A Profile-Based AI-Assisted Dynamic Scheduling Approach for Heterogeneous Architectures

2021 ◽  
Author(s):  
Tongsheng Geng ◽  
Marcos Amaris ◽  
Stéphane Zuckerman ◽  
Alfredo Goldman ◽  
Guang R. Gao ◽  
...  
Keyword(s):  
Dynamic Scheduling ◽  
Heterogeneous Architectures

Dynamic Scheduling of Post-Earthquake Emergency Material Based on the Baseline Perspective

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Ziqi Tang ◽  
Hui Hu ◽  
Guangyuan Yang ◽  
Rundong Wu
Keyword(s):  
Dynamic Scheduling

Dual priority dynamic scheduling algorithm based on multi-FPGA

2013 ◽  
Vol 33 (3) ◽  
pp. 862-865
Author(s):  
Shuangzhi DU ◽  
Yong WANG ◽  
Xiaoling TAO
Keyword(s):  
Dynamic Scheduling ◽  
Scheduling Algorithm

scholarly journals High-throughput fuzzy clustering on heterogeneous architectures

2020 ◽  
Vol 106 ◽  
pp. 401-411 ◽  
Author(s):  
Juan M. Cebrian ◽  
Baldomero Imbernón ◽  
Jesus Soto ◽  
José M. García ◽  
José M. Cecilia
Keyword(s):  
High Throughput ◽  
Fuzzy Clustering ◽  
Heterogeneous Architectures

scholarly journals A Real-Time, Automatic, and Dynamic Scheduling and Control System for PET Patients Based on Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong
Keyword(s):  
Control System ◽  
Real Time ◽  
Human Error ◽  
Dynamic Scheduling ◽  
Wearable Sensors ◽  
Time Data ◽  
Scan Time ◽  
Number Of Patients ◽  
And Control ◽  
Automatic Scheduling

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.

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