monitoring

2021 ◽  
pp. 106-120
Author(s):  
Christian Bartolo Burlò ◽  
Adrian Francalanza ◽  
Alceste Scalas ◽  
Catia Trubiani ◽  
Emilio Tuosto
Keyword(s):  
Session Type

scholarly journals Session Type Inference in Haskell

2011 ◽  
Vol 69 ◽  
pp. 74-91 ◽  
Author(s):  
Keigo Imai ◽  
Shoji Yuen ◽  
Kiyoshi Agusa
Keyword(s):  
Type Inference ◽  
Session Type

scholarly journals A Comparison of Methods Used for Quantifying Internal Training Load in Women Soccer Players

2008 ◽  
Vol 3 (3) ◽  
pp. 320-330 ◽  
Author(s):  
Helen Alexiou ◽  
Aaron J. Coutts
Keyword(s):  
Heart Rate ◽  
Training Load ◽  
Soccer Players ◽  
Comparison Of Methods ◽  
Intermittent Training ◽  
Session Type ◽  
Training Activities ◽  
Soccer Training ◽  
The Mean ◽  
Individual Training

Purpose:The purpose of this study was to compare the session-RPE method for quantifying internal training load (TL) with various HR-based TL quantification methods in a variety of training modes with women soccer players.Methods:Fifteen elite women soccer players took part in the study (age: 19.3 ± 2.0 y and VO2max: 50.8 ± 2.7 mL·kg−1·min−1). Session-RPE, heart rate, and duration were recorded for 735 individual training sessions and matches over a period of 16 wk. Correlation analysis was used to compare session-RPE TLs with three commonly used HR-based methods for assessing TL.Results:The mean correlation for session-RPE TL with Banister’s TRIMP, LTzone TL and Edwards’s TL were (r = 0.84, 0.83, and 0.85, all P < .01, respectively). Correlations for session-RPE TL and three HR-based methods separated by session type were all significant (all P < .05). The strongest correlations were reported for technical (r = 0.68 to 0.82), conditioning (r = 0.60 to 0.79), and speed sessions (r = 0.61 to 0.79).Conclusion:The session-RPE TL showed a significant correlation with all training types common to soccer. Higher correlations were found with less intermittent, aerobic-based training sessions and suggest that HR-based TLs relate better to session-RPE TLs in less intermittent training activities. These results support previous findings showing that the session-RPE TL compares favorably with HR-based methods for quantifying internal TL in a variety of soccer training activities.

scholarly journals Efficient Session Type Guided Distributed Interaction

2010 ◽  
pp. 152-167 ◽  
Author(s):  
K. C. Sivaramakrishnan ◽  
Karthik Nagaraj ◽  
Lukasz Ziarek ◽  
Patrick Eugster
Keyword(s):  
Session Type

scholarly journals Service Equivalence via Multiparty Session Type Isomorphisms

2019 ◽  
Vol 291 ◽  
pp. 1-11
Author(s):  
Assel Altayeva ◽  
Nobuko Yoshida
Keyword(s):  
Session Type

Context-Free Session Type Inference

2019 ◽  
Vol 41 (2) ◽  
pp. 1-37
Author(s):  
Luca Padovani
Keyword(s):  
Type Inference ◽  
Session Type ◽  
Context Free

Repeated exercise paired with “imperceptible” dead space loading does not alter V˙e of subsequent exercise in humans

2002 ◽  
Vol 92 (3) ◽  
pp. 1159-1168 ◽  
Author(s):  
S. H. Moosavi ◽  
A. Guz ◽  
L. Adams
Keyword(s):  
Associative Learning ◽  
Dead Space ◽  
Breathing Circuit ◽  
Conditioning Session ◽  
Repeated Exercise ◽  
Session Type ◽  
End Tidal ◽  
Response To Exercise ◽  
Exercise In Humans ◽  
Test Control

We employed an associative learning paradigm to test the hypothesis that exercise hyperpnea in humans arises from learned responses forged by prior experience. Twelve subjects undertook a “conditioning” and a “nonconditioning” session on separate days, with order of performance counterbalanced among subjects. In both sessions, subjects performed repeated bouts of 6 min of treadmill exercise, each separated by 5 min of rest. The only difference between sessions was that all the second-to-penultimate runs of the conditioning session were performed with added dead space in the breathing circuit. Cardiorespiratory responses during the first and last runs (the “control” and “test” runs) were compared for each session. Steady-state exercise end-tidal Pco 2 was significantly lower ( P= 0.003) during test than during control runs for both sessions (dropping by 1.8 ± 2 and 1.4 ± 3 Torr during conditioning and nonconditioning sessions, respectively). This and all other test-control run differences tended to be greater during the first session performed regardless of session type. Our data provide no support for the hypothesis implicating associative learning processes in the ventilatory response to exercise in humans.

scholarly journals Frequency and Location of Head Impact Exposures in Individual Collegiate Football Players

2010 ◽  
Vol 45 (6) ◽  
pp. 549-559 ◽  
Author(s):  
Joseph J. Crisco ◽  
Russell Fiore ◽  
Jonathan G. Beckwith ◽  
Jeffrey J. Chu ◽  
Per Gunnar Brolinson ◽  
...  
Keyword(s):  
National Collegiate Athletic Association ◽  
Median Number ◽  
Head Impact ◽  
Clinical Aspects ◽  
Brain Concussion ◽  
Head Impacts ◽  
Session Type ◽  
Subconcussive Impacts ◽  
Player Positions ◽  
Collegiate Football

Abstract Context: Measuring head impact exposure is a critical step toward understanding the mechanism and prevention of sport-related mild traumatic brain (concussion) injury, as well as the possible effects of repeated subconcussive impacts. Objective: To quantify the frequency and location of head impacts that individual players received in 1 season among 3 collegiate teams, between practice and game sessions, and among player positions. Design: Cohort study. Setting: Collegiate football field. Patients or Other Participants: One hundred eighty-eight players from 3 National Collegiate Athletic Association football teams. Intervention(s): Participants wore football helmets instrumented with an accelerometer-based system during the 2007 fall season. Main Outcome Measure(s): The number of head impacts greater than 10g and location of the impacts on the player's helmet were recorded and analyzed for trends and interactions among teams (A, B, or C), session types, and player positions using Kaplan-Meier survival curves. Results: The total number of impacts players received was nonnormally distributed and varied by team, session type, and player position. The maximum number of head impacts for a single player on each team was 1022 (team A), 1412 (team B), and 1444 (team C). The median number of head impacts on each team was 4.8 (team A), 7.5 (team B), and 6.6 (team C) impacts per practice and 12.1 (team A), 14.6 (team B), and 16.3 (team C) impacts per game. Linemen and linebackers had the largest number of impacts per practice and per game. Offensive linemen had a higher percentage of impacts to the front than to the back of the helmet, whereas quarterbacks had a higher percentage to the back than to the front of the helmet. Conclusions: The frequency of head impacts and the location on the helmet where the impacts occur are functions of player position and session type. These data provide a basis for quantifying specific head impact exposure for studies related to understanding the biomechanics and clinical aspects of concussion injury, as well as the possible effects of repeated subconcussive impacts in football.

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