task splitting
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2021 ◽  
Vol 11 (1) ◽  
Author(s):  
James N. Cousins ◽  
Ruth L. F. Leong ◽  
S. Azrin Jamaluddin ◽  
Alyssa S. C. Ng ◽  
Ju Lynn Ong ◽  
...  

AbstractDaytime naps have been linked with enhanced memory encoding and consolidation. It remains unclear how a daily napping schedule impacts learning throughout the day, and whether these effects are the same for well-rested and sleep restricted individuals. We compared memory in 112 adolescents who underwent two simulated school weeks containing 8 or 6.5 h sleep opportunities each day. Sleep episodes were nocturnal or split between nocturnal sleep and a 90-min afternoon nap, creating four experimental groups: 8 h-continuous, 8 h-split, 6.5 h-continuous and 6.5 h-split. Declarative memory was assessed with picture encoding and an educationally realistic factual knowledge task. Splitting sleep significantly enhanced afternoon picture encoding and factual knowledge under both 6.5 h and 8 h durations. Splitting sleep also significantly reduced slow-wave energy during nocturnal sleep, suggesting lower homeostatic sleep pressure during the day. There was no negative impact of the split sleep schedule on morning performance, despite a reduction in nocturnal sleep. These findings suggest that naps could be incorporated into a daily sleep schedule that provides sufficient sleep and benefits learning.


2020 ◽  
Author(s):  
James N. Cousins ◽  
Ruth L. F. Leong ◽  
S. Azrin Jamaluddin ◽  
Alyssa S. C. Ng ◽  
Ju Lynn Ong ◽  
...  

AbstractDaytime naps have been linked with enhanced memory encoding and consolidation. It remains unclear how a daily napping schedule impacts learning throughout the day, and whether these effects are the same for well-rested and sleep restricted individuals. We compared memory in 112 adolescents who underwent two simulated school weeks containing 8 or 6.5 hour sleep opportunities each day. Sleep episodes were nocturnal or split between nocturnal sleep and a 90-min afternoon nap, creating four experimental groups: 8h-continuous, 8h-split, 6.5h-continuous and 6.5h-split. Declarative memory was assessed with picture encoding and an educationally realistic factual knowledge task. Splitting sleep significantly enhanced afternoon picture encoding and factual knowledge under both 6.5h and 8h durations. Splitting sleep also significantly reduced slow-wave activity during nocturnal sleep, suggesting lower homeostatic sleep pressure during the day. There was no negative impact of the split sleep schedule on morning performance, despite a reduction in nocturnal sleep duration. These findings suggest that naps could be incorporated into a daily sleep schedule that provides sufficient sleep and benefits learning.


2020 ◽  
pp. 1-1
Author(s):  
Daniel Casini ◽  
Alessandro Biondi ◽  
Giorgio Carlo Buttazzo

Author(s):  
Adhishtha Tyagi ◽  
Sonia Sharma

Hadoop framework has been emerged as the most effective and widely adopted framework for Big Data processing. Map Reduce programming model is used for processing as well as generating large data sets. Data security has become an important issue as far as storage is concerned. By default theres no security mechanism in hadoop and it is the first choice of the business analyst and industrialists to store and manage data as well as theres a need to introduce security solutions to Hadoop in order to secure the important data in the Hadoop environment. We implemented and evaluated Dynamic Task Splitting Scheduler (DTSS) which explores the tradeoffs between fairness and data performance by splitting the tasks dynamically before processing in hadoop along with AES-MR (an Advanced Encryption Standard based encryption using mapreduce) encryption in MapReduce paradigm. This paper would be useful for beginners and researchers for understanding DTSS scheduling along with security.


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