scholarly journals Neural Approach for Resource Selection with PSO for Grid Scheduling

2012 ◽  
Vol 53 (11) ◽  
pp. 37-41
Author(s):  
T. R.Srinivasan ◽  
R. Shanmugalakshmi
Keyword(s):  
Resource Selection ◽  
Grid Scheduling

Resource selection and space use ofMyotis evotisin a western juniper woodland in Oregon

2018 ◽  
Vol 100 (1) ◽  
pp. 239-248
Author(s):  
Christopher R Anthony ◽  
Dana M Sanchez
Keyword(s):  
Resource Selection ◽  
Space Use ◽  
Western Juniper ◽  
Juniper Woodland

Governmental Governance of Megaprojects: The Case of EXPO 2010 Shanghai

2017 ◽  
Vol 48 (1) ◽  
pp. 37-50 ◽  
Author(s):  
Zhao Zhai ◽  
Tuomas Ahola ◽  
Yun Le ◽  
Jianxun Xie
Keyword(s):  
Resource Selection ◽  
The State ◽  
Role Of The State ◽  
Leadership Accountability ◽  
Selection Decisions ◽  
Chinese State ◽  
Organization Construction

While the governance of Western megaprojects is indirectly influenced by governments through legislation and regulations, the Chinese state actively oversees and controls projects of societal importance. To provide clarity on the role of the state in Chinese megaprojects, we carried out a case study focusing on EXPO 2010 Shanghai. Our analysis revealed that through a project-specific organization Construction Headquarter (CHQ), the Chinese state executes administrative strength, forces authorities to temporarily integrate their processes for the benefit of the project, influences contractor and resource selection decisions, induces leadership accountability, and promotes shared project values.

scholarly journals Estimating a resource selection function with line transect sampling

2002 ◽  
Vol 6 (4) ◽  
pp. 213-228 ◽  
Author(s):  
Bryan F. J. Manly
Keyword(s):  
Resource Selection ◽  
Probability Function ◽  
Resource Selection Function ◽  
Line Transect ◽  
Selection Function ◽  
Line Transect Sampling ◽  
Selection Probability ◽  
Transect Sampling ◽  
Conditional Maximum ◽  
Habitat Variables

A resource selection probability function is a function that gives the prob- ability that a resource unit (e.g., a plot of land) that is described by a set of habitat variables X1 to Xp will be used by an animal or group of animals in a certain period of time. The estimation of a resource selection function is usually based on the comparison of a sample of resource units used by an animal with a sample of the resource units that were available for use, with both samples being assumed to be effectively randomly selected from the relevant populations. In this paper the possibility of using a modified sampling scheme is examined, with the used units obtained by line transect sampling. A logistic regression type of model is proposed, with estimation by conditional maximum likelihood. A simulation study indicates that the proposed method should be useful in practice.

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