Effective Adaptive Computing Environment Management via Dynamic Optimization

2005 ◽  
Author(s):  
Shiwen Hu ◽  
M. Valluri ◽  
L.K. John
Keyword(s):  
Dynamic Optimization ◽  
Adaptive Computing ◽  
Computing Environment ◽  
Environment Management

scholarly journals Condor enhancements for a rapid-response adaptive computing environment for LHC

2010 ◽  
Vol 219 (6) ◽  
pp. 062035 ◽  
Author(s):  
D Bradley ◽  
S Dasu ◽  
M Livny ◽  
A Mohapatra ◽  
T Tannenbaum ◽  
...  
Keyword(s):  
Rapid Response ◽  
Adaptive Computing ◽  
Computing Environment

Optimizing genotype-environment-management interactions to ensure silage maize production in the Chinese Maize Belt

2020 ◽  
Vol 80 (2) ◽  
pp. 133-146
Author(s):  
L Zhang ◽  
Z Zhang ◽  
J Cao ◽  
Y Luo ◽  
Z Li
Keyword(s):  
Field Experiments ◽  
Weather Conditions ◽  
Growth Cycle ◽  
High Energy ◽  
Risk Level ◽  
Energy Yield ◽  
Maize Production ◽  
Early Date ◽  
Environment Management ◽  
Silage Maize

Grain maize production exceeds the demand for grain maize in China. Methods for harvesting good-quality silage maize urgently need a theoretical basis and reference data in order to ensure its benefits to farmers. However, research on silage maize is limited, and very few studies have focused on its energetic value and quality. Here, we calibrated the CERES-Maize model for 24 cultivars with 93 field experiments and then performed a long-term (1980-2017) simulation to optimize genotype-environment-management (G-E-M) interactions in the 4 main agroecological zones across China. We found that CERES-Maize could reproduce the growth and development of maize well under various management and weather conditions with a phenology bias of <5 d and biomass relative root mean square error values of <5%. The simulated results showed that sowing long-growth-cycle cultivars approximately 10 d in advance could yield good-quality silage. The optimal sowing dates (from late May to July) and harvest dates (from early October to mid-November) gradually became later from north to south. A high-energy yield was expected when sowing at an early date and/or with late-maturing cultivars. We found that Northeast China and the North China Plain were potential silage maize growing areas, although these areas experienced a medium or even high frost risk. Southwestern maize experienced a low risk level, but the low soil fertility limited the attainable yield. The results of this paper provide information for designing an optimal G×E×M strategy to ensure silage maize production in the Chinese Maize Belt.

Survey and Analysis of Computing Education at Japanese Universities: Non-IT Departments and Courses

2019 ◽  
Vol 13 ◽  
pp. 57-79
Author(s):  
Tetsuro KAKESHITA ◽  
Mika OHTSUKI
Keyword(s):  
Educational Achievement ◽  
Academic Discipline ◽  
Teaching Staff ◽  
Computing Environment ◽  
Computing Education ◽  
Major Subject ◽  
Curriculum Guidelines ◽  
Essential Input ◽  
Organization Quality ◽  
It Departments

We conducted the first national survey of computing education at Japanese universities in 2016. In this paper, we report the survey result of the computing education at non-IT departments and faculties whose major subject is not computing. The survey covers various aspects of computing education including program organization, quality and quantity of educational achievement, students, teaching staff and computing environment. We collected 994 answers through the survey. At least 87,000 non-ICT students are taking computing education in Japan. Although computing education is carried out at every major academic discipline, teaching effort greatly differs depending on the academic discipline. We also find shortage of teaching staff for computing education. The analysis result will be an essential input to develop reasonable curriculum guidelines and accreditation criteria to improve computing education at non-IT departments.

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