The Image Computation Problem in Hybrid Systems Model Checking

2007 ◽  
pp. 473-486 ◽  
Author(s):  
André Platzer ◽  
Edmund M. Clarke
Keyword(s):  
Model Checking ◽  
Hybrid Systems ◽  
Systems Model ◽  
Image Computation

From Offline toward Real Time: A Hybrid Systems Model Checking and CPS Codesign Approach for Medical Device Plug-and-Play Collaborations

2014 ◽  
Vol 25 (3) ◽  
pp. 642-652 ◽  
Author(s):  
Tao Li ◽  
Feng Tan ◽  
Qixin Wang ◽  
Lei Bu ◽  
Jian-Nong Cao ◽  
...  
Keyword(s):  
Model Checking ◽  
Real Time ◽  
Hybrid Systems ◽  
Medical Device ◽  
Plug And Play ◽  
Systems Model

Toward online hybrid systems model checking of cyber-physical systems' time-bounded short-run behavior

2011 ◽  
Vol 8 (2) ◽  
pp. 7-10 ◽  
Author(s):  
Lei Bu ◽  
Qixin Wang ◽  
Xin Chen ◽  
Linzhang Wang ◽  
Tian Zhang ◽  
...  
Keyword(s):  
Model Checking ◽  
Hybrid Systems ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Systems Model ◽  
Short Run

Abstraction and Counterexample-Guided Refinement in Model Checking of Hybrid Systems

2003 ◽  
Author(s):  
Edmund Clarke ◽  
Ansgar Fehnker ◽  
Zhi Han ◽  
Bruce Krogh ◽  
Joel Ouaknine ◽  
...  
Keyword(s):  
Model Checking ◽  
Hybrid Systems

scholarly journals A Systems Biology Approach in Therapeutic Response Study for Different Dosing Regimens—a Modeling Study of Drug Effects on Tumor Growth using Hybrid Systems

2012 ◽  
Vol 11 ◽  
pp. CIN.S8185 ◽  
Author(s):  
Xiangfang Li ◽  
Lijun Qian ◽  
Michale L. Bittner ◽  
Edward R. Dougherty
Keyword(s):  
Systems Biology ◽  
Drug Development ◽  
Tumor Growth ◽  
Hybrid Systems ◽  
Anticancer Agents ◽  
Therapeutic Response ◽  
Therapeutic Effects ◽  
Systems Model ◽  
Optimal Drug ◽  
Dosing Regimens

Motivated by the frustration of translation of research advances in the molecular and cellular biology of cancer into treatment, this study calls for cross-disciplinary efforts and proposes a methodology of incorporating drug pharmacology information into drug therapeutic response modeling using a computational systems biology approach. The objectives are two fold. The first one is to involve effective mathematical modeling in the drug development stage to incorporate preclinical and clinical data in order to decrease costs of drug development and increase pipeline productivity, since it is extremely expensive and difficult to get the optimal compromise of dosage and schedule through empirical testing. The second objective is to provide valuable suggestions to adjust individual drug dosing regimens to improve therapeutic effects considering most anticancer agents have wide inter-individual pharmacokinetic variability and a narrow therapeutic index. A dynamic hybrid systems model is proposed to study drug antitumor effect from the perspective of tumor growth dynamics, specifically the dosing and schedule of the periodic drug intake, and a drug's pharmacokinetics and pharmacodynamics information are linked together in the proposed model using a state-space approach. It is proved analytically that there exists an optimal drug dosage and interval administration point, and demonstrated through simulation study.

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