scholarly journals Predicting thermal behavior for temperature management in time-critical multicore systems

2013 ◽  
Author(s):  
Buyoung Yun ◽  
K. G. Shin ◽  
Shige Wang
Keyword(s):  
Thermal Behavior ◽  
Temperature Management ◽  
Multicore Systems ◽  
Time Critical

Techniques for temperature management

2009 ◽  
Vol 36 (S 02) ◽  
Author(s):  
J Peterson
Keyword(s):  
Temperature Management

A Retrospective Single-center Study on Time Critical Neurological Disorders in the Emergency Room of a Tertiary Pediatric Center

2019 ◽  
Author(s):  
Michaela Bonfert ◽  
Claire Andonian ◽  
Christoph Bidlingmaier ◽  
Claudia Berlin ◽  
Ingo Borggraefe ◽  
...  
Keyword(s):  
Emergency Room ◽  
Neurological Disorders ◽  
Single Center ◽  
Single Center Study ◽  
Time Critical ◽  
Pediatric Center ◽  
Center Study

Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Predictive Analytics ◽  
Paper Industry ◽  
Quality Parameters ◽  
Fast Change ◽  
The Face ◽  
Model Tuning ◽  
Reducing Costs ◽  
Time Critical

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.

Comparative analysis of butter thermal behavior in combination with bovine tallow

2020 ◽  
Vol 40 (suppl 2) ◽  
pp. 597-604
Author(s):  
Zahra NILCHIAN ◽  
Mohamad Reza EHSANI ◽  
Zahra PIRAVI-VANAK ◽  
Hossein BAKHODA
Keyword(s):  
Comparative Analysis ◽  
Thermal Behavior

NUMERICAL AND EXPERIMENTAL STUDY OF TRANSIENT THERMAL BEHAVIOR OF ELECTRONIC INFRARED RADIATION CONTROL MODULE

2019 ◽  
Vol 50 (17) ◽  
pp. 1721-1736
Author(s):  
Kaiqiang Hou ◽  
Xiaolong Weng ◽  
Wei Luo ◽  
Le Yuan ◽  
Wei Duan ◽  
...  
Keyword(s):  
Experimental Study ◽  
Thermal Behavior ◽  
Infrared Radiation ◽  
Control Module ◽  
Radiation Control ◽  
Transient Thermal
Sign in / Sign up

Export Citation Format

Share Document