scholarly journals A novel clustering-based algorithm for solving spatially-constrained robotic task sequencing problems

Author(s):  
Cuebong Wong ◽  
Carmelo Mineo ◽  
Erfu Yang ◽  
Xiu-Tian Yan ◽  
Dongbing Gu
2002 ◽  
Vol 142 (2) ◽  
pp. 282-293 ◽  
Author(s):  
Edward F. Stafford ◽  
Fan T. Tseng
Keyword(s):  

2018 ◽  
Vol 24 (5) ◽  
pp. 642-665 ◽  
Author(s):  
Aleksandra Malicka

This study set out to test the theoretical premise of the SSARC model of pedagogic task sequencing, which postulates that tasks should be sequenced for learners from cognitively simple to complex. This experiment compared the performance of three tasks differing in cognitive complexity in a simple–complex sequence versus in the absence of any other tasks. There were two groups in the study: (1) participants who performed the three tasks in the simple–complex sequence, and (2) participants who performed either the simple, the complex, or the most complex task. The participants’ speech was analysed using fluency, accuracy, and complexity measures. The results indicate that simple–complex sequencing led to a higher speech rate, greater dysfluency, enhanced accuracy, and greater structural complexity, as compared to individual task performance. The results are discussed in terms of the SSARC model and pedagogical implications of the findings are presented.


Author(s):  
Abbas Al-Refaie ◽  
Mays Judeh ◽  
Ming-Hsien Li

AbstractLittle research has considered fuzzy scheduling and sequencing problem in operating rooms. Multiple-period fuzzy scheduling and sequencing of patients in operating rooms optimization models are proposed in this research taking into consideration patient‘s preference. The objective of the scheduling optimization model is obtaining minimal undertime and overtime and maximum patients' satisfaction about the assigned date. The objective of sequencing the optimization model is both to minimize overtime and to maximize patients' satisfaction about the assigned time. A real-life case study from a hospital that offers comprehensive surgical procedures for all surgical specialties is considered for illustration. Research results showed that the proposed models efficiently scheduled and sequenced patients while considering their preferences and hospitals operating costs. In conclusion, the proposed optimization models may result in improving patient satisfaction, utilizing hospital's resources efficiently, and providing assistance to decision makers and planners in solving effectively fuzzy scheduling and sequencing problems of operating rooms.


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