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We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-β signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis.
Here, we proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad-dependent TGF-β signaling pathway by fitting experimental data and incorporating the qualitative constraints from the experimental analysis.
This thesis addresses these three problems by proposing a constraint solver based framework that can be applied to these problems and experimentally evaluates its scalability and feasibility.
In this paper, we propose a constraint programming approach to cutset problems and design a global constraint for computing cutsets.
To resolve the problem in a timely manner, we propose a constraint satisfaction based web service composition algorithm that combines tabu search and simulated annealing meta-heuristics.
The objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models.
To ensure a practically reachable trajectory, this paper proposes a constraint reference frame to develop MAPF so that the decomposed forces from MAPF can be matched with the physical constraints of the UAV for online adjustment.
This paper proposes a Constraint Programming approach for cyclic scheduling problems, based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms.
We propose a constraint for the total variation (TV) regularization-based image magnification model.
Our contributions can be summarized as follows: 1) We propose a constraint for the total variation (TV) regularization-based image magnification model.
As a first approach to assess the identifiability a priori and select a set of parameters which are identifiable, we propose a constraint satisfaction problem.
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